Research

PUBLISHED PAPERS

→  Winner of the INQUIRE 2017 Europe Research Grant 

Conference presentations: LBS Summer Finance Symposium (2019), Market Microstructure and High Frequency Data Conference (University of Chicago) (2019), Utah Winter Finance Conference (2019), SFS Asia Pacific (2018), BI-SHOF (2018), TSE Financial Econometrics Conference (2018), NBER-NSF SBIES (2018), IAAE (2018)

Data:  Filtered Dividend Growth Series (various frequencies)


Conference presentations: AFA (2020), SFS Asia Pacific (2018), HKUST Finance Symposium (2018), EFA (2017), CEPR Gerzensee (2017), FIRS (2017), Financial Research Association (FRA 2016), Miami Behavioral Finance Conference (2016)

Data: Economic Areas to Zipcodes


Conference presentations: Real-Time Analysis, Methods and Application (Banque de France) (2021), IAAE - International Association for Financial Econometrics (2020) , North American Summer Meeting of the Econometric Society (2021)



WORKING PAPERS


Conference presentations: FIRS (2017), Utah Winter Finance Conference (2016), European Finance Association (EFA 2015), USC Marshall Ph.D. Conference in Finance (2015), Southern California Finance Conference (2015)

→  Winner of the Best paper award at USC Marshall Ph.D. Conference (2015)

Abstract: The lack of predictability of aggregate dividends by the traditional dividend-price ratio has long been considered a puzzle - “the dog that did not bark,” Cochrane (2008a). I show that this evidence is due to the mismeasurement of dividends used in empirical work. If M&A cash dividends are taken into account, the adjusted R2 from a regression of dividend growth on the lagged dividend-price ratio goes from being negative (-1.07%) to positive (17.47%), and coefficients become highly statistically significant. Strong improvements are also found for consumption growth (-1.09% to 10.63%), and out-of-sample return predictability. I also document that dividend-price variation is strongly linked to cash flow news and not only to discount rate news. Lastly, I find stronger predictability in industries with the largest M&A activity. 


→  Winner of the GWIM Research Grant
→  ICPM Award Honorable Mention

Conference presentations: MFA (2022), NFN Young Scholars (2020), Eastern Finance Association (2021), BI-SHoF (2021), NFA (2021)

Abstract: We construct tradable, long-short risk factors using combinations of large and liquid mutual funds (long leg) and ETFs (long and short legs), based on their holdings, for both retail and institutional investors. Exploiting a novel dataset, our tradable factors explicitly take into account ETF shorting costs and the capacity constraints of factor strategies. The tradable risk factors constitute valid benchmarks to evaluate portfolio managers and trading strategies, and they perform differently from "on-paper" risk factors (2% to 5% per year) due to implementation frictions in the short leg. 


Conference presentations: AFA (2024)

Abstract: We estimate a demand system linking 401(k) plans ownership of individual stocks and funds to their demand for equities, and quantify the effect of 401(k) stock holdings on investor behavior. We introduce a new variable, stock-level 401(k) ownership, and find it to be a key determinant of investor demand, with a one standard deviation increase in 401(k) ownership leading to 11-19% increase in stock demand. We also estimate the equilibrium price impact of a change in stock-level 401(k) ownership to be positive and increasing over time, consistent with the shift from active to passive investing. Lastly, we document that funds managing a larger fraction of 401(k) assets tilt their portfolios toward winners, high beta and long duration stocks, and they hold less cash.      


→  Winner of the INQUIRE 2020 Europe Research Grant 

Conference presentations: SoFie (2023), European Winter Finance Summit (2023)

Abstract: We estimate cash flow news, cash flow betas, and their price of risk for the most prominent equity anomalies, at different frequencies, by directly modeling the dividend growth process instead of relying on a VAR-residual approach. We find the term structure of cash flow betas to be upward sloping for most anomaly portfolios. Moreover, the price of cash flow risk appears to be anomaly-specific -- different anomalies tend to display heterogeneous sensitivity to cash flow news -- and frequency-dependent -- for a given anomaly, this sensitivity varies with the horizon at which portfolios are evaluated.


Conference presentations: 9th Cherry Blossom Financial Education Institute (2024), SFA Cavalcade (2024), WFA (2023)

Abstract: We study the performance of IRA pension plans from 2004 through 2018. We document novel evidence of large return heterogeneity across income groups in the US, and provide estimates of its impact on wealth inequality. High-income households substantially outperform low-income ones, and this return differential is almost three times as large in “tax-free” Roth IRAs. These returns cannot be matched by equity market returns, but are consistent with high-income individuals having exposure to private assets.  

Media: Investopedia, ThinkAdvisor


Conference presentations: Finance Workshop @ Ca' Foscari University of Venice (2023), 8th Conference on New Developments in Business Cycle Analysis (Danmark Nationalbank/Deutsche Bundesbank/Norges Bank joint conference (2021),  Corporations and Covid-19 (2021)

Abstract: We use high-frequency data on firms’ dividend and buyback suspensions to estimate the effect on firm value from preserving cash during periods of financial market distress such as the Global Financial Crisis and the Covid-19 pandemic. Our results suggest that saving one percent in cash by suspending dividends is associated with a 2.5 percent increase in firm value. New dynamic tests based on the sequencing of firms’ financing decisions suggest that firm behavior was more in line with the Myers and Majluf (1984) pecking order theory during the pandemic than during the Global Financial Crisis.


Abstract: In this paper I show that information about fundamentals of the aggregate economy derived from closely held firms help predict stock returns. I construct a new economy-wide dividend price ratio that takes into account dividends and market capitalization of both listed (public) and non-listed (private) U.S. companies and show that it strongly predicts stock returns with in-sample and out-of-sample annual adjusted R2 of 15.35% and 16.28%, compared to the standard dividend price ratio values of 5.32% and -1.14%, respectively. I also find that changes in dividends of private firms lead those of public firms and that the economy-wide dividend price ratio subsumes the standard dividend price ratio.


WORK IN PROGRESS (ADVANCED)