Topics in Asset Pricing
Paper Session
Monday, Jan. 4, 2021 12:15 PM - 2:15 PM (EST)
- Chair: Zhao Han, College of William & Mary
Arbitrage in the Binary Option Market: Distinguishing Behavioral Biases
Abstract
In the first empirical analysis of the binary option market, we show that U.S. retail traders forgo clear arbitrage opportunities by purchasing binary options when strictly dominant portfolios of traditional call options are available at lower prices. Using a yearlong sample of binary option trades, we find that 19% of S&P index, 21% of gold, and 25% of silver trades violate our no-arbitrage condition. The amount of money lost is large: buyers of binary options on average lose about a third of the contract price by forgoing the dominating call option portfolio. After rejecting standard institutional justifications for the existence of arbitrage, including random price volatility and various forms of trading costs, we examine possible behavioral explanations. We show that our results cannot be explained by canonical behavioral models such as prospect theory or cumulative prospect theory. Instead, we rationalize our findings with a novel behavioral model in which investors prefer simple binary lotteries to more complicated sets of outcomes. An online survey of binary option traders supplements our analysis of market data, providing direct evidence that a "preference for simplicity" is more common among these traders than prospect theory preferences.Announcements, Expectations, and Stock Returns with Asymmetric Information
Abstract
Revisions of consensus forecasts of macroeconomic variables positively predict announcement day forecast errors, whereas stock market returns on forecast revision days negatively predict announcement day returns. A dynamic noisy rational expectations model with periodic macroeconomic announcements quantitatively accounts for these findings. Under asymmetric information, average beliefs are not Bayesian: they underweight new information and positively predict subsequent belief errors. In addition, stock prices are partly driven by noise, and therefore negatively predict returns on announcement days when noise is revealed and the market corrects itself.Disagreement, Information Quality and Asset Prices
Abstract
We solve analytically a pure exchange general equilibrium model with a continuumof agents that agree to disagree on how they interpret information. Disagreement
fluctuates with information quality and the disagreement model is estimated using
data on professional forecasts. We find that fluctuations in information quality generate about half the stock price volatility in the data, help explain the equity premium, and explain empirical relations between the forecast dispersion and asset prices. Constant information quality cannot account for the variation in forecast dispersion and in this case, disagreement has almost no effect on the stock return volatility.
The Asset Durability Premium
Abstract
This paper studies how the durability of assets affects the cross-section of stock returns. More durable assets incur lowers frictionless user costs but are more "expensive", in the sense that they need more down payments making them hard to finance. In recessions, firms become more financially constrained and prefer "cheaper" less durable assets. As a result, the price of less durable assets is less procyclical and therefore less risky than that of durable assets. We provide strong empirical evidence to support this prediction. Among financially constrained stocks, firms with higher asset durability earn average returns about 5% higher than firms with lower asset durability. We develop a general equilibrium model with heterogeneous firms and collateral constraints to quantitatively account for such a positive asset durability premium.Predictable End-of-Month Treasury Returns
Abstract
We document a distinct pattern in the timing of excess returns on coupon Treasury securities. Average returns are positive and highly significant in the last few days of the month, and are not significantly different from zero at other times. A long Treasury position for just the last few days of each month gives a high annualized Sharpe ratio of around 1. We attribute this pattern to temporary spikes in investor demand for specific securities due to window dressing and portfolio rebalancing. We find evidence in quantities that aggregate insurer transactions contribute to the end-of-month price pattern. In particular life insurers are large net buyers of Treasury securities on benchmark index rebalancing dates.JEL Classifications
- G1 - Asset Markets and Pricing