Main Strategy

At AlphaStone, we use machine learning to predict the stock market. Our short-term strategy is based on our AI's ability to detect recent short-term anomalies in the market. This allows us to trade with precision and confidence.

Strategies Under Research

One strategy we're researching is Mean Reversion Trend Following. This strategy is designed to be safe and at the same time provide adequate returns. The strategy trades according to three principles. First is risk management. Algorithm manages risk by distributing overall assets considering various statistics. Second, short holding time. Algorithm focuses on trades that make profits by holding short-term stocks rather than investing by holding stocks for a long time. The strategy specializes in predicting the short-term future. Lastly, the use of specialized algorithms—that are less influenced by the market. The use of appropriate algorithms according to market conditions adds to the stability of the strategy.

Another strategy we're researching is the use of Hidden Markov Models to predict stock market trends. HMMs are statistical models that can be used to analyze time series data, such as stock prices. By using HMMs, we can model the underlying dynamics of the stock market and make predictions about future trends. This can help us identify profitable trading opportunities and make more informed investment decisions.