Worst case risk/reward analysis

The following techincal indicator is based on worst case algorithmic analysis of time series mainly based on the techiniques in the papers Prediction Strategies without loss and some improvements from Differential Equations Approach to Optimal Regret (some related follow up papers on this topic are 1 , 2 but are not used here). The methods are based on an optimal tradeoff between reward and risk and are intended to extract a higher reward for the same amount of risk (or a lower risk for the same reward). We have measured the risk/reward performance based on the commonly used sharpe ratio and calmar ratio. Here we are showing the perfomance of our algorithms when applied on the following individual index funds S&P500, HangSeng, Nikkei, Gold, Oil, 10-year-yield, and EURUSD. The following charts are updated daily and include 1) The daily recommendations for each index individually (as a delta with respect to the buy and hold strategy), 2) the performance of our algorithm on historical data till today and 3) the sharpe and calmar ratio of our algorithm vs those of the underlying index for the entire historical period and for the last 3 months. In the plots over historical data, the blue line is the tracks the wealth of the buy and hold strategy for the index and the green line is the wealth of the our algorithm when applied to that index (we measure the change in log wealth which is approximately the percentage change / 100). DISCLAIMER: Please do not use these algorithms for investments (we will not assume any risk or liability).

Generated on Tue May 14 16:11:18 2013

Sharpe ratio of S&P500 = 0.6375
Sharpe ratio of algo on S&P500 = 0.8818
Calmar ratio of S&P500 = 0.4812
Calmar ratio of algo on S&P500 = 0.9567