Weaknesses of Discretionary Trading

Discretionary trading, decisions guided by intuition, market “feel,” or personal judgment, has long been appealing to market participants. The ability to adapt, improvise, and react to evolving conditions is often seen as an edge. Yet the empirical record and behavioral research suggest otherwise: discretionary trading is structurally fragile. Without probabilistic anchors or systematic discipline, discretionary styles are prone to cognitive bias, inconsistency, and behavioral drift. 

This memo examines why discretionary trading underperforms and highlights the structural benefits of systematic approaches. Join our Volatility Mailing List to get more content like this.

Cognitive Biases in Decision-Making

The most consistent problem with discretionary trading is its susceptibility to cognitive biases.

• Overconfidence: Traders systematically overestimate their ability to predict outcomes, leading to excessive risk-taking (Kahneman & Tversky, 1979).
  

• Recency Bias: Recent outcomes are overweighted relative to long-term statistical patterns. For example, a winning streak often creates unwarranted confidence, while short-term losses can prompt premature strategy abandonment (Barberis & Thaler, 2003).
  

• Loss Aversion: Traders exhibit asymmetry in risk preferences, holding onto losing trades too long while cutting winners prematurely, reducing expected value over time.
  
  These behavioral distortions consistently impair calibration to actual market probabilities.

Inconsistency and Lack of Repeatability

Unlike systematic frameworks, discretionary approaches lack repeatability. Decisions often vary by time of day, trader mood, or prevailing narratives. Over extended horizons, this inconsistency introduces behavioral drift — an evolution of strategy not guided by robust research but by emotions and anecdotal experience.

Adaptive markets theory suggests that financial markets themselves evolve (Lo, 2017). While adaptability is necessary, discretionary trading tends to lag this evolution, with traders reacting to market shifts through intuition rather than rigorous model updates.

Empirical Underperformance

Research into mutual fund managers and individual investors consistently demonstrates underperformance of discretionary styles. Persistence in performance is rare, and much of the variation can be attributed to chance rather than skill (Carhart, 1997). 

By contrast, systematic approaches grounded in probability and data tend to deliver more consistent outcomes.

Discretionary trading suffers from three structural weaknesses: cognitive bias, lack of repeatability, and inconsistent calibration to evolving markets. While discretion may occasionally produce outsized gains, these are rarely sustainable. By contrast, volatility-aware, systematic approaches mitigate these weaknesses by grounding decisions in probability, statistical modeling, and robust process.

References

• Barberis, N., & Thaler, R. (2003). A survey of behavioral finance. Handbook of the Economics of Finance, 1, 1053–1128.
  

• Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
  

• Lo, A. W. (2017). Adaptive markets: Financial evolution at the speed of thought. Princeton University Press.

• Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57–82.

  Custom HTML/CSS/JAVASCRIPT