arXiv 26 Jul 2023 · Econometrics · 1 citations (OpenAlex)
arXiv:2307.14499 · PDF · DOI · OpenAlex · Extracted main text
The Hansen-Jagannathan (HJ) distance statistic is one of the most dominant measures of model misspecification. However, the conventional HJ specification test procedure has poor finite sample performance, and we show that it can be size distorted even in large samples when (proxy) factors exhibit small correlations with asset returns. In other words, applied researchers are likely to falsely reject a model even when it is correctly specified. We provide two alternatives for the HJ statistic and two corresponding novel procedures for model specification tests, which are robust against the presence of weak (proxy) factors, and we also offer a novel robust risk premia estimator. Simulation exercises support our theory. Our empirical application documents the non-reliability of the traditional HJ test since it may produce counter-intuitive results when comparing nested models by rejecting a four-factor model but not the reduced three-factor model. At the same time, our proposed methods are practically more appealing and show support for a four-factor model for Fama French portfolios.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Frank Kleibergen (2009) Tests of risk premia in linear factor models | 1.000 | 9 | 3 | 100% |
| 2 | Frank Kleibergen and Zhaoguo Zhan (2015) Unexplained factors and their effects on second pass r-squared’s | 1.000 | 9 | 3 | 100% |
| 3 | Frank Kleibergen and Zhaoguo Zhan (2020) Robust inference for consumption-based asset pricing | 0.956 | 8 | 4 | 88% |
| 4 | Stanislav Anatolyev and Anna Mikusheva (2018) Factor models with many assets: strong factors, weak factors, and the two-pass procedure | 0.932 | 21 | 5 | 81% |
| 5 | Frank Kleibergen, Lingwei Kong, and Zhaoguo Zhan (2020) Identification robust testing of risk premia in finite samples self | 0.928 | 5 | 3 | 80% |
| 6 | Stefano Giglio and Dacheng Xiu (2017) Inference on risk premia in the presence of omitted factors | 0.874 | 6 | 4 | 67% |
| 7 | Tim A Kroencke (2017) Asset pricing without garbage | 0.874 | 5 | 2 | 100% |
| 8 | Nikolay Gospodinov, Raymond Kan, and Cesare Robotti (2017) Spurious inference in reduced-rank asset-pricing models | 0.830 | 7 | 3 | 57% |
| 9 | Martin Lettau and Sydney Ludvigson (2001) Consumption, aggregate wealth, and expected stock returns | 0.737 | 3 | 3 | 67% |
| 10 | Ravi Jagannathan and Zhenyu Wang (1996) The conditional capm and the cross-section of expected returns | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 31 scored citations.