Empirical analysis of financial data such as the daily, weekly or monthly prices of assets such as bonds, stocks, currencies and commodities have shown that asset prices approximately follow a martingale process, but the distribution of asset returns tend to be fat-tailed. This paper examines...

The upward bias of the widely used Thompson-Waller estimator has been pointed out in the literature. In contrast the current paper provides a case the estimator would have downward bias. Such case satisfies the two conditions: (i) the buy (sell) order tends to follow buy (sell) order and (ii)...

We develop a new method to estimate private equity funds' market beta from cash flows. Our methodology extends the widely known public market equivalent calculation to a cross-sectional regression. By simply regressing funds' internal rates of return on their paired market internal rates of...

Since the seminal paper of Vasicek and Fong (1982), the term structures of interest rates have been fitted assuming that yields are cross-sectionally homoskedastic. We show that this assumption does not hold when there are differences in liquidity, even for bonds of the same issuer. Lower...

This paper proposes a simple and crude way of approximating the XVA sensitivities. In short, the idea is simply to recycle the existing base simulated portfolio values for the bumped ones. This is done by re-simulating the risk factors for the bumped market and finding out which other base state...

The paper proposes a new robust estimator for GARCH-type models: the nonlinear iterative least squares (NL-ILS). This estimator is especially useful on specifications where errors have some degree of dependence over time (weak-GARCH) or when the conditional variance is misspecified. I illustrate...

We meticulously scrutinize the widely acknowledged measures of the Probability of Informed Trading (PIN) and the Volume-Synchronized Probability of Informed Trading (VPIN), initially posited by David Easley et al., which have achieved considerable eminence within the realm of financial academia....