This paper proposes methods to estimate and compare asset pricing models in settings
with a large number of test assets. Models are specified through a linear stochastic discount
factor (SDF). We propose two regularization schemes to extend the Hansen-Jagannathan
distance to high-dimensional environments. In addition to stabilizing the inversion of the
covariance matrix, the proposed regularizations admit an economic interpretation as relaxing
the exact pricing restrictions, thereby accommodating market frictions.
We derive the asymptotic properties of the SDF parameter estimator under a double
asymptotic framework in which both the cross-sectional and time dimensions grow. These
results allow for inference on whether individual factors are priced. We further develop tests
for comparing competing asset pricing models under misspeci cation, providing a formal
procedure to identify the least misspecified model. The analysis covers both nested and
non-nested specifications.
An empirical application compares 4 models using a dataset of 647 test portfolios.
This work develops fast methods for conditional forecasting and structural scenario analysis with high-dimensional Bayesian vector autoregressions (VARs) and compute counterfactual predictions for oil price scenarios in the context of the 2026 closure of the Strait of Hormuz.
Niko Hauzenberger, Michael Pfarrhofer· 0 citations
This paper presents a comprehensive review of two foundational portfolio models in modern finance: the Markowitz mean-variance model and the Sharpe single-index model. The study systematically examines their theoretical frameworks, computational requirements, empirical performance, and practical applicability. The Mark...
Portfolio replication, or the construction of a tradable basket of assets to match the risk-return profile of a target benchmark, is fundamentally an ill-posed inverse problem. When restricted to a subset of available assets, classical variance-minimizing models often yield unstable, over-leveraged portfolios highly vu...
This paper introduces a novel methodology for analyzing anomalies in conditional asset pricing models with time-varying risk exposures and premia. Our approach extends the conventional two-pass methodology to include both ordinary and weighted least-squares estimation in a conditional setting. We establish closed-for...
Valentina Raponi, P. Zaffaroni· Management Sciences· 0 citations
In this article, we introduce the new community-contributed commands xtdhazard and cfbinout. The former implements the own-differences instrumental-variables estimator proposed by Farbmacher and Tauchmann (2023, Econometric Reviews 42: 635-654) for dealing with time-invariant unobserved heterogeneity in the discrete-ti...
H. Tauchmann, Elena Yurkevich· The Stata Journal· 0 citations
We introduce the nonlinear arbitrage correction (NAC), the residual that renders a linear benchmark model arbitrage-free while preserving the law of one price. The price of NAC captures the marginal Sharpe ratio increase consistent with no-arbitrage and upper-bounds the constrained Hansen–Jagannathan distance. Using...
Mirela Sandulescu, P. Schneider· The Review of financial stud...· 0 citations
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