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Thoughts on Reversion to Mean criteria

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 Justin Orwin, Founder ChartSmart Trading.

 Monday, April 9, 2018

I discovered the hard way that reversion to mean trading is not simply about how far price has traveled from the mean. Selling an OB oscillator or thinking, "it can't go any further" is a recipe for pain. Lots of it. I found I needed to understand the interplay of: 1) Distance from mean in pips 2) Time spent away from mean 3) Rate of change of the mean 4) Translation of above into probability numbers 5) Trading skill I also needed to understand this information interaction over large sample sizes of data as a benchmark against which to analyse and compare current price action. I could find no software available on the market to provide me with the data and so I built it myself. If I tried to simplify the formula for calculating RTM probability it might look something like this: Time(spent away from the mean) X Distance (traveled away from the mean) / Rate of change (of the mean) ..... compared to as much historical data of the above calculation as possible. The above then needs to be applied to the market using a systematic consistent trading approach / system with correct risk controls in place. If you are a reversion to mean trader and want to discuss further, please drop me a line, I'm always keen for a (Skype) coffee and some trading talk. The above approach has made all the difference in my trading and I am very happy to share my findings with you. If we want to trade Reversion To Mean successfully I don't think we can focus on any single metric and expect consistent success. Wishing you every success in your trading. *Please see my earlier post for trading results and videos linked to adopting the above principles in my trading.


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5 comments on article "Thoughts on Reversion to Mean criteria"

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 Justin Orwin, Founder ChartSmart Trading.

 Monday, April 30, 2018



Chaipat, thanks for sharing...interesting stuff. I like the concept from a timing perspective. Extreme volatility can be linked with market exhaustion points - will be doing more reading on this for sure.


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 Olubunmi Omidire, VP Financial Accounting at Credit Suisse

 Monday, April 30, 2018



Need to read more on this. I have always thought mean reversion strategies work best when comparing implied vol to historical vol. Empirical evidence shows implied vol will always revert back to mean hence why short premium strategies do work....well 80% of the time!

Interesting


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 Shanil Manwani, Managed futures - Hedge fund professional

 Tuesday, May 1, 2018



Very interesting subject. Lot of work on my trading strategy is revolved around the mean reversion. As pointed Imp Volatility def plays a big role and the last few years low vol environment and sudden regime change of high vol this year has made it all the more important to restudy the robustness of working strategy


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 Justin Orwin, Founder ChartSmart Trading.

 Tuesday, May 1, 2018



Absolutely Shanil, and as Olubunmi mentioned above implied vol will always revert back to the mean. In a similar manner Time and Distance spent away from the mean will also always cause price to revert back to the mean, otherwise it could not be the mean. Our job in this instance is to understand the role ROC of the mean plays in our probability projections and risk control. Many traders I have spoken to see mean reversion trading as the opposite of trend trading. I can see where they are coming from, however I have a slightly different view in that price can mean revert many many times over a long protracted trend. Mean reversion occurs within trends as well as within periods of consolidation, the only key difference between the 2 states of mean reversion is ROC of the mean, which if managed correctly can be extremely rewarding. In fact understanding the role mean reversion plays within trends is critical to effective trend trading. Thanks for sharing your thoughts.


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 Jon Grah, Trading Signals Automation Expert AwarenessForex.com

 Thursday, May 24, 2018



A lot of these discussions refuse to talk about mean reversion as part of an overall market making scheme. In other words, how is your strategy solving a problem within the larger context of market microstructure? This is the difference between trying your luck and solving a problem that other market participants have.

When you go to the local farmers market (ECN) or supermarket (dealer), what problem do the suppliers/vendors (liquidity suppliers) solve? Are you taking liquidity (consumer) or providing liquidity (arbitrage, value trading, etc)?

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