Does Risk Seeking Drive Asset Prices

We investigate whether risk seeking or non-concave utility functions can help to explain the cross-sectional pattern of stock returns. For this purpose, we analyze the stochastic dominance efficiency classification of the value-weighted market portfolio relative to benchmark portfolios based on market capitalization, book-to-market equity ratio and momentum. We use various existing and novel stochastic dominance criteria that account for the possibility that investors exhibit local risk seeking behavior. Our results suggest that Markowitz type utility functions, with risk aversion for losses and risk seeking for gains, can capture the cross-sectional pattern of stock returns. The low average yield on big caps, growth stocks and past losers may reflect investors' twin desire for downside protection in bear markets and upside potential in bull markets.

We use various stochastic dominance criteria that account for (local) risk seeking to analyze market portfolio efficiency relative to benchmark portfolios formed on market capitalization, book-to-market equity ratio and price momentum. Our results suggest that reverse S-shaped utility functions with risk aversion for losses and risk seeking for gains can explain stock returns. The results are also consistent with a reverse S-shaped pattern of subjective probability transformation. The low average yield on big caps, growth stocks, and past losers may reflect investors` twin desire for downside protection in bear markets and upside potential in bull markets.

In recent years, portfolio flows to emerging markets have become increasingly large and volatile. Using weekly portfolio fund flows data, the paper finds that their short-run dynamics are driven mostly by global “push” factors. To what extent do these cross-border flows and global risk aversion drive asset volatility in emerging markets? We use a Dynamic Conditional Correlation (DCC) Multivariate GARCH framework to estimate the impact of portfolio flows and the VIX index on three asset prices, namely equity returns, bond yields and exchange rates, in 17 emerging economies. The analysis shows that global risk aversion has a significant impact on the volatility of asset prices, while the magnitude of that impact correlates with country characteristics, including financial openness, the exchange rate regime, as well as macroeconomic fundamentals such as inflation and the current account balance. In line with earlier literature, portfolio flows to emerging markets are also found to affect the level of asset prices, as was the case in particular during the global financial crisis.

Financial Markets and the Real Economy reviews the current academic literature on the macroeconomics of finance.

Classical and behavioral finance are often seen as being at odds, but the idea of “popularity” has been introduced as a way of reconciling the two approaches. Investors like or dislike various characteristics of securities for rational reasons (as in classical finance) or irrational reasons (as in behavioral finance), which makes the assets popular or unpopular. In the capital markets, popular (unpopular) securities trade at prices that are higher (lower) than they would be otherwise; hence, the shares may provide lower (higher) expected returns.This book builds on this idea and expands it in two major ways. First, it introduces a rigorous asset pricing model, the popularity asset pricing model (PAPM), which adds investor preferences for security characteristics other than the risk and expected return that are part of the capital asset pricing model. A major conclusion of the PAPM is that the expected return of any security is a linear function of not only its systematic risk (beta) but also of all security characteristics that investors care about. The other major contribution of the book is new empirical work that, while confirming the well-known premiums (such as size, value, and liquidity) in a popularity context, supports the popularity hypothesis on the basis of portfolios of stocks based on such characteristics as brand value, sustainable competitive advantage, and reputation. Popularity unifies the factors that affect price in classical finance with those that drive price in behavioral finance, thus creating a unifying theory or bridge between classical and behavioral finance.

The Capital Asset Pricing Model (CAPM) and the mean-variance (M-V) rule, which are based on classic expected utility theory, have been heavily criticized theoretically and empirically. The advent of behavioral economics, prospect theory and other psychology-minded approaches in finance challenges the rational investor model from which CAPM and M-V derive. Haim Levy argues that the tension between the classic financial models and behavioral economics approaches is more apparent than real. This book aims to relax the tension between the two paradigms. Specifically, Professor Levy shows that although behavioral economics contradicts aspects of expected utility theory, CAPM and M-V are intact in both expected utility theory and cumulative prospect theory frameworks. There is furthermore no evidence to reject CAPM empirically when ex-ante parameters are employed. Professionals may thus comfortably teach and use CAPM and behavioral economics or cumulative prospect theory as coexisting paradigms.