Research Interests: asset pricing, econometrics, international finance, macroeconomics
Links: Personal Website
PhD, University of Chicago, 1994; MA, University of Chicago, 1991; MA, Tel-Aviv University, 1988; BA, Tel-Aviv University, 1985
2004 Smith Breeden Award for Distinguished Papers; Alfred Sloan Dissertation Fellowship, 1994
Wharton: 1997-present (named Robert Morris Professor of Banking, 2009; named Gilbert and Shelly Harrison Term Associate Professor, 2008-2009). Previous appointments: Carnegie Mellon University
Visiting Scholar, Institute for International Economic Studies, Stockholm University, June 1996, 2003; Summer Intern, Research Department, International Monetary Fund, 1993; Unit Head, The Financial Advisor to the Chief of Staff, Israel Defense Foreces, 1985-89
Leonid Kogan, Dmitry Livdan, Amir Yaron (Forthcoming), Oil Futures Prices in a Production Economy with Investment Constraints, Journal of Finance, 2009, 64 (3), 1345-1375.
Di (Andrew) Wu, Amir Yaron, Ravi Bansal (Draft), Socially Responsible Investing: Good is Good, Bad is Bad.
Gill Segal, Ivan Shaliastovich, Amir Yaron (2015), Good and Bad Uncertainty: Macroeconomic and Financial Market Implications, Journal of Financial Economics, 117 (2), pp. 369-397. 10.1016/j.jfineco.2015.05.004
Abstract: We decompose aggregate uncertainty into `good' and `bad' volatility components, associated with positive and negative innovations to macroeconomic growth. We document that in line with our theoretical framework, these two uncertainties have opposite impact on aggregate growth and asset prices. Good uncertainty predicts an increase in future economic activity, such as consumption, output, and investment, and is positively related to valuation ratios, while bad uncertainty forecasts a decline in economic growth and depresses asset prices. Further, the market price of risk and equity beta of good uncertainty are positive, while negative for bad uncertainty. Hence, both uncertainty risks contribute positively to risk premia, and help explain the cross-section of expected returns beyond cash flow risk.
Abstract: Uncertainty plays a key role in economics, finance, and decision sciences. Financial markets, in particular derivative markets, provide fertile ground for understanding how perceptions of economic uncertainty and cashflow risk manifest themselves in asset prices. We demonstrate that the variance premium, defined as the difference between the squared VIX index and expected realized variance, captures attitudes toward uncertainty. We show conditions under which the variance premium displays significant time variation and return predictability. A calibrated, generalized Long-Run Risks model generates a variance premium with time variation and return predictability that is consistent with the data, while simultaneously matching the levels and volatilities of the market return and risk free rate. Our evidence indicates an important role for transient non-Gaussian shocks to fundamentals that affect agents' views of economic uncertainty and prices.
Kjetil Storesletten, Chris Telmer, Amir Yaron (2007), Asset Pricing with Idiosyncratic Risk and Overlapping Generations, Review of Economic Dynamics, 2007, vol-10(4), 519-548.
Abstract: What is the effect of non-tradeable idiosyncratic risk on asset-market risk premiums? Constantinides and Duffie (1996) and Mankiw (1986) have shown that risk premiums will increase if the idiosyncratic shocks become more volatile during economic contractions. We add two important ingredients to this relationship: (i) the life cycle, and (ii) capital accumulation. We show that in a realistically calibrated life-cycle economy with production these ingredients mitigate the ability of idiosyncratic risk to account for the observed Sharpe ratio on U.S. equity. While the Constantinides-Duffie model can account for the U.S. value of 41% with a risk-aversion coefficient of 8, our model generates a Sharpe ratio of 33%, which is roughly half-way to the complete-markets value of 25%. Almost all of this reduction is due to capital accumulation. Life-cycle effects are important in our model — we demonstrate that idiosyncratic risk matters for asset pricing because it inhibits the intergenerational sharing of aggregate risk — but their net effect on the Sharpe ratio is small.
Joao F. Gomes, Amir Yaron, Lu Zhang (2006), Asset Pricing Implications of Firms’ Financing Constraints, Review of Financial Studies, Vol. 19 (No. 4), pp. 1321-1356.
Abstract: We use a production-based asset pricing model to investigate whether financing constraints are quantitatively important for the cross-section of returns. Specifically, we use GMM to explore the stochastic Euler equation imposed on returns by optimal investment. Our methods can identify the impact of financial frictions on the stochastic discount factor with cyclical variations in cost of external funds. We find that financing frictions provide a common factor that improves the pricing of cross-sectional returns. Moreover, the shadow cost of external funds exhibits strong procyclical variation, so that financial frictions are more important in relatively good economic conditions.
Kjetil Storesletten, Chris Telmer, Amir Yaron (2006), Asset Prices and Intergenerational Risk Sharing: The Role of Idiosyncratic Earnings Shocks, In Handbook of Investments, Volume 1; Equity Risk Premium, edited by Rajnish Mehra, North-Holland, 2007.
Abstract: In their seminal paper, Mehra and Prescott (1985), Rajnish Mehra and Edward Prescott were the first among many subsequent authors to suggest that non-traded labor-market risk may provide a resolution to the equity-premium puzzle. The most direct demonstration of this was Constantinides and Duffie (1996), who showed that, under certain conditions, cross-sectionally uncorrelated unit-root shocks which become more volatile during economic contractions can resolve the puzzle. We examine the robustness of this to life-cycle effects. Retired people, for instance, do not face labor-market risk. If we incorporate them, to what extent will the equity premium be resurrected? Our answer is “not very much." Our model, with realistic life cycle features, can still account for about 75% of the average equity premium and the Sharpe ratio observed on the U.S. stock market.
FNCE 219 is a course on international financial markets. Major topics include foreign exchange rates, international money markets, currency and interest rate derivatives (forwards, options, and swaps), international stock and bond portfolios, and cryptocurrencies. Students learn about the features of financial instruments and the motivations of market participants. The class focuses on risk management, investing, and arbitrage relations in these markets. In addition to course prerequisites, FNCE 101 is recommended.
Integrates the work of the various courses and familiarizes the student with the tools and techniques of research.
This course covers topics on foreign exchange rates, international money markets, currency and interest rate derivatives (forwards, options, and swaps), international stock and bond portfolios, and cryptocurrencies. Students learn about the features of financial instruments and the motivations of market participants. The class focuses on risk management, investing, and arbitrage relations in these markets. In addition to prerequisites, FNCE 613 is recommended but not required.
Independent Study Projects require extensive independent work and a considerable amount of writing. ISP in Finance are intended to give students the opportunity to study a particular topic in Finance in greater depth than is covered in the curriculum. The application for ISP's should outline a plan of study that requires at least as much work as a typical course in the Finance Department that meets twice a week. Applications for FNCE 899 ISP's will not be accepted after the THIRD WEEK OF THE SEMESTER. ISP's must be supervised by a Standing Faculty member of the Finance Department.
This course is an introduction to empirical methods commonly employed in finance. It provides the background for FNCE 934, Empirical Research in Finance. The course is organized around empirical papers with an emphasis on econometric methods. A heavy reliance will be placed on analysis of financial data.
This is a doctoral level course on macroeconomics, with special emphasis on intertemporal choice under uncertainty and topics related to finance. Topics include: optimal consumption and saving, the stochastic growth model, q-theory of investment, (incomplete) risk sharing and asset pricing. The course will cover and apply techniques, including dynamic programming, to solve dynamic optimization problems under uncertainty. Numerical solution methods are also discussed.
This course has three main objectives: The first object is to introduce students to the fundamental works and the frontier of research in dynamic asset pricing. We will cover recent models that have been proposed to shed light on intreguing and important empirical patterns in the cross section and in the time series. Topics include non-separable utilities, market incompleteness, learning, uncertainty, differences of opionions, ex-ante and ex-post asymmetric information, ambiguity and Knightian uncertainty. The second objective is to teach students how to think of asset pricing research under a bigger or richer framework. We shall focus on the interactions between asset pricing and other fields such as macroeconomics, corporate finance, financial institutions, and international finance. The goal of inventigating the joint dynamics is not only to better understand how asset prices are determined, but also (maybe more importantly) how would asset pricing dynamics affect other important economic vaiables such as investment, corporate payout and financing, unemployment, risk sharing, and international capital flows. Students will learn production-based asset pricing models, particularly the asset pricing models with investment-specific technology shocks, risk shocks, financial friction, searching frictions and information frictions. Of course, the advanced solution methods will focus too. The third objective is to introduce advanced empirical methods to analyze the data and the quantitative dynamic models. It includes how to estimate structural dynamic models, how evaluate structural models beyond goodness-of-fit tests, how confront the models predictions with empirical data by simulation and re-sampling techniques, and how to efficiently test models and explore new patterns using asset pricing and macro data.
It’s a commonly held belief that investors hate uncertainty. But new Wharton research shows that in key respects, the net effects of uncertainty are greater than previously thought -- and they are not always bad.Knowledge @ Wharton - 2015/06/2