Financial Intermediaries and Demand for Duration
with A. Tamoni and M. Zanotti, Aug 2025
4th LTI-Bank of ItalyWorkshop on Long-Term Investors’ Trends, 2023 SFI Research Days, 2024 Midwest Finance Association Meeting, 2024 SGF,
2024 World Symposium on Investment Research, and Italian Financial Economists Association Conference
Abstract: Stocks with long-term cash flows earn lower expected returns because they hedge fluctuations in investment opportunities. We study the role of financial institutions in shaping this duration premium using equity holdings of primary dealers, pension funds, banks, and insurance companies. We find that intermediaries’ demand for equity duration varies systematically with their risk-bearing capacity. In the time series, institutions reduce their demand for longduration claims and increase their exposure to reinvestment risk when aggregate capital ratios are low. Such a result extends cross-sectionally: better-capitalized and better-performing institutions tilt their portfolios more strongly toward long-duration stocks than their constrained peers. These patterns align with an ICAPM framework in which hedging demand declines with risk aversion. Counterfactual exercises show that shifts in intermediaries’ preferences generate monotonic changes in expected returns across duration deciles, with especially large effects when demand shocks operate at the holding-company level.
Backcasting, Nowcasting, and Forecasting Residential Repeat-Sales Returns: Forecast Combination meets Mixed Frequency
with M. Garzoli and R. Valkanov, Dec 2021
SoFiE 2021
Abstract: The Case-Shiller is the reference repeat-sales index for the U.S. residential real estate market, yet it is released with a two-month delay. We find that incorporating recent information from 71 financial and macro predictors improves backcasts, nowcasts, and short-term out-of-sample forecasts of the index returns. Combining individual forecasts delivers large improvements in forecast accuracy at all horizons. Additional gains are obtained with mixed-data sampling methods that exploit the daily frequency of financial variables, reducing the out-of-sample mean squared forecast error by as much as 11% compared to a simple autoregressive benchmark. The forecast improvements are largest during economic turmoil and throughout the 2020 COVID-19 pandemic period.
Does Monetary Policy Impact Sovereign Credit Risk Co-Movement?
with M. Caporin and L. Pelizzon, Dec 2021
Fourth International Conference on Sovereign Bond Markets (Singapore); Banking in Emerging Markets Conference (Cape Town); CREDIT 2017; Paris Annual Meeting 2017; 2nd CEBRA’s International Finance and Macroeconomics meeting
Abstract: This paper shows that FED policy announcements are accompanied with a significant increase in international co-movement in the sovereign CDS market. The effect is strongest for emerging markets, when the FED relaxes unconventional monetary policies, and for countries that are open to the trading of goods and flows, even with floating exchange rates. The announcements also affect closed economies whose currencies are pegged to the dollar. The evidence is consistent with recent theories of a global financial cycle and the pricing of a FED put. In contrast, ECB announcements hardly affect co-movement, even in the Eurozone.
The Risk-Return Relationship and Financial Crises
with E. Ghysels and R. Valkanov; permanent working paper
The risk-return trade-off implies that a riskier investment should demand a higher expected return relative to the risk-free return. The approach of Ghysels, Santa-Clara, and Valkanov (2005) consisted of estimating the risk-return trade-off with a mixed frequency, or MIDAS, approach. MIDAS strikes a compromise between on the one hand the need for longer horizons to model expected returns and on the other hand to use high frequency data to model the conditional volatility required to estimate expected returns. Using the approach of Ghysels, Santa-Clara, and Valkanov (2005), after correcting a coding error pointed out to us, we find that the Merton model holds over samples that exclude financial crises, in particular the Great Depression and/or the subprime mortgage financial crisis and the resulting Great Recession. We find that a simple flight to safety indicator separates the traditional risk-return relationship from financial crises which amount to fundamental changes in that relationship.