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PAMR: Passive Aggressive Mean Reversion Strategy for Portfolio Selection

By JohnLast 2726 days ago

PAMR: Passive Aggressive Mean Reversion Strategy  for Portfolio Selection by Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan

On this link you can download the Matlab Source code. Otherwise the article is here.

The Bin Li's doctoral dissertation is about "on-line portfolio selection", which intertwines machine learning and portfolio selection. The key issues in the topic is to find effective patterns among markets and then effectively allocate the capital for portfolio trading. He has mainly involved in two types of approaches.

1. He firstly uses nonparametric learning to extract a set, whose patterns are expected to be similar to future pattern. And then, he exploits the patterns via portfolio trading (using Kelly's approach).

2. After realizing that mean reversion is a common pattern among the markets, then he designs learning algorithms to trade on such pattern. 

The backtest results of the two approaches on real market are real encouraging according to him. 

For other techniques beyond his thesis, he thinks that the main usage of machine learning is to automatically identify (unknown/unknown) patterns among markets. Then feeding the related inputs is critical, such as neural network, or genetic algorithms.

You can contact Ben Li in linkedin.