Systematic vs. Discretionary Trading
Many systematic strategies now incorporate fundamental data; some are complex algorithms trying to capture noise, such as high-frequency programs, or even particular word groupings inputs from social media. On the flipside, discretionary traders are not simply traders trying to capitalize on a “gut feeling” derived from “divining” the fundamentals and/or price action. Most discretionary traders have well-defined trading strategies that assess and evaluate the supply/demand fundamentals. Those that have the wherewithal to survive for a reasonable or long trading history invariably have specific risk management parameters. Nearly all discretionary traders incorporate technicals to enter and exit the market, to implement risk management, and to varying degrees, to confirm fundamental evaluations. One caveat: A discretionary trader is more apt to exit a position prior to his technical parameters if the trade is not behaving to price action expectations.
In this analysis of systematic vs. discretionary trading we will examine the BarclayHedge Systematic and Discretionary Traders Indexes, the Barclay BTOP50 Index, the Barclay Agricultural Traders Index and the Société General (formerly Newedge) Macro Trading Indexes (Quantitative and Discretionary).
Let’s start with an examination of the BarclayHedge Systematic Traders Index and Discretionary Index. Not surprisingly, the number of programs has grown steadily in the period covered (February 1987 through May 2017) and now stands at 409 in the Systematic Traders Index and at 106 in the Discretionary Traders Index. BarclayHedge defines its Systematic Traders Index as programs that make decisions using automated systems in at least 95% of cases. Their Discretionary Traders Index includes programs that make at least 65% of their decisions in a discretionary way.
“Head to head,” (above) shows a VAMI (value-added monthly index) chart and a risk table of the two indexes. VAMI is the growth in value of an average $1,000 investment. VAMI assumes the reinvestment of all profits and interest income.
As one can see, there is very little difference in the returns of the two sub-indexes and 50/50 combination. This is somewhat surprising given the major differences in approach, the different trade generators, the numerous strategies and the number of markets traded by the different styles. What this presents is that the Discretionary Traders Index has significantly higher risk-adjusted returns as reflected by the Sortino Ratio. Given the similar returns, this difference stems from the greater volatility of the Systematic Traders Index, particularly to the downside. The Kurtosis numbers are huge and deserve some study.
Kurtosis and skewness are statistics that quantify the shape of a non-normal distribution. The higher the kurtosis, the fatter the tails and the greater the probability of a wider distribution. For now, let’s attribute the high numbers to the fact that these are indexes rather than individual programs/strategies. Skewness indicates a propensity of direction of the surprise (fat tails). What the kurtosis and skewness statistics indicate is that all three have extremely fat tails with a strong propensity to surprise in positive returns with the Discretionary Traders Index having the most extreme numbers for positive surprise.
The correlation between the two indexes is a relatively high 0.62. The degree of correlation is high enough as not to overcome the substantial difference in risk-adjusted-returns between the two. Consequently, 50/50 portfolio fell in between the two indexes in risk-adjusted returns but did yield the highest annualized return by a small margin.
Despite the similarity in returns, systematic traders have higher volatility as noted the risk metrics (see “Drawdowns, above). Broadly speaking, one could describe the Discretionary Traders Index’s returns stream as slower, smoother and generally less volatile that the Systematic Traders Index, though yielding similar net returns. The result being better risk-adjusted returns. The 50/50 Portfolio did produce lower drawdowns.