About MCarloRisk3D
Don't just multiply volatility by root(t), do a monte carlo study and cover the extreme bases. Give the symbol-pushers a run for their money. Can your equation throw in random, out of the ordinary shocks of different...
Don't just multiply volatility by root(t), do a monte carlo study and cover the extreme bases. Give the symbol-pushers a run for their money. Can your equation throw in random, out of the ordinary shocks of different magnitude and probability? Well, this app can. MCarloRisk3D: with 3D viewing options for better understanding of the estimated probability surface.
Now with price data feeds for the highest market cap crypto coins: BTC, Ethereum, Ripple, Litecoin, ADA, EOS, BitcoinCash.
Stock price risk analyzer app for the common man. Now with optional Black Swan events and tunable forward volatility.
Estimates future price distribution using random walk theory.
Background discussion: E. Fama article on early random walk studies from the 1960's:
http://www.ifa.com/Media/Images/PDF%20files/FamaRandomWalk.pdf
New model calibration tutorial:
http://diffent.com/tuning1.pdf
Example use case & training guide for studying "AAPL to $320" can be found at:
http://diffent.com/AAPL320arialP.pdf
The app uses prior data from the stock in question for volatility estimates.
User can control how far back in time to use historical data to capture only the current "epoch" of a company or of the market as a whole if desired.
Built-in backtesting, verification, and model tuning tools.
-- Details --
This app models daily stock returns as a stable stochastic process and estimates a future price distribution by Monte Carlo re-sampling from an "empirical distribution" of a user-specified subset of prior (known) daily returns.
Be sure to press the Run Monte button on the Monte Carlo tab after changing settings or downloading a new data set.
This app downloads historical data from Google Finance as base data to resample. Prices are converted to daily returns [P(t)/P(t-1)] before resampling. The user can choose how far back to resample. By estimating a probability distribution of future prices at the user-specified investment horizon in this manner, we can give risk-of-loss estimates in thumb-rule fashion.
Reports out estimated price and %loss estimates at the commonly used levels of 1st percentile and 5th percentile (1% and 5% risk). Also reports out median (50th percentile) price estimates at the given number of days forward. Calculations are performed on daily Closing price data. An artificial shock filter is provided, which can be used to reject the resampling of prior returns that are artificially large (due to splits or other artificial re-valuations that do not affect the underlying value of the asset).
The stochastic model may be tuned or calibrated only by adjusting the maximum number of days backwards to sample or adjusting the black swan parameters.
Model Validation features:
On the Monte Carlo tab, you can withhold any number of recent days from the model and then plot the results of the stochastic risk forecast as lower-bound envelopes at 1% and %5 estimated probability (risk) levels.
Validate tab:
This allows you to perform an exhaustive validation on your model by withholding several points, computing the model, comparing the forward prediction of the model versus the actual reserved data, and repeating this in increasing time sequence for all withheld points.
A vertical "Cursor Beam" is provided that you can drag across the new plots in the Monte Carlo tab and the Validate tab to show the plotted values from several curves at once, with the values color-coded to the curves.
Show the full price probability plot linked to the days-forward setting of the Monte Carlo graph. This is a slice thru the probability surface generated by the Monte Carlo procedure.
The app provider makes no claims as to the suitability of this app for any purpose whatsoever, and the user should consult an investment advisor before making investment decisions.
Oct 28, 2023
Version 16.2
Add link to new ML macOS app.
Options data message.
Add pop up alerts for pop tech articles regarding this app.
Add additional percentiles to the summary report on the Monte Carlo screen.
Previous Versions
Here you can find the changelog of MCarloRisk3D since it was posted on our website on 2016-11-08 19:22:02.
The latest version is 16.2 and it was updated on 2024-04-19 19:46:48. See below the changes in each version.
MCarloRisk3D version 16.2
Updated At: 2023-10-28
Changes: Oct 28, 2023
Version 16.2
Add link to new ML macOS app.
Options data message.
Add pop up alerts for pop tech articles regarding this app.
Add additional percentiles to the summary report on the Monte Carlo screen.
MCarloRisk3D version 15.5
Updated At: 2023-05-18
Changes: May 18, 2023
Version 15.5
Sync up user interface changes from macOS Intel version, additional small UI adjustments. Rebuild on newer XCode per Apple requirements.
MCarloRisk3D version 15.1
Updated At: 2023-03-01
Changes: Mar 1, 2023
Version 15.1
Update market holiday calendar through 2024 for more accurate date report-outs for forecasts involving stocks & ETFs (e.g. translating trading days forward into a calendar date).
MCarloRisk3D version 13.0
Updated At: 2022-08-17
Changes: Aug 17, 2022 Version 13.0
Add support for more crypto coins:
SOL$ DOT MATIC TRX$ AVAX WBTC LEO$ UNI FTT CRO LINK$ NEAR$ ATOM$ ALGO APE FLOW VET$ FIL ICP MANA SAND$ XTZ HBAR AAVE THETA QNT
The dollar signs following some symbols are to distinguish them from stocks of the same symbol.
E.g. SOL$ is Solana crypto.
MCarloRisk3D version 11.9
Updated At: 2020-11-22
Changes: Nov 22, 2020 Version 11.9
Match up to the macOS app by adding forward Sharpe and Sortino ratios, and the standard deviations of returns that feed into them.
MCarloRisk3D version 11.5.1
Updated At: 2020-09-29
Changes: Sep 29, 2020 Version 11.5.1
Add volatility correction (if it is included in the model) to the new 25% and 75% targets in the Validate Report.
MCarloRisk3D version 11.5
Updated At: 2020-09-27
Changes: Sep 27, 2020 Version 11.5
Add 25% and 75% quartile level metrics to Validate report. This checks how well your model validates at convenient levels between the 50% and 5%/95% levels. Also optionally allow these 2 additional levels to be added to the parameter validate / optimize objective in the new Param scan screen. Increase Validate report vertical size so it is possible to scroll and see all 7 metrics and the objective value at once.
MCarloRisk3D version 10.3
Updated At: 2020-09-17
Changes: Sep 17, 2020 Version 10.3
Report out objective value = sum of absolute errors for 5 targets
(5 different percentiles) in the Validate report. Lower = better.
On the Monte Carlo envelope plot,
draw a whisker extension to the dark green bar that represents
the 5th to 95th percentile backtest residual. The whisker
extensions show the 1% to 99% results. Make the dark
green bar thicker to show more distinction from the whisker plot.
Speed up Validate runs.
Add power function instead of square root to stochastic volatility model
as an option. Default is still power = 0.5 = square root.
Speed up stochastic volatility model evaluation when correlation
factor rho is non-zero.
MCarloRisk3D version 10.2
Updated At: 2020-09-01
Changes: Sep 1, 2020 Version 10.2
Fix excessive memory use in some cases.
MCarloRisk3D version 10.0
Updated At: 2020-08-29
Changes: Aug 29, 2020 Version 10.0
Add a feature to allow a theoretical normal returns distribution to be used for modeling instead of the empirical returns distribution which this ordinarily uses. This switch is in the Tune panel of the app, accessed from the Monte Carlo tab, upper right blue Tune button. The mean and standard deviation of this distribution is computed automatically, and are the same numbers as shown on the returns distribution "bell curve" on the Prices & Rtns tab of the graph. In other words, we take the same returns data window that the app would have used as the empirical distribution and we use the mean and stdev of this data for our theoretical normal distribution data generation.
Disclaimer
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