In a recent post, Henry Carstens has offered two rules of automated system development. He suggests that the odds of creating a viable system vary directly with the system's holding time, and he conjectures that systems with shorter holding periods will be more likely to degrade in performance.
Henry has more experience in system development than I ever will have, but my limited experience supports his hypotheses. I have found that the largest "edges" in trading occur over holding periods measured in days, not minutes. I have also seen the greatest fall off in performance among discretionary traders whose holding periods are measured in minutes, not hours or days.
My conjecture is that the technology arms race that has led to automated market making and increased high frequency trading has created a high proportion of noise around any possible very short-term market signals. Though markets may still move from Point A to Point B over a period of hours or days, that automated trade has greatly influenced the path from A to B.
I recall, in my earlier days, that experienced traders used to teach beginners who were learning to scalp to limit losses to one tick losers. Today that advice would be silly. It's not unusual to see buy or sell programs come into the market and take out several ticks at a time.
Over longer holding periods, that noise is easier to sit through: a "swipe" in the market that takes out three ticks is not a threat to a swing position targeting a move of 10 ES points; it is a potentially fatal threat to a scalper hoping to risk a few ticks to make a point or two.
Henry's conclusion is that, on average, automated trading systems should outperform discretionary trading over longer holding periods. Discretionary traders with a feel for order flow and momentum can adjust to shifts in participation close to the markets in a way that systems cannot. Systems, on the other hand, can sit through noise and capture signal in a way that often eludes traders beset by perceptual and cognitive biases.
Might it be the case that valid, backtested systems offer an unusually promising platform for teaching new traders how to trade? The systems provide setups with an edge, requiring traders to learn the execution and trade management skills to make the most of the trade. The degree to which traders outperform the system signals reflects the value that their discretionary trading brings to their accounts.
Perhaps one definition of a good discretionary trader is one who adds value to an established trading system.