This script offers a toolkit for quantitative options trading, using Monte Carlo simulations based on actual historical returns to model potential future price paths for underlying assets. A range of metrics related to options trading are also provided.
Monte Carlo Simulations:
The script employs Monte Carlo simulations to model future price paths...
This script “Monte Carlo Simulation - Your Strategy” uses Monte Carlo simulations for your inputted strategy returns or the asset on your chart!
Monte Carlo Simulation: Performs Monte Carlo simulation to generate multiple future paths.
Asset Price or Strategy: Can simulate either future asset prices based on historical log returns or a...
Some methods for the Black Scholes Options Model, which demonstrates several approaches to the valuation of a European call.
asset_path(s0, mu, sigma, t1, n) Simulates the behavior of an asset price over time.
s0 : float, asset price at...
Methods to implement Markov Chain Monte Carlo Simulation (MCMC)
markov_chain(weights, actions, target_path, position, last_value) a basic implementation of the markov chain algorithm
weights : float array, weights of the Markov Chain.
actions : float array, actions of the Markov Chain.
target_path : float...
Inspired by the Brownian Motion ("BM") model that could be applied to conducting Monte Carlo Simulations, this indicator plots out the Drift factor contributing to BM.
Interpretation : If the Drift value is positive, then prices are possibly moving in an uptrend. Vice versa for negative drifts.
This is an experimental study designed to forecast the range of price movement from a specified starting point using a Monte Carlo simulation.
Monte Carlo experiments are a broad class of computational algorithms that utilize random sampling to derive real world numerical results.
These types of algorithms have a number of applications in numerous fields of study...
Monte Carlo Simulation is a model used to predict the probability of different outcomes when the intervention of random variables is present. it is used by professionals in such widely disparate fields as finance, project management etc. You can find many articles about Monte Carlo Simulation on the net.
In this script I tried to make Monte Carlo...
Example execution of Monte Carlo Simulation applied to the markets(this is my interpretation of the algo so inconsistencys may appear).
the algorithm is very demanding so performance is limited.
About the Indicator
The Crawling Neural Network is a unique algorithm that identifies clusters of random walks that are crossing above or below the market price of the asset.
The random walks always exist, but the specific series that contribute to the cluster can only be seen during their significant period.
When the price trends strongly in a direction, it...
Understanding the Random Walk Simulation
This indicator randomly generates alternative price outcomes derived from the price movements of the underlying security. Monte Carlo methods rely on repeated random sampling to create a data set that has the same characteristics as the sample source, representing examples of alternate outcomes. The data set created using...
Understanding the Monte Carlo Simulation
This indicator uses Monte Carlo methods to predict the future price of a security using 200 random walks.
Monte Carlo methods rely on repeated random sampling to create a data set that has the same characteristics as the sample source, representing examples of alternate possible outcomes. The data set created using...