Members of the NBER's Asset Pricing Program met at Stanford University November 30. Research Associates Tano Santos and Harrison Hong, both of Columbia University organized the meeting, which was sponsored by the Alfred P. Sloan Foundation. These researchers' papers were presented and discussed:
Yaron Levi, University of Southern California, and Ivo Welch, University of California, Los Angeles and NBER
Market-Beta and Downside Risk
The plain market-beta was a good predictor of stock returns not only during bull and ordinary markets, but also during bear markets and crashes. Thus, it was indeed a good measure of the hedge against market risk. This plain beta also predicted the subsequent down-beta (i.e., measured only on days when the stock market declined) better than the prevailing down-beta. Stocks with higher ex-ante down-betas did not earn a positive risk premium. Levi and Welch conclude that ex-ante down-betas were neither useful hedging nor useful risk-pricing measures.
Michael Sockin, University of Texas at Austin, and Wei Xiong, Princeton University and NBER
A Model of Cryptocurrencies
The surge in the number of initial coin offerings (ICOs) in recent years has led to both excitement about cryptocurrencies as a new funding model for innovations in the digital age, and to anxiety about a potential bubble. Sockin and Xiong develop a model to address several basic questions: What determines the fundamental value of a cryptocurrency? How would market trading interact with its fundamentals in an uncertain and opaque environment? In the model, a cryptocurrency constitutes membership in a platform developed to facilitate transactions of certain goods or services. The complementarity in the households' participation in the platform acts as an endogenous, yet fragile, fundamental of the cryptocurrency. There exist either two or no equilibria, and the two equilibria, when they exist, have disparate properties. When the transaction demand for the platform is unobservable, the trading price and volume of the cryptocurrency serve as important channels for not only aggregating private information about its fundamental, but also facilitating coordination on a certain equilibrium.
Valentin Haddad, University of California, Los Angeles and NBER; Paul Ho, Princeton University; and Erik Loualiche, University of Minnesota
Episodes of booming firm creation often coincide with intense speculation on financial markets. Haddad, Ho, and Loualiche show that while speculation leads to more firm entry, it might actually mitigate over-entry, leading to efficient innovative booms. More broadly, disagreement among investors completely transforms the economics of optimal firm creation. The researchers characterize the interaction between speculation and classic entry externalities from growth theory through a general entry wedge formula for a non-paternalistic planner. The business-stealing effect is mitigated when investors believe they can identify the best firms, hence more entry goes along with less excess entry. The appropriability effect also vanishes, leaving only general equilibrium effects on input prices, aggregate demand, or knowledge. As a result, speculation reverses the role of many industry characteristics such as the labor share for efficiency. Further, economies with identical aggregate properties but a different market structure have the same efficiency with agreement, but differ in presence of bubbles.
Zhengyang Jiang, Northwestern University, and Arvind Krishnamurthy and Hanno Lustig, Stanford University and NBER
Foreign Safe Asset Demand and the Dollar Exchange Rate (NBER Working Paper No. 24439)
Jiang, Krishnamurthy, and Lustig develop a theory that links foreign investors' demand for the safety of U.S. Treasury bonds to the value of the dollar in spot markets. An increase in the convenience yield that foreign investors derive from holding U.S. Treasurys induces an immediate appreciation of the U.S. dollar and, going forward, lowers the expected return to a foreign investor from owning Treasury bonds. Under the researchers' theory, they show that the foreign convenience yield can be measured by the 'Treasury basis,' defined as the wedge between the yield on foreign government bonds and the currencyhedged yield on U.S. Treasury bonds. They measure the convenience yield using data from a cross-country panel going back to 1988 and the US/UK cross going back to 1970. In both datasets, regression evidence strongly supports the theory. The results help to resolve the exchange rate disconnect puzzle: the Treasury basis variation accounts for up to 41% of the quarterly variation in the dollar. The results also provide support for recent theories which ascribe a special role to the U.S. as a provider of world safe assets.
Martin Lettau, University of California, Berkeley and NBER, and Markus Pelger, Stanford University
Factors that Fit the Time Series and Cross-Section of Stock Returns (NBER Working Paper No. 24858)
Lettau and Pelger propose a new method for estimating latent asset pricing factors that fit the time-series and cross-section of expected returns. The estimator generalizes Principal Component Analysis (PCA) by including a penalty on the pricing error in expected returns. The researchers show that the estimator strongly dominates PCA and finds weak factors with high Sharpe-ratios that PCA cannot detect. Studying a large number of characteristic sorted portfolios the researchers find that five latent factors with economic meaning explain well the cross-section and time-series of returns. The research shows that out-of-sample the maximum Sharpe-ratio of the five factors is more than twice as large as with PCA with significantly smaller pricing errors. The researchers' factors are based on only a subset of the stock characteristics implying that a significant amount of characteristic information is redundant.
Cecilia Parlatore, New York University, and Eduardo Dávila, New York University and NBER
Volatility and Informativeness
Parlatore and Dávila explore the equilibrium relation between price volatility and price informativeness in financial markets, with the ultimate goal of characterizing the type of inferences that can be drawn about price informativeness by observing price volatility. The researchers identify two different channels (noise reduction and equilibrium learning) through which changes in price informativeness are associated with changes in price volatility. They show that when informativeness is sufficiently high (low) volatility and informativeness positively (negatively) co-move in equilibrium for any change in primitives. In the context of the researchers' leading application, they provide conditions on primitives that guarantee that volatility and informativeness always comove positively or negatively. The research uses data on U.S. stocks to recover stock specific primitives and show that most stocks lie in the region of the parameter space in which informativeness and volatility co-move negatively.