Adaptive Modeler 1.5.0 Professional Edition – Altreva

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Stock market forecasting with simulation models

Altreva Adaptive Modeler is a software application for forecasting stocks, forex currency pairs, Bitcoin, other cryptocurrencies, ETFs, commodities or other markets. Based on unique and innovative technology, it creates market simulation models in which thousands of virtual traders apply their own trading strategies to real-world market data to trade, compete and adapt on a virtual market. Their collective behavior is used to generate one-step-ahead price forecasts and trading signals. Models coevolve in parallel with the real market without overfitting to historical data. This results in better adaptation to changing market conditions and more consistent performance.

•  used and endorsed by professional traders, investors and researchers
•  award winning
•  suitable for day trading and swing trading strategies and others

Forecasting Bitcoin and other cryptocurrencies

Adaptive Modeler can also be used to forecast Bitcoin and other cryptocurrencies. In fact cryptocurrencies are likely to be easier to predict than stocks since cryptocurrency markets are still less mature and less efficient than stock markets. Also the high volatility, when combined with accurate forecasting performance, provides attractive opportunities.

Forecasting forex currency pairs

Altreva Adaptive Modeler is also being used in forex markets and has in fact contributed to new evidence of technical trading profitability in the forex market. Independent scientific research with Adaptive Modeler has demonstrated attractive returns for several of the most traded currency pairs, outperforming traditional econometric forecasting models.

Forecasting commodities and other markets

Basically Adaptive Modeler can be used with any market price data or other time series such as gold, silver, platinum, oil, etc. As with all markets, forecasting performance will depend (amongst other factors) on the (in)efficiency and predictability of the market, which typically varies over time.

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