Natalie Zhu



  • Ph.D. Financial Economics, Yale School of Management, 2020 (expected)
  • B.A. Economics, Washington University in St. Louis, 2013

About Me

Welcome to my website. I am a Ph.D. candidate in Financial Economics at the Yale School of Management. My current research interests include Behavioral Finance, Empirical Asset Pricing, and Household Finance.

I am on the job market this year and will be available at the ASSA 2020 Meetings in San Diego.

Curriculum Vitae

Dissertation Committee

Working Papers

Online Appendix

I propose and document empirically that investors form “range-based” expectations – expectations that are influenced by an asset’s past trading range – and that these beliefs affect trading behavior and asset prices. I find that, if an asset’s price is high (low) relative to its 52-week trading range, investors erroneously believe that the asset’s future return distribution is negatively (positively) skewed. Consistent with these beliefs, less sophisticated investors trade options in a way that decreases their exposure to underlying stocks that have a high price relative to their 52-week range; moreover, individual investors are more likely to sell and not buy such stocks. Also consistent with these beliefs, stocks with a high (low) price relative to their past trading range earn high (low) subsequent returns, on average.

I present a simple framework in which a representative investor evaluates corporate bonds according to prospect theory. Because the investor overweights the low default probability and is averse to default losses, the model generates a higher credit spread relative to the benchmark. The results shed light on the credit spread puzzle–the finding that credit spreads predicted by traditional models are much lower than actual spreads. In addition, using a novel dataset on U.S. corporate bonds, I find that a bond whose past return distribution is appealing (unappealing) under prospect theory yields a low (high) subsequent credit spread, suggesting that prospect theory helps explain variation in the credit spread over time.