As artificial intelligence becomes more advanced, machines will be able to more quickly and effectively comb the massive quantities of market data to identify patterns and other investment intelligence that traders can use to outperform the market.
AI platform Kavout uses machine learning, predictive analytics and big data coupled with its Kai quantitative analysis model to analyze Russell 3000 stocks and identify potential short-term winners and losers. Kai incorporates 200 different correlation metrics and then assigns a Kai Score for each stock. The higher the Kai Score, the more likely a stock is to outperform the overall market over the next month. Kavout calls its fundamental and quantitative analysis approach “quantamental investing.”
Kavout has used this approach to create stock portfolios based on Kai Scores dating back to January 2012. The Top Picks portfolio consists of stocks with the highest Kai Scores, and the Bottom Picks portfolio consists of stocks with the lowest Kai Scores. The portfolios are equal-weighted, and they are rebalanced on a monthly basis.
Kai’s Track Record
Since its inception in 2012, the Top Picks portfolio has delivered an overall return of more than 200 percent, or a compound annual growth rate of 21.9 percent. In that same time, the S&P 500 had delivered a CAGR of only 13.3 percent. Remarkably, the Top Picks portfolio has demonstrated less volatility in that time than the overall market.
The Kai Bottom Picks portfolio has delivered a CAGR of 2.5 percent during the same stretch, or an alpha of -11.4 percent.
Analysis Is Key
Models such as the Kai Model take massive quantities of data and extremely complex correlations and market dynamics and condense all that information into a single number that can easily be used as a trading indicator. Big data is…
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