The traditional fund-by-fund performance evaluation method suffers from various econometric problems such as multiple hypothesis testing, time-varying coefficients, cross-sectional dependence, etc. To overcome these problems, we tailor three high-dimensional cross-sectional tests to empirically...

This paper develops an empirical procedure for analyzing the impact of model misspecification and calibration errors on measures of portfolio credit risk. When applied to large simulated portfolios with realistic characteristics, this procedure reveals that violations of key assumptions of the...

This article aims to extend evaluation of the classic multifactor model of Carhart (1997) for the case of global equity indices and to expand analysis performed in Sakowski et. al. (2015). Our intention is to test several modifications of these models to take into account different dynamics of...

The purpose of this paper is introducing rigorous methods and formulas for bilateral counterparty risk credit valuation adjustments (CVA's) on interest-rate portfolios. In doing so, we summarize the general arbitrage-free valuation framework for counterparty risk adjustments in presence of...

This paper proposes an affine-based approach which jointly captures the nominal interest rate, the real interest rate, and the inflation risk premium to price inflation-indexed derivatives, including zero-coupon inflation-indexed swaps, year-on-year inflation-indexed swaps, inflation-indexed...

Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the non-normality of individual mutual fund returns is accounted for...

We investigate the validity and reliability of the bootstrap approach in fund performance evaluation by gauging the size. Monte Carlo simulations suggest that cross-sectional dependence may alter the size of this test and we propose a new panel bootstrap approach