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Measuring Risk and Ambiguity in Stock Prices

By Menachem Brenner, Research Professor of Finance and Yehuda Izhakian, Visiting Scholar

Measuring Risk and Ambiguity in Stock Prices by Menachem Brenner

The research demonstrates that risk is positively correlated to the market equity risk premium, while ambiguity tends to be negatively correlated.

While investment managers and risk managers are well acquainted with risk and how to quantify it, finding a way to price assets to account for its more nebulous cousin, ambiguity, has proven elusive. In new research NYU Stern Professor Menachem Brenner and visiting scholar Dr. Yehuda Izhakian propose a new measure of ambiguity, derived from market data, and show how it affects stock prices.

In recognition of this achievement, on Feb. 21, the Investor Responsibility Research Center (IRRC) Institute awarded their paper, “Asset Pricing and Ambiguity: Empirical Evidence,” a $10,000 prize for their contribution to “understanding the interaction of the real economy with investment theory.”

According to the IRRC, the paper finds that stock prices are affected by ambiguity, the unknown probabilities that generate risk—also known to academics as Knightian uncertainty. The research demonstrates that risk is positively correlated to the market equity risk premium, while ambiguity tends to be negatively correlated.

The researchers focused on testing the effect of ambiguity on asset prices in a time series context, using the ETF on the S&P 500 index as a proxy for a market portfolio. Their empirical results show that this measure has a significant effect on stock market returns.

This study is likely the first empirical study that uses market data to measure ambiguity based on a theoretically derived model that combines risk and ambiguity.