We find that deviations from the covered interest rate parity (CIP) condition imply large, persistent, and systematic arbitrage opportunities in one of the largest asset markets in the world. Contrary to the common view, these deviations for major currencies are not explained away by credit risk or transaction costs. They are particularly strong for forward contracts that appear on banks' balance sheets at the end of the quarter, pointing to a causal effect of banking regulation on asset prices. The CIP deviations also appear significantly correlated with other fixed income spreads and with nominal interest rates.

This paper investigates the impact of foreign institutional ownership on firm-level stock return volatility in China, based on our study of a sample of 1458 firms between 1998 and 2008. The empirical results show that share ownership by foreign institutions (both financial and non-financial) increases firm-level stock return volatility, even after controlling for a complete ownership structure, firm size, turnover, and leverage, and correcting for potential endogeneity problems. However, the results also show that foreign individual shareholdings reduce volatility. Furthermore, we document a positive relationship between domestic shareholdings (individual, institutional, and governmental) and firm-level stock return volatility. Empirical results with interaction terms show that foreign institutional ownership increases firm-level return volatility by strengthening the positive impact of liquidity on volatility. The volatility reduction effect of foreign individual ownership is attenuated by government ownership suggests a poor governance environment as a result of the involvement of the Chinese government.

We analyze how employee compensation contracts of target firms affect merger terms and outcomes. Using unique data from merger agreements, we document that in 80.0% of all merger and acquisition (M&A) deals, at least some of the target’s employee stock options (ESOs) are canceled by the acquirer and not replaced by new equity-based grants. Contract modifications reduce the value of ESOs by 38.4% in the average M&A deal. Further, the combined merger returns are larger when employees experience greater losses. Overall, our results indicate that the benefits of reducing the number of ESOs outweigh the potential negative effects on firm value.

This paper examines how culture affects information asymmetry in financial markets. We extract firms traded in the United States but headquartered in regions sharing Chinese culture (“Chinese firms”), and we manually identify a group of U.S. analysts of Chinese ethnic origin (“Chinese analysts”). We find that Chinese analysts issue more accurate forecasts on Chinese firms than non-Chinese analysts. The effect is stronger among firms with less transparent information environments. Further evidence suggests that cultural proximity can go beyond language commonality and analysts’ pre-existing channels for information. Market reaction is stronger when Chinese analysts issue favorable forecast revisions or upgrades about Chinese firms.

We document that governments whose local currency debt provides them with greater hedging benefits actually borrow more in foreign currency. We introduce two features into a government's debt portfolio choice problem to explain this finding: risk‐averse lenders and lack of monetary policy commitment. A government without commitment chooses excessively countercyclical inflation ex post, which leads risk‐averse lenders to require a risk premium ex ante. This makes local currency debt too expensive from the government's perspective and thereby discourages the government from borrowing in its own currency.

This paper examines the informational role of equity options trading around Federal Open Market Committee (FOMC) announcements. We find that information contained in option trades prior to FOMC rate change announcements, measured as implied volatility spread, predicts bank stock returns to a greater degree than does volatility spread prior to non-meeting days. We examine U.S. banks due to their interest rate sensitivity; however, we also show that return predictability around rate changes is reliably stronger in all firms, across all industries that are more interest rate sensitive. We find that return predictability is primarily driven by surprise changes in interest rates that occur during meetings with high degrees of information asymmetry. Finally, we document that volatility spread impounds information about FOMC meetings before that information is reflected in stock prices; this effect is significantly greater during surprise events, suggesting that the options market is an important source of informed trading.

Financial market information can provide an objective assessment of losses anticipated from temperature changes. In an APT model in which temperature shocks are a systematic risk factor, the risk premium is significantly negative, loadings for most assets are negative, and asset portfolios in more vulnerable industries have stronger negative loadings on a temperature shock factor. Weighted average increases in the cost of equity capital attributed to uncertainty about temperature changes are 0.22 percent, implying a present value loss of 7.92 percent of wealth. These costs represent a new channel that may contribute to cost of climate change assessment.

We propose and validate a new measure of earnings quality based on a hidden Markov model. This measure, termed earnings fidelity, captures how faithful earnings signals are in revealing the true economic state of the firm. We estimate the measure using a Markov chain Monte Carlo procedure in a Bayesian hierarchical framework that accommodates cross-sectional heterogeneity. Earnings fidelity is positively associated with the forward earnings response coefficient. It significantly outperforms existing measures of quality in predicting two external indicators of low-quality accounting: restatements and Securities and Exchange Commission comment letters.

The Basel Committee and the Financial Stability Board require a consensus on the identification of characteristics that make a financial institution more prone than others to be severely hit by systemic shocks. This paper introduces a new tool to achieve this goal: a model for the Conditional Average Systemic Effects (CASE). The CASE quantifies the average effect of a system wide shock or market downturn on the profit and loss account of a bank, a firm or on the return of an asset. We propose a linear model for CASE with heterogeneous effects in observable characteristics. These models complement alternative measures of systemic risk and allow researchers to identify the determinants of the vulnerability of a given financial institution. We develop bootstrap inference that accounts for both estimation risk and model misspecification risk, and show the utility of our results in Monte Carlo simulations and an empirical application to 100 large U.S. financial firms.