Hao Pang
Hello and Welcome!
About Me
I am a finance PhD candidate at Duke University, Fuqua School of Business. I will be joining the UT Dallas Naveen Jindal School of Management 2024 Fall.
My research interests are in asset pricing, macro-finance, monetary policy, and behavioral macro. My current research agenda is centered around the expectations of different agents (professional forecasters, the Fed, etc.) about macrovariables and how these affect asset pricing.
I am also interested in applying machine learning and natural language processing in macro-finance research.
Please find my latest CV here: [CV]
Contact
Email: hao [dot] pang [at] duke [dot] edu
Phone: +1 (919) 638-7602
Add: 100 Fuqua Dr, Durham NC 27708
Job Market Paper
The term structure of inflation expectations and Treasury yields [Latest version]
I study how agents form inflation expectations across different forecast horizons. Short-horizon survey forecasts of inflation underreact, while long-horizon forecasts overreact to inflation news. To reconcile the cross-horizon forecast behavior, I propose a new expectations formation model whereby agents display a long-run bias by subjectively attributing part of transitory shocks to permanent shocks. Because agents perceive persistent inflation shocks as more volatile relative to an assessment of a rational econometrician, they tend to overshoot their long-term forecasts. Combining the long-run bias with a realistic trend-cycle model of inflation dynamics, I show that the model outperforms diagnostic expectations and over-extrapolation in matching the survey forecasts across horizons. To analyze the asset pricing implications, I embed the long-run bias in inflation expectations within a yield curve model. The overreaction in long-horizon inflation expectations translates into a long-term yields' overreaction, thus generating excess yield sensitivity to news. The model implies a long-term bond risk premium that is substantially less volatile than that implied by the predictive regressions or estimates that impose full-information rational expectations (FIRE). I argue that the good performance of bonds since the early 1980s came largely as a surprise to investors and has been enhanced by biased inflation beliefs.
Published Papers
Common shocks in stocks and bonds, with Anna Cieslak, Journal of Financial Economics, 2021, 142(2), 880-904
We propose an approach to identify economic shocks (monetary, growth, and risk premium news) from stock returns and Treasury yield changes, which allows us to study the drivers of asset prices at a daily frequency since the early 1980s. We apply the identification to examine investors’ responses to news from the Fed and key macro announcements. We uncover two risk premium shocks—time-varying compensation for discount rate and cash flow news—which have distinct effects on stocks and bonds. Since the mid-1990s, the Fed-induced reductions in both risk premium sources have generated high average stock returns but an ambiguous response in bonds on FOMC days.
Contagion in a network of heterogeneous banks, with Ramazan Gençay, Michael C Tseng, Yi Xue, Journal of Banking & Finance, 2020, 111, 105725
(Extended from undergraduate thesis)
We consider a financial network where banks are heterogeneous in scale and each bank has only local knowledge regarding the network. Each bank must make counterparty and portfolio decisions while anticipating uncertainty regarding the network structure. Such network uncertainty is an important consideration in banks’ risk management practice, which aims to minimize the effect of exogenous liquidity shocks and hedge against possible fire-sale in asset markets. We show that network uncertainty gives rise to an endogenous core-periphery structure which is optimal in mitigating financial contagion yet concentrates systemic risk at the core of big banks.
Working Papers
Fed. vs. Market, inflation expectations and monetary policy risk premium
I document large and non-random differences between the professional forecasters' inflation expectations and the Fed's expectations. Fed's expectations are close to full information rational expectation (FIRE), while professional forecasters' expectations are non-FIRE. Moreover, the square of the expectational difference can significantly predict Treasury bonds' excess return, suggesting that the market is aware of the difference and requires a risk premium for it. I build a bond pricing model where agents learn about the volatility of monetary policy shocks through observed shocks. The inflation expectation difference between the Fed and the market then has a first-order risk premium effect through agents' perceived volatility. Estimation of this model suggests that this type of risk premium accounts for most of the total premium for long-term bonds, even more than the inflation risk premium.
Work in Progress
Two-speed economy, mixed frequency identification, with Anna Cieslak and Dongho Song
Teaching Experience
TA, (MBA) Financial Management (2022)
TA, (EMBA) Investment (2021-2022)
TA, (MQM) Financial Risk Management (2019-2022)
TA, (MQM) Fixed Income Securities (2019-2022)
TA, (MQM) Intermediate Finance (2019-2022)
TA, (PHD) Finance IV: Empirical Asset Pricing (2022)
TA, (PHD) Finance I: Theoretical Asset Pricing (2020-2022)
TA, (MQM) Introductory Finance (2019)