本文精选了金融学国际顶刊《Journal of Finance》近期发表的论文，提供金融学研究领域最新的学术动态。

Political Polarization Affects Households' Financial Decisions: Evidence from Home Sales

原刊和作者：

Journal of Finance Volume79, Issue2

W. BEN MCCARTNEY （University of Virginia）

JOHN ORELLANA-LI （Federal Reserve Bank of Philadelphia）

CALVIN ZHANG （Federal Reserve Bank of Philadelphia）

Abstract

Political identity and partisanship are salient features of today's society. Using deeds records and voter rolls, we show that current residents are more likely to sell their homes when opposite-party neighbors move in nearby than when unaffiliated or same-party neighbors do. This is especially true when the new neighbors are politically active, consistent with an animosity between parties mechanism. We conclude that affective polarization is not limited to purely political settings and affects one of the household's most important financial decisions, their home transactions.

Link: https://doi.org/10.1111/jofi.13315

Measuring “Dark Matter” in Asset Pricing Models

原刊和作者：

Journal of Finance Volume79, Issue2

HUI CHEN （MIT）

WINSTON WEI DOU （University of Pennsylvania）

LEONID KOGAN （MIT）

Abstract

We formalize the concept of “dark matter” in asset pricing models by quantifying the additional informativeness of cross-equation restrictions about fundamental dynamics. The dark-matter measure captures the degree of fragility for models that are potentially misspecified and unstable: a large dark-matter measure indicates that the model lacks internal refutability (weak power of optimal specification tests) and external validity (high overfitting tendency and poor out-of-sample fit). The measure can be computed at low cost even for complex dynamic structural models. To illustrate its applications, we provide quantitative examples applying the measure to (time-varying) rare-disaster risk and long-run risk models.

Link: https://doi.org/10.1111/jofi.13317

Informed Trading Intensity

原刊和作者：

Journal of Finance Volume79, Issue2

VINCENT BOGOUSSLAVSKY （Boston College）

VYACHESLAV FOS （Boston College）

DMITRIY MURAVYEV （Michigan State University）

Abstract

We train a machine learning method on a class of informed trades to develop a new measure of informed trading, informed trading intensity (ITI). ITI increases before earnings, mergers and acquisitions, and news announcements, and has implications for return reversal and asset pricing. ITI is effective because it captures nonlinearities and interactions between informed trading, volume, and volatility. This data-driven approach can shed light on the economics of informed trading, including impatient informed trading, commonality in informed trading, and models of informed trading. Overall, learning from informed trading data can generate an effective informed trading measure.

Link: https://doi.org/10.1111/jofi.13320

How Integrated are Credit and Equity Markets? Evidence from Index Options

原刊和作者：

Journal of Finance Volume79, Issue2

PIERRE COLLIN-DUFRESNE （EPFL and Swiss Finance Institute）

BENJAMIN JUNGE （Capital Fund Management）

ANDERS B. TROLLE （Copenhagen Business School）

Abstract

We study the extent to which credit index (CDX) options are priced consistent with S&P 500 (SPX) equity index options. We derive analytical expressions for CDX and SPX options within a structural credit-risk model with stochastic volatility and jumps using new results for pricing compound options via multivariate affine transform analysis. The model captures many aspects of the joint dynamics of CDX and SPX options. However, it cannot reconcile the relative levels of option prices, suggesting that credit and equity markets are not fully integrated. A strategy of selling CDX volatility yields significantly higher excess returns than selling SPX volatility.

Link: https://doi.org/10.1111/jofi.13300

Dissecting the Long-Term Performance of the Chinese Stock Market

Journal of Finance Volume79, Issue2

FRANKLIN ALLEN （Business School of Imperial College London）

JUN (QJ) QIAN （Fudan University）

CHENYU SHAN （Shanghai University of Economics and Finance）

JULIE LEI ZHU （Fudan University）

Abstract

Domestically listed Chinese (A-share) firms have lower stock returns than externally listed Chinese, developed, and emerging country firms during 2000 to 2018. They also have lower net cash flows than matched unlisted Chinese firms. The underperformance of both stock and accounting returns is more pronounced for large A-share firms, while small firms show no underperformance along either dimension. Investor sentiment explains low stock returns in the cross-country and within-A-share samples. Institutional deficiencies in listing and delisting processes and weak corporate governance in terms of shareholder value creation are consistent with the underperformance in stock returns and net cash flows.

Link: https://doi.org/10.1111/jofi.13312