Quantitative Trading Strategies for European Stocks

September 20, 2017

In the following, we analyze the performance of our “European Stocks” Package by evaluating quantitative trading strategies which invest on a daily basis in the European stocks selected by our AI system and can easily be recreated by using the daily forecasts provided to clients.

We show that the I Know First algorithm’s signals including the costs of bid-ask spreads and commissions results in a high-performing trading strategy with excellent statistics:

Returns of up to 128% in a 2-year time period
Alphas over 20%
Betas below 0.15
Sharpe ratios reaching 1.4

Quantitative Trading Strategies

The I Know First Market Prediction System models and predicts the flow of money between the markets. It separates the predictable information from any “random noise”. It then creates a model that projects the future trajectory of the given market in the multidimensional space of other markets. The system outputs the predicted trend as a number (the signal), positive or negative, along with the wave chart that predicts how the waves will overlap the trend. This helps the trader decide which direction to trade, at what point to enter the trade, and when to exit.

In the following, we use the daily top 10 signals generated by our algorithm for European stocks to trade the top 2, 3, and 4 stocks long and short. We rebalance the portfolio based on the daily algorithmic forecasts, thus maintaining our investments in line with the market trends identified by the algorithm. We apply one basic filter to the algorithmic signals: we filter out stocks which have had overnight (from market close to market open) moves of over 2% since in this case the algorithmic predictions are missing significant amounts of return information (our predictions are computed using closing prices, thus overnight moves are not accounted for in the daily AI signals and if large, such moves can have significant effects on the predictions).

Strategy Performance

The results of these quantitative trading strategies for stocks for the period 08/18/2015 – 08/15/2017 including the effect of bid-ask spreads and commissions (0.08% per trade), are summarized in the following table (click on the table to enlarge). Rows 1 through 3 present the statistics of the I Know First Portfolios while row 4 shows those of the benchmark, the iShares MSCI Europe UCITS ETF Acc (market cap weighted top 445 European stocks ETF).

As can be seen in the table all three portfolios significantly outperform the benchmark in terms of total return (128.5%, 64.26%, and 43.22% versus 2.44%) with controlled Beta (below 0.15) and solid Alpha (above 20%), while also presenting excellent risk-adjusted returns (Sharpe ratios of 1.46, 1.00, and 0.84).

The performance lines for the three quantitative trading strategies are shown in the following graph.

As can be seen above, the strategies exhibit excellent returns with stable growth over the benchmark which performed miserably in the analyzed time period. The consistency of the performance lines is thus well expressed in the high Sharpe ratios. The high Alphas indicate strategies with consistent gains over the markets while the low Beta values show that the returns are not strongly correlated to the market, and thus will hold in market downturns. Both of these portfolio features are clearly discernable in the above lines, all in all, presenting statistically very solid strategies with very high returns, indicating that these portfolios will perform well in the future as well.

Conclusion

In this article, we presented an analysis of quantitative trading strategies based on the daily signals for European stocks of our AI based forecasting program.

We show that these strategies result in portfolios that have strong returns (over 40% in the last 2 years versus the benchmarks return of 2.4%), controlled risk (Sharpe ratios above 0.81 versus the benchmarks 0.16), excellent Alpha and Beta statistics (Alpha above 20% and Beta below 0.15), exhibiting steady growth over the market in the last 2 years. All these features point to strategies that will continue their excellent performance into the future.