Julia Selgrad

I am a Ph.D. candidate in Finance at NYU Stern and will be on the 2023-2024 academic job market. 


Research Areas: Asset Pricing, Monetary Policy, Macro-Finance

Contact:  jselgrad@stern.nyu.edu

CV 

Working Papers

Testing the Portfolio Rebalancing Channel of Quantitative Easing
Job Market Paper

The Fed argues that quantitative easing (QE) lowers yields across asset markets via the portfolio rebalancing channel. I provide a direct test for this channel, quantify its magnitude, and document its real effects. I first construct a novel QE shock measuring the unexpected amount that the Fed purchases of each Treasury during each QE operation. Combining this shock with holdings data, I find that investors rebalance over 60% of proceeds from QE-induced Treasury sales into corporate bonds, predominantly into bonds with similar maturities to those the Fed purchased and bonds issued by firms whose bonds they already own. Consistent with the portfolio rebalancing channel, the yields of these bonds fall. To quantify the channel’s magnitude, I use my reduced-form estimates to calibrate a preferred habitat model with investors who substitute between Treasurys and corporate bonds. I find a large effect: $100 billion of Treasury purchases lower corporate bond yields by 8bps on impact, with the effect dissipating over the following year. Turning to real effects, I find that affected firms increase bond issuance and do so at lower yields. Firms use the funds to increase their capital investment and cash buffers. Overall, the results point to a strong portfolio rebalancing channel.

A Quantity-Based Approach to Constructing Climate Risk Hedge Portfolios, with Georgij Alekseev, Stefano Giglio, Quinn Maingi, and Johannes Stroebel
R&R, Journal of Finance

Abstract: We propose a new methodology to build portfolios that hedge the economic and financial risks from climate change. Our quantity-based approach exploits information on how mutual fund managers trade in response to idiosyncratic changes in their climate risk beliefs. We exploit two types of idiosyncratic belief shocks: (i) instances when fund advisers experience local extreme heat events that are known to shift climate change beliefs, and (ii) instances when fund managers change the language in shareholder disclosures to express concerns about climate risks. We use the funds’ observed portfolio changes around such idiosyncratic belief shocks to predict how investors will reallocate their capital in response to aggregate climate news shocks that shift the beliefs and asset demands of many investors and thus move equilibrium prices. We show that a portfolio that is long stocks that investors tend to buy after experiencing negative idiosyncratic climate belief shocks, and short stocks that investors tend to sell, appreciates in value in periods with negative aggregate climate news shocks. Our quantity-based portfolios have superior out-of-sample hedge performance compared to portfolios constructed using existing alternative methods. The key advantage of the quantity-based approach is that it learns from rich cross-sectional trading responses rather than time-series price information, which is particularly limited in the case of newly emerging risks such as those from climate change. We also demonstrate the versatility of the quantity-based approach by constructing successful hedge portfolios for aggregate unemployment and house price risk.

Work in Progress

Effects of the Reverse Repurchase Facility on Treasury Market Liquidity

Quantifying the Financial Costs of Geopolitical Tensions, with Paul Schmidt-Engelbertz and Samuel Slocum

The Effect of Quantitative Easing on Stock Market Valuations