Intraday Value-at-Risk (VaR) is one of the risk measures used by market participants involved in high-frequency trading. High-frequency log-returns feature important kurtosis (fat tails) and volatility clustering (extreme log-returns appear in clusters) that VaR models should take into account....

When analyzing relative performance, especially at the institutional level, the traditional data envelopment analysis (DEA) models do not recognize vastly different and important activities as separate functions and therefore cannot identify which function may be the main source of inefficiency....

This paper proposes new metrics for the process of price discovery on the main electronic trading platform for euro-denominated government securities. Analysing price data on daily transactions for 107 bonds over a period of 27months, we find a greater degree of price leadership of the dominant...

We consider the channel consisting in transferring the credit risk associated with refinancing operations between financial institutions to market participants. In particular, we analyze liquidity and volatility premia on the French government debt securities market, since these assets are used...

This paper studies the incentives of rating agencies to reveal the information that they obtain about their client firms. In the model, rating agencies seek to maximize their reputation and protect their market power. They observe public information and obtain either precise or noisy private...

This paper examines the volatility timing of US mutual funds by controlling the false discovery rate to find out how many funds are truly countercyclical (procyclical) timing funds. Empirical results show that, given the whole universe of our sample funds, the percentages of countercyclical and...

This paper investigates the joint response of stock and foreign exchange (FX) market returns to macroeconomic surprises, employing a system method of estimation that allows for the cross-country and cross-market interaction for asset returns and risk premia. Using US and Japanese data, we find...

Industry returns cannot be explained fully by well-known asset pricing models. This study reveals that common factors extracted from industry returns carry significant risk premiums that go beyond the explanatory power of size, book-to-market (BM) ratios, and momentum. In particular, this study...

Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying...

In this paper we prove that partial-moments-based performance measures (e.g., Omega, Kappa, upside-potential ratio, Sortino–Satchell ratio, Farinelli–Tibiletti ratio), value-at-risk-based performance measures (e.g., VaR ratio, CVaR ratio, Rachev ratio, generalized Rachev ratio), and other...