In the era of social media a strategy for the markets is not enough. A meta-strategy to deal with infoxication is absolutely necessary.
This is an edited excerpt from this week’s report for the blog subscribers:
On top of economic uncertainty there is also high level of noise generated by various pundits, blogs, financial media and even central banks. Staying focused on the markets has become as difficult as developing and following a winning strategy to trade. In fact, the essential meta-strategy is to remain focused, identify and filter the sources of noise.
The noise benefits the sell side and various other market participants that have the purchasing power to take advantage of the random actions of most traders. From social media posts there are indications the noise has succeeded in causing traders to act randomly. Success is tied to conviction that a certain strategy, or ensemble of strategies, will continue to perform well in the future. Conviction is far from knowledge but could offer a shield against random information from sources that attempt to gain an edge in a zero-sum game.
On top of strategy wars, that is the clash of the various edges in the markets, there is also an information war. As information and trading become more “democratized” due to technological progress, there is a need of a meta-strategy edge on top of a market strategy edge. There are several ways of achieving that. An extreme way is by escaping from social media as one fund manager did recently and focusing on strategy edge exclusively. But that cancels all the interaction and its benefits. It’s a solution but not for most people. Those who elect to be constantly exposed to the information war must work on a meta-strategy. That is not something you can backtest but must be based on sound principles and heuristics. It is much harder than most people may think because the impact of proliferation of information is deeper than most realize. Understanding the problem is the first step only. The system that emerges from proliferation of information but also from information distortion and noise is very complex. This isn’t an easy problem to solve because in the current state the signal to noise ratio is close to zero and at some point it will be extremely hard to identify any signal at all.
Disclaimer: No part of the analysis in this blog constitutes a trade recommendation. The past performance of any trading system or methodology is not necessarily indicative of future results. Read the full disclaimer here.