Research Interests

Selected Working Papers

The Trade Imbalance Network and Currency Returns (with Ai Jun Hou and Lucio Sarno, available online at SSRN) local download

Stockholm University (2022)*; Bank of Lithuania (Sep. 2023); University of Cambridge (Oct. 2023)*; Bank of Canada 13th Workshop on Exchange Rates (Dec. 2023); SGF Conference (Apr. 2024)*; Frontier of Factor Investing Conference (Apr. 2024); XJTLU (Mar. 2024); WFA (Jun. 2024)

Generalized Black-Litterman with Decision Fusion (with Xinyu Huang, Massimo Guidolin, David P. Newton, and Emmanouil Platanakis, available online at SSRN) local download

37th AFFI*; 11th FBES*; 2023 EFMA*; University of Liechtenstein*(2022)

Global Trade Network and Term Premia Dynamics (with Ai Jun Hou and Caihong Xu available online at SSRN) local download

Stockholm Business School (2022); 2023 CICF*; 2023 AMES (Tsinghua University, Beijing)*

Commodity Inflation Risk Premium and Stock Market Returns (with Ai Jun Hou, Emmanouil Platanakis, and Guofu Zhou, available online at SSRN) local download data download data page

2022 Rochester Conference in Econometrics*; 2022 Annual Meeting of EFMA*; 2022 FMA Europe*; 2022 Annual Meeting of the FMA US*; 2022 Annual Conference of the MMF; 11th FEBS*; 6th ENTFIN Annual Meeting*; Stockholm University*(Jun. 2022); Swedish House of Finance* (Jul, 2022); University of Exeter (Aug. 2022); XJTLU (Jun. 2022); University of Bath (Jul. 2022); SGF Conference (Mar. 2023)*

Voluntary Disclosures and Climate Change Uncertainty: Evidence from CDS Premiums (with Michael B. Imerman and Ran Zhao, available online at SSRN) local download

19th Chinese Finance Annual Meeting (Oct. 2022); RES & SES 2023 Annual Conference (Apr. 2023)

Informational Friction, Economic Uncertainty, and CDS-Bond Basis (with Charlie X. Cai and Ran Zhao, available online at SSRN) local download, a short video summary is available here. Presentation slides 

Durham University Business School (Feb. 2021); ICMA Centre, University of Reading (Apr. 2021); University of Bath School of Management (Jul. 2021); 52nd MMF Annual Conference (Sep. 2021); Annual Meeting of FMA (Oct. 2021)*; 2022 MFA conference (Mar 2022)* 

( * presented by co-authors )

Journal articles

On the (Almost) Stochastic Dominance of Cryptocurrency Factor Portfolios & Implications for Cryptocurrency Asset Pricing (with Weihao Han, David Newton, Emmanouil Platanakis, and Charles Sutcliffe, available online at SSRN) forthcoming in European Financial Management

2021 Southwestern Finance Association Annual Meeting*; The 28th Annual Global Finance Conference*; 2021 Annual Meeting of the European Financial Management Association*; The 19th Annual Conference of the Hellenic Finance and Accounting Association*; BAFA: 2021 Annual Conference*; International Conference of the Financial Engineering and Banking Society (2021)*; The Finance Symposium 2021* (Best Paper Award); 2021 China Finance Review International Conference* (Best Paper Award)

A key criterion for being a successful asset pricing factor model is to be able to account for long-short portfolios from well-known characteristics that generate sizable and significant excess returns. However, finding these long-short portfolios as testing assets for cryptocurrencies is not straightforward due to their highly non-normal return distribution. Conventional measures fail to identify portfolios with objectively significant returns. Stochastic Dominance is free of the drawbacks of conventional measures. After identifying truly performing cryptocurrency portfolios using Stochastic Dominance, we find a new three-factor model is needed to account for them. 

Product market competition, labor mobility, and the cross-section of stock returns (with Shamim Ahmed and Ziwen Bu, available online at SSRN) local download Presentation slides, Review of Asset Pricing Studies, Volume 13, Issue 3, September 2023, Pages 440–480. Replication code

Eastern Finance Association Annual Meeting (Apr. 2021); 37th International Conference of the French Finance Association (May 2021); Annual Meeting of FMA (Oct. 2021); University of Liverpool Management School (Jun. 2022)

Labor mobility and production market concentration both affect firms' exposure to productivity shocks but in the opposite way. We theoretically and empirically show that the labor mobility premium documented in previous literature is only significant in less concentrated industries.

Illiquidity, R&D investment, and stock returns (with Shamim Ahmed and Ziwen Bu, available online at SSRN) local download, forthcoming in Journal of Money, Credit and Banking. Replication code

The positive R&D-return relation means that more R&D-intensive firms have higher exposure to systematic risk, therefore, R&D investment is positively related to expected stock returns in equilibrium. Firm value is a concave function of R&D success rate. Therefore, uncertainty about R&D success rate amplifies the systematic risk exposure due to R&D investment. Firm's stock market illiquidity measures this uncertainty and, in turn, affects the positive R&D-return relation.

Credit Derivatives and Corporate Default Prediction (with Fan Yu and Ran Zhao, available online at SSRN) local download, Journal Banking and Finance, Volume 138, May 2022, 106418 

Midwest Finance Association Annual Meeting (Mar. 2021)* 

We should definitely incorporate CDS market signals in forecasting corporate default if they are available. Among the various components (liquidity, physical default, and risk premium) in CDS spreads, only the physical default component contributes significantly to default prediction. Therefore a CDS model that can perform such decomposition will further improve default prediction. 

Hedge Fund Strategies, Performance & Diversification: A Portfolio Theory & Stochastic Discount Factor Approach (with David Newton, Emmanouil Platanakis, Dimitrios Stafylas, and Charles Sutcliffe, available online at SSRN) British Accounting Review, September 2021, Volume 53, Issue 5, 101000

BAFA: Corporate Finance and Asset Pricing Conference (Sep. 2019)*

Hedge funds with the best stand-alone performance might not provide the best diversification benefit in a portfolio. Hedge funds tend to reduce portfolio risk, rather than increase returns. 

Horses for Courses: Mean-Variance for Asset Allocation and 1/N for Stock Selection (with Emmanouil Platanakis and Charles Sutcliffe, available online at SSRN) local download, Media mention: CXO Advisory Group European Journal of Operational Research, January 2021, Volume 288, Issue 1, Pages 302-317. Lead article in 'Innovative Applications of O.R.' 

BAFA: Corporate Finance and Asset Pricing Conference (Sep. 2019); The 7th Paris Financial Management Conference (Dec. 2019)*; International Conference of the Financial Engineering and Banking Society (2020)*

The performance of mean-variance v.s. 1/N has long been a debate topic in the literature of portfolio management and asset pricing. We show theoretically and empirically that the superiority of mean-variance over 1/N is increased when the assets have lower idiosyncratic volatility. The results justify the common practice of a two-stage process in portfolio management: mean-variance for asset allocation and 1/N for stock selection.

How Does the Market View Bank Regulatory Capital Forbearance Policies? (with Van Son Lai, available online at SSRN) local download with online appendix Journal of Money, Credit and Banking, December 2020, Volume 52, Issue 8, Pages 1873-1907. Lead article; A digested abstract is featured in Policy, Law and Regulation in World Banking Abstracts (April 2021). Replication code

International Conference of the Financial Engineering and Banking Society, Guildford, UK (Jun. 2014); Finance Workshop at School of Economics and Finance, Victoria University of Wellington, New Zealand (Nov. 2014); FMA European Conference (Jun. 2015)*; 9th Annual Risk Management Conference, Singapore (Jul. 2015); 4th International Conference on Credit Analysis and Risk Management, Basel, Switzerland (Aug. 2015); seminar at Econometric Institute, Erasmus University Rotterdam, Netherlands (Nov. 2015); Finance seminar at Wang Yanan Institute for Studies in Economics, Xiamen University, China (Dec. 2015); Multinational Finance Society Conference, Stockholm, Sweden (Jun. 2016)*; Annual Meeting of FMA, Boston, USA (Oct. 2017)*; 2017 China International Risk Forum, Shanghai Jiao Tong University, China (Dec. 2017)

The extent of capital forbearance can be quantified more rigorously using option-theoretic techniques and stock market information. Given changing trends in regulation and deregulation, it is important to accommodate time variation in modeling forbearance. Our empirical analysis shows that the forbearance capital starts increasing three years before the start of the 2008 financial crisis.

Unifying Gaussian Dynamic Term Structure Models from a Heath-Jarrow-Morton Perspective (with Haitao Li and Fan Yu, available online at SSRN) local download European Journal of Operational Research, November 2020, Volume 286, Issue 3, Pages 1153-1167

Theoretically, we show most existing Gaussian dynamic term structure models can be nested as special cases under a unified HJM-based framework. Empirically, our analysis reveals that the existing models impose restrictive constraints limiting their flexibility in capturing key features of the correlations and volatilities of the forward rates.

Are Market Views on Banking Industry Useful for Forecasting Economic Growth? (with Van Son Lai and Lu Zhao)  local download Pacific-Basin Finance Journal, October 2019, Volume 57,101082

Equity markets provide novel information regarding the soundness of the banking industry. These market views on the banking industry predict real economic growth. We provide international evidence showing the strong predictive power on GDP growth from model-based market view variables. 

Modeling Municipal Yields with (and without) Bond Insurance (with Albert Lee Chun, Ethan Namvar, and Fan Yu, available online at SSRN) forthcoming version online appendices Management Science, August 2019, Volume 65, Issue 8, Pages 3694-3713

Seminars at McMaster University*; University of New South Wales*; University of Sydney*; University of Technology Sydney (Oct, 2015)*; University of Toronto*; 49th MMF Annual Conference, London, UK (Sep. 2017)

When monolines' credit is in deep trouble, municipal bonds insured by them could become cheaper than those uninsured (yield inversion)! Illiquidity due to the troubled credit of monolines provides an explanation for this puzzling yield inversion phenomenon. Our model quantifies the credit and liquidity interaction in the context of insured and uninsured municipal bonds that can be attributed to the yield inversion.

Exploring Mispricing in the Term Structure of CDS Spreads (with Robert Jarrow, Haitao Li, and May Hu, available online at SSRNlocal download Review of Finance, February 2019, Volume 23, Issue 1, Pages 161–198,

4Th Annual Conference on Advances in the Analysis of Hedge Fund Strategies, London, UK (Dec. 2009)*; RMI Special Seminar, Singapore (Apr. 2010); Workshop on Financial Econometrics, Toronto, Canada (Apr. 2010)*; Quant Congress, New York, USA (Jul. 2010)*

Mispricing in term structures of CDS spreads (North America single names) is large and persistent. The volatility of credit and liquidity risks partially explains the dynamics of mispricing, signaling potential market manipulation. 

Counter-Credit-Risk Yield Spreads: A Puzzle in China’s Corporate Bond Market (with Jian Luo and May Hu, available online with internet appendix at SSRN) local download International Review of Finance, June 2016, Volume 16, Issue 2, pages 203–241

5th Financial Markets & Corporate Governance Conference (Best Paper Award in the Asset Pricing), Brisbane, Australia (Apr. 2014); China International Conference in Finance, Chengdu, China (Jul. 2014); School of Economics and Finance, Victoria University of Wellington, New Zealand (Nov. 2014)

It is puzzling to observe a negative correlation between credit risk and credit spreads. Evidence did present such a puzzle in the Chinese corporate bond market (from 2006 to 2013) when the Chinese government had “zero tolerance” for corporate defaults. 

Optimizing Enterprise Risk Management (with Yongrok Choi, Amanda Luo, and Lu Zhao) local download, Annals of Operations Research, February 2016, Volume 237, Issue 1–2, pp 281–300

The literature on enterprise risk management methodologies is worth reviewing. 

A New Approach to Measuring Market Expectations and Term Premia, Journal of Fixed Income, Spring 2015, Vol. 24, No. 4: pp. 22-46 (previously titled "Market Expectations, Term Premia, and the Short Rate in the Term Structure of Interest Rates" )  Updated term premium data are available here ! Term premium term structure data for more countries are available here !

4th Joint BIS-World Bank Public Investors Conference, Washington DC, USA (Dec. 2012); AIDEA Bicentenary conference, Banking and Finance Track, Lecce, Italy (Sep. 2013)

Factor loadings in Gaussian term structure models are model-dependent even for the same factors, while the unconditional contemporaneous impacts (UCI) are factor-specific but model-independent. Constraining UCI in estimating P-measure parameters gives rise to more sensible estimates for market expectations and term premiums. 

Book Chapter

Term Structure, Market Expectations of the Short Rate, and Expected Inflation (with Jian Luo) In: Mili M., Samaniego Medina R., di Pietro F. (eds) New Methods in Fixed Income Modeling. Contributions to Management Science. Springer, Cham, August 2018


Conference Discussions

Discussion: "Do Firms Leave Workers in the Dark Before Wage Negotiations?" by Sunny (Seung Yeon) Yoo, the 37th International Conference of the French Finance Association-AFFI (May, 2021, remotely)

Discussion: "The Market Risk Premium for Unsecured Consumer Credit Risk" by Matthias Fleckenstein and Francis A. Longstaff, Eastern Finance Association 2021 Annual Meeting (Apr, 2021, remotely)

Discussion: "The social value of public information when not everyone is privately informed" by Stephanie Chan, 3rd GCFC, Xiamen, China (Dec, 2020, remotely)

Discussion: “Does Model Complexity add Value to Asset Allocation? Evidence from Machine Learning Forecasting Models” by Iason Kynigakis and Ekaterini Panopoulou, 12th IAFDS, Milan, Italy (Jun, 2019).

Discussion: “The Relation between Counter-party Default and Interest Rate Volatility, and Its Impact on the Credit Risk of Interest Rate Derivatives” by Geoffrey R. Harris, Tao L. Wu, and Jiarui Yang, FMA 2015, Orlando, USA (Oct, 2015).

Discussion: “Pricing of Implicit Guarantees for Financial Institutions” by Jakob J. Bosma, FMA 2015, Orlando, USA (Oct, 2015).

Discussion: “Systematic Risk and Yield Premiums in the Bond Market” by Liang Fu, Austin Murphy, and Terry Benzschawel, 4th Conference on Credit Analysis and Risk Management, Basel, Switzerland (Aug, 2015).

Discussion: “Risk and Return Trade-o. in the U.S. Treasury Market” by Eric Ghysels, Anh Le, Sunjin Park, and Haoxiang Zhu, China International Conference in Finance, Chengdu, China (Jul, 2015).

Discussion: “Inferring Volatility Dynamics and Variance Risk Premia: An Efficient Bayesian Approach” by Andras Fulop and Junye Li, China International Conference in Finance, Chengdu, China (Jul, 2015).

Discussion: “Forecasting Corporate Bond Returns: A Regressed Combination Approach” by Hai Lin, Chunchi Wu, and Guofu Zhou, Finance Workshop at School of Economics and Finance, Victoria University of Wellington, New Zealand (Nov, 2014).

Discussion: “Sentiment and Corporate Bond Valuations Before and After the Onset of the Credit Crisis” by Jing-Zhi Huang, Marco Rossi, and Yuan Wang, China International Conference in Finance, Chengdu, China (Jul, 2014).

Discussion: “Pricing Performance of Ad-Hoc Black-Scholes Models vis-à-vis TSRV Based Black-Scholes Model: Empirical Evidences from Indian Options Market” by Alok Dixit and Shivam Singh, Financial Markets & Corporate Governance Conference, Brisbane, Australia (Apr. 2014).

Discussion: “The Impact of Liquidity on Senior Credit Spreads during the Subprime Crisis” by Miriam Marra, AIDEA Bicentenary conference, Banking and Finance Track, Lecce, Italy (Sep. 2013).

Discussion: “The Determinants of the Credit Rating of Local Government Financing Vehicle Bonds in China” by Robin H. Luo and Linfeng Chen, Workshop in Fixed Income and Bond Markets, Xiamen University, China (Oct. 2011).

Discussion: “Corporate Distress and Innovation in Asia” by R. Moro, S. Aliakbari, G.Prato, and D. Nepelski, 5th Annual Risk Management Conference, Singapore (Jul. 2011).

Contribution to Erratum