July 10, 2011

Finally, here is my latest paper. Alpha Power: The ImplementationIt is all about my quest for alpha points. After all the research, last winter was finally the time for my implementation phase using real market data. A lot of this continued search has been documented; almost real time on my webpage. For those that followed this journey over the last few years and wondered how the alpha power method would do with real market data, please note that performance results exceeded theoretical settings.

I think the reason for this is that the market shows a lot more volatility than was used in my randomly generated stock prices. And since the methodology trades over market cycles of significance while still having for objective to accumulate shares for the long term; each cycle is pumping cash in the system for the next cycle which in turn will accumulate more shares.

We are all on the same quest and that is to outperform the long-term averages: to gain alpha points. As your own research must have shown, these alpha points are very hard to get and the higher you go, the harder it gets.

I often describe my methods as mini-Buffett style in the sense that you do the same philosophically as Mr. Buffett but on a mini-scale: a lot less equity. See my earlier paper: The Trading Game, where a comparison is made on the similarities of trading techniques. However, starting small does not mean that you cannot grow big.

This new paper adds more insight into the trading methodology as well as a simplified view of its governing equations. In my opinion, all this affirms that there is another frontier beyond the “efficient market frontier” and it has an increasing Sharpe ratio.

All the simulation tests were done on the old WL4 site where you can only provide your script and the stock to test on. All trades were done at least at bar+1 with some scripts even using some randomly generated entries. (Note: The old WL4 website has been taken down and replaced with it newer version).


Created on ... July 10, 2011,   © Guy R. Fleury. All rights reserved.