Universal Valuation System Overview 🔍
The Universal Valuation System (UVS) is an advanced valuation-focused indicator that provides insights into whether an asset is statistically overvalued or undervalued, helping traders understand where an asset sits within its historical value range. Unlike trend indicators, UVS emphasizes value analysis through a unique combination of performance ratios and statistical metrics, synthesizing this data into an overall Z-score. This score reflects the asset’s position within a typical normal distribution curve, allowing traders to make data-driven decisions based on historical valuation patterns.
Normal Distribution: A Statistical Foundation for Valuation 📊
The UVS leverages the normal distribution model as its core statistical framework. In a normal distribution, values tend to cluster around a central mean, with predictable probabilities for deviation. In financial markets, this means that most price or valuation levels hover around an average range, while extreme highs or lows are less frequent.
Under normal distribution:
68% of values lie within one standard deviation of the mean.
95% of values lie within two standard deviations.
99.7% of values lie within three standard deviations.
Using Z-scores, UVS calculates where current valuation metrics fall relative to this distribution, identifying overvalued (above-average) or undervalued (below-average) zones. This helps traders interpret an asset’s relative value, showing whether it is more likely to revert toward its mean or is experiencing an exceptional deviation.
Key Components and Ratios in UVS 🔀
UVS includes a range of valuation metrics that work together to determine the Z-score:
Sharpe Ratio: Measures return relative to risk, offering insight into the quality of returns.
Sortino Ratio: Focuses on downside deviation, helping gauge negative returns’ impact.
Omega Ratio: Assesses the likelihood of gains versus losses, providing a risk-adjusted performance measure.
Crosby Ratio: Examines volatility patterns, adding dimension to the valuation signal.
VWAP (Volume-Weighted Average Price) Z-Score: Assesses price relative to volume, highlighting valuation when volume supports price movements.
Price ROC Z-Score: Uses the rate of price change to give a volatility-adjusted price movement signal.
By averaging these ratios, UVS forms a composite Z-score representing an overall valuation signal. This Z-score directly reflects the asset’s position within its historical distribution, indicating whether it’s in a typical, overbought, or oversold range.
DCA (Dollar-Cost Averaging) Application with UVS 💵
The UVS provides powerful insights for those using Dollar-Cost Averaging (DCA) by signaling periods when an asset may be overvalued or undervalued relative to its historical distribution. This model-based approach helps traders strategically adjust their DCA timing:
Overvalued (Overbought) Zones:
When the Z-score indicates that an asset is in an overbought zone (typically above +2 standard deviations), DCA buyers may choose to reduce purchases or pause, as this zone suggests the asset is currently at a premium relative to its historical norms.
Undervalued (Oversold) Zones:
In undervalued regions (typically below -2 standard deviations), the UVS suggests a favorable accumulation point for DCA. These periods allow traders to buy at below-average valuations, optimizing their cost basis over time.
Valuation Zone Display and Accessibility 🌈
UVS includes several user-friendly display options, helping traders interpret its signals easily:
Composite Zone Highlighting: Displays overbought and oversold zones with color gradients, clearly visualizing statistical extremes.
Ratio Breakdown: Allows users to view individual Z-scores for each component, understanding the specific contributions to the overall valuation signal.
Color Blindness Mode: Offers multiple color settings to ensure clear interpretation across different visual needs.
Summary: Structured Value Analysis for Informed DCA Decisions
UVS is designed to be a reliable tool for traders looking to anchor their DCA and valuation-based strategies in statistical reality. By identifying valuation zones within a normal distribution framework, UVS enables a disciplined approach to asset accumulation based on relative value rather than price trends.
Important Note: UVS does not predict future performance. It provides a statistical view of historical valuation, which should be supplemented with additional analysis and risk management practices. Past patterns do not guarantee future results.
DCA
Dollar Cost Averaging (YavuzAkbay)The Dollar Cost Averaging (DCA) indicator is designed to support long-term investors following a Dollar Cost Averaging strategy. The core aim of this tool is to provide insights into overbought and oversold levels, assisting investors in managing buy and sell decisions with a clear visual cue system. Specifically developed for use in trending or fluctuating markets, this indicator leverages support and resistance levels to give structure to investors' buying strategies. Here’s a detailed breakdown of the indicator’s key features and intended usage:
Key Features and Color Coding
Overbought/Oversold Detection:
The indicator shades candles from light green to dark green when an asset becomes increasingly overbought. Dark green signals indicate a peak, where the asset is overbought, suggesting a potential opportunity to take partial profits.
Conversely, candles turn from light red to dark red when the market is oversold. Dark red signifies a heavily oversold condition, marking an ideal buying window for initiating or adding to a position. This color scheme provides a quick visual reference for investors to manage entries and exits effectively.
Support and Resistance Levels:
To address the risk of assets falling further after an overbought signal, the DCA indicator dynamically calculates support and resistance levels. These levels guide investors on key price areas to watch for potential price reversals, allowing them to make more informed buying or selling decisions.
Support levels help investors assess whether they should divide their capital across multiple buy orders, starting at the current oversold zone and extending to anticipated support zones for maximum flexibility.
Usage Methodology
This indicator is intended for Dollar Cost Averaging, a method where investors gradually add to their position rather than entering all at once. Here’s how it complements the DCA approach:
Buy at Oversold Levels: When the indicator shows a dark red candle, it signals that the asset is oversold, marking an optimal entry point. The presence of support levels can help investors determine if they should fully invest their intended amount or stagger buys at potential lower levels.
Sell at Overbought Levels: When the indicator transitions to dark green, it suggests that the asset is overbought. This is an ideal time to consider selling a portion of holdings to realize gains. The resistance levels, marked by the indicator, offer guidance on where the price may encounter selling pressure, aiding investors in planning partial exits.
Customizable Settings
The DCA indicator offers several user-adjustable parameters:
Pivot Frequency and Source: Define the pivot point frequency and the source (candle wick or body) for more tailored support/resistance detection.
Maximum Pivot Points: Set the maximum number of pivot points to be used in support/resistance calculations, providing flexibility in adapting to different market structures.
Channel Width and Line Width: Adjust the width of the channel for support/resistance levels and the thickness of the lines for easier visual tracking.
Color Intensities for Overbought/Oversold Levels: Customize the shading intensity for each overbought and oversold level to align with your trading preferences.
Fractional Accumulation Distribution Strategy🔹 INTRODUCTION:
As traders and investors, we often find ourselves searching for ways to maximize our market positioning—trying to capture the best price, manage risk, and adapt to ever-changing volatility. Through years of working with a variety of traders and investors, a common theme emerged: the most successful market participants were those who accumulated positions strategically over time, rather than relying on one-off, rigid entry points. However, even the best of them struggled to consistently time their entries and exits for optimal results.
That's why I created the Fractional Accumulation/Distribution Strategy (FADS)—an adaptable solution designed to dynamically adjust position sizing and entry points based on changing market conditions, enabling both passive and active market participants to optimize their approach.
The FADS trading strategy combines volatility-based trend detection and adaptive position scaling to maximize profitability across varied market conditions. By using the price ranges from higher timeframes, FADS pinpoints extreme demand and supply zones with a high statistical probability of reversal, making it effective in both high and low volatility environments. By applying adjustable threshold settings, users can focus on meaningful price movements to reduce unnecessary trades. Adaptive position scaling further enhances this approach by adjusting position sizes based on entry level distances, allowing for strategic position building that balances risk and reward in uncertain markets. This systematic scaling begins with smaller positions, expanding as the trend solidifies, creating a refined, robust trading experience.
🔹 FEATURES:
Multi-Timeframe Volatility-Based Trend Detection
Accumulation/Distribution Level Filter
Customizable Period for Highest/Lowest Prices Capture
Adjustable Sensitivity & Frequency in Positioning
Broad control settings of Strategy
Adaptive Position Scaling
🔹 SETTINGS:
Volatility : Determines trading range based on market volatility . Highest range value number of periods.
Factor : Adjusts the width of the Accumulation & Distribution bands separately. The Level Filter feature offers customizable triggering bands, allowing users to fine-tune the initiation point for the Accumulation/Distribution sequence. This flexibility enables traders to align entries more precisely with market conditions, setting optimal thresholds for initiating trade chains, whether in accumulating positions during uptrends or distributing in downtrends.
Lowest : Choose the price source (e.g., Close, Low). Number of bars considered when determining the lowest price level. Selecting the checkbox generate a signal when the price crosses below the previous lowest value for calculating the lowest value used for trade signals.
Highest : Choose the price source (e.g., Close, High). Number of bars considered when determining the highest price levels. Selecting the checkbox generate a signal when the price crosses above the previous highest value for calculating the highest value used for trade signals.
Accumulation Spread : Adjusts the buying frequency sensitivity by setting the distance between entries based on personal risk tolerance. Larger values for less frequent buys; smaller values for more frequent buys.
Distribution Spread : Adjusts the selling frequency sensitivity by setting the distance between exits based on reward preference. Larger values for less frequent sells; smaller values for more frequent sells.
Percentage of Capital Allocation : Sets the portion of total capital used for the initial trade in a strategy. It sets the scale for subsequent trades during accumulation phase.
🔹 APPLICATIONS:
❖ Accumulation and Distribution Phases
Early entries are avoided by initiating accumulation only after a trend reversal is confirmed and price breaks below long-term range.
Position sizes are determined by the distance between consecutive trades, smaller distance results in smaller position sizes and vice versa.
Average position cost is reduced by accumulating larger positions at the lower prices, potentially resulting in improved profitability.
Early exits are avoided by initiating distribution only after trend reversal is confirmed and price breaks above long-term range.
The pace of distribution can be tracked by the violet line that represents average positions during distribution phase
❖ Use Cases (Different than default setting input is used for illustration purposes)
If the starting point of accumulation starts too high for the risk preference, Accumulation Level Filter can be lowered by increasing the 🟢 threshold Factor.
If the starting point of distribution is too low for the reward preference, the Distribution Level Filter can be raised by increasing the 🔴 threshold Factor.
In lower timeframes, positions during the accumulation phase could be purchased at higher levels relative to prior entry positions. To optimize for this, consider extending the period used to capture the lowest prices. Similarly, during the distribution phase, increasing the period for identifying higher prices can improve accuracy.
🔹 Strategy Properties:
Adjusting properties within the script settings is recommended to align with specific accounts and trading platforms, ensuring realistic strategy results.
Balance (default): $100,000
Initial Order Size: 1% of the default balance
Commission: 0.1%
Slippage: 5 Ticks
Backtesting: Backtested using TradingView’s built-in strategy testing tool with default commission rates of 0.1% and slippage of 5 ticks. It reflects average market conditions for Apple Inc. (APPL) on 1-hour timeframe
Disclaimers: Commission and slippage varies with market conditions and brokerage policies. The assumed value may not represent all trading environments.
PAST PERFORMANCE DOESN’T GUARANTEE FUTURE RESULTS!
Disclaimer: Please remember that past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script don’t provide any financial advice.
This invite-only script is being published as part of my commitment to developing tools that align with TradingView’s community standards. Access requests will be reviewed carefully after the script passes TradingView's moderation process.
Universal Trend and Valuation System [QuantAlgo]Universal Trend and Valuation System 📊🧬
The Universal Trend and Valuation System by QuantAlgo is an advanced indicator designed to assess asset valuation and trends across various timeframes and asset classes. This system integrates multiple advanced statistical indicators and techniques with Z-score calculations to help traders and investors identify overbought/sell and oversold/buy signals. By evaluating valuation and trend strength together, this tool empowers users to make data-driven decisions, whether they aim to follow trends, accumulate long-term positions, or identify turning points in mean-reverting markets.
💫 Conceptual Foundation and Innovation
The Universal Trend and Valuation System by QuantAlgo provides a unique framework for assessing market valuation and trend dynamics through a blend of Z-score analysis and trend-following algorithm. Unlike traditional indicators that only reflect price direction, this system incorporates multi-layered data to reveal the relative value of an asset, helping users determine whether it’s overvalued, undervalued, or approaching a trend reversal. By combining high quality trend-following tools, such as Dynamic Score Supertrend, DEMA RSI, and EWMA, it evaluates trend stability and momentum quality, while Z-scores of performance ratios like Sharpe, Sortino, and Omega standardize deviations from historical trends, enabling traders and investors to spot extreme conditions. This dual approach allows users to better identify accumulation (undervaluation) and distribution (overvaluation) phases, enhancing strategies like Dollar Cost Averaging (DCA) and overall timing for entries and exits.
📊 Technical Composition and Calculation
The Universal Trend-Following Valuation System is composed of several trend-following and valuation indicators that create a dynamic dual scoring model:
Risk-Adjusted Ratios (Sharpe, Sortino, Omega): These ratios assess trend quality by analyzing an asset’s risk-adjusted performance. Sharpe and Sortino provide insight into trend consistency and risk/reward, while Omega evaluates profitability potential, helping traders and investors assess how favorable a trend or an asset is relative to its associated risk.
Dynamic Z-Scores: Z-scores are applied to various metrics like Price, RSI, and RoC, helping to identify statistical deviations from the mean, which indicate potential extremes in valuation. By combining these Z-scores, the system produces a cumulative score that highlights when an asset may be overbought or oversold.
Aggregated Trend-Following Indicators: The model consolidates multiple high quality indicators to highlight probable trend shifts. This helps confirm the direction and strength of market moves, allowing users to spot reversals or entry points with greater clarity.
📈 Key Indicators and Features
The Universal Trend and Valuation System combines various technical and statistical tools to deliver a well-rounded analysis of market trends and valuation:
The indicator utilizes trend-following indicators like RSI with DEMA smoothing and Dynamic Score Supertrend to minimize market noise, providing clearer and more stable trend signals. Sharpe, Sortino, and Omega ratios are calculated to assess risk-adjusted performance and volatility, adding a layer of analysis for evaluating trend quality. Z-scores are applied to these ratios, as well as Price and Rate of Change (RoC), to detect deviations from historical trends, highlighting extreme valuation levels.
The system also incorporates multi-layered visualization with gradient color coding to signal valuation states across different market conditions. These adaptive visual cues, combined with threshold-based alerts for overbought and oversold zones, help traders and investors track probable trend reversals or continuations and identify accumulation or distribution zones, adding reliability to both trend-following and mean-reversion strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the Universal Trend-Following Valuation System to your favourites and to your chart.
👀 Monitor Trend Shifts and Valuation Levels: Watch the average Z score, trend probability state and gradient colors to identify overbought and oversold conditions. During undervaluation, consider using a DCA strategy to gradually accumulate positions (buy), while overvaluation may signal distribution or profit-taking phases (sell).
🔔 Set Alerts: Configure alerts for significant trend or valuation changes, ensuring you can act on market movements promptly, even when you’re not actively monitoring the charts.
🌟 Summary and Usage Tips
The Universal Trend and Valuation System by QuantAlgo is a highly adaptable tool, designed to support both trend-following and valuation analysis across different market environments. By combining valuation metrics with high quality trend-following indicators, it helps traders and investors identify the relative value of an asset based on historical norms, providing more reliable overbought/sell and oversold/buy signals. The tool’s flexibility across asset types and timeframes makes it ideal for both short-term trading and long-term investment strategies like DCA, allowing users to capture meaningful trends while minimizing noise.
Cyatophilum SmartStrategy MakerThis indicator allows you to use any other indicator from the TradingView library and create complex entry and exit conditions with ease thanks to several external inputs. Add risk management to your strategy and backtest it before creating alerts!
Key Features:
1 — Entry Conditions: Traders can define their entry conditions using up to three sources. They can choose from several options such as "Cross," "Crossover," "Crossunder," "Above," "Below," or "Equal" for comparing the selected sources.
2 — Entry Gates: Users can set logical gates (e.g., "AND," "OR," "XOR," "NAND," "XNOR") to combine multiple entry conditions.
3 — Exit Conditions: Similar to entry conditions, traders can define exit conditions based on two sources and select from various comparison options.
4 — Stop Loss: The indicator allows users to enable or disable a stop-loss feature. The stop-loss value is calculated based on a percentage of the base order price.
5 — Take Profit: Traders can set multiple take-profit levels by specifying the number of take profits, a base percentage, and a step value. Take profits can be defined as a percentage from the total volume or the base order.
6 — Safety Orders (DCA): The indicator supports the use of safety orders (Dollar Cost Averaging) to help manage risks. Users can set the number of safety orders, price deviation, step scale, and volume scale.
7 — Backtest Settings: Traders can define the start and end periods for backtesting their strategy. This feature allows them to analyze the performance of their strategy within specific timeframes.
8 — Alerts: The indicator provides the option to create alerts for entry, exit, stop loss, take profit, and safety orders. Users can customize the alert messages using placeholders for dynamic values like price, symbol, and order size.
Wolf DCA CalculatorThe Wolf DCA Calculator is a powerful and flexible indicator tailored for traders employing the Dollar Cost Averaging (DCA) strategy. This tool is invaluable for planning and visualizing multiple entry points for both long and short positions. It also provides a comprehensive analysis of potential profit and loss based on user-defined parameters, including leverage.
Features
Entry Price: Define the initial entry price for your trade.
Total Lot Size: Specify the total number of lots you intend to trade.
Percentage Difference: Set the fixed percentage difference between each DCA point.
Long Position: Toggle to switch between long and short positions.
Stop Loss Price: Set the price level at which you plan to exit the trade to minimize losses.
Take Profit Price: Set the price level at which you plan to exit the trade to secure profits.
Leverage: Apply leverage to your trade, which multiplies the potential profit and loss.
Number of DCA Points: Specify the number of DCA points to strategically plan your entries.
How to Use
1. Add the Indicator to Your Chart:
Search for "Wolf DCA Calculator" in the TradingView public library and add it to your chart.
2. Configure Inputs:
Entry Price: Set your initial trade entry price.
Total Lot Size: Enter the total number of lots you plan to trade.
Percentage Difference: Adjust this to set the interval between each DCA point.
Long Position: Use this toggle to choose between a long or short position.
Stop Loss Price: Input the price level at which you plan to exit the trade to minimize losses.
Take Profit Price: Input the price level at which you plan to exit the trade to secure profits.
Leverage: Set the leverage you are using for the trade.
Number of DCA Points: Specify the number of DCA points to plan your entries.
3. Analyze the Chart:
The indicator plots the DCA points on the chart using a stepline style for clear visualization.
It calculates the average entry point and displays the potential profit and loss based on the specified leverage.
Labels are added for each DCA point, showing the entry price and the lots allocated.
Horizontal lines mark the Stop Loss and Take Profit levels, with corresponding labels showing potential loss and profit.
Benefits
Visual Planning: Easily visualize multiple entry points and understand how they affect your average entry price.
Risk Management: Clearly see your Stop Loss and Take Profit levels and their impact on your trade.
Customizable: Adapt the indicator to your specific strategy with a wide range of customizable parameters.
MetaFOX DCA (ASAP-RSI-BB%B-TV)Welcome To ' MetaFOX DCA (ASAP-RSI-BB%B-TV) ' Indicator.
This is not a Buy/Sell signals indicator, this is an indicator to help you create your own strategy using a variety of technical analyzing options within the indicator settings with the ability to do DCA (Dollar Cost Average) with up to 100 safety orders.
It is important when backtesting to get a real results, but this is impossible, especially when the time frame is large, because we don't know the real price action inside each candle, as we don't know whether the price reached the high or low first. but what I can say is that I present to you a backtest results in the worst possible case, meaning that if the same chart is repeated during the next period and you traded for the same period and with the same settings, the real results will be either identical to the results in the indicator or better (not worst). There will be no other factors except the slippage in the price when executing orders in the real trading, So I created a feature for that to increase the accuracy rate of the results. For more information, read this description.
Below I will explain all the properties and settings of the indicator:
A) 'Buy Strategies' Section: Your choices of strategies to Start a new trade: (All the conditions works as (And) not (OR), You have to choose one at least and you can choose more than one).
- 'ASAP (New Candle)': Start a trade as soon as possible at the opening of a new candle after exiting the previous trade.
- 'RSI': Using RSI as a technical analysis condition to start a trade.
- 'BB %B': Using BB %B as a technical analysis condition to start a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to start a trade.
B) 'Exit Strategies' Section: Your choices of strategies to Exit the trades: (All the conditions works as (And) not (OR), You can choose more than one, But if you don't want to use any of them you have to activate the 'Use TP:' at least).
- 'ASAP (New Candle)': Exit a trade as soon as possible at the opening of a new candle after opening the previous trade.
- 'RSI': Using RSI as a technical analysis condition to exit a trade.
- 'BB %B': Using BB %B as a technical analysis condition to exit a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to exit a trade.
C) 'Main Settings' Section:
- 'Trading Fees %': The Exchange trading fees in percentage (trading Commission).
- 'Entry Price Slippage %': Since real trading differs from backtest calculations, while in backtest results are calculated based on the open price of the candle, but in real trading there is a slippage from the open price of the candle resulting from the supply and demand in the real time trading, so this feature is to determine the slippage Which you think it is appropriate, then the entry prices of the trades will calculated higher than the open price of the start candle by the percentage of slippage that you set. If you don't want to calculate any slippage, just set it to zero, but I don't recommend that if you want the most realistic results.
Note: If (open price + slippage) is higher than the high of the candle then don't worry, I've kept this in consideration.
- 'Use SL': Activate to use stop loss percentage.
- 'SL %': Stop loss percentage.
- 'SL settings options box':
'SL From Base Price': Calculate the SL from the base order price (from the trade first entry price).
'SL From Avg. Price': Calculate the SL from the average price in case you use safety orders.
'SL From Last SO.': Calculate the SL from the last (lowest) safety order deviation.
ex: If you choose 'SL From Avg. Price' and SL% is 5, then the SL will be lower than the average price by 5% (in this case your SL will be dynamic until the price reaches all the safety orders unlike the other two SL options).
Note: This indicator programmed to be compatible with '3COMMAS' platform, but I added more options that came to my mind.
'3COMMAS' DCA bots uses 'SL From Base Price'.
- 'Use TP': Activate to use take profit percentage.
- 'TP %': Take profit percentage.
- 'Pure TP,SL': This feature was created due to the differences in the method of calculations between API tools trading platforms:
If the feature is not activated and (for example) the TP is 5%, this means that the price must move upward by only 5%, but you will not achieve a net profit of 5% due to the trading fees. but If the feature is activated, this means that you will get a net profit of 5%, and this means that the price must move upward by (5% for the TP + the equivalent of trading fees). The same idea is applied to the SL.
Note: '3COMMAS' DCA bots uses activated 'Pure TP,SL'.
- 'SO. Price Deviation %': Determines the decline percentage for the first safety order from the trade start entry price.
- 'SO. Step Scale': Determines the deviation multiplier for the safety orders.
Note: I'm using the same method of calculations for SO. (safety orders) levels that '3COMMAS' platform is using. If there is any difference between the '3COMMAS' calculations and the platform that you are using, please let me know.
'3COMMAS' DCA bots minimum 'SO. Price Deviation %' is (0.21)
'3COMMAS' DCA bots minimum 'SO. Step Scale' is (0.1)
- 'SO. Volume Scale': Determines the base order size multiplier for the safety orders sizes.
ex: If you used 10$ to buy at the trade start (base order size) and your 'SO. Volume Scale' is 2, then the 1st SO. size will be 20, the 2nd SO. size will be 40 and so on.
- 'SO. Count': Determines the number of safety orders that you want. If you want to trade without safety orders set it to zero.
'3COMMAS' DCA bots minimum 'SO. Volume Scale' is (0.1)
- 'Exchange Min. Size': The exchange minimum size per trade, It's important to prevent you from setting the base order Size less than the exchange limit. It's also important for the backtest results calculations.
ex: If you setup your strategy settings and it led to a loss to the point that you can't trade any more due to insufficient funds and your base order size share from the strategy becomes less than the exchange minimum trade size, then the indicator will show you a warning and will show you the point where you stopped the trading (It works in compatible with the initial capital). I recommend to set it a little bit higher than the real exchange minimum trade size especially if you trade without safety orders to not stuck in the trade if you hit the stop loss
- 'BO. Size': The base order size (funds you use at the trade entry).
- 'Initial Capital': The total funds allocated for trading using your strategy settings, It can be more than what is required in the strategy to cover the deficit in case of a loss, but it should not exceed the funds that you actually have for trading using this strategy settings, It's important to prevent you from setting up a strategy which requires funds more than what you have. It's also has other important benefits (refer to 'Exchange Min. Size' for more information).
- 'Accumulative Results': This feature is also called re-invest profits & risk reduction. If it's not activated then you will use the same funds size in each new trade whether you are in profit or loss till the (initial capitals + net results) turns insufficient. If it's activated then you will reuse your profits and losses in each new trade.
ex: The feature is active and your first trade ended with a net profit of 1000$, the next trade will add the 1000$ to the trade funds size and it will be distributed as a percentage to the BO. & SO.s according to your strategy settings. The same idea in case of a loss, the trade funds size will be reduced.
D) 'RSI Strategy' Section:
- 'Buy': RSI technical condition to start a trade. Has no effect if you don't choose 'RSI' option in 'Buy Strategies'.
- 'Exit': RSI technical condition to exit a trade. Has no effect if you don't choose 'RSI' option in 'Exit Strategies'.
E) 'TV Strategy' Section:
- 'Buy': TradingView Crypto Screener technical condition to start a trade. Has no effect if you don't choose 'TV' option in 'Buy Strategies'.
- 'Exit': TradingView Crypto Screener technical condition to exit a trade. Has no effect if you don't choose 'TV' option in 'Exit Strategies'.
F) 'BB %B Strategy' Section:
- 'Buy': BB %B technical condition to start a trade. Has no effect if you don't choose 'BB %B' option in 'Buy Strategies'.
- 'Exit': BB %B technical condition to exit a trade. Has no effect if you don't choose 'BB %B' option in 'Exit Strategies'.
G) 'Plot' Section:
- 'Signals': Plots buy and exit signals.
- 'BO': Plots the trade entry price (base order price).
- 'AVG': Plots the trade average price.
- 'AVG options box': Your choice to plot the trade average price type:
'Avg. With Fees': The trade average price including the trading fees, If you exit the trade at this price the trade net profit will be 0.00
'Avg. Without Fees': The trade average price but not including the trading fees, If you exit the trade at this price the trade net profit will be a loss equivalent to the trading fees.
- 'TP': Plots the trade take profit price.
- 'SL': Plots the trade stop loss price.
- 'Last SO': Plots the trade last safety order that the price reached.
- 'Exit Price': Plots a mark on the trade exit price, It plots in 3 colors as below:
Red (Default): Trade exit at a loss.
Green (Default): Trade exit at a profit.
Yellow (Default): Trade exit at a profit but this is a special case where we have to calculate the profits before reaching the safety orders (if any) on that candle (compatible with the idea of getting strategy results at the worst case).
- 'Result Table': Plots your strategy result table. The net profit percentage shown is a percentage of the 'initial capital'.
- 'TA Values': Plots your used strategies Technical analysis values. (Green cells means valid condition).
- 'Help Table': Plots a table to help you discover 100 safety orders with its deviations and the total funds needed for your strategy settings. Deviations shown in red is impossible to use because its price is <= 0.00
- 'Portfolio Chart': Plots your Portfolio status during the entire trading period in addition to the highest and lowest level reached. It's important when evaluating any strategy not only to look at the final result, but also to look at the change in results over the entire trading period. Perhaps the results were worryingly negative at some point before they rose again and made a profit. This feature helps you to see the whole picture.
- 'Welcome Message': Plots a welcome message and showing you the idea behind this indicator.
- 'Green Net Profit %': It plots the 'Net Profit %' in the result table in green color if the result is equal to or above the value that you entered.
- 'Green Win Rate %': It plots the 'Win Rate %' in the result table in green color if the result is equal to or above the value that you entered.
- 'User Notes Area': An empty text area, Feel free to use this area to write your notes so you don't forget them.
The indicator will take care of you. In some cases, warning messages will appear for you. Read them carefully, as they mean that you have done an illogical error in the indicator settings. Also, the indicator will sometimes stop working for the same reason mentioned above. If that happens then click on the red (!) next to the indicator name and read the message to find out what illogical error you have done.
Please enjoy the indicator and let me know your thoughts in the comments below.
panpanXBT BTC Risk Metric OscillatorThis is the Bitcoin Risk Metric. Inspired by many power law analysts, this script assigns a risk value to the price of Bitcoin. The model uses regression of 'fair value' data to assign risk values and residual analysis to account for diminishing returns as time goes on. This indicator is for long-term investors looking to maximise their returns by highlighting periods of under and overvaluation for Bitcoin.
This is a companion script for panpanXBT BTC Risk Metric . Use this indicator in tandem to achieve the view shown in the chart above.
Please note, this indicator will only work on BTCUSD charts but will work on any timeframe.
DISCLAIMER: The product on offer presents a novel way to view the price history of Bitcoin. It should not be relied upon solely to inform financial decisions. What you do with the information is entirely up to you. Please thoroughly consider your decisions and consult many different sources to make sure you're making the most well-informed decision.
### How to Interpret
The risk scale goes from 0 to 100,
Blue - 0 being low risk, and
Red - 100 being high risk.
Low risk values represent periods of historical undervaluation, while high values represent overvaluation. These periods are marked by a colourscale from blue to red.
### Use Cases and Best Practice
A dynamic DCA strategy would work best with this indicator, whereby an amount of capital is deployed/retired on a regular basis. This amount deployed grows or shrinks depending on the proximity of the risk level to the extremes (0 and 100).
Let's say you have a maximum of $500 to deploy per month.
When risk is between 0 and 10, you could deploy the full $500.
When risk is between 10 and 20, you could deploy $400.
When risk is between 20 and 30, you could deploy $300.
When risk is between 30 and 40, you could deploy $200.
When risk is between 40 and 50, you could deploy $100.
Conversely, when risk is above 50, you could:
Sell 1/15th of your BTC stack when risk is between 50 and 60.
Sell 2/15th of your BTC stack when risk is between 60 and 70.
Sell 3/15th of your BTC stack when risk is between 70 and 80.
Sell 4/15th of your BTC stack when risk is between 80 and 90.
Sell 5/15th of your BTC stack when risk is between 90 and 100.
This framework allows the user to accumulate during periods of undervaluation and derisk during periods of overvaluation, capturing returns in the process.
In contrast, simply setting limit orders at 0 and 100 would yield the absolute maximum returns, however there is no guarantee price will reach these levels (see 2018 where the bear market bottomed out at 20 risk, or 2021 where price topped out at 97 risk).
### Caveats
"All models are wrong, some are useful"
No model is perfect. No model can predict exactly what price will do as there are too many factors at play that determine the outcome. We use models as a guide to make better-informed decisions, as opposed to shooting in the dark. This model is not a get rich quick scheme, but rather a tool to help inform decisions should you consider investing. This model serves to highlight price extremities, which could present opportune times to invest.
### Conclusion
This indicator aims to highlight periods of extreme values for Bitcoin, which may provide an edge in the market for long-term investors.
Thank you for your interest in this indicator. If you have any questions, recommendations or feedback, please leave a comment or drop me a message on TV or twitter. I aim to be as transparent as possible with this project, so please seek clarification if you are unsure about anything.
panpanXBT BTC Risk MetricThis is the Bitcoin Risk Metric. Inspired by many power law analysts, this script assigns a risk value to the price of Bitcoin. The model uses regression of 'fair value' data to assign risk values and residual analysis to account for diminishing returns as time goes on. This indicator is for long-term investors looking to maximise their returns by highlighting periods of under and overvaluation for Bitcoin.
This is a companion script for panpanXBT BTC Risk Metric Oscillator . Use this indicator in tandem to achieve the view shown in the chart above.
Please note, this indicator will only work on BTCUSD charts but will work on any timeframe.
DISCLAIMER: The product on offer presents a novel way to view the price history of Bitcoin. It should not be relied upon solely to inform financial decisions. What you do with the information is entirely up to you. Please thoroughly consider your decisions and consult many different sources to make sure you're making the most well-informed decision.
### How to Interpret
The risk scale goes from 0 to 100,
Blue - 0 being low risk, and
Red - 100 being high risk.
Low risk values represent periods of historical undervaluation, while high values represent overvaluation. These periods are marked by a colourscale from blue to red.
### Use Cases and Best Practice
A dynamic DCA strategy would work best with this indicator, whereby an amount of capital is deployed/retired on a regular basis. This amount deployed grows or shrinks depending on the proximity of the risk level to the extremes (0 and 100).
Let's say you have a maximum of $500 to deploy per month.
When risk is between 0 and 10, you could deploy the full $500.
When risk is between 10 and 20, you could deploy $400.
When risk is between 20 and 30, you could deploy $300.
When risk is between 30 and 40, you could deploy $200.
When risk is between 40 and 50, you could deploy $100.
Conversely, when risk is above 50, you could:
Sell 1/15th of your BTC stack when risk is between 50 and 60.
Sell 2/15th of your BTC stack when risk is between 60 and 70.
Sell 3/15th of your BTC stack when risk is between 70 and 80.
Sell 4/15th of your BTC stack when risk is between 80 and 90.
Sell 5/15th of your BTC stack when risk is between 90 and 100.
This framework allows the user to accumulate during periods of undervaluation and derisk during periods of overvaluation, capturing returns in the process.
In contrast, simply setting limit orders at 0 and 100 would yield the absolute maximum returns, however there is no guarantee price will reach these levels (see 2018 where the bear market bottomed out at 20 risk, or 2021 where price topped out at 97 risk).
### Caveats
"All models are wrong, some are useful"
No model is perfect. No model can predict exactly what price will do as there are too many factors at play that determine the outcome. We use models as a guide to make better-informed decisions, as opposed to shooting in the dark. This model is not a get rich quick scheme, but rather a tool to help inform decisions should you consider investing. This model serves to highlight price extremities, which could present opportune times to invest.
### Conclusion
This indicator aims to highlight periods of extreme values for Bitcoin, which may provide an edge in the market for long-term investors.
Thank you for your interest in this indicator. If you have any questions, recommendations or feedback, please leave a comment or drop me a message on TV or twitter. I aim to be as transparent as possible with this project, so please seek clarification if you are unsure about anything.
TTP Intelligent AccumulatorThe intelligent accumulator is a proof of concept strategy. A hybrid between a recurring buy and TA-based entries and exits.
Distribute the amount of equity and add to your position as long as the TA condition is valid.
Use the exit TA condition to define your exit strategy.
Decide between adding only into losing positions to average down or take a riskier approach by allowing to add into a winning position as well.
Take full profit or distribute your exit into multiple take profit exists of the same size.
You can also decide if you allow your exit conditions to close your position in a loss or require a minimum take profit %.
The strategy includes a default built-in TA conditions just for showcasing the idea but the final intent of this script is to delegate the TA entries and exists to external sources.
The internal conditions use RSI length 7 crossing below the BB with std 1 for entries and above for exits.
To control the number of orders use the properties from settings:
- adjust the pyramiding
- adjust the percentage of equity
- make sure that pyramiding * % equity equals 100 to prevent over use of equity (unless using leverage)
The script is designed as an alternative to daily or weekly recurring buys but depending on the accuracy of your TA conditions it might prove profitable also in lower timeframes.
The reason the script is named Intelligent is because recurring buy is most commonly used without any decision making: buy no matter what with certain frequency. This strategy seeks to still perform recurring buys but filtering out some of the potential bad entries that can delay unnecessarily seeing the position in profits. The second reason is also securing an exit strategy from the beginning which no recurring buy option offers out-of-the-box.
BotDCA | Algorithmic Smart DCA Bot🌌 What the script does, how it does ?
At the heart of its algorithm, this script incorporates the concept of Dollar Cost Averaging (DCA), a method of periodically allocating funds to an asset to mitigate the effects of market volatility.
Before we start, it's important to clarify that the script is adapted for the cryptocurrency market on USDT & USDC pairs in Spot, and on the Daily timeframe (D).
For this reason, and to optimize profits, the script will generate very few buy and sell positions.
Please also note that the script does not repaint.
Essentially, BotDCA generates buy and sell orders.
These buy and sell orders are generated using the following logic :
BUYING LOGIC :
• Volume : Current volume is compared with a linear percentile of volume over a short period.
This means that if current volume is higher than observed volumes over this period, the volume criteria is considered valid.
• Momentum & Volatility : The Average True Range (ATR) indicator adjusted by a square root is used as a measure of volatility.
Momentum is then calculated as the difference between the current closing price and a short moving average, normalized by this adjusted volatility.
The oversold condition is validated when momentum exceeds a specific level.
For the buy order to be triggered, the volume, momentum and volatility criteria must be validated.
SELLING LOGIC :
• Volume : Similar to the buy logic, the volume criteria is validated when current volume is higher than previous volumes.
• Momentum & Volatility : Volatility is measured using the adjusted ATR indicator, similar to the buy logic.
An overbought condition is validated when normalized momentum, calculated as the difference between the current closing price and a volatility-adjusted short-period moving average, exceeds a specific level.
• Trend : The general market trend is considered for the sell logic.
The trend criteria is validated when the current moving average is higher than that of the previous period.
For the sell order to be triggered, the volume, momentum, volatility and trend criteria must be validated.
These orders are also adjusted according to what the user defines as buy and sell settings :
🔵 Buying settings
• Quantity per order ($) : Defines the amount in stable coins to be invested for each buy order.
• └> Mult. quantity (x) : Multiplication factor applied to the buy quantity for successive orders, enabling the investment to be increased in the event of a price fall.
Example : If Quantity per order is $200 and Mult. quantity is x2, then the second buy order will be $400, the third buy order will be $800, the fourth buy order will be $1600 ...
After a sell order, the multiplier is cancelled.
Note : If value is set to 1 : Disabled
• └> Max. quantity (x) : Sets a maximum purchase quantity limit, preventing orders from exceeding this amount.
Example : If Quantity per order is $200, Mult. quantity is x2, and Max. quantity is $700, then the second buy order will be $400, the third buy order will be $700, the fourth buy order will be $700 ...
Note : If value is less than Quantity or is set to 0 : Disabled
• └> If Price > Average price : Enable or disable quantity multiplier when current price exceeds average price.
• Min. delay (in days) : Establishes a minimum interval in days between two successive purchases to avoid investing too close together.
Example : By default the time interval for the bot is set to D, so if you set 20 as the value, the bot will wait at least 20 days between buy orders before entering a position.
Note : If value is set to 0 : Disabled
• └> Min. deviation (%) : Defines the minimum price difference in percent to trigger a new purchase after the first.
Note : If value is set to 0 : Disabled
• └> Mult. deviation (x) : Apply a multiplication factor to the price differential for successive buys, progressively increasing the purchase interval.
Example : If Mult. deviation is 10% and Min. deviation is x2, then between the first and second buy orders the minimum deviation will be 10%, between the second and third buy orders the minimum deviation will be 20%, between the third and fourth buy orders the minimum deviation will be 40%...
After a sell order, the multiplier is cancelled.
Note : If value is set to 1 : Disabled
• Display help for these settings : On chart, displays help text about buying settings.
🟢 Selling settings
• Quantity (% position) : Percentage of the position to be sold in each sell order.
Example : If the first buy order is 0.1 BTC and the second buy order is 0.2 BTC, then the position is 0.3 BTC.
If Quantity (% position) is set to 20, then the first sell order will be 0.06 BTC (20% of 0.3 BTC), the second sell order will be 0.048 BTC (20% of 0.24 BTC) ...
(Auto ?) : If this option is enabled, the bot will automatically sell part of your position.
The quantity sold depends on the volatility of the last 30 days : the higher the volatility, the more it sells, and the lower the volatility, the less it sells.
The minimum sale defined is 10%, while the maximum sale will not exceed 50%.
• └> Min. deviation (%) : Minimum percentage of price deviation to trigger a sale.
Example : If Average price of BTC is 30 000 USDT and Min. deviation is 10%, then the first sell order will be at least 33 000 USDT, the second sell order will be at least 36 300 USDT ...
Note : If value is set to 0 : Disabled
(Auto ?) : If this option is activated, the bot automatically determines the sell minimum deviation percentage.
The deviation set depends on the volatility of the last 30 days : the higher the volatility, the higher the deviation, and the lower the volatility, the lower the deviation.
A start and end date defines when the script should generate buy and sell positions :
📆 Date settings
• Start date : Indicate the script launch date (If it’s a new launch, you must choose today’s date before creating your TradingView alert).
• End date : Enter the date on which you want the script to stop.
Other parameters can be configured to fine-tune buys and sells :
⏲️ Trading session settings
• Days : Allows you to select the specific days on which the script will be active, offering the possibility of excluding certain days.
🏛️ Exchange settings
• Fees (%) : Indicate the percentage fee applied by the exchange platform on each transaction.
• Price spread (%) : Specifies the price spread to be considered for realistic order adjustment.
🤖 Bot settings
• Add to Position ? : Allows tokens to be manually added to the position when the script is launched.
• └> How much ? (Base) : Number of tokens to add.
• └> Cost ? ($) : Stable coins amount of addition to position.
These settings are included in the calculation when an order is triggered.
Advanced visual customization options can be modified :
🎨 Visual settings
• TradingView Theme : Choose between a light or dark theme for the bot interface.
• Panel : Enables or disables the display of the information panel on the graph, and modifies its size and alignment.
• Positions : Show or hide buy and sell position labels on the chart, and modify their size and appearance (several display modes : basic, simple, advanced).
• Average price : Enables or disables the display of the average price line and modifies its size and color.
• Simulator : Enables or disables the ATH percentage-based simulator line and modifies its size and color.
• Trading session : Displays or hides the background of specified trading sessions.
• Hide warning messages ? : Hide or show warning messages on graph.
A profit simulator can be configured :
🕹️ Simulator settings
• Price (% ATH) : Determines a percentage of the token's ATH to simulate potential gains if the token reaches this price level again.
Users can also activate buying and selling alerts in the settings :
🤖 Bot settings
• START THE BOT ? » ALERTS ON : REAL MODE : Enable or disable the bot to execute real orders based on alerts.
• Mode FULL Auto ? : Enables the Mode FULL Auto, requiring additional configuration for connection to exchange APIs.
• └> Password FULL Auto : Password required to activate the Mode FULL Auto.
By activating FULL Auto Mode with TradingView's webhook system, the user can connect the script to the APIs of compatible exchanges, and receive notifications of buy and sell orders by e-mail, Telegram or Discord.
On the chart, a panel displays a variety of information, and also a backtesting / result of the script.
Here is a list of elements displayed by the panel :
💻 Informations panel
General :
• Pair
• Exchange
• └> Fees
• └> Price spread
• Period
• Start date
• End date
• Trading days
Buying
• Quantity per order
• └> Mult. quantity
• └> Max. quantity
• └> If Price > Average price
• └> Min. deviation
• └> Mult. deviation
• Min. delay (in days)
Selling
• Quantity (% position)
• └> Min. deviation
Exchange
• Next buy
• Next sell
Backtesting / Results
• No. of buys
• No. of sells
• Average price
• Actual position
• Actual net profit
• └> Simulator
• Last buy
• Last sell
🌌 About default settings
Default settings are defined as an example.
Above in the description, you will find details of each setting.
Here's a description of how user-defined setting categories affect the script's buy and sell positions :
📆 Date : Determines between which time ranges buy and sell positions are generated.
⏲️ Trading session : Exclude selected days disables buy positions on deselected days.
🕹️ Simulator : Does not affect buying and selling. It is for information purposes only.
🏛️ Exchange : Fees should be as close as possible to your exchange and price spread depends on your tolerance. This affects buy and sell position.
🔵 Buy : Depending on your investment capacity and risk management, these settings have an impact on buy positions.
🟢 Sell : These settings determine profit-taking. This has an impact on sell positions.
🎨 Visual : Does not affect buy and sell positions. For information only.
🤖 Bot : This part is mainly used to use the script with TradingView alerts. Only the 'Add to position' option affects buy and sell positions.
Once you've set all your settings for the script, you can view the backtesting displayed in the panel on the chart.
🌌 How to use it ?
To summarize how to use this script successfully, please follow these steps :
1. First, choose a cryptocurrency pair (e.g. BTC/USDT).
2. Set a start date (preferably today's date if it's your first launch) and an end date.
3. According on your preferences, you can choose specific trading days, or default to all days of the week.
4. Depending on your exchange, you can set fees and a price spread.
5. Then, based on your portfolio management and investment capabilities, define buy and sell parameters.
6. You can set the bot's appearance on the chart.
7. Once you have configured your settings, you can choose a simulation price.
8. Finally, to activate TradingView Alerts, check the box START THE BOT ? ALERTS ON : REAL MODE.
🌌 Overview
Here's a preview of the script with a few screenshots :
BTC/USDT • Basic display
SOL/USDT • Simple display
XRP/USDT • Advanced display
MATIC/USDT • Light theme
Script settings
🌌 Why do I have to pay ?
BotDCA uses advanced indicators and complex calculations to identify buying and selling opportunities.
With TradingView's alert system, it automates your investment strategy, eliminating the need for constant manual analysis and constant market monitoring.
This saves you precious time.
With adjustable buy and sell settings, you can customize the script to suit your risk tolerance and investment objectives.
This flexibility adds considerable value, allowing you to optimize the script to suit your situation.
Paid access ensures that you benefit from ongoing support and updates, which are essential for maintaining the script's effectiveness.
🌌 Disclaimer
This script is provided for educational purposes only and should not be construed as investment advice.
Users should be aware that trading in the financial markets involves risks, and that past performance of a script does not guarantee future results.
It is strongly recommended that you carry out a detailed analysis and consider your financial situation and risk tolerance before committing yourself to trading/investing.
Smart DCA StrategyINSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost .
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on BITSTAMP:BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size , you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
STRATEGY IN ACTION
Here you see the indicator running on the BITSTAMP:BTCUSD pair. You can read the indicator as follows:
Vertical green bands on historical candles represents where buy signals triggered in the past
Table on the top right represents the results of the A/B backtest against a standard DCA strategy
Green Smart Buy column shows that Smart DCA was more profitable than standard DCA on this backtest. That is shown by the percentage GOA (Gain on Account) and the Avg Cost
Smart Buy Zone label marks the threshold which the entire candle must be below to trigger a buy signal (line can be changed to a box under plotting settings)
Green color of Smart Buy Zone label represents that the open candle is still valid for a buy signal. A signal will only be generated if the candle closes while this label is still green
Below is the same BITSTAMP:BTCUSD chart a couple of days later. Notice how the threshold has been broken and the Smart Buy Zone label has turned from green to red. No buy signal can be triggered for this day - even if the candle retraced and closed below the threshold before daily candle close.
Notice how the green vertical bands tend to be present after significant pullbacks in price. This is the reason the strategy works! Below is the same BITSTAMP:BTCUSD chart, but this time zoomed out to present a clearer picture of the times it would invest vs times it would sit out of the market. You will notice it invests heavily in bear markets and significant pullbacks, and does not buy anything during bull markets.
Finally, to visually demonstrate the indicator on an asset other than BTC, here is an example on CRYPTO:ETHUSD . In this case the current daily high has not touched the threshold so it is still possible for this to be a valid buy trigger on daily candle close. The vertical green band will not print until the buy trigger is confirmed.
BACKTEST RESULTS
Now for some backtest results to demonstrate the improved performance over a standard DCA strategy using all non-stablecoin assets in the top 30 cryptos by marketcap.
I've used the TradingView ticker (exchange name denoted as CRYPTO in the symbol search) for every symbol tested with the exception of BTCUSD because there was some dodgy data at the beginning of the TradingView BTCUSD chart which overinflated the effectiveness of the Smart DCA strategy on that ticker. For BTCUSD I've used the BITSTAMP exchange data. The symbol links below will take you to the correct chart and exchange used for the test.
I'm using the GOA (Gain on Account) values to present how each strategy performed.
The value on the left side is the standard DCA result and the right is the Smart DCA result.
✅ means Smart DCA strategy outperformed the standard DCA strategy
❌ means standard DCA strategy outperformed the Smart DCA strategy
To avoid overfitting, and to prove that this strategy does not suffer from overfitting, I've used the exact same input parameters for every symbol tested below. The settings used in these backtests are:
Buying strictness scale: 9
Validation days: 0
You can absolutely tweak the values per symbol to further improve the results of each, however I think using identical settings on every pair tested demonstrates a higher likelihood that the results will be similar in the live markets.
I'm presenting results for two time periods:
First price data available for trading pair -> closing candle on Friday 26th Jan 2024 (ALL TIME)
Opening candle on Sunday 1st Jan 2023 -> closing candle on Friday 26th Jan 2024 (JAN 2023 -> JAN 2024)
ALL TIME:
BITSTAMP:BTCUSD 80,884% / 133,582% ✅
CRYPTO:ETHUSD 17,231% / 36,146% ✅
CRYPTO:BNBUSD 5,314% / 2,702% ❌
CRYPTO:SOLUSD 1,745% / 1,171% ❌
CRYPTO:XRPUSD 2,585% / 4,544% ✅
CRYPTO:ADAUSD 338% / 353% ✅
CRYPTO:AVAXUSD 130% / 160% ✅
CRYPTO:DOGEUSD 13,690% / 16,432% ✅
CRYPTO:TRXUSD 414% / 466% ✅
CRYPTO:DOTUSD -16% / -7% ✅
CRYPTO:LINKUSD 1,161% / 2,164% ✅
CRYPTO:TONUSD 25% / 47% ✅
CRYPTO:MATICUSD 1,769% / 1,587% ❌
CRYPTO:ICPUSD 70% / 50% ❌
CRYPTO:SHIBUSD -20% / -19% ✅
CRYPTO:LTCUSD 486% / 718% ✅
CRYPTO:BCHUSD -4% / 3% ✅
CRYPTO:LEOUSD 102% / 151% ✅
CRYPTO:ATOMUSD 46% / 91% ✅
CRYPTO:UNIUSD -16% / 1% ✅
CRYPTO:ETCUSD 283% / 414% ✅
CRYPTO:OKBUSD 1,286% / 1,935% ✅
CRYPTO:XLMUSD 1,471% / 1,592% ✅
CRYPTO:INJUSD 830% / 1,035% ✅
CRYPTO:OPUSD 138% / 195% ✅
CRYPTO:NEARUSD 23% / 44% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset since the creation of each asset, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 4,998.65%
Profit: $499,865
Closing balance: $509,865
Smart DCA Strategy results:
Average percent return: 7,906.03%
Profit: $790,603
Closing balance: $800,603
JAN 2023 -> JAN 2024:
BITSTAMP:BTCUSD 47% / 66% ✅
CRYPTO:ETHUSD 26% / 33% ✅
CRYPTO:BNBUSD 15% / 17% ✅
CRYPTO:SOLUSD 272% / 394% ✅
CRYPTO:XRPUSD 7% / 12% ✅
CRYPTO:ADAUSD 43% / 59% ✅
CRYPTO:AVAXUSD 116% / 151% ✅
CRYPTO:DOGEUSD 8% / 14% ✅
CRYPTO:TRXUSD 48% / 65% ✅
CRYPTO:DOTUSD 24% / 35% ✅
CRYPTO:LINKUSD 83% / 124% ✅
CRYPTO:TONUSD 7% / 21% ✅
CRYPTO:MATICUSD -3% / 7% ✅
CRYPTO:ICPUSD 161% / 196% ✅
CRYPTO:SHIBUSD 1% / 8% ✅
CRYPTO:LTCUSD -15% / -7% ✅
CRYPTO:BCHUSD 47% / 68% ✅
CRYPTO:LEOUSD 9% / 11% ✅
CRYPTO:ATOMUSD 1% / 15% ✅
CRYPTO:UNIUSD 9% / 23% ✅
CRYPTO:ETCUSD 27% / 40% ✅
CRYPTO:OKBUSD 21% / 30% ✅
CRYPTO:XLMUSD 11% / 19% ✅
CRYPTO:INJUSD 477% / 446% ❌
CRYPTO:OPUSD 77% / 91% ✅
CRYPTO:NEARUSD 78% / 95% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset for the duration of 2023, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 61.42%
Profit: $6,142
Closing balance: $16,142
Smart DCA Strategy results:
Average percent return: 78.19%
Profit: $7,819
Closing balance: $17,819
CARNAC Magic DCAThe "CARNAC Magic DCA" indicator is designed for investors looking for the best opportunities for Dollar-Cost Averaging (DCA).
How it works:
The Carnac Dynamic DCA Threshold calculates a dynamic threshold for DCA entries using Exponential Moving Average (EMA), Average True Range (ATR), and the maximum distance from the EMA over a full lookback period, aiding in identifying optimal buy opportunities. It also only signals a DCA buying opportunity after a bearish candle, which helps lower the average DCA price.
Configurable Inputs:
EMA Start Length: Sets the initial length for the series of EMAs, affecting their sensitivity to price changes.
ATR Length: Determines the period for the ATR calculation, influencing the dynamic DCA threshold's responsiveness to market volatility.
ATR Multiplier: Modifies the impact of the ATR on the DCA threshold, allowing for finer control over the threshold's sensitivity to volatility.
Start Calculation From: Enables setting a specific start date for calculations, tailoring the analysis to a particular trading period.
DCA Buy Signal Alert: Generates an alert when the price is below both the dynamic DCA threshold and the opening price, indicating a potential buy signal based on DCA strategy.
Ten EMAs: Carnac Magic DCA includes a ten EMA plot, which decrease in length from the user-defined starting length, offering a multi-layered trend analysis.
EMA Color Coding: The sequential arrangement of EMAs is visually represented through color coding, facilitating quick trend recognition.
Average Buy Price Analysis: Calculates and displays the average buy price and its percentage difference from the average closing price since the user-defined start date, helping assess the strategy’s effectiveness compared to traditional DCA methods (purchasing at the close of every candle).
Visual Indicators and Labels: Includes visual alerts for buy signals and informative labels showing average buy prices and related statistics.
Martingale + Grid DCA Strategy [YinYangAlgorithms]This Strategy focuses on strategically Martingaling when the price has dropped X% from your current Dollar Cost Average (DCA). When it does Martingale, it will create a Purchase Grid around this location to likewise attempt to get you a better DCA. Likewise following the Martingale strategy, it will sell when your Profit has hit your target of X%.
Martingale may be an effective way to lower your DCA. This is due to the fact that if your initial purchase; or in our case, initial Grid, all went through and the price kept going down afterwards, that you may purchase more to help lower your DCA even more. By doing so, you may bring your DCA down and effectively may make it easier and quicker to reach your target profit %.
Grid trading may be an effective way of reducing risk and lowering your DCA as you are spreading your purchases out over multiple different locations. Likewise we offer the ability to ‘Stack Grids’. What this means, is that if a single bar was to go through 20 grids, the purchase amount would be 20x what each grid is valued at. This may help get you a lower DCA as rather than creating 20 purchase orders at each grid location, we create a single purchase order at the lowest grid location, but for 20x the amount.
By combining both Martingale and Grid DCA techniques we attempt to lower your DCA strategically until you have reached your target profit %.
Before we start, we just want to make it known that first off, this Strategy features 8% Commission Fees, you may change this in the Settings to better reflect the Commission Fees of your exchange. On a similar note, due to Commission Fees being one of the number one profit killers in fast swing trade strategies, this strategy doesn’t focus on low trades, but the ideology of it may result in low amounts of trades. Please keep in mind this is not a bad thing. Since it has the ability to ‘Stack Grid Purchases’ it may purchase more for less and result in more profit, less commission fees, and likewise less # of trades.
Tutorial:
In this example above, we have it set so we Martingale twice, and we use 100 grids between the upper and lower level of each martingale; for a total of 200 Grids. This strategy will take total capital (initial capital + net profit) and divide it by the amount of grids. This will result in the $ amount purchased per grid. For instance, say you started with $10,000 and you’ve made $2000 from this Strategy so far, your total capital is $12,000. If you likewise are implementing 200 grids within your Strategy, this will result in $12,000 / 200 = $60 per grid. However, please note, that the further down the grid / martingale is, the more volume it is able to purchase for $60.
The white line within the Strategy represents your DCA. As the Strategy makes purchases, this will continue to get lower as will your Target Profit price (Blue Line). When the Close goes above your Target Profit price, the Strategy will close all open positions and claim the profit. This profit is then reinvested back into the Strategy, which may exponentially help the Strategy become more profitable the longer it runs for.
In the example above, we’ve zoomed in on the first example. In this we want to focus on how the Strategy got back into the trades shortly after it sold. Currently within the Settings we have it set so our entry is when the Lowest with a length of 3 is less than the previous Lowest with a length of 3. This is 100% customizable and there are multiple different entry options you can choose from and customize such as:
EMA 7 Crossover EMA 21
EMA 7 Crossunder EMA 21
RSI 14 Crossover RSI MA 14
RSI 14 Crossunder RSI MA 14
MFI 14 Crossover MFI MA 14
MFI 14 Crossunder MFI MA 14
Lowest of X Length < Previous Lowest of X Length
Highest of X Length > Previous Highest of X Length
All of these entry options may be tailored to be checked for on a different Time Frame than the one you are currently using the Strategy on. For instance, you may be running the Strategy on the 15 minute Time Frame yet decide you want the RSI to cross over the RSI MA on the 1 Day to be a valid entry location.
Please keep in mind, this Strategy focuses on DCA, this means you may not want the initial purchase to be the best location. You may want to buy when others think it is a good time to sell. This is because there may be strong bearish momentum which drives the price down drastically and potentially getting you a good DCA before it corrects back up.
We will continue to add more Entry options as time goes on, and if you have any in mind please don’t hesitate to let us know.
Now, back to the example above, if we refer to the Yellow circle, you may see that the Lowest of a length of 3 was less than its previous lowest, this triggered the martingales to create their grids. Only a few bars later, the price went into the first grid and went a little lower than its midpoint (Yellow line). This caused about 60% of the first grid to be purchased. Shortly after the price went even lower into this grid and caused the entire first martingale grid to be purchased. However, if you notice, the white line (your DCA) is lower than the midpoint of the first grid. This is due to the fact that we have ‘Stack Grid Purchases’ enabled. This allows the Strategy to purchase more when a single bar crosses through multiple grid locations; and effectively may lower your average more than if it simply executed a purchase order at each grid.
Still looking at the same location within our next example, if we simply increase the Martingale amount from 2 to 3 we can see something strange happens. What happened is our Target Profit price was reached, then our entry condition was met, which caused all of the martingale grids to be formed; however, the price continued to increase afterwards. This may not be a good thing, sure the price could correct back down to these grid locations, but what if it didn’t and it just kept increasing? This would result in this Strategy being stuck and unable to make any trades. For this reason we have implemented a Failsafe in the Settings called ‘Reset Grids if no purchase happens after X bars’.
We have enabled our Failsafe ‘Reset Grids if no purchase happens after X bars’ in this example above. By default it is set to 100 bars, but you can change this to whatever works best for you. If you set it to 0, this Failsafe will be disabled and act like the example prior where it is possible to be stuck with no trades executing.
This Failsafe may be an important way to ensure the Strategy is able to make purchases, however it may also mean the Grids increase in price when it is used, and if a massive correction were to occur afterwards, you may lose out on potential profit.
This Strategy was designed with WebHooks in mind. WebHooks allow you to send signals from the Strategy to your exchange. Simply set up a Custom TradingView Bot within the OKX exchange or 3Commas platform (which has your exchange API), enter the data required from the bot into the settings here, select your bot type in ‘Webhook Alert Type’, and then set up the alert. After that you’re good to go and this Strategy will fully automate all of its trades within your exchange for you. You need to format the Alert a certain way for it to work, which we will go over in the next example.
Add an alert for this Strategy and simply modify the alert message so all it says is:
{{strategy.order.alert_message}}
Likewise change from the Alert ‘Settings’ to Alert ‘Notifications’ at the top of the alert popup. Within the Notifications we will enable ‘Webhook URL’ and then we will pass the URL we are sending the Webhook to. In this example we’ve put OKX exchange Webhook URL, however if you are using 3Commas you’ll need to change this to theirs.
OKX Webhook URL:
www.okx.com
3Commas Webhook URL:
app.3commas.io
Make sure you click ‘Create’ to actually create this alert. After that you’re all set! There are many Tutorials videos you can watch if you are still a little confused as to how Webhook trading works.
Due to the nature of this Strategy and how it is designed to work, it has the ability to never sell unless there it will make profit. However, because of this it also may be stuck waiting in trades for quite a long period of time (usually a few months); especially when your Target Profit % is 15% like in the example above. However, this example above may be a good indication that it may maintain profitability for a long period of time; considering this ‘Deep Backtest’ is from 2017-8-17.
We will conclude the tutorial here. Hopefully you understand how this Strategy has the potential to make calculated and strategic DCA Grid purchases for you and then based on a traditional Martingale fashion, bulk sell at the desired Target Profit Percent.
Settings:
Purchase Settings:
Only Purchase if its lower than DCA: Generally speaking, we want to lower our Average, and therefore it makes sense to only buy when the close is lower than our current DCA and a Purchase Condition is met.
Purchase Condition: When creating the initial buy location you must remember, you want to Buy when others are Fearful and Sell when others are Greedy. Therefore, many of the Buy conditions involve times many would likewise Sell. This is one of the bonuses to using a Strategy like this as it will attempt to get you a good entry location at times people are selling.
Lower / Upper Change Length: This Lower / Upper Length is only used if the Purchase Condition is set to 'Lower Changed' or 'Upper Changed'. This is when the Lowest or Highest of this length changes. Lowest would become lower or Highest would become higher.
Purchase Resolution: Purchase Resolution is the Time Frame that the Purchase Condition is calculated on. For instance, you may only want to start a new Purchase Order when the RSI Crosses RSI MA on the 1 Day, but yet you run this Strategy on the 15 minutes.
Sell Settings:
Trailing Take Profit: Trailing Take Profit is where once your Target Profit Percent has been hit, this will trail up to attempt to claim even more profit.
Target Profit Percent: What is your Target Profit Percent? The Strategy will close all positions when the close price is greater than your DCA * this Target Profit Percent.
Grid Settings:
Stack Grid Purchases: If a close goes through multiple Buy Grids in one bar, should we amplify its purchase amount based on how many grids it went through?
Reset Grids if no purchase happens after X Bars: Set this to 0 if you never want to reset. This is very useful in case the price is very bullish and continues to increase after our Target Profit location is hit. What may happen is, Target Profit location is hit, then the Entry condition is met but the price just keeps increasing afterwards. We may not want to be sitting waiting for the price to drop, which may never happen. This is more of a failsafe if anything. You may set it very large, like 500+ if you only want to use it in extreme situations.
Grid % Less than Initial Purchase Price: How big should our Buy Grid be? For instance if we bought at 0.25 and this value is set to 20%, that means our Buy Grid spans from 0.2 - 0.25.
Grid Amounts: How many Grids should we create within our Buy location?
Martingale Settings:
Amount of Times 'Planned' to Martingale: The more Grids + the More Martingales = the less $ spent per grid, however the less risk. Remember it may be better to be right and take your time than risk too much and be stuck too long.
Martingale Percent: When the current price is this percent less than our DCA, lets create another Buy Grid so we can lower our average more. This will make our profit location less.
Webhook Alerts:
Webhook Alert Type: How should we format this Alert? 3Commas and OKX take their alerts differently, so please select the proper one or your webhooks won't work.
3Commas Webhook Alerts:
3Commas Bot ID: The 3Commas Bot ID is needed so we know which BOT ID we are sending this webhook too.
3Commas Email Token: The 3Commas Email Token is needed for your webhooks to work properly as it is linked to your account.
OKX Webhook Alerts:
OKX Signal Token: This Signal Token is attached to your OKX bot and will be used to access it within OKX.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Grospector DCA V.4This is system for DCA with strategy and can trade on trend technique "CDC Action Zone".
We upgrade Grospector DCA V.3 by minimizing unnecessary components and it is not error price predictions.
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Idea : Everything has average in its life. For bitcoin use 4 years for halving. I think it will be interesting price.
Default : I set MA is 365*4 days and average it again with 365 days.
Input :
len: This input represents the length of the moving average.
strongLen: This input represents the length of the moving average used to calculate the strong buy and strong sell zone.
shortMulti: This input represents the multiplier * moveing average used to calculate the short zone.
strongSellMulti: This input represents the multiplier used to calculate the strong sell signal.
sellMulti: This input represents the multiplier * moveing average used to calculate the sell zone.
strongBuyMulti: This input represents the multiplier used to calculate the strong sell signal.
longMulti: This input represents the multiplier * moveing average used to calculate the long zone.
*Diff sellMulti and strongBuyMulti which is normal zone.
useDerivative: This input is a boolean flag that determines whether to use the derivative display zone. If set to true, the derivative display zone will be used, otherwise it will be hidden.
zoneSwitch: This input determines where to display the channel signals. A value of 1 will display the signals in all zones, a value of 2 will display the signals in the chart pane, a value of 3 will display the signals in the data window, and a value of 4 will hide the signals.
price: Defines the price source used for the indicator calculations. The user can select from various options, with the default being the closing price.
labelSwitch: Defines whether to display assistive text on the chart. The user can select a boolean value (true/false), with the default being true.
zoneSwitch: Defines which areas of the chart to display assistive zones. The user can select from four options: 1 = all, 2 = chart only, 3 = data only, 4 = none. The default value is 2.
predictFuturePrice: Defines whether to display predicted future prices on the chart. The user can select a boolean value (true/false), with the default being true.
DCA: Defines the dollar amount to use for dollar-cost averaging (DCA) trades. The user can input an integer value, with a default value of 5.
WaitingDCA: Defines the amount of time to wait before executing a DCA trade. The user can input a float value, with a default value of 0.
Invested: Defines the amount of money invested in the asset. The user can input an integer value, with a default value of 0.
strategySwitch: Defines whether to turn on the trading strategy. The user can select a boolean value (true/false), with the default being true.
seperateDayOfMonth: Defines a specific day of the month on which to execute trades. The user can input an integer value from 1-31, with the default being 28.
useReserve: Defines whether to use a reserve amount for trading. The user can select a boolean value (true/false), with the default being true.
useDerivative: Defines whether to use derivative data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
useHalving: Defines whether to use halving data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
extendHalfOfHalving: Defines the amount of time to extend the halving date. The user can input an integer value, with the default being 200.
Every Zone: It calculate percent from top to bottom which every zone will be splited 10 step.
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
Broadview Algorithmic StudioWelcome! This is the writeup for the Broadview Algorithmic Studio.
There are many unique features in this script.
- Broadview Underpriced & Overpriced
- Broadview Blackout Bollinger Bands
- Trailing Take Profit Suite
- Algorithmic Weights
- VSA Score
- Pip Change Log
- Activation Panel
- Weight Scanner
There are 116 primary inputs that allow users to algorithmically output unique DCA signal-sets. There are 85 inputs that allow users to control individual lengths, levels, thresholds, and multiplicative weights of the script. You will not find any other script with this many inputs, properly strung together for you to produce unlimited strategies for any market. The entire premise for the Broadview Algorithmic Studio is for users to be able to have extensive-cutting-edge features that allow them to produce more strategies, having control over every element that outputs a signal set. The number of unique strategies you can output with this script is VAST, and each continues to follow a safe DCA methodology.
This script is ready for use with 3Commas, interactive brokers, and other means of automation. It provides detailed information on Base Orders and Safety Orders, giving the number, cumulative spending, position average, and remaining balance for each SO in the series. Using this script we will explore the depths of strategic volume scaling, and the algorithms we use to determine spending.
Let me first start by saying the number of safe DCA-friendly signal-sets this script can output is absolutely staggering.
Let's limit the scope just to the Broadview Underpriced & Overpriced and Broadview Dominance indicators.
Each band of the Dominance Suite can be controlled individually with unique lengths, levels, and weights. This means the Dominance Suite can establish Bearish or Bullish dominance, in any market condition, and give it a unique overloading weight. The Broadview Underpriced & Overpriced indicator finally gives us the ability to establish these "market conditions" first with cycles. Of all the cycles this indicator establishes, the two primary are Underpriced & Overpriced. We determine this using a composite Overbought & Oversold with an Exponential Moving Average. So the script can now know, what cycle it is in, who is dominant during that cycle, and exactly how much weight in volume scaling the order should have.
Brand new is the ability for indicators of this level to be able to talk together in a single script. The Broadview Underpriced & Overpriced indicator and the Broadview Dominance indicator can inform one another across multiple vectors, create a unique market snapshot, and give that snapshot a unique weight every bar. The unique weight is compiled in the volume scaling math, thus giving us an automated-strategic-safe and quite efficient volume scaling for every order. In our coming updates we will explore this synergy to its very deepest layers. These indicators can be laced together in many ways, called vectors.
Only in the Algorithmic Studio do we explore these depths and yield those findings, features, and inputs to the user.
Let me take a quick break to explain another area-of-opportunity for our research and development.
The VSA Score is something we've tried before, but until the creation of the Broadview Blackout Bollinger Bands Auto Indicator it was not possible. The concept we want to explore is "Positional Honing". Over time we want users and the script itself to be able to understand the difference between a script-config that produces a high number of Hits, from a configuration that produces a high number of "Misses". The Volume Scaling Accuracy Score uses the BBB Auto Indicator as a heavily reliable, non-repainting, method of determining what the very-best signals for increased volume-scaling are.
Increased volume scaling is denoted by the near-white highlighter line running vertically. This line will either fall inside the BBB Auto Indicator bands (which are hidden), or, they will fall below and outside the BBB Auto bands. If increased spending happens inside the bands it's a "Miss". If increased spending happens below and outside the bands, it's a Hit. Oftentimes misses are actually pretty good spots for extra spending, which helps lower your position average, but Hits are always better. The Hits that the BBB Auto Indicator provides are extremely good.
Let's talk about the Trailing Take Profit Suite. This suite allows us to set a trailing take profit which is a feature that lets one maximize their profits. If the trailing take profit is engaged, then when the regular take profit is hit, it will trigger, denoted in red vertical lines, and the trailing take profit will look for a specified rate of change before it actually takes profit. This usually helps traders in those times when their regular take profit was set too low, allowing them to maximize their profits with a Trailing Take Profit.
For the moment, let's think about our scores. In the dashboard you'll notice a score beginning the Pip Change Log, the VSA Score, and the Activation Panel.
These scores use a new kind of logistic correlation formula where 4 digits are given to activation, rather than 1. This is to allow room for a future concept in AI we call "Deadzones" or you can think of it as impedance. This is not a bias in logistic regression. It's an entirely different concept. A neuron, which a perceptron attempts to mimic, has a bias.. but it also has a sort of electrical resistance. This is because a neuron is individually-alive entity. So a perceptron, as it were, would need to have both a bias and a natural resistance, or deadzone.
It is a lot of fun to watch the scores and how they react during playback. They tend to smooth trends but are also quite quick to correct to accuracy. In the future we will add the deadzones and biases to the scores. This should help both users and the script produce better signal sets. The Pip Change Log is an indicator that measures Rate of Change in Pips. This is one that I am particularly excited to study, as I am a huge fan of ROC. The Activation Panel shows these scores for 4 primary indicators: On Balance Volume, Relative Strength Index, Average Directional Index, and Average True Range.
Having the Pip Change Log, VSA Score, and Activation Panel up on the dashboard with their logistic correlation scores allows traders to study markets and setups quite intimately. The weight scanner at the bottom allows users to track the cumulative applied multiplicative weights during playback. The massive number of inputs, connected vectors of indicators, input-weights, lengths, levels, and thresholds sets up all the algorithmic infrastructure for powerusers to explore every idea and strategy output they could imagine. Also with the connected vector infrastructure we can deepen our indicators in a way where, "How they talk to each other.", comes first in every development conversation.
The Algorithmic Studio is for the Power-user.
These are not basic equations coming together to determine spending. This is a massive multi-layered-perceptron with everything from Trailing-Take-Profits to strategic-automatic algorithmic downscaling. The Broadview Algorithmic Studio gives a home to the poweruser who wants access to everything in a trading and investing AI, right up until the backpropagation. The Broadview Algorithmic Studio, gives users the ability to sit in the chair of the would-be AI.
Thank you.
Greedy DCA█ OVERVIEW
Detect price crashes in volatile conditions. This is an indicator for a greedy dollar cost average (DCA) strategy. That is, for people who want to repeatedly buy an asset over time when its price is crashing.
█ CONCEPTS
Price crashes are indicated if the price falls below one or more of the 4 lower Bollinger Bands which are calculated with increasing multipliers for the standard deviation.
In these conditions, the price is far below the average. Therefore they are considered good buying opportunities.
No buy signals are emitted if the Bollinger Bands are tight, i.e. if the bandwidth (upper -lower band) is below the value of the moving average multiplied with a threshold factor. This ensures that signals are only emitted if the conditions are highly volatile.
The Bollinger Bands are calculated based on the daily candles, irrespective the chart time frame. This allows to check the strategy on lower time frames
DCA Liquidation Calculation [ChartPrime]The DCA Liquidation Calculator is a powerful table indicator designed for both manual and bot-assisted traders who practice Dollar Cost Averaging (DCA). Its primary objective is to help traders avoid getting liquidated and make informed decisions when managing their positions. This comprehensive table indicator provides essential information to DCA traders, enabling them to plan their trades effectively and mitigate potential risks of liquidation.
Key Features:
Liquidation Price Awareness: The DCA Liquidation Calculator calculates and displays the liquidation price for each trade within your position. This critical information empowers traders to set appropriate stop-loss levels and avoid being liquidated in adverse market conditions, especially in leveraged trading scenarios.
DCA Recommendations: Whether you are executing DCA manually or using a trading bot, the DCA Liquidation Calculator offers valuable guidance. It suggests optimal entry prices and provides insights into the percentage deviation from the current market price, helping traders make well-timed and well-informed DCA decisions.
Position Sizing: Proper position sizing is essential for risk management. The DCA Liquidation Calculator helps traders determine the percentage of capital to allocate to each trade based on the provided insights. By using the recommended position sizing, traders can protect their capital and potentially maximize profits.
Profit and Loss Visualization: Gain real-time visibility into your Profit and Loss (PnL) with the DCA Liquidation Calculator. This feature allows you to monitor your trades' performance, enabling you to adapt your strategies as needed and make data-driven decisions.
Margin Call Indicators: Anticipating potential margin calls is crucial for maintaining a healthy trading account. The DCA Liquidation Calculator's smart analysis helps you identify and manage potential margin call situations, reducing the risk of account liquidation.
Capital Requirements: Before entering a trade, it's vital to know the required capital. The DCA Liquidation Calculator provides you with this information, ensuring you are adequately prepared to execute your trades without overextending your resources.
Maximum Trade Limit: Considering your available capital, the DCA Liquidation Calculator helps you determine the maximum number of trades you can enter. This feature ensures you maintain a disciplined and sustainable trading approach aligned with your financial capabilities.
Color-Coded Risk Indicators:
Green Liquidation Price Cell: Indicates that the position is considered safe from liquidation at the given parameters.
Yellow Liquidation Price Cell: Warns traders of potential liquidation risk. Exercise caution and monitor the trade closely to avoid undesirable outcomes.
Purple Liquidation Price Cell: Shows the liquidation price, but it does not necessarily indicate an imminent liquidation. Use this information to make prudent risk management decisions.
Red Row: Signals that the trade cannot be executed due to insufficient capital. Consider alternative strategies or ensure adequate capitalization before proceeding.
Settings explained:
In conclusion, the DCA Liquidation Calculator equips traders with essential tools to make well-calculated decisions, minimize liquidation risks, and optimize their Dollar Cost Averaging strategy. By offering comprehensive insights into your trading position, this indicator empowers you to navigate the markets with confidence and increase your potential for successful and sustainable trading.
Average purchase price 0.1 [PATREND]
Average purchase price
This tool calculates the average purchase and sell price and the profit/loss ratio for the selected symbol based on the user's inputs for the purchase and sell prices and the entry and exit amounts.
Using Average purchase price with DCA strategy
This tool can be used to track the performance of your dollar cost averaging (DCA) investment strategy.
This tool allows you to enter information about your purchase and sell transactions, such as the purchase and sell price and the entry and exit amount, and it calculates the average purchase and sell price and the profit/loss ratio based on this information.
When using a DCA strategy, you can enter information about your regular purchase and sell transactions and the tool will calculate the average purchase and sell price for you.
You can use this information to determine if your strategy is working well and make the necessary adjustments.
In addition, this tool can help you determine when you should increase or decrease the regular investment amounts that you make as part of your DCA strategy.
It can also show you the profit/loss ratio for each sell transaction that you made.
_________________________________
We hope you find it useful.
Don't hesitate to try this tool and customize its settings to meet your trading needs.
We look forward to seeing your opinions and comments.
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Average purchase price
هذه الأداة تحسب متوسط سعر الشراء والبيع ونسبة الربح / الخسارة للرمز المحدد بناءً على إدخالات المستخدم لأسعار الشراء والبيع ومبالغ الدخول والخروج.
استخدام Average purchase price مع استراتيجية DCA
يمكن استخدام هذه الأداة لتتبع أداء استراتيجية الاستثمار المتوسط التكلفة الدولارية (DCA) الخاصة بك.
تتيح لك هذه الأداة إدخال معلومات عن عمليات الشراء والبيع الخاصة بك، مثل سعر الشراء والبيع وكمية الدخول والخروج، ويقوم بحساب متوسط سعر الشراء والبيع ونسبة الربح / الخسارة بناءً على هذه المعلومات.
عند استخدام استراتيجية DCA، يمكنك إدخال معلومات عن عمليات الشراء والبيع المنتظمة التي تقوم بها وستقوم الأداة بحساب متوسط سعر الشراء والبيع لك. يمكنك استخدام هذه المعلومات لتحديد ما إذا كانت استراتيجيتك تعمل بشكل جيد وإجراء التعديلات اللازمة.
بالإضافة إلى ذلك
يمكن لهذه الأداة مساعدتك في تحديد متى يجب عليك زيادة أو تقليل مبالغ الاستثمار المنتظمة التي تقوم بها كجزء من استراتيجية DCA. كما يمكنها أن تظهر لك نسبة الربح / الخسارة في كل عملية بيع قمت بها.
تصرف كخبير ترجمه مختص باسواق المال وترجم هذا النص للغه الانكليزيه بشكل دقيق
_________________________________
نأمل أن تجدوه مفيدًا لكم .
لا تترددوا في تجربة هذه الأداة وتخصيص إعداداتها لتلبية احتياجاتكم التداولية.
نتطلع إلى رؤية آرائكم وتعليقاتكم .
GDCA ScreenerThis is upgrated system for Screener to DCA from "Grospector DCA V.3".
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Price Type: Allows the user to select the price type (open, high, low, close) for calculations.
ALL SET
Length MA for normal zone: The length of the moving average used in the normal zone.
Length for strong zone: The length of the moving average used in the strong zone, which is averaged from the normal zone moving average.
Multiple for Short: The multiplication factor applied to determine the threshold for the short zone.
Multiple for Strong Sell: The multiplication factor applied to determine the threshold for the strong sell zone.
Multiple for Sell Zone: The multiplication factor applied to determine the threshold for the sell zone.
Multiple for Buy Zone: The multiplication factor applied to determine the threshold for the buy zone.
Multiple for Strong Buy: The multiplication factor applied to determine the threshold for the strong buy zone.
Multiple for Long: The multiplication factor applied to determine the threshold for the long zone.
ZONE
Start Short Zone %: The start percentage of the short zone.
End Short Zone %: The end percentage of the short zone.
Start Sell Zone %: The start percentage of the sell zone.
End Sell Zone %: The end percentage of the sell zone.
Start Normal Zone %: The start percentage of the normal zone.
End Normal Zone %: The end percentage of the normal zone.
Start Buy Zone %: The start percentage of the buy zone.
End Buy Zone %: The end percentage of the buy zone.
Start Long Zone %: The start percentage of the long zone.
End Long Zone %: The end percentage of the long zone.
DISPLAY
Show Price: Controls the visibility of the price column in the display table.
Show Mode: Controls the visibility of the mode column in the display table.
Show GDCA: Controls the visibility of the GDCA column in the display table.
Show %: Controls the visibility of the percentage column in the display table.
Show Short: Controls the visibility of the short column in the display table.
Show Strong Sell: Controls the visibility of the strong sell column in the display table.
Show Sell: Controls the visibility of the sell column in the display table.
Show Buy: Controls the visibility of the buy column in the display table.
Show Strong Buy: Controls the visibility of the strong buy column in the display table.
Show Long: Controls the visibility of the long column in the display table.
Show Suggestion Trend: Controls the visibility of the suggestion trend column in the display table.
Show Manual Custom Code: Controls the visibility of the manual custom code column in the display table.
Show Dynamic Trend: Controls the visibility of the dynamic trend column in the display table.
Symbols: Boolean parameters that control the visibility of individual symbols in the display table.
Mode: Integer parameters that determine the mode for each symbol, specifying different settings or trends.
My mindset has been customed = AAPL , MSFT
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
DCA-Integrated Trend Continuation StrategyIntroducing the DCA-Integrated Trend Continuation Strategy 💼💰
The DCA-Integrated Trend Continuation Strategy represents a robust trading methodology that harnesses the potential of trend continuation opportunities while seamlessly incorporating the principles of Dollar Cost Averaging (DCA) as a risk management and backup mechanism. This strategy harmoniously blends these two concepts to potentially amplify profitability and optimize risk control across diverse market conditions.
This strategy is well-suited for both trending and ranging markets. During trending markets, it aims to capture and ride the momentum of the trend while optimizing entry points. In ranging markets or pullbacks, the DCA feature comes into play, allowing users to accumulate more assets at potentially lower prices and potentially increase profits when the market resumes its upward trend. This cohesive approach not only enhances the overall effectiveness of the strategy but also fosters a more resilient and adaptable trading approach in ever-changing market dynamics.
💎 How it Works:
▶️ The strategy incorporates a customizable entry signal based on candlestick patterns, enabling the identification of potential trend continuation opportunities. By focusing on consecutive bullish candles, it detects the presence of bullish momentum, indicating an optimal time to enter a long position.
To refine the precision of the signals, traders can set a specific percentage threshold for the closing price of the candle, ensuring it is above a certain percentage of its body. This condition verifies strong bullish momentum and confirms significant upward movement within the candle, thereby increasing the reliability of the signal.
In addition, the strategy offers further confirmation by examining the relationship between the closing price of the signal candle and its previous candles. If the closing price of the signal candle is higher than its preceding candles, it provides an additional layer of assurance before entering a position. This approach is particularly effective in detecting sharp movements and capturing significant price shifts, as it focuses on identifying instances where the closing price shows clear strength and outperforms the previous candle's price action. By prioritizing such occurrences, the strategy aims to capture robust trends and capitalize on notable market movements.
▶️ During market downturns, the strategy incorporates intelligent management of price drops, offering flexibility through fixed or customizable price drop percentages. This unique feature allows for additional entries at specified drop percentages, enabling traders to accumulate positions at more favorable prices.
By strategically adjusting the custom price drop percentages, you can optimize your entry points to potentially maximize profitability. Utilizing lower percentages for initial entries takes advantage of price fluctuations, potentially yielding higher returns. On the other hand, employing higher percentages for final entries adopts a more cautious approach during significant market downturns, emphasizing enhanced risk management. This adaptive approach ensures that the strategy effectively navigates challenging market conditions while seeking to optimize overall performance.
▶️ To enhance performance and mitigate risks, the strategy integrates average purchase price management. This feature dynamically adjusts the average buy price percentage decrease after each price drop, expediting the achievement of the target point even in challenging market conditions. By reducing recovery times and ensuring investment safety, this strategy optimizes outcomes for traders.
▶️ Risk management is at the core of this strategy, prioritizing the protection of capital. It incorporates an account balance validation mechanism that conducts automatic checks prior to each entry, ensuring alignment with available funds. This essential feature provides real-time insights into the affordability of price drops and the number of entries, enabling traders to make informed decisions and maintain optimal risk control.
▶️ Furthermore, the strategy offers take profit options, allowing traders to secure gains by setting fixed percentage profits from the average buy price or using a trailing target. Stop loss protection is also available, enabling traders to set a fixed percentage from the average purchase price to limit potential losses and preserve capital.
▶️ This strategy is fully compatible with third-party trading bots, allowing for easy connectivity to popular trading platforms. By leveraging the TradingView webhook functionality, you can effortlessly link the strategy to your preferred bot and receive accurate signals for position entry and exit. The strategy provides all the necessary alert message fields, ensuring a smooth and user-friendly trading experience. With this integration, you can automate the execution of trades, saving time and effort while enjoying the benefits of this powerful strategy.
🚀 How to Use:
To effectively utilize the DCA-Integrated Trend Continuation Strategy, follow these steps:
1. Choose your preferred DCA Mode - whether by quantity or by value - to determine how you want to size your positions.
2. Customize the entry conditions of the strategy to align with your trading preferences. Specify the number of consecutive bullish candles, set a desired percentage threshold for the close of the signal candle relative to its body, and determine the number of previous candles to compare with.
3. Adjust the pyramiding parameter to suit your risk tolerance and desired returns. Whether you prefer a more conservative approach with fewer pyramids or a more aggressive stance with multiple pyramids, this strategy offers flexibility.
4. Personalize the price drop percentages based on your risk appetite and trading strategy. Choose between fixed or custom percentages to optimize your entries in different market scenarios.
5. Configure the average purchase price management settings to control the percentage decrease in the average buy price after each price drop, ensuring it aligns with your risk tolerance and strategy.
6. Utilize the account balance validation feature to ensure the strategy's actions align with your available funds, enhancing risk management and preventing overexposure.
7. Set take profit options to secure your gains and implement stop loss protection to limit potential losses, providing an additional layer of risk management.
8. Use the date and time filtering feature to define the duration during which the strategy operates, allowing for specific backtesting periods or integration with a trading bot.
9. For automated trading, take advantage of the compatibility with third-party trading bots to seamlessly integrate the strategy with popular trading platforms.
By following these steps, traders can harness the power of the DCA-Integrated Trend Continuation Strategy to potentially maximize profitability and optimize their trading outcomes in both trending and ranging markets.
⚙️ User Settings:
To ensure the backtest result is representative of real-world trading conditions, particularly in the highly volatile Crypto market, the default strategy parameters have been carefully selected to produce realistic results with a conservative approach. However, you have the flexibility to customize these settings based on your risk tolerance and strategy preferences, whether you're focusing on short-term or long-term trading, allowing you to potentially achieve higher profits. The backtesting was conducted using the BTCUSDT pair in 15-minute timeframe on the Binance exchange. Users can configure the following options:
General Settings:
- Initial Capital (Default: $10,000)
- Currency (Default: USDT)
- Commission (Default: 0.1%)
- Slippage (Default: 5 ticks)
Order Size Management:
- DCA Mode (Default: Quantity)
- Order Size in Quantity (Default: 0.01)
- Order Size in Value (Default: $300)
Strategy's Entry Conditions:
- Number of Consecutive Bullish Candles (Default: 3)
- Close Over Candle Body % (Default: 50% - Disabled)
- Close Over Previous Candles Lookback (Default: 14 - Disabled)
- Pyramiding Number (Default: 30)
Price Drop Management:
- Enable Price Drop Calculations (Default: Enabled)
- Enable Current Balance Check (Default: Enabled)
- Price Drop Percentage Type (Default: Custom)
- Average Price Move Down Percentage % (Default: 50%)
- Fixed Price Drop Percentage % (Default: 0.5%)
- Custom Price Drop Percentage % (Defaults: 0.5, 0.5, 0.5, 1, 3, 5, 5, 10, 10, 10)
TP/SL:
- Take Profit % (Default: 3%)
- Stop Loss % (Default: 100%)
- Enable Trailing Target (Default: Enabled)
- Trailing Offset % (Default: 0.1%)
Backtest Table (Default: Enabled)
Date & Time:
- Date Range Filtering (Default: Disabled)
- Start Time
- End Time
Alert Message:
- Alert Message for Enter Long
- Alert Message for Exit Long
By providing these customizable settings, the strategy allows you to tailor it to your specific needs, enhancing the adaptability and effectiveness of your trading approach.
🔐 Source Code Protection:
The source code of the DCA-Integrated Trend Continuation Strategy is designed to be robust, reliable, and highly efficient. Its original and innovative implementation merits protecting the source code and limiting access, ensuring the exclusivity of this strategy. By safeguarding the code, the integrity and uniqueness of the strategy are preserved, giving users a competitive edge in their trading activities.
Mizar_LibraryThe "Mizar_Library" is a powerful tool designed for Pine Script™ programmer’s, providing a collection of general functions that facilitate the usage of Mizar’s DCA (Dollar-Cost-Averaging) bot system.
To begin using the Mizar Library, you first need to import it into your indicator script. Insert the following line below your indicator initiation line: import Mizar_Trading/Mizar_Library/1 as mizar (mizar is the chosen alias).
In the import statement, Mizar_Trading.Mizar_Library_v1 refers to the specific version of the Mizar Library you wish to use. Feel free to modify mizar to your preferred alias name.
Once the library is imported, you can leverage its functions by prefixing them with mizar. . This will prompt auto-completion suggestions displaying all the available user-defined functions provided by the Mizar Library.
Now, let's delve into some of the key functions available in the Mizar Library:
DCA_bot_msg(_cmd)
The DCA_bot_msg function accepts an user-defined type (UDT) _cmd as a parameter and returns a string with the complete JSON command for a Mizar DCA bot.
Parameters:
_cmd (bot_params) : ::: User-defined type (UDT) that holds all the necessary information for the bot command.
Returns: A string with the complete JSON command for a Mizar DCA bot.
rounding_to_ticks(value, ticks, rounding_type)
The rounding_to_ticks function rounds a calculated price to the nearest actual price based on the specified tick size.
Parameters:
value (float) : ::: The calculated price as float type, to be rounded to the nearest real price.
ticks (float) : ::: The smallest possible price obtained through a request in your script.
rounding_type (int) : ::: The rounding type for the price: 0 = closest real price, 1 = closest real price above, 2 = closest real price below.
Returns: A float value representing the rounded price to the next tick.
bot_params
Bot_params is an user-defined type (UDT) that represents the parameters required for a Mizar DCA bot.
Fields:
bot_id (series string) : The ID number of your Mizar DCA bot.
api_key (series string) : Your private API key from your Mizar account (keep it confidential!).
action (series string) : The command to perform: "open" (standard) or "close" optional .
tp_perc (series string) : The take profit percentage in decimal form (1% = "0.01") optional .
base_asset (series string) : The cryptocurrency you want to buy (e.g., "BTC").
quote_asset (series string) : The coin or fiat currency used for payment (e.g., "USDT" is standard if not specified) optional .
direction (series string) : The direction of the position: "long" or "short" (only applicable for two-way hedge bots) optional .
To obtain the JSON command string for the alert_function call, you can use the DCA_bot_msg function provided by the library. Simply pass the cmd_msg UDT as an argument and assign the returned string value to a variable.
Here's an example to illustrate the process:
// Import of the Mizar Library to use the included functions
import/Mizar_Trading/Mizar_Library/1 as mizar
// Example to set a variable called “cmd_msg” and all of its parameters
cmd_msg = mizar.bot_params. new()
cmd_msg.action := "open"
cmd_msg.api_key := "top secret"
cmd_msg.bot_id := "9999"
cmd_msg.base_asset := "BTC"
cmd_msg.quote_asset := "USDT"
cmd_msg.direction := "long"
cmd_msg.tp_perc := "0.015"
// Calling the Mizar conversion function named “DCA_bot_msg()” with the cmd_msg as argument to receive the JSON command and save it in a string variable called “alert_msg”
alert_msg = mizar.DCA_bot_msg(cmd_msg)
Feel free to utilize (series) string variables instead of constant strings. By incorporating the Mizar Library into your Pine Script, you gain access to a powerful set of functions and can leverage them according to your specific requirements.
For additional help or support, you can join the Mizar Discord channel. There, you'll find a dedicated Pine Script channel where you can ask any questions related to Pine Script.
DCA EMA Simple Bot [Starbots]
This is a simple idea of DCA trading on EMA crosses. Strategy is not repainting.
The difference between this and any other strategy is, that this script allows you to preset DCA buy triggers at desired levels and customize each DCA order size independently. Alerts are working, this strategy is easily used for automatic trading.
I mainly trade on Cryptohopper, Pionex, 3commas. This was created for community, alerts are working and non-repainting. Should work on any other as well.
Trading Condition:
It's buying when Fast EMA crosses up Slow EMA. Set your paramters.
It's selling if EMA's crosses back, signaling a sell. Optional.
DCA:
You can enter DCA on 20 custom levels or layers. It buys DCA when price hits the plotted blue line on the chart that's set by input % triggers. (buy 1st DCA at 2% drop, buy 2nd DCA at 5% drop,...)
Set your Inital Capital and Pyramiding in Properties tab, Initial Order Size and DCA Order Size (lot1,lot2,lot3,..), Order Type are changed in strategy inputs.
-By default you can see that we buy when EMA's cross up and signal a buy for 10% of equity, if market is dropping you will then place a first DCA order ( 20% equity) at 2% drop (lower) from initial order. If market keeps dropping you have more DCA levels where you can buy and average down your holding position. For selling you can use Take profit and Stop Loss targets that averages down multiple open positions, it will sell it once it reaches your desirable Take Profit and close a deal. You can also close your trade if EMA signals a sell.
Pyramiding - number of orders you can open at a time
Your first buy order is pyramiding 1. To allow it to buy 1 DCA or merge one time, set pyramding to 2.
Want to DCA 10 times? Set pyramiding at 11. (+1 always)
More features:
- Profit Calendar
- Show Balance label before every new trade
- DCA table - visualize how much of your investment is used in trades. If a background of the table is green you are okay, if the background color is red - you are using more money for orders than you actually have.
Buy Orders << Strategy Equity/Capital
- Show / Hide DCA lines - if your chart processing is getting slow you should hide some DCA levels to speed it up
- Backtesting Range - for testing the strategy in different time windows
- Alerts
When all trades are closed on your chart, winning rate of the strategy is 100% actually.
Win rate is shown differently as it's actually closing and opening every trade individually by default in TradingView system. We merge positions together and average it down into one big position to later sell for a profit (DCA).
You use this Trading Algorithm at your own risk. Do not trade before testing or invest something you cannot afford to lose on markets.
Simple Dollar Cost AverageThis simple DCS indicator shows:
Invested Amount
Portfolio Value
Profit
Assets
Cost per Share
Fees
You can define:
Starting Investment
Investment per Cycle
Fee Ratio
Cycle Frequency
Start and End Date
