This study investigates the day of the week effect on the volatility of major stock market indexes for the period of 1988 through 2002. Using a conditional variance framework, we find that the day of the week effect is present in both return and volatility equations. The highest volatility...

A common approach to comparing asset pricing models involves a competition in pricing test-asset returns. In contrast, we show that for models with traded factors, when the comparison is framed appropriately in terms of success in pricing both the test-asset and factor returns, the extent to...

In this essay, we investigate corporate bond trading in a fully pre-trade transparent market environment using a unique data sample from the Swiss corporate bond market. Contrary to the U.S. market, the Swiss market lists corporate bonds in a central limit order book (CLOB). While dealers place...

In this paper, we estimate the risk spillovers among 74 U.S. REITs using the state-dependent sensitivity value-at-risk (SDSVaR) approach. This methodology allows for the quantification of the spillover size as a function of a company's financial condition (tranquil, normal, and volatile REIT...

In this paper, we estimate the risk spillovers among 74 U.S. REITs using the state-dependent sensitivity value-at-risk (SDSVaR) approach. This methodology allows for the quantification of the spillover size as a function of a company's financial condition (tranquil, normal, and volatile REIT...

This paper attempts to address both theoretical and practical considerations for a tax such as financial transactions taxes (FTT). It includes examples of FTT in the wider context, for example, on stocks and derivatives, currency transactions, and tangible property. Most of the discussion...

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based...