Investors Feel Losses More in Calm Markets, Study Finds, Challenging Core Models

Aug. 04, 2025

Investors perceive losses as more painful during calm markets than in volatile ones, according to a new study, casting doubt on traditional asset pricing models and offering new insight into how risk is priced.

 

New Method to Estimate Investor Risk Perceptions

In a paper published in the Journal of Financial Economics, Tobias Sichert (SHoF/SSE) and David Schreindorfer (Michigan State University) propose "a statistical methodology for jointly estimating the pricing kernel and conditional physical return densities from option prices." They show that "negative stock market returns are significantly more painful to investors in low-volatility periods."

"The pricing kernel’s projection onto stock market returns reveals how investors’ marginal utility varies with returns," the authors say. "The steeper curve in periods of low volatility shows that negative returns are significantly more painful to investors when they occur in calm markets."

Using data from equity index options, the authors estimate that a 10% market drop is about three times more painful for investors when it happens in a calm market than during a volatile one.

This means investors place far more value on each dollar during unexpected downturns, suggesting that losses are perceived as more painful when they come as a shock. The finding highlights how investor sensitivity to risk is not constant but depends heavily on the broader market environment.

Standard Models Fall Short

The study’s approach provides a new lens through which to view expected returns, volatility, and investor behavior.

"Our estimates imply that rising volatility affects expected returns through two opposing channels. It increases expected returns due to higher risk […] and it decreases expected returns due to lower risk prices."

The researchers also find that previous models fail to capture key features of risk pricing.

"None of the models come close to capturing basic properties of conditional return distributions or the pricing kernel," they say. "This is troubling because it is arguably the models’ main objective to explain the nature and pricing of stock market risks."

Challenging a Seminal Study

This paper challenges the lower-bound for the equity premium proposed in an influential paper by Martin (2017). The authors show that the lower bound does not hold during periods of market distress like the 2008 financial crash or the Covid-19 market shock. In such volatile times, the lower bound overestimates how much extra return investors should expect.

“Martin’s (2017) lower bound on the equity premium is violated in high-volatility periods,” the authors say. “Martin’s bound overstates the extent to which risk premia spike during economic crises.”

A Stronger Link Between Risk and Return

The paper revives the long-running debate over whether riskier markets reliably offer higher returns.

"Our estimates imply a strong risk–return trade-off despite countercyclical risk prices," the authors write, noting that a one standard deviation increase in volatility raises expected returns by 3.8 percentage points annually.

They also provide the first time-series evidence linking skewness risk—exposure to rare, extreme losses—to higher expected returns, finding that a one standard deviation drop in skewness increases returns by about 1 percentage point per year. This suggests investors demand extra compensation not just for the risk in form of volatility, but also for the risk of sudden downturns.

Implications for Risk Management and Regulation

The findings could have implications for asset managers, central banks, and financial regulators seeking better tools to assess market stress and pricing behavior.

The new method can estimate the full distribution of future market returns, allowing users to quantify the likelihood of various outcomes. Their approach enables real-time risk assessment by capturing the range of possible future returns, the authors say.