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A contrarian indicator to optimize risk management at brokers

By Jingwei Li, Researcher, Autochartist.com

Some brokers simply take the position of “take on as much risk as possible and therefore maximize profitability”, while others assume a more moderate approach of balancing the liquidity of their company with profitability.

In this short article we investigate the use of a sentiment-based indicator to assist brokers in their risk management processes.

SSI is the short name for Speculative Sentiment Index. This indicator is a count of the number of long and short positions in the market and is therefore a view on how traders are really feeling about an instrument. If there are more traders long than those are short, the ratio is positive. For example, if EURUSD SSI is 1.5, that means that there are 1.5 traders long for every short. If the number is negative, then there are more short positions than long.

The SSI is a contrarian indicator in that it assumes that retail traders mostly lose their money (which is statistically true)So based on this previous experience, when majority traders sell, the price goes up, when majority traders buy, the price goes down.

Below is a plot for EURUSD from April 2006 to July 2015. The dark blue curve is the daily price of EURUSD, and the vertical lines are daily SSI values. Light blue ones are positive SSI, means more traders go long while light red ones are negative SSI, means more traders go short.

We can see how traders sell during the up-trend and buy during the downtrend.

Additionally, the absolute value of SSI means the degree of net long or short. A ratio of positive or negative 3 is stronger than 2.

To test the theory in the market, we did a back-test on the EURUSD sample data. The entry rule is: trade short when SSI is larger than 2, and trade long when SSI smaller than -2. We exit the position after 5 days.

We identified a total of 381 trades in a 9 year period. The plot below shows the accumulated profit in pips. As you can see the results for this very simple strategy are not bad at all.

In the below image we map the executed trades on the price chart.

The red dots represent short positions and the green dots represent long positions. One can clearly see that the flat parts of the equity curve are because of low trading volume during certain market conditions. The plot below shows that when market trends up we placed a lot of long trades, while during the down trend we placed short trades. We certainly predicted the market direction correctly most of the time.

Although the above piece of research is far from complete, we believe that the SSI index is worth investigating more deeply as an input into a broker’s risk metrics.