I am been working on various mean reverting or “inside tunnel” trading model for recent low vol market, however, none of them work nicely, any fresh idea to brain storm for discuss?
Take a look at thishttp://en.wikipedia.org/wiki/Ornstein%E2%80%93Uhlenbeck_process .
Hope it helps.
-i guess esp in mean reverting in low vol it wont work and voltility is diff to gauge
mean reverting desnt work in low volatility as we take fixed period means and as day passes by we add new day price and take out the 1st price —–so it wont work in case of low volatility
Take a look at Perry Kaufman’s new book “Alpha Trading”.
Is anyone else aware of any other text ( or academic paper ) about mean reverting strategies ?
before proceeding with the discussion/advice could you please give us a hint about the instruments and timeframes/resolution/scale you’re attempting to trade?
well, since they did not work I was thinking you could tell us what you were doing, what mean reverting strategies you were using.
This may be obvious, but for a mean reverting trading strategy to work, the market must first tend to mean revert, meaning in the data you should see negative serial correlation of returns, or non parametrically, divergence of price from some MA must be predictive of a higher probability of a move towards the mean than a similar sized move away from it. Is the issue with the data or the implementation?
In my amateur opinion, I believe several factors contribute to the success or failure of any trading strategy, especially in a low volume environment. Factors such as AUM, execution platforms and strategy correlation between firms (herd mentality) contribute to trading performance more than most traders would like to admit. You may have a successful strategy, but problems or constraints in another area may be adversely affecting your performance. I suggest you evaluate your entire trading environment as part of your brainstorming session.