The Psychophysiology of Market Execution: Why Your Body Is Your Most Important Trading Tool
Every trade journal on the market — Edgewonk, TradeZella, Tradervue, TraderSync — tracks the same financial variables: entry price, exit price, P&L, win rate. Not a single one tracks the most powerful predictor of trading performance that decades of neuroscience research has identified: the biological state of the trader themselves.
Cortisol, Testosterone, and the Biology of Risk
John Coates, a former Wall Street trader turned Cambridge neuroscientist, conducted the seminal field study on hormones and trading in 2008. Working with traders on a London trading floor, Coates measured salivary cortisol and testosterone levels under real working conditions.
Key Findings (Coates & Herbert, PNAS 2008)
- Testosterone predicts profitability: 14/17 traders had higher profits on high-testosterone days. One trader on a 6-day winning streak saw testosterone rise 74% above baseline. Effect size: Cohen's d = 1.37 for experienced traders.
- Cortisol tracks volatility: Group cortisol correlated with market implied volatility at r² = 0.86.
- The Winner Effect: Success raises testosterone, increasing risk appetite — until the loop becomes pathological during bull markets.
A subsequent interventional study (Cueva et al., 2015, N=142) confirmed the causal relationship: administering cortisol to subjects before they played a trading game significantly altered investment behavior and predicted price instability. The research reveals an inverted U-shaped dose-response curve: moderate stress may optimize performance, while extremes in either direction predict poor outcomes.
Sleep Deprivation: The Worst Possible Combination for Traders
A 2007 fMRI study by Venkatraman et al. (Duke University, published in SLEEP) revealed that sleep deprivation creates a dual neurological impairment: it elevates expectation of gains while simultaneously attenuating the brain's response to losses. This is the worst possible combination for a trader — inflated upside expectations and muted loss sensitivity.
More recent research (Xu et al., 2024, Frontiers in Neuroscience) found that sleep-deprived subjects could still recognize winning patterns but failed to learn from losing ones. For a trader, this means you keep doubling down on what worked yesterday while being blind to today's losses. A 2025 scoping review of 25 studies confirmed that effects are particularly pronounced for "hot" decisions involving emotional and motivational factors — precisely the kind of decisions made in active trading.
The Somatic Marker Hypothesis: Your Gut Feelings Are Data
Antonio Damasio's Somatic Marker Hypothesis (SMH) proposes that emotions and bodily sensations — heart rate, gut feelings, muscle tension — play a critical role in fast decision-making under uncertainty. In the Iowa Gambling Task, healthy participants develop anticipatory skin conductance responses — essentially "gut feelings" — before choosing from risky decks, even before they can consciously articulate why. This is why our journal asks you to tag your emotional state: it's not soft science, it's Damasio's core hypothesis that body state encodes risk intelligence.
Circadian Rhythms and Your Optimal Trading Window
Research on chronotype and cognitive performance (Dickinson & McElroy, 2016, Scientific Reports) found that a three-hour phase difference in molecular clockwork between morning-types and evening-types is sufficient to influence risk-taking behavior. A 2023 systematic review found cognitive performance varies 9% to 40.3% by time of day for attention tasks. Our journal tracks time of trade entry and correlates it with your self-reported energy — surfacing insights like "Your win rate is 67% for trades entered between 9-11 AM but drops to 42% after 2 PM."
Behavioral Pattern Detection
Beyond health correlations, the journal algorithmically detects destructive behavioral patterns that operate below conscious awareness:
- Revenge Trading: Detects trades entered within 15 minutes of a losing trade with increased position sizes.
- Tilt: Flags 3+ consecutive losses with escalating position sizes.
- Decision Fatigue: Warns when trades are entered after extended screen time or with low self-reported energy.
- Pre-Commitment Rules: Set your own rules ("Don't trade with <6h sleep") and the journal warns you with your own data when you break them.
The Trade Readiness Score
Inspired by Oura Ring's Readiness Score, the Trade Readiness Score (TRS) synthesizes your self-reported health data into a single 0-100 number. Sleep is weighted highest (25%), followed by energy (20%), stress and screen time (15% each), exercise (10%), meal timing (10%), and caffeine (5%). The score reflects an inverted-U relationship with stress and caffeine — moderate levels are optimal, while extremes predict poor outcomes.
TRS Interpretation
The Cold Start and Statistical Power
For 80% statistical power to detect a medium effect (r = 0.30) at alpha = 0.05, approximately 84 observations are needed. The journal is transparent about this: health-performance correlations first appear at 15+ trades with caveats, become meaningful at 30-50 trades, and are highly reliable at 100+ trades. The insights get better with more data, creating a "data moat" that makes this tool more valuable the longer you use it.
Key References
- Coates JM, Herbert J. "Endogenous steroids and financial risk taking on a London trading floor." PNAS (2008).
- Cueva C et al. "Cortisol and testosterone increase financial risk taking and may destabilize markets." Scientific Reports (2015).
- Venkatraman V et al. "Sleep deprivation elevates expectation of gains and attenuates response to losses." SLEEP (2007).
- Xu J et al. "Sleep deprivation impairs negative feedback utilization." Frontiers in Neuroscience (2024).
- Damasio AR. "The somatic marker hypothesis and the possible functions of the prefrontal cortex." Phil. Trans. R. Soc. (1996).
- Killgore WDS et al. "Sleep deprivation reduces perceived emotional intelligence and constructive thinking skills." Sleep Medicine (2006).
- Dickinson DL, McElroy T. "Circadian effects on strategic reasoning." Scientific Reports (2016).
- Ericsson KA et al. "The role of deliberate practice in the acquisition of expert performance." Psychological Review (1993).
- FINRA Rule 2111. Suitability: educational exemptions for analysis tools.