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Description
Drift-diffusion Monte Carlo forecaster from raw asset price data including crypto assets, with bulk backtesting.
This lite version of the app provides an intro to these types of models and runs in full screen windows, useful for demonstrations and educational purposes.
Instead of time series (traditional charting), the app is based on the statistical properties of daily return data (percent change in asset price per trading day).
This app resamples from empirical daily returns to generate forward-in-time monte carlo paths (random walks).
No distribution shape assumptions are needed, works with empirical returns distribution (historical data as-is). This is especially useful for new assets such as crypto or more exotic equities which may not conform to normal or lognormal return assumptions, especially in shorter time periods.
Aggregates monte carlo paths into a (price, time, probability) surface. Allows user to slice thru and examine this surface (e.g. price over time versus probability) and visualize the surface in 3D and with shaded contour plots.
Allows user to set up bulk backtests by withholding the most recent data and examining the model versus this withheld data.
Allows display of a sampling of monte carlo random walk paths before they are aggregated, allowing highlighting of individual paths; for teaching and example purposes. Detailed training and examples available online in the Help tab.
Raw price data from IEX Exchange or cryptocompare.com