Noted market technician John Murphy contends that prices move in a series of peaks and troughs and the direction of those peaks and troughs determines market trends. A peak is defined as a price resistance point. A trough is defined as a price support point where selling pressure overcomes buying pressure and a price advance is turned back.
Round numbers often serve as strong support and resistance points. Murphy states, “Traders tend to think in terms of important round numbers, such as 10, 20, …and multiples of 100 as price objectives and act accordingly.”
Carol Osler of Brandeis University documented clustering in currency stop-loss and take-profit orders. The study showed that requested execution rates for stop-loss and take-profit orders clustered at round numbers, consistent with evidence in stock markets. Osler’s previous research had demonstrated that, among support and resistance levels for currencies distributed by technical analysts to their customers, 96% end in 0 or 5, and 20% end in 00.
Here we attempt to profit from the aggregate trader psychology in market support and resistance points around round numbers. The discussion is specifically interested in profitable trading around the ultimate round number, “the figure” of 1.3400, 1.3500, etc. All data are the euro spot market at the four-hour window. The determination of the market trend is examined via exponential moving averages (a fast EMA and a slow EMA). The concept of girth is used to determine if the trend is continuing. Girth is the scaled difference between the fast and slow EMAs (“Adding girth to your profits,” Futures, December 2008). For the trend to be continuing, girth must be greater than 0 for a long position and less than 0 for a short position.
Two scenarios were tested:
- S1: Examination of profitability when terminating trade at the figure (example, 1.3500, 1.3600, 1.3700): The figure was the resistance point (limit) if the trend was up (the fast EMA above the slower EMA) or the support (limit) if the trend was down (the slow EMA above the fast EMA).
- S2: Examination of profitability when terminating trade slightly after the round number.
The average monthly historical volatility in the euro spot market was examined against the month’s profitability for the above two scenarios to determine a refinement of the trade tactics. “The facts of the trade” (below) provides the salient details about our test parameters.
Strategy 1 results
It would be expected that, because trader psychology regarding support/resistance points at round numbers is widely known, then setting limits at the nearest figure number would not result in profitable trades. However, over the 7.5 years tested, the trade proved a cumulative 16.08% profitability. It would seem that traders set their limits around the figure and not exactly on the figure.
From 2012 to present, the strategy has been unprofitable (see “Strategy one” right). What also is interesting is that the month of December, across the 89 months tested, produced little or no profit in each year examined.
Were market traders adjusting for known trader psychology and setting limits/stops around the figure and not exactly at the figure? Could a trade be constructed to profit from this altered mentality? In an attempt to profit from perhaps altered trader psychology, Scenario S1 was adjusted to setting a limit on a long above the figure and a limit on a short below the figure.
Strategy 2 results
It appeared that traders allowed long positions to run over the figure and short positions to run under the figure in an attempt to optimize their trading potential. This was the case: Over the 7.5 years tested, S2 proved a cumulative 34.84% profitable vs. 16.08% for S1. This is more than a 100% increase in cumulative returns. From these results, increasing the profitable trading months from 46 (S1) to 53 (S2) greatly increased the simulated accumulated trading profits. Losses were lower in S2 than in S1 (see “Strategy two,” right). However, December once again proved an unprofitable trading month for this transaction.
“Annual results” (below) shows how a simple adjustment of exiting the trade slightly above the figure on a long, and slightly below the figure for a short, increases profits and reduces losses on the transactions. We also tested exiting the trade before the figure (10 pips before the figure on a long/12 pips before the figure on a short). This trade was drastically unsuccessful. The results are listed against S1 and S2 on the table and labeled S3. Therefore, it appears that there is a “run-through” bias on the figure trade and not a “limit-out before figure” bias in trader psychology.
Just by looking at the returns on the three scenarios and having some experience of market volatility over the last several years, it can be seen that extremely low market volatility crushes this trade. To simulate some kind of quick and dirty backtest of volatility, an annualized trailing four-period historical volatility model was constructed. The purpose of the model was to force a comparison against the EMAs used: Two-period and four-period.
To produce a snapshot of monthly volatility, the 9 a.m. (Eastern) four-hour window for the annualized trailing four-period historical volatility was assumed to be the market volatility for the day. This daily snapshot was averaged across all the trading days of the month to produce an average view on market volatility for that particular month.
From the table and graph in “Volatility adjustment” (below), it can be seen that the extremely low volatility years of 2007 and 2013-present in the currency spot market do not support the use of this trade in this current market as volatility is extremely low. In fact, using S2 adjusted for the elimination of trading during the month of December, of the 63% profitable trading months, it appears that market volatility must be at or above 6% to capture 96% of those profitable months. Therefore, it could be broadly stated that to profitably enact this trading with about 63% chance of profit, market volatility should be at or above 6%. It could be stated that the trader psychology of limiting/running trades over the figure is void in extremely low-volatility months. With the recent pop in volatility in the currency market, this trade should once again be profitable.
Leslie McNew is an adjunct professor of finance, Driehaus College of Business, DePaul University and managing director and owner of the M. Demon Fund (DePaul). Back testing and validation of this strategy was provided by Christine Muench, risk analyst, gas and power, E.ON Global Commodities North America and Zachary Hardaway, Trading Operator/Analyst, high frequency market making/arbitrage group, Geneva Trading. McNew may be reached at firstname.lastname@example.org.