Job Market Candidates 2025/26
We are proud to present our current candidates on the job market and introduce the next generation of talent who are ready to make a difference.
- Academic Placement Director: Prof. Felix Kübler
- Discover successful placements of graduates from our department:Graduates page
Table of contents
Glen Gostlow
Job Market Candidate, Postdocs, Senior Researchers
Research Interest: Asset Pricing, Climate Finance, Economic Geography
Contact:
glen.gostlow@df.uzh.ch
Personal Website
Main Advisor: Prof. Markus Leippold
Additional Letter Writers: Prof. Alexander Wagner, Prof. Luca Taschini
Job Market Paper: Anything Goes: Pricing Physical Climate Risk
I study whether physical climate risk matters for asset prices given the mixed empirical evidence. Using Form 8-K filings, a nontraded factor signals increased risk by capturing the proportion of US firms that experience material events. It is less noisy than existing measures, negatively related to future consumption, and positively related to climate disasters. Assets that negatively covary with the factor earn a positive risk premium of 0.18% per month, yet most of its variation is unpriced. In contrast, a factor based on hazard exposure has a negative risk premium, implying ex-ante risks are not well understood. Overall, investors appear to weakly price physical climate risk as a disaster risk, but ex-ante hazard risk exposure does not compensate investors.
Mohamed Hamoud
Job Market Candidate, PhD Candidate, SFI Program
Research Interest: Asset Pricing, Macro-Finance, Household Finance
Contact:
mohamed.hamoud@df.uzh.ch
Personal Website
Main Advisor: Prof. Felix Kübler
Job Market Paper: Monetary Policy Surprises and the Term Structure of Equity Yields
Mohamed's Job Market Paper addresses the long-standing debate over how monetary policy affects stock markets. While early literature finds that policy surprises move equities primarily through risk premia and dividend expectations rather than risk-free rates, more recent work reaches precisely the opposite conclusion: risk-free rate changes matter most. The paper reconciles these conflicting findings by showing that monetary policy's impact beyond risk-free rates is time-varying and substantially stronger in low-rate environments. However, this time variation is hidden in estimates of long-term average effects. Since the average effect estimated over a sample depends on the rate environments it covers, estimated average effects vary across samples, explaining conflicting findings.
Mojtaba Hayati
Job Market Candidate, PhD Candidate, SFI Program
Research Interest: Macro-Finance, Asset Pricing, Household Finance
Contact:
mojtaba.hayati@df.uzh.ch
Personal Website
Main Advisor: Prof. Felix Kübler
Additional Letter Writers: Prof. Dirk Kruger, Prof. Yucheng Yang
Job Market Paper: Scale-dependent Returns and the Interest Rate
I revisit the empirical relationship between wealth and returns on wealth of U.S. households over the past 70 years. While recent studies suggest that returns on wealth increase with wealth and that the richest households earn the highest returns, I show that this pattern is specific to post-1980. Before 1980, returns declined at the top 10 percent of the wealth distribution, and in fact, the bottom 90 percent had higher returns than the top 10 percent. I attribute this reversal to differences in households’ exposure to interest rate risk. Because wealthier households tend to hold longer-duration assets, such as stocks and private businesses, changes in real interest rates affect their portfolios more strongly. When real rates rose, as they did before 1980, the top 10 percent households experienced lower returns, whereas falling real rates after 1980 boosted their returns. To explain why wealthier households hold longer-duration assets, I develop a model in which households select portfolio duration to hedge their income risk. Since richer households’ income is more correlated with short-term interest rates, they optimally choose a longer-duration (countercyclical) to hedge this exposure.
Alex Osberghaus
Job Market Candidate, PhD Candidate, SFI Program
Research Interest: Financial Intermediation, Corporate Finance, NBFIs
Contact:
alex.osberghaus@df.uzh.ch
Personal Website
Letter Writers:
Prof. Steven Ongena
Prof. Andreas Fuster
Prof. Anthony Saunders
Dr. Glenn Schepens
Job Market Paper: Synthetic, but How Much Risk Transfer?
Banks use synthetic risk transfers (SRTs) to offload potential losses in their loan portfolios to non-bank investors while retaining the loans on their balance sheets. We investigate this trillion-euro market using transaction-level data from the euro area, the largest SRT market, and highlight three channels of potential risks to financial stability. First, we causally show that banks synthetically transfer loans that are capital-expensive relative to their riskiness. As banks redeploy the freed capital, they become effectively less capitalized. Second, after entering an SRT, banks reduce their monitoring efforts compared to other banks lending to the same firm. Third, banks and non-bank investors are interconnected. Banks are more likely to sell SRTs to investors to which they also grant credit, and total bank credit to these investors increases before the SRT investment, suggesting that SRTs are partially debt-financed. The investors' leverage, however, remains modest.
Tingyu Yu
Job Market Candidate, Postdocs, Senior Researchers
Research Interest: Climate Finance, Corporate Innovation, Natural Language Processing
Contact:
tingyu.yu@df.uzh.ch
Personal Website
Advisors: Prof. Zacharias Sautner, Prof. Markus Leippold
Job Market Paper: Carbon in the Cloud
This paper examines the climate impact of corporate AI investments using a large global sample. Firms that hire AI workers subsequently reduce Scope 1 emissions, an effect not explained by other technologies or pre-existing green initiatives. Exploiting lottery-driven variation in H-1B visa allocations as an instrument supports a causal interpretation. The emission reductions, however, are highly heterogeneous and arise mainly among low-emitting firms, where AI improves forecasting and resource allocation. By contrast, firms in Energy and Utilities show little abatement or even higher emissions when AI enhances fossil asset utilization. This suggests that AI is directed to complement business models and reinforces the emission profiles of existing production technologies. Without climate-aware deployment, AI may amplify transition risk by widening sectoral disparities in emission trajectories.
Link to paper
