Showing results 1 to 9 of approximately 9.(refine search)
Why Has the Stock Market Risen So Much Since the US Presidential Election?
This paper looks at the evolution of U.S. stock prices from the time of the Presidential elections to the end of 2017. It concludes that a bit more than half of the increase in the aggregate U.S. stock prices from the presidential election to the end of 2017 can be attributed to higher actual and expected dividends. A general improvement in economic activity and a decrease in economic policy uncertainty around the world were the main factors behind the stock market increase. The prospect and the eventual passage of the corporate tax bill nevertheless played a role. And while part of the rise ...
Does Smooth Ambiguity Matter for Asset Pricing?
We use the Bayesian method introduced by Gallant and McCulloch (2009) to estimate consumption-based asset pricing models featuring smooth ambiguity preferences. We rely on semi-nonparametric estimation of a flexible auxiliary model in our structural estimation. Based on the market and aggregate consumption data, our estimation provides statistical support for asset pricing models with smooth ambiguity. Statistical model comparison shows that models with ambiguity, learning and time-varying volatility are preferred to the long-run risk model. We analyze asset pricing implications of the ...
Taxonomy of Global Risk, Uncertainty, and Volatility Measures
A large number of measures for monitoring risk and uncertainty surrounding macroeconomic and financial outcomes have been proposed in the literature, and these measures are frequently used by market participants, policy makers, and researchers in their analyses. However, risk and uncertainty measures differ across multiple dimensions, including the method of calculation, the underlying outcome (that is, the asset price or macroeconomic variable), and the horizon at which they are calculated. Therefore, in this paper, we review the literature on global risk, uncertainty, and volatility ...
Firm-Specific Risk-Neutral Distributions : The Role of CDS Spreads
We propose a method to extract individual firms' risk-neutral return distributions by combining options and credit default swaps (CDS). Options provide information about the central part of the distribution, and CDS anchor the left tail. Jointly, options and CDS span the intermediate part of the distribution, which is driven by moderate-sized jump risk. We study the returns on a trading strategy that buys (sells) stocks exposed to positive (negative) moderate-sized jump risk unspanned by options or CDS individually. Controlling for many known factors, this strategy earns a 0.5% premium per ...
Measuring Ambiguity Aversion
We confront the generalized recursive smooth ambiguity aversion preferences of Klibanoff, Marinacci, and Mukerji (2005, 2009) with data using Bayesian methods introduced by Gallant and McCulloch (2009) to close two existing gaps in the literature. First, we use macroeconomic and financial data to estimate the size of ambiguity aversion as well as other structural parameters in a representative-agent consumption-based asset pricing model. Second, we use estimated structural parameters to investigate asset pricing implications of ambiguity aversion. Our structural parameter estimates are ...
Institutions and return predictability in oil-exporting countries
We study whether stock market returns in oil-exporting countries can be predicted by oil price changes, and we investigate the link between predictability and the quality of each country's institutions. Returns are predictable for half the countries we consider, and predictability is stronger when institutional quality is lower. We argue that the relation between predictability and institutional quality reflects the preference of countries with weaker institutions to consume oil windfalls locally rather than smooth out the impact of windfalls by, for instance, investing the proceeds through a ...
When do low-frequency measures really measure transaction costs?
We compare popular measures of transaction costs based on daily data with their high-frequency data-based counterparts. We find that for U.S. equities and major foreign exchange rates, (i) the measures based on daily data are highly upward biased and imprecise; (ii) the bias is a function of volatility; and (iii) it is primarily volatility that drives the dynamics of these liquidity proxies both in the cross section as well as over time. We corroborate our results in carefully designed simulations and show that such distortions arise when the true transaction costs are small relative to ...
Macroeconomic Effects of Banking Sector Losses across Structural Models
The macro spillover effects of capital shortfalls in the financial intermediation sector are compared across five dynamic equilibrium models for policy analysis. Although all the models considered share antecedents and a methodological core, each model emphasizes different transmission channels. This approach delivers "model-based confidence intervals" for the real and financial effects of shocks originating in the financial sector. The range of outcomes predicted by the five models is only slightly narrower than confidence intervals produced by simple vector autoregressions.
Downside Variance Risk Premium
We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and significant link between the downside variance risk premium and the equity premium, as well as a ...