Muscularity and Investment Performance: What the Evidence Actually Says

Executive Summary

The short version: there is almost no direct, clean evidence that simply being more muscular (higher muscle mass or strength) reliably predicts better investment performance (risk-adjusted returns net of costs). Where the literature does touch finance directly, it typically uses indirect biological or physical proxies (e.g., facial metrics, digit ratios, hormones) and finds mixed—and sometimes negative—associations with investing outcomes. citeturn27view0turn5view0turn18search7

A rigorous synthesis across your requested dimensions points to three distinct “evidence layers”:

Direct finance evidence (closest to your question) is sparse and inconsistent.
One of the strongest field papers linking a physical attribute proxy to delegated portfolio performance finds that more “masculine” facial structure (higher facial width-to-height ratio, fWHR) predicts worse hedge fund performance, with economically large underperformance magnitudes (e.g., spreads on the order of several percentage points per year, depending on the specification and subsample). citeturn27view0turn27view1turn4view1
However, another finance setting reports better performance among high-fWHR financial analysts (a different role and outcome metric), highlighting that “physical masculinity proxy → performance” is not directionally stable across contexts. citeturn4view6

Exercise and strength training show reasonably consistent cognitive/psychological benefits, but translating those benefits into investing skill is largely inferential.
A large umbrella review/meta-meta-analysis of randomized controlled trial (RCT) reviews reports small-to-moderate improvements in cognition domains from exercise (general cognition SMD≈0.42; memory SMD≈0.26; executive function SMD≈0.24). citeturn25view2
Yet another umbrella review focusing on RCT meta-analyses argues that publishing/analytic biases may inflate reported effects, with estimated effects shrinking substantially after accounting for moderators and publication bias (down to near-negligible in some corrections). citeturn10view0turn10view2turn10view3
This matters because a “muscularity → better investing” claim often relies on a presumed chain “strength training → cognition/self-control → better financial decisions,” and the middle link is credible but not uniformly large or clean. citeturn25view2turn10view0

Behavioral traits correlated with strength/muscularity can cut both ways for investing.
Evidence from psychology/evolutionary behavioral science links greater strength to traits like entitlement/assertive bargaining and (in some work) sensation seeking—traits plausibly connected to risk tolerance, confidence, and overconfidence. citeturn26view3turn24search3turn24search0
Behavioral finance, meanwhile, shows that overconfidence is strongly associated with excessive trading and worse net performance in large brokerage datasets. citeturn26view0turn26view1
So even if muscularity correlates with confidence/risk appetite, this may raise trading intensity or risk-taking beyond skill, harming performance in many real-world settings. citeturn26view0turn26view1turn27view0

Bottom line: muscularity is not a validated signal of “investor quality.” If anything, the most directly relevant field evidence using masculinity proxies suggests the relationship can be negative for professional delegated management—consistent with a “risk-taking/overconfidence tax” story—while exercise itself may still be beneficial for health, stress resilience, and some cognitive domains that could support better decision processes. citeturn27view0turn25view2turn26view0

Definitions and Scope

What “muscularity,” “strength,” “fitness,” and “exercise” mean in research practice

Muscularity is not a single construct. In empirical work it is usually operationalized as one (or more) of:

• Muscle mass / lean mass (e.g., DXA-derived fat-free mass, appendicular lean mass; sometimes anthropometric proxies such as arm/chest circumference).
• Muscular strength (force production), commonly handgrip strength (HGS) via dynamometer, or 1RM-type tests in trained populations.
• Perceived muscularity (self-report or observer ratings)—which can diverge from objective strength. citeturn15view5turn12search7

Muscular strength is commonly defined as the ability to exert maximal force against resistance. citeturn12search0turn12search8
Hypertrophy (muscle size gain) and strength are correlated but dissociable: training can improve strength without much hypertrophy (neural adaptation) and vice versa. citeturn12search7

Fitness often refers to cardiorespiratory fitness (e.g., VO₂max) and/or a broad set of physical capacities. Public-health guidelines treat muscle-strengthening activity as a distinct component of recommended activity, separate from aerobic volume. citeturn12search9turn12search25

What counts as “investment performance” or “investor quality”

Because “investor quality” is vague, studies typically use one (or more) of:

• Net performance: returns after fees, spreads, and commissions (highly relevant for individuals). citeturn26view0turn26view1
• Risk-adjusted performance (“alpha”): abnormal returns relative to factor models (common for funds/hedge funds). citeturn27view0turn27view1
• Behavioral quality: lower disposition effect, better diversification and tax-loss harvesting, avoiding systematic mistakes. citeturn26view2turn26view0
• Task-based financial risk-taking in experiments (often not tightly linked to real investing). citeturn15view0turn4view7

This distinction is crucial: risk tolerance is not the same as investment skill. Many investors can take more risk and still earn worse risk-adjusted or net outcomes if they trade too much, mis-time, or concentrate. citeturn26view0turn27view0

Exercise, Strength Training, and Cognition

What meta-analytic evidence says about cognitive effects of exercise

A very large umbrella review/meta-meta-analysis aggregating systematic reviews of RCTs reports statistically significant improvements from exercise across cognition domains (general cognition SMD≈0.42; memory SMD≈0.26; executive function SMD≈0.24), spanning ages and populations. citeturn25view2
These magnitudes are often described as small-to-moderate, and subgroup findings suggest effects can vary by age group and intervention characteristics. citeturn25view2

However, a separate umbrella review focused on causal evidence in healthy populations argues that effects may be overestimated due to low statistical power, selective inclusion, publication bias, and analytic flexibility. It reports a pooled exercise–cognition benefit around d≈0.22, shrinking after moderating adjustments (d≈0.13) and becoming near-negligible after publication-bias correction (d≈0.05, with wide uncertainty). citeturn10view0turn10view2turn10view3

Taken together, the literature supports:
Exercise can improve cognition on average, but effect sizes are heterogeneous and sensitive to bias corrections. citeturn25view2turn10view0

Resistance training and executive function

Evidence specifically implicating resistance training (rather than aerobic exercise) includes:

• A 12‑month RCT in older women reporting benefits to executive cognitive functions related to selective attention/conflict resolution following once- or twice-weekly resistance training. citeturn4view4
• A meta-analysis in mild cognitive impairment reporting improvements in general cognition (SMD≈0.53) and executive function (SMD≈0.50), though this is a clinical population and not directly about investing ability. citeturn25view0
• A systematic review/meta-analysis in older adults reporting that exercise benefits both physical function (g≈0.39) and cognitive function (g≈0.24), and—importantly—study-level improvements in physical and cognitive outcomes are positively related (b≈0.41). citeturn25view1

These results make it plausible that improving physical function (including strength) can co-occur with improved cognitive function, but they do not establish that greater muscularity per se produces better financial decision outcomes. citeturn25view1turn12search7

Exercise, arousal, and risk-taking behavior

A small randomized crossover lab study found that a single bout of moderate-to-vigorous cycling affected some risk-taking outcomes differently by sex (e.g., fewer “explosions” on a balloon risk task post-exercise among females), highlighting that acute exercise can alter risk behavior but not necessarily in a uniform direction. citeturn4view5

In finance-relevant experimental work, hormones tied to stress/arousal can shift investment behavior. In an experimental asset market setting, administering cortisol or testosterone shifted investment toward riskier assets, with testosterone operating through increased optimism about future price changes (a psychological channel adjacent to overconfidence). citeturn4view7

Behavioral Traits Linked to Muscularity

Strength, entitlement, and assertiveness

A widely cited behavioral science paper argues and finds evidence that more formidable/stronger individuals (especially men) report greater success in resolving interpersonal conflicts and feel more entitled to better treatment, consistent with an “assertive bargaining” interpretation. citeturn26view3

Related work applying conflict models to modern policy preferences finds that among men, greater upper-body strength predicts more endorsement of self-beneficial positions in redistribution attitudes (direction depends on own socioeconomic position), suggesting strength can calibrate self-interest assertions even in contexts where physical strength is payoff-irrelevant. citeturn15view4

These findings are not about money management directly, but they provide empirical grounding for a plausible behavioral pathway: strength ↔ social dominance/entitlement ↔ confidence/assertiveness, which could influence market behavior (e.g., willingness to “go big,” resist contrary information, or persist after losses). citeturn26view3turn15view4

Muscularity and self-perceived ability: a route to overconfidence?

Work on men’s self-perception of fighting ability finds that upper-body muscularity relates to higher self-perceived fighting ability, only partially mediated by grip strength—suggesting that visually salient muscle mass can influence self-assessment beyond actual performance capacity. citeturn15view5

While “fighting ability” is a different domain, the structure resembles a classic overconfidence setup: visible trait → inflated self-perception → behavior. Translating to finance, this would predict that muscularity may correlate with higher confidence and potentially overconfidence, which behavioral finance shows can be costly. citeturn15view5turn26view0

Strength and sensation seeking (a risk tolerance correlate)

A study of young men reports that handgrip strength correlates positively with sensation seeking (notably “thrill and adventure seeking”), even after controlling for body size and sports engagement. citeturn24search3turn24search0
Sensation seeking is not identical to financial risk tolerance, but it is conceptually aligned with a general preference for intense/novel experiences and willingness to accept risk. citeturn24search3

Empirical Evidence Connecting Physical Attributes to Financial Decision-Making and Performance

This section separates (i) closest-to-investing studies (fund/trader/household finance), from (ii) behavioral-finance “bridge” findings that are highly relevant to whether any muscularity-linked traits would help or harm performance.

Key empirical studies closest to finance outcomes

Study (label)	Sample & setting	Design	Physical / biological measure	Financial outcome measure	Main finding	Effect size (as reported)
Hedge fund managers’ facial structure and performance	Hedge funds with identifiable male manager photos; sample period Jan 1994–Dec 2015; also out-of-sample mutual funds (CRSP)	Observational field study; portfolio sorts + factor models	fWHR from manager photos (and fund-level averages)	Risk-adjusted performance (factor-model alpha), flows, other fund behaviors	High-fWHR managers’ funds underperform low-fWHR managers’ funds; authors interpret via behavioral biases (e.g., risk-related). citeturn6view0turn27view0turn28view1	Hedge funds: underperformance about 5.30%/yr; risk-adjusted about 4.43%/yr; among funds ≥$50m AUM, risk-adjusted spread about 4.02%/yr. citeturn27view0turn27view1 Mutual funds: top vs bottom fWHR deciles underperform about 8.80%/yr risk-adjusted; photos obtained for 5,740 funds (from 12,322 eligible). citeturn4view1turn28view1
Financial analysts’ facial structure and performance	Chinese financial analysts	Observational field study	fWHR	Analyst behaviors (e.g., site visits) and performance metrics	High-fWHR analysts are more likely to do site visits and show better performance; interpreted as “achievement drive.” citeturn4view6	Effect size not in accessible excerpt. citeturn4view6
CEO fitness and firm value	CEOs of S&P 1500 firms 2001–2011; “fit” if they finish a marathon	Observational field study	Binary “fitness” via marathon completion	Firm value (Tobin’s Q), profitability; M&A announcement returns	Positive relation between CEO fitness and firm value; stronger in high workload/older/tenured subsamples; fit CEOs linked to higher abnormal announcement returns in certain M&A contexts. citeturn6view3turn6view5	Abnormal returns in complex/large M&A contexts about 1.7–3.0 percentage points higher with fit CEOs (reported ranges). citeturn6view5
CEO facial masculinity and firm/bank risk	US CEOs; banking and non-financial firms (separate studies)	Observational field studies	CEO fWHR (“facial masculinity”)	Risk proxies: stock return volatility, leverage, acquisitions, idiosyncratic risk	More masculine-faced CEOs lead firms/banks with higher risk metrics (volatility, idiosyncratic risk, leverage, acquisitiveness). citeturn5view5turn5view6	Effect sizes not in accessible excerpt. citeturn5view5turn5view6
Endogenous steroids on a trading floor	Male traders under real working conditions	Observational field study	Salivary testosterone/cortisol	Daily profitability; volatility/variance	Morning testosterone predicts same-day profitability; cortisol tracks volatility and variance. citeturn5view0	Effect size not in accessible excerpt. citeturn5view0
Hormones in experimental asset markets	Participants in an experimental asset market; plus hormone administration sub-studies	Lab experiment + hormone administration	Endogenous cortisol/testosterone; administered hydrocortisone or testosterone gel	Risky asset allocation and price instability in a trading game	Both cortisol and testosterone shift investment toward riskier assets; testosterone acts via increased optimism about future price changes. citeturn4view7	Directional; quantitative magnitudes not extracted here. citeturn4view7
Large testosterone administration RCT on economic preferences	1,000 men (18–45), double-blind RCT	Preregistered RCT	Single-dose intranasal testosterone vs placebo	Economic tasks: risk, fairness, altruism, competitiveness	No evidence of treatment effects on nine primary outcomes; challenges earlier small-sample claims. citeturn18search7turn18search0	“No effect” across primary outcomes (reported). citeturn18search7turn18search0
Exercise and household risky asset allocation	China Family Panel Studies 2010–2022	Observational (panel)	Physical exercise (behavioral measure)	Risky asset amount and share (stocks, funds, etc.)	Exercise associated with higher risky-asset allocation; mechanisms proposed: health and future confidence; stronger among higher income / lower economic pressure. citeturn15view1	Effect size not in accessible excerpt. citeturn15view1
Physical activity stage and economic preferences	Low-income urban African American neighborhood; n=169	Cross-sectional with incentivized tasks	Physical activity stage (self-report), BMI/waist	Incentivized financial risk tolerance and time preferences	More risk tolerant (OR≈1.31) and more patient (OR≈1.68) individuals are in more advanced physical activity stages. citeturn15view0	Odds ratios reported above. citeturn15view0
Attractiveness stereotypes in fund markets	Survey experiments + Chinese fund manager photo dataset (n≈4,448 managers)	Experiments + field evidence	AI-rated attractiveness from photos	Investor allocations / fund flows	Investors prefer attractive managers absent performance info; contrary return info can override; field fund flows align with “attractiveness halo.” citeturn5view7	Directional; specific effect sizes not extracted here. citeturn5view7

Interpretation: Even the “closest” studies rarely measure muscle mass or objective strength directly. Instead, the finance literature uses observed fitness (marathon), hormones, or facial masculinity proxies. For your exact question—muscularity → investing success—the evidence is mostly indirect and can plausibly reflect selection and confounding rather than a causal effect of muscle. citeturn6view3turn18search7turn16search1

Behavioral-finance bridge evidence: why confidence is not automatically good

Two well-identified regularities in behavioral finance are directly relevant to any muscularity-linked “confidence/risk appetite” channel:

1) Active trading tends to reduce net returns for individual investors.
A classic large-brokerage study reports that the most active traders earned about 11.4% annual return vs 17.9% for the market, and states its central message: trading is hazardous to wealth. citeturn26view0

2) Overconfidence appears to increase trading, and men trade more than women in a large dataset—reducing net returns.
A study using >35,000 households reports that men trade 45% more than women and that trading reduces men’s net returns by about 2.65 percentage points/year versus 1.72 for women. citeturn26view1

A separate strand of household finance evidence links cognitive ability to better investing behaviors and reduced biases: one paper using near-universal IQ testing data (Finnish male cohort) reports that higher-IQ investors are less subject to disposition effects and exhibit better timing/stock selection/trade execution. citeturn26view2turn17search0

Why this matters for muscularity:
If muscularity correlates with confidence/sensation seeking, it could increase risk exposure and trading intensity; whether that helps hinges on whether it also predicts skill (rare) rather than overconfidence (common). Finance field evidence on performance penalties from trading suggests this channel can easily be negative. citeturn26view0turn26view1turn27view0

Confounders, Measurement, and Bias

A realistic causal model: why “muscularity → investing skill” is hard to identify

Muscularity and strength correlate with multiple variables that also correlate with investing outcomes—making naïve associations hard to interpret:

• Sex and hormones: baseline testosterone differs by sex and changes across age; many finance datasets are male-dominated for traders/CEOs. citeturn5view0turn18search7
• Age: strength rises and then declines; investment participation, wealth accumulation, and risk preferences also vary with age. citeturn13search18turn17search19
• Socioeconomic status (SES): wealth and education can predict both better health/strength and greater investment participation/choice sets. Cross-national evidence shows wealth and education gradients in handgrip strength among older adults. citeturn13search6turn16search1
• Early-life conditions: parental SES is associated with young adults’ skeletal muscle mass, consistent with life-course confounding. citeturn16search6
• Occupation and time constraints: high-income finance roles may both enable structured fitness routines and select for certain traits. citeturn6view3turn15view1
• Health status: “strength” is often a marker of general health; health shocks can increase risk aversion (a grip-strength-identified shock approach), suggesting health dynamics can drive preferences. citeturn15view2turn14search0

Measurement issues: self-report vs objective measures

Handgrip strength (HGS) is widely used as a convenient proxy for overall strength, with large normative datasets available. citeturn13search18
But measurement is not frictionless:

• Device-to-device agreement can be poor even when reliability is high, implying that “strength” estimates can be instrument-dependent and require standardization/cutoffs. citeturn12search10
• HGS captures a narrow motor output (upper-limb grip) and reflects technique, hand size, and body size, motivating normalization approaches and careful protocol control. citeturn13search18turn12search10

Muscle mass measures (DXA, BIA) and perceived muscularity can diverge from actual strength and from discipline/fitness habits—important if one hypothesizes that “investor quality” relates more to habit formation and self-regulation than to raw muscle tissue. citeturn12search7turn15view5

Proxy risks and selection bias in “physical traits → finance” studies

The closest “physical attribute → investing performance” study uses facial structure (fWHR) from photos and explicitly filters for photo characteristics (e.g., forward-facing, minimal facial adiposity in some parts), which can induce selection and generalizability limits. citeturn28view1turn28view2
Moreover, facial metrics are debated proxies for hormones/behavior, and measurement method choices can change results in related research on masculinity and behavior. citeturn5view4

Reverse causality is also plausible in lifestyle-based work: individuals who are more risk tolerant and patient may simply be more likely to adopt exercise routines, rather than exercise causing those preferences. citeturn15view0

A confounding-directed view (mermaid DAG)

flowchart TB
  SES[Socioeconomic status\n(education, wealth, early-life conditions)] --> M[Muscularity/Strength]
  SES --> I[Investment participation & outcomes]
  H[Health status\n(chronic disease, injury, sleep)] --> M
  H --> I
  A[Age] --> M
  A --> I
  S[Sex & endocrine milieu] --> M
  S --> I
  P[Personality traits\n(sensation seeking, dominance,\nself-control)] --> M
  P --> I
  E[Exercise habits] --> M
  E --> C[Cognition & stress regulation]
  C --> I
  M --> SC[Self-confidence / perceived ability]
  SC --> RT[Risk tolerance / trading intensity]
  RT --> I

This structure makes clear why observed correlations can flip sign depending on context: the net effect depends on whether muscularity primarily loads onto (a) cognition/self-control/stress tolerance or (b) sensation seeking/overconfidence/trading intensity, and which confounders are controlled. citeturn25view2turn26view0turn24search3

Practical Implications and Strength of Evidence

What investors should (and should not) conclude

Muscle mass or visible muscularity is not a validated predictor of investing edge.
The most direct performance evidence using a physical masculinity proxy finds strong underperformance for more masculine facial structure among delegated managers, which is directionally opposite the “stronger = better investor” stereotype. citeturn27view0turn4view1

Exercise and strength training remain plausibly beneficial for investors—just not via “muscularity causes alpha.”
The best-supported benefits are in health, stress buffering, and (on average) modest cognitive improvements; these could support better decision hygiene (sleep, mood, attentional control), even if they do not guarantee superior returns. citeturn25view2turn25view1turn4view4

Beware the confidence trap.
If muscularity correlates with sensation seeking or entitlement/confidence, it may increase the temptation to trade, lever, or “bet conviction,” and large-scale evidence indicates that excessive trading typically reduces net performance. citeturn24search3turn26view0turn26view3

What employers should conclude about “investor quality”

Using physical appearance, muscularity, or “fitness vibe” as a hiring signal is not just scientifically weak; it risks reinforcing bias:

• Investors show physical-attractiveness stereotyping of fund managers even without evidence of superior performance. citeturn5view7
• “Masculinity proxies” (faces) can be statistically linked to risk-taking or performance in some datasets, but the mechanism is uncertain, and using such cues in selection would be ethically fraught and likely discriminatory. citeturn27view0turn5view6turn5view4

Summary table: strength of evidence by hypothesis

Hypothesis	Evidence base	Direction consistency	Causal credibility	Overall strength
Greater muscularity (muscle mass/strength) → better investment performance	Very limited direct evidence; mostly absent	N/A	N/A	Very low
Strength training/exercise → improved cognition relevant to decisions	Many RCT reviews/meta-analyses; effects heterogeneous	Generally positive but debated after bias correction	Moderate (RCTs), but effect-size uncertainty	Moderate citeturn25view2turn10view0
Strength/muscularity → higher confidence/dominance/entitlement	Multiple psychology/evolutionary studies	Fairly consistent within studied populations (often male samples)	Mostly correlational	Moderate citeturn26view3turn15view5turn24search3
Strength/muscularity → higher risk tolerance / sensation seeking	Some evidence (e.g., HGS–sensation seeking), mixed in broader econ preference settings	Partial	Correlational	Low–moderate citeturn24search3turn15view0
Physical masculinity proxies (fWHR) → investor/manager performance	Several field studies; outcomes differ by role (hedge funds vs analysts)	Mixed	Correlational; selection issues	Low–moderate citeturn27view0turn4view6turn5view4
Testosterone (acute) → risky economic choices	Large preregistered RCT finds no effect on main outcomes; smaller studies mixed	Inconsistent	High for acute dosing (RCT), but context-dependent	Moderate (for “no large acute effect”) citeturn18search7turn4view7
Overconfidence → worse net investor performance via trading	Large field evidence + theory; robust	Consistent	High (field evidence with mechanisms)	High citeturn26view0turn26view1

Timeline of the most relevant literature threads (conceptual)

timeline
  2000 : "Trading is hazardous to wealth" brokerage evidence links heavy trading to lower returns
  2001 : Gender/overconfidence study: men trade more, suffer larger net-return penalty
  2008 : Field endocrinology on trading floor: testosterone predicts daily profitability
  2009 : Strength/formidability linked to entitlement and assertive bargaining traits
  2014 : CEO marathon-based fitness associated with higher firm value and M&A announcement returns
  2022 : Hedge fund manager facial masculinity proxy (fWHR) linked to underperformance
  2023 : Umbrella review warns exercise–cognition evidence may be inflated by bias
  2025 : Large umbrella review finds small-to-moderate cognitive benefits of exercise across populations
  2025 : Large preregistered RCT: intranasal testosterone shows no effect on economic preferences

The key inference from this timeline is that behavioral-finance fundamentals about overconfidence and trading costs are far better established than any muscle-based predictor, and the “biology → finance” literature is still too sparse and proxy-driven to justify strong claims about muscularity and investor quality. citeturn26view0turn27view0turn18search7turn25view2