Publications
12. Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence, Journal of Financial Economics, 2021, 142(3), 1017-1037.
Co-authors: Turan Bali and Quan Wen
We provide time-series and cross-sectional evidence on the significance of a risk-return tradeoff in the bond and equity markets. We also propose novel measures of systematic and idiosyncratic risk for individual corporate bonds and find a significantly positive cross-sectional relation between systematic risk and expected bond returns, whereas there is no significant link between idiosyncratic risk and future bond returns.
11. Safe Asset Shortages: Evidence from the European Government Bond Lending Market, Journal of Financial and Quantitative Analysis, 2021, 56(8), 2689 - 2719.
Co-authors: Reena Aggarwal, and Luc Laeven
We identify the unique role of the government bond lending market in accessing safe assets during periods of market stress: collateral transformation.
10. Is the Credit Spread Puzzle a Myth? Journal of Financial Economics, 2020, 137, 297-319.
Co-authors: Robert Goldstein and Fan Yang
Even though credit spreads on short-maturity investment grade bonds appear "high" given their low historical default rates, these high Sharpe ratios should be interpreted as "fair compensation" for downward jump-risk.
9. The CDS-Bond Basis, Financial Management, 2019, 48(2), 417-439.
Co-author: Pierre Collin-Dufresne
The limit-of-arbitrage story for the difference between CDS and cash-bond implied credit spread.
8. Common Risk Factors in the Cross-Section of Corporate Bond Returns, Journal of Financial Economics, 2019, 131, 619-642.
Co-authors: Turan Bali and Quan Wen
We investigate the cross-sectional determinants of corporate bonds and find that downside risk is the strongest predictor of future bond returns. We also introduce common risk factors based on the prevalent risk characteristics of corporate bonds -- downside risk, credit risk, and liquidity risk -- and find that these novel bond market factors have economically and statistically significant risk premia, which cannot be explained by the long-established stock and bond market factors. We further show that these newly proposed risk factors outperform all other models considered in the literature in explaining the returns of the industry-sorted and size/maturity-sorted portfolios of corporate bonds.
7. The Leverage Effect and the Basket-Index Put Spread, Journal of Financial Economics, 2019, 131, 186-205.
Co-authors: Robert Goldstein and Fan Yang
A model specifies asset dynamics instead of equity dynamics alone can explain the large spread in prices between put options written on individual banks and options written on the bank index during the financial crisis, even without the government bail-out story. It's important to look at equity and debt together!
6. Measuring Liquidity Mismatch in the Banking Sector, Journal of Finance, 2018, 73(1), 51-93.
Co-authors: Arvind Krishnamurthy and Charles-Henri Weymuller
We propose a novel measure, "Liquidity Mismatch Index (LMI)," to gauge the mismatch between the market liquidity of assets and the funding liquidity of liabilities for the banking sector. LMI can be used for macro-prudential liquidity stress test, and for predicting cross-sectional bank risk. The outperformance of LMI than Basel III's LCR, NSFR results from the time-varying liquidity sensitivity weights which are driven by market prices.
5. Have Financial Markets Become More Informative? Journal of Financial Economics, 2016, 122(3), 625-654.
Co-authors: Thomas Philippon and Alexi Savov. Media: -Bloomberg, New York Times
The finance industry has grown, financial markets have become more liquid, information technology has been revolutionized. But have financial market prices become more informative?
4. Anchoring Corporate Credit Spreads to Firm Fundamentals, Journal of Financial & Quantitative Analysis, 2016, 51(5), 1521-1543.
Co-author: Liuren Wu
This paper examines the capability of firm fundamentals in explaining the cross-sectional variation of CDS spreads.
3. On Bounding Credit Event Risk Premia, Review of Financial Studies, 2015, 28(9), 2608-2642.
Co-authors: Pierre Collin-Dufresne, Robert Goldstein, and Jean Helwege
Reduced form models of default that attribute a large fraction of credit spreads as compensation for credit event risk typically preclude the most plausible economic justification for such risk to be priced, namely, a ``contagious" response of the market portfolio during the credit event.
2. Property Rights Gaps and CDS Spreads: When Is There a Strong Transfer Risk from the Sovereigns to the Corporates? Quarterly Journal of Finance, 2017, 7(4), 1750013. Co-author: Shang-Jin Wei
Strong property rights institutions tend to weaken the sovereign transfer risk, whereas contracting institutions (protection of creditor rights or minority shareholder rights) do not matter.
1. State Space Models and MIDAS Regressions, Econometric Reviews, 2013, 32(7), 779-813. Co-authors: Eric Ghysels and Jonathan Wright
We examine the relationship between MIDAS and Kalman filter state space models applied to mixed frequency data.
Co-authors: Turan Bali and Quan Wen
We provide time-series and cross-sectional evidence on the significance of a risk-return tradeoff in the bond and equity markets. We also propose novel measures of systematic and idiosyncratic risk for individual corporate bonds and find a significantly positive cross-sectional relation between systematic risk and expected bond returns, whereas there is no significant link between idiosyncratic risk and future bond returns.
11. Safe Asset Shortages: Evidence from the European Government Bond Lending Market, Journal of Financial and Quantitative Analysis, 2021, 56(8), 2689 - 2719.
Co-authors: Reena Aggarwal, and Luc Laeven
We identify the unique role of the government bond lending market in accessing safe assets during periods of market stress: collateral transformation.
10. Is the Credit Spread Puzzle a Myth? Journal of Financial Economics, 2020, 137, 297-319.
Co-authors: Robert Goldstein and Fan Yang
Even though credit spreads on short-maturity investment grade bonds appear "high" given their low historical default rates, these high Sharpe ratios should be interpreted as "fair compensation" for downward jump-risk.
9. The CDS-Bond Basis, Financial Management, 2019, 48(2), 417-439.
Co-author: Pierre Collin-Dufresne
The limit-of-arbitrage story for the difference between CDS and cash-bond implied credit spread.
8. Common Risk Factors in the Cross-Section of Corporate Bond Returns, Journal of Financial Economics, 2019, 131, 619-642.
Co-authors: Turan Bali and Quan Wen
We investigate the cross-sectional determinants of corporate bonds and find that downside risk is the strongest predictor of future bond returns. We also introduce common risk factors based on the prevalent risk characteristics of corporate bonds -- downside risk, credit risk, and liquidity risk -- and find that these novel bond market factors have economically and statistically significant risk premia, which cannot be explained by the long-established stock and bond market factors. We further show that these newly proposed risk factors outperform all other models considered in the literature in explaining the returns of the industry-sorted and size/maturity-sorted portfolios of corporate bonds.
7. The Leverage Effect and the Basket-Index Put Spread, Journal of Financial Economics, 2019, 131, 186-205.
Co-authors: Robert Goldstein and Fan Yang
A model specifies asset dynamics instead of equity dynamics alone can explain the large spread in prices between put options written on individual banks and options written on the bank index during the financial crisis, even without the government bail-out story. It's important to look at equity and debt together!
6. Measuring Liquidity Mismatch in the Banking Sector, Journal of Finance, 2018, 73(1), 51-93.
Co-authors: Arvind Krishnamurthy and Charles-Henri Weymuller
We propose a novel measure, "Liquidity Mismatch Index (LMI)," to gauge the mismatch between the market liquidity of assets and the funding liquidity of liabilities for the banking sector. LMI can be used for macro-prudential liquidity stress test, and for predicting cross-sectional bank risk. The outperformance of LMI than Basel III's LCR, NSFR results from the time-varying liquidity sensitivity weights which are driven by market prices.
5. Have Financial Markets Become More Informative? Journal of Financial Economics, 2016, 122(3), 625-654.
Co-authors: Thomas Philippon and Alexi Savov. Media: -Bloomberg, New York Times
The finance industry has grown, financial markets have become more liquid, information technology has been revolutionized. But have financial market prices become more informative?
4. Anchoring Corporate Credit Spreads to Firm Fundamentals, Journal of Financial & Quantitative Analysis, 2016, 51(5), 1521-1543.
Co-author: Liuren Wu
This paper examines the capability of firm fundamentals in explaining the cross-sectional variation of CDS spreads.
3. On Bounding Credit Event Risk Premia, Review of Financial Studies, 2015, 28(9), 2608-2642.
Co-authors: Pierre Collin-Dufresne, Robert Goldstein, and Jean Helwege
Reduced form models of default that attribute a large fraction of credit spreads as compensation for credit event risk typically preclude the most plausible economic justification for such risk to be priced, namely, a ``contagious" response of the market portfolio during the credit event.
2. Property Rights Gaps and CDS Spreads: When Is There a Strong Transfer Risk from the Sovereigns to the Corporates? Quarterly Journal of Finance, 2017, 7(4), 1750013. Co-author: Shang-Jin Wei
Strong property rights institutions tend to weaken the sovereign transfer risk, whereas contracting institutions (protection of creditor rights or minority shareholder rights) do not matter.
1. State Space Models and MIDAS Regressions, Econometric Reviews, 2013, 32(7), 779-813. Co-authors: Eric Ghysels and Jonathan Wright
We examine the relationship between MIDAS and Kalman filter state space models applied to mixed frequency data.
Working Papers
We study how the implementation of emissions trading systems (ETS) impacts emissions reductions and the usage of renewable energy using a panel sample of the largest 100 countries worldwide. Exploiting the cross-country variations in ETS implementations, we show that ETS adoption materially reduced greenhouse gas (carbon dioxide) emissions by 12.1% (18.1%). Moreover, ETSs reduced the overall emissions by cutting fossil fuel usage, such as coal, by 23.70% while boosting the usage of renewable energy by 61.59%, on average. In contrast, the introduction of carbon taxes has a less effective impact on emissions reduction and fails to boost the usage of renewable energy.
Using a structural model, we estimate the value of data to fixed-income investors and study its main drivers. In the model, data is more valuable for bonds that are volatile and for which price-insensitive liquidity trades are more likely. Empirically, we find that the value of data on corporate bonds increases with yield, time-to-maturity, size, callability, liquidity, and uncertainty during normal times. However, these cross-sectional differences vanish as the value of data falls during financial crises. Using two separate regression discontinuities based on maturity and rating, we provide causal evidence that investor composition affects the value of data.
We study information substitutability in the financial market through a quasi-natural experiment: the pandemic-triggered lockdown that has hampered people's physical interactions and hence the ability to collect, process, and transmit human-interaction-based information. Exploiting the cross-sectional and time-series variation of lockdown and its implications for proximate investment, we investigate how the difficulty of using human-interaction-based information in lockdown has prompted a switch to non-interaction-based information. We show that lockdown reduces fund investment in proximate stocks and generates a portfolio rebalancing toward distant stocks. Such rebalancing negatively impacts fund performance by reducing fund raw (excess) returns an additional 0.51% (0.19%) per month during lockdown, suggesting that human-interaction-based and non-interaction-based information is not easily substitutable. Last, we show that the edge of human-interaction-based information originates preeminently from physical contacts, primarily in cafés, restaurants, bars, and fitness centers, and that the virtual world based on Zoom/Skype/Teams cannot substitute for personal meetings in generating sufficient information.
Despite common wisdom that equities and bonds are segmented, the organization structure of fund families can offset frictions regarding cross-asset segmentation. We find that actively-managed equity funds and corporate bond funds linked within a mutual fund family exhibit a significant co-movement in holdings of commonly-held firms' equities and bonds. Such cross-holdings facilitate information spillover, manifesting itself in the co-movement. Synthesizing cross-asset information can predict future equity returns and create profits for fund families as well as general investors. Our findings accentuate the importance of collaboration between equity funds and bond funds within fund families.
We study whether and how the efficiency in the equity market affects the credit market. We exploit a unique experiment (“Regulation SHO”) which, by exogenously reducing transaction costs for short-sellers, improves efficiency in the equity market through increasing the informativeness of the firm. We show that higher efficiency significantly improves the buy-side investor-paid ratings but have little impact on sell-side issuer-paid ratings, because the change of ratings comes not from a lower probability of distress per se, but from a reduction in the uncertainty about the riskiness of the firm and from an enhancement of governance quality. The effect is stronger for firms rated below investment grades, for firms with low analyst coverage, and for firms with low institutional ownership.
based informed demand only have predictive power in corporate bonds, but not in its derivative contract CDS. Therefore, the informed demand help explain the CDS-Bond basis, especially in normal times when limits-to-arbitrage constraints unbind.
We analyze two reasons for export prices to be different across markets, namely quality differentiation and variable markups, and attempt to parse their relative importance and some of their underlying drivers. To overcome the substantial measurement issues in this task, we consider a particular industry as a special case: Chinese fine art. The simplicity of the supply-side of art vis-a-vis marginal cost and the wealth of data on its quality characteristics makes it possible to separately identify the markup and quality components of international relative prices for Chinese artworks. Through this lens, we trace the process of internationalization of Chinese art since the year 2000 and uncover a rich set of facts. We find strong support for quality sorting into international markets at both the level of artist and artwork, as well as substantial markup differences across destinations. Using a structural model of endogenous quality choice by Feenstra and Romalis (2012), we argue that much of the international quality premium is driven by specific distribution costs (whether physical or informational) rather than destination-specific preferences for quality.
Using a structural model, we estimate the value of data to fixed-income investors and study its main drivers. In the model, data is more valuable for bonds that are volatile and for which price-insensitive liquidity trades are more likely. Empirically, we find that the value of data on corporate bonds increases with yield, time-to-maturity, size, callability, liquidity, and uncertainty during normal times. However, these cross-sectional differences vanish as the value of data falls during financial crises. Using two separate regression discontinuities based on maturity and rating, we provide causal evidence that investor composition affects the value of data.
We study information substitutability in the financial market through a quasi-natural experiment: the pandemic-triggered lockdown that has hampered people's physical interactions and hence the ability to collect, process, and transmit human-interaction-based information. Exploiting the cross-sectional and time-series variation of lockdown and its implications for proximate investment, we investigate how the difficulty of using human-interaction-based information in lockdown has prompted a switch to non-interaction-based information. We show that lockdown reduces fund investment in proximate stocks and generates a portfolio rebalancing toward distant stocks. Such rebalancing negatively impacts fund performance by reducing fund raw (excess) returns an additional 0.51% (0.19%) per month during lockdown, suggesting that human-interaction-based and non-interaction-based information is not easily substitutable. Last, we show that the edge of human-interaction-based information originates preeminently from physical contacts, primarily in cafés, restaurants, bars, and fitness centers, and that the virtual world based on Zoom/Skype/Teams cannot substitute for personal meetings in generating sufficient information.
- Security Lending and Corporate Financing: Evidence from Bond Issuance (with Massimo Massa and Hong Zhang)
Despite common wisdom that equities and bonds are segmented, the organization structure of fund families can offset frictions regarding cross-asset segmentation. We find that actively-managed equity funds and corporate bond funds linked within a mutual fund family exhibit a significant co-movement in holdings of commonly-held firms' equities and bonds. Such cross-holdings facilitate information spillover, manifesting itself in the co-movement. Synthesizing cross-asset information can predict future equity returns and create profits for fund families as well as general investors. Our findings accentuate the importance of collaboration between equity funds and bond funds within fund families.
- Have Mutual Fund Managers Studied Corporate Finance? Pecking Order Theory and Portfolio Choice (with Massimo Massa and Jun Kyung Auh)
- The Great Wall Debt: Real Estate, Political Risk, and Chinese Local Government Financing Cost, (with Andrew Ang and Hao Zhou)
- Can Equity Market Efficiency Help Improve the Quality of Credit Ratings? Evidence from a Controlled Experiment (with Sterling Huang, Massimo Massa and Hong Zhang)
We study whether and how the efficiency in the equity market affects the credit market. We exploit a unique experiment (“Regulation SHO”) which, by exogenously reducing transaction costs for short-sellers, improves efficiency in the equity market through increasing the informativeness of the firm. We show that higher efficiency significantly improves the buy-side investor-paid ratings but have little impact on sell-side issuer-paid ratings, because the change of ratings comes not from a lower probability of distress per se, but from a reduction in the uncertainty about the riskiness of the firm and from an enhancement of governance quality. The effect is stronger for firms rated below investment grades, for firms with low analyst coverage, and for firms with low institutional ownership.
- What Bond Lending Reveals? The Role of Informed Demand in Predicting Credit Spread Changes, August 2018
based informed demand only have predictive power in corporate bonds, but not in its derivative contract CDS. Therefore, the informed demand help explain the CDS-Bond basis, especially in normal times when limits-to-arbitrage constraints unbind.
- Do Distributional Characteristics of Corporate Bonds Predict Their Future Returns? (with Turan Bali and Quan Wen)
- The Microstructure of Chinese Government Bond Market, (with Michael Fleming, and Casidhe Horan)
- `Going Global': Markups and Product Quality in the Chinese Art Market, (with Benjamin Mandel and Jia Guo)
We analyze two reasons for export prices to be different across markets, namely quality differentiation and variable markups, and attempt to parse their relative importance and some of their underlying drivers. To overcome the substantial measurement issues in this task, we consider a particular industry as a special case: Chinese fine art. The simplicity of the supply-side of art vis-a-vis marginal cost and the wealth of data on its quality characteristics makes it possible to separately identify the markup and quality components of international relative prices for Chinese artworks. Through this lens, we trace the process of internationalization of Chinese art since the year 2000 and uncover a rich set of facts. We find strong support for quality sorting into international markets at both the level of artist and artwork, as well as substantial markup differences across destinations. Using a structural model of endogenous quality choice by Feenstra and Romalis (2012), we argue that much of the international quality premium is driven by specific distribution costs (whether physical or informational) rather than destination-specific preferences for quality.
Policy Report
- The New Bank Resolution Regimes and "Too Big To Fail", (with Christian Cabanilla, and Menno Middeldorp, both from the Federal Reserve Bank of New York), Liberty Street Economics, October 2012.
- The Effects of Entering and Exiting a Credit Default Swap Index (with Or Sharchar, Federal Reserve Bank of New York), Liberty Street Economics, 2015