Hierarchical Time-Varying Estimation of Asset Pricing Models

This paper presents a new hierarchical methodology for estimating multi factor dynamic asset pricing models. The approach is loosely based on the sequential Fama–MacBeth approach and developed in a kernel regression framework. However, the methodology uses a very flexible bandwidth selection method which is able to emphasize recent data and information to derive the most appropriate estimates of risk premia and factor loadings at each point in time. The choice of bandwidths and weighting schemes are achieved by a cross-validation procedure; this leads to consistent estimators of the risk premia and factor loadings. Additionally, an out-of-sample forecasting exercise indicates that the hierarchical method leads to a statistically significant improvement in forecast loss function measures, independently of the type of factor considered.

The Effects of the COVID-19 Crisis on Risk Factors and Option-Implied Expected Market Risk Premia: An International Perspective

Institutional investors often have to decide which strategy to use across international business cycles. This is especially important during economic and financial crises. The exogenous nature of the outbreak of the dramatic COVID-19 crisis represents a unique opportunity to understand the performance of risk factors during severe economic times across international stock markets. Even more important is to analyze how these factors behave across very different economic crises, such as the COVID-19 pandemic and the Great Recession. Although, the overall results show that the momentum and quality factors are the winners, with the value factor as the loser, this research also reports different responses of factors across crises and countries. The size, value, and defensive factors tend to perform worse during the health crisis relative to the Great Recession, while the momentum factor shows a poor performance during the financial crisis, but a positive one during the outbreak of COVID-19. The quality factor is an extraordinary defensive factor in both crises. Similarly, this paper reports heterogeneous responses of option-implied expected market risk premia across alternative stock market indices, and between the Great Recession and the COVID-19 crisis.

Stranded Assets: How Policy Uncertainty affects Capital, Growth, and the Environment

The paper considers stochastic environmental policy and its effects on the environment, portfolio composition, and economic growth. Capital accumulation causes pollution which is reduced by private green services and public abatement. The government subsidizes green services and taxes dirty capital albeit at a rate which may become random, causing unexpected capital write-offs. Tax jumps depend on natural degradation and environmental activism. We derive how uncertainty and political activism affect the risk premia for investors. We analyze the incentives for firms to increase the greenness of production in order to reduce political uncertainty. Stochastic taxation is shown to act as a substitute for green subsidies when uncertainty decreases in the ratio of green services to capital and agents use their green activities strategically. Tax uncertainty may trigger precautionary savings, causing additional growth and enhanced environmental deterioration.