Mutual Fund and Hedge Fund Performance
Paper Session
Friday, Jan. 3, 2025 8:00 AM - 10:00 AM (PST)
- Justin Birru, Ohio State University
Displaced by Big Data? Evidence from Active Fund Managers
Abstract
Alternative data provides new signals for active fund managers, but requires specific skills to leverage. Managers lacking these skills could experience a decline in their ability to outperform, unless their expertise produces information distinct from that in alternative data. Consistent with the former, we find that the release of satellite data tracking firms’ parking lots significantly reduces fund managers’ stock-picking abilities in covered stocks. This effect is stronger for funds leveraging traditional expertise, like industry specialization or geographic proximity, leading them to divest from covered stocks. Our findings suggest that alternative data can reshape the determinants of active funds’ performance.Remeasuring Scale in Active Management
Abstract
We argue at least 65% more total assets should be included in estimating scale of actively managed portfolios. By merging two major datasets on institutional products, we identify trillions of institutional assets that are managed under the same investment strategy as their twin mutual funds with an average return correlation of 99.9%. Overlooking the assets under management for institutional products skews crucial estimates in asset management research. We show that after including these assets in the scale metric reduces fund-level (industry-level) diminishing returns to scale of mutual funds by up to 90% (50%), suggesting a larger capacity of active asset management than the literature believed. We also observe that dollar value added of active strategies is more substantial and persistent than past assessments suggested.Volatility Timing Using ETF Options: Evidence from Hedge Funds
Abstract
We find that hedge funds’ positions in exchange-traded fund (ETF) options contain volatility information about underlying ETF returns. Greater hedge fund option demand predicts higher variance of ETF returns over the following quarter and on days of macroeconomic news releases. The predictive power holds for options on both equity and non-equity ETFs, like fixed income and currency ETFs. A tracking portfolio of straddles based on funds’ straddle positions earns quarterly abnormal returns of 7.95%. Net of fees, funds using ETF straddles deliver lower risk and higher benchmark-adjusted returns than nonusers. We conclude that ETF options are an important venue for market volatility timing strategies.Discussant(s)
Ryan Israelsen
,
Michigan State University
Clifton Green
,
Emory University
Alexander Chinco
,
CUNY-Baruch College
Sophia Zhengzi Li
,
Rutgers University
JEL Classifications
- G1 - General Financial Markets