Stock Predictions: Daily Stock Selection Based On State Of The Art Algorithm. Time Period: January 7th, 2016 – July 1st, 2016

short-term trading

Stock Predictions: Short-Term Trading

Daily Stock Selection Based On a Self-Learning Algorithm

 

Stock prediction

Time Period: January 7th, 2016 – July 1st, 2016
Stock Forecasting

Stock predictions: the short term signals of I Know First’s proprietary algorithm can be successfully utilized besides their application for better timing of the mid and long term investments. Variety of rules based on those can be developed for trades execution and rebalancing on a daily basis. A high predictability level and signal strength are key factors for the most intuitive approach of selecting the highest ranked stocks. However, there can be several ways of integrating a trend or mean reversion logic into the selection process to account for trader’s approach and/or market conditions. Below the back test results of five strategies in this context are given for the S&P 500 stocks universe since the begin of 2016. At most 20 highest ranked stocks per day (if available) are traded in each case, the equity lines represent the value of corresponding equally weighted and daily rebalanced baskets of stocks, set up to outperform the broader universe. For three of them, additionally to the predictability and signal level, the price and signal dynamics are taken into account for the respective selection processes. No technical analysis elements (indicators, oscillators) are part of the analysis below.

The signals are generated daily before the market opens and subsequently used to rank the stocks. For simplification purposes the simulation uses close-to-close price changes only and hence no limit orders or stop losses are considered for further performance enhancement. Both long and short positions can be taken, no leverage is applied.

The overall return in the period January 7th 2016 – July 1st 2016 ranges between 14% and 38% while the S&P 500 increased by 5.46%.

Stock prediction

The following table summarizes the overall results and the annualized figures (assuming 252 business days in a year) for each of the strategies.

Stock PredictionsThe table below breaks down the analysis into the respective trade statistics over the considered period:

Stock Forecasting

Overall, without the default predictability filter applied and without considering any specific strategy, below are the averages of the daily trade returns depending on the signal strength vs. the realized average S&P500 stocks return:

Stock Predictions

Focusing on the trades with a higher level of predictability further improves the returns for stronger signals:

Stock Predictions

 

 

short-term trading

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