Both Trend-Following and Mean-Reversion Have Performed Well This Year
All attention this year has been on trend-following and the large returns of CTAs and ETFs tracking CTA indexes. Our PSI5TF trend-following strategy is up about 30% year-to-date.
The strategy is based on our PSI5 algo in divergent mode. The instrument universe includes 24 liquid future contracts. In the period of the backtest, from 01/03/2000 to 11/04/2022, the annualized return is 13%. This type of strategy has provided high convexity during years of down-equity markets.
There is a misconception that convergent algos (mean-reversion) are losing money this year. The truth is that profitability depends on the type of convergent algo. A simple convergent algo has performed well for three major ETFs: SPY, QQQ, and TLT. We call this the MRETFLS strategy.
The strategy trades long and short all three ETFs. From 01/02/2003 to 11/04/2022, the annualized return is 5.5%. Year-to-date the strategy is up about 11.6%. Note that in 2008 the strategy gained 6.7%. This strategy has also offered convexity in down-equity periods.
More interesting is the fact that good convergent algos have generated excellent returns also in long-only mode. Below is the performance of a simple convergent algo with Dow Jones Industrial Average stocks from 01/02/1993 to 11/04/2022. We call this the B2S2 strategy.
The annualized return for the B2S2 long-only strategy in the period of the test is 17.4% vs. 9.5% for the SPY ETF total return. The strategy trades all 30 Dow Jones Industrial Average stocks but holds up to 10 open long positions at a time. The selection of stocks is based on a simple rank metric.
Also note that in the backtest of the B2S2 strategy, delistings were taken into account. We used Norgate data for the Dow 30 index that includes current and past constituents.
It is worth mentioning that there is a major difference between divergent and convergent strategies.
The divergent strategies use stops and attempt to identify outliers (trends). The risk is tightly controlled, and if there is a crash in one position, the impact on the strategy is small due to a large ensemble and diversification.
On the other hand, convergent strategies do not use stops and look for price inefficiencies. Protecting against extreme events can be controlled by the allocation of the strategy. Usually, the allocation to convergent strategies is small and less than 10% of available equity.
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Disclaimer
CFTC RULE 4.41 — HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN.
Commodity Futures, Trading Commission Futures, Derivatives, and Options trading have large potential rewards, but also large potential risks. You must be aware of the risks and be willing to accept them to invest in the futures and options markets. Don’t trade with money you can’t afford to lose. The past performanceof any trading system or methodology is not necessarily indicative of future results.
