1 / 37

Investors' Horizons and the Amplification of Market Shocks

Investors' Horizons and the Amplification of Market Shocks. Cristina Cella Stockholm School of Economics Andrew Ellul Indiana University Mariassunta Giannetti Stockholm School of Economics, CEPR and ECGI. Research Motivation.

ally
Download Presentation

Investors' Horizons and the Amplification of Market Shocks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Investors' Horizons and the Amplification of Market Shocks Cristina Cella Stockholm School of Economics Andrew Ellul Indiana University Mariassunta Giannetti Stockholm School of Economics, CEPR and ECGI

  2. Research Motivation • Severe market shocks cause panic selling precisely when potential buyers are financially constrained • Investors with shorter trading horizons are inclined or forced to sell in bad times • Because of preferences or specialization, they care about short-term returns • Because they face constraints, such as investor outflows or margin constraints, shortening their horizons • De Long, Shleifer, Summers, Waldmann (1990)

  3. Theoretical Mechanisms Selling pressure Lack of potential buyers Market frictions Duffie, 2010; Duffie and Strulovici, 2009 Market frictions prevent buying capital from moving quickly to buy temporary undervalued stocks Sales of distressed assets Shleifer and Vishny, 1992 When a distressed seller tries to sell an asset, she faces two types of potential buyers: (a) from the same industry and (b) outside the industry If investors in the same industry are distressed as well, then buyers have to come from outside the industry • Limits to arbitrage • Shleifer and Vishny, 1997 • Expectations of outflows due to negative performance may lead investors to sell undervalued stocks • Financial market runs • Bernardo and Welch, 2003; Morris and Shin, 2004 • Short horizon investors sell in anticipation of sales of other market participants • Investors with long horizons can wait out the storm and generate less selling pressure • Margin constraints • Brunnermeierand Pedersen, 2009

  4. This Paper • Can institutional investors’ trading horizons amplify the price effects of severe market shocks? • Such shocks will naturally impact stocks’ fundamentals • Stocks’ returns may vary cross-sectionally depending on the horizons of investors • Do stocks of firms held by short horizon investors experience larger temporary drops after negative shocks?

  5. Hypotheses • During severe market shocks, stocks mostly held by short-term investors should experience: • Larger drops – returns drop below their normal (expected) returns • Larger reversals • If prices fall below their fundamental values then reversals should occur as buyers move in to buy these stocks. Reversals should be largest precisely for stocks that have suffered the most severe drops.

  6. Related literature • Fire sales • Coval and Stafford (2007), Mitchell, Pedersen and Pulvino (2007), Pulvino (1998), Campbell, Giglio and Pathak (2008) and Ellul, Jotikasthira and Lundblad (2009) • We explore the role of investor horizon in accentuating fire sales • Literature exploring the effects of investor horizon on corporate policies • Bushee (1998 and 2000); Gaspar, Massa, and Matos (2005) etc… • Papers exploring the effects of firm characteristics on returns during financial crises • E.g. Fahlenbrach and Stulz (2011); Lemmon and Lins (2003); Mitton (2002)

  7. The Main Event • Large stock market declines after Lehman Brothers’ bankruptcy in September 2008

  8. Data Sources • Quarterly ownership information reported by Thomson Financial in 13Fs over the period 1990-2006 • CRSP • COMPUSTAT

  9. Investor Horizons • Horizon is identified as average holding period • (e.g., Carhart (1997), Barber and Odean (2000), Bushee (1998, 2000 and 2001), Gaspar, Massa and Matos (2005) and Yan and Zhang (2009)) • We use the average investor’ turnover from 1990 to 2006

  10. Investor Horizons • Large variation in investor portfolio turnover • 5th percentile turns over less than 1% of their portfolio in a quarter • 95th percentile turn over more than 50% of their holdings in a quarter • Short horizon investors are not necessarily active investors • Portfolio turnover has low correlation with the proportion of the portfolio that deviates from the relevant index (Cremers and Petajisto, 2009)

  11. Investor Turnover • The average Investor Turnover (IT) of a high IT firm is 0.37 and that of a low IT firm is 0.19 • An average turnover of 0.37 (0.19) implies that institutional investors holding these stocks rotate almost 19% (9.5%) of a portfolio in each quarter, and 76% (37%) in each year • This means that on average investors in high turnover firms hold their position for less than 16 months, while investors in low turnover firms hold their position for almost 33 months

  12. Trading and Investors’Horizons In the aftermath of the Lehman shock, short-term investors sold 21% of their holdings compared to 7% sold by long-term investors

  13. Investors’ Horizons and Selling Pressure • Selling pressure during episodes of market turmoil may not necessarily be related to investors’ trading horizons • Some hedge funds had strict lock-up periods that limited outflows and had a lower propensity to sell during the crisis (Ben-David, Franzoni, and Moussawi (2010)) • Index mutual funds without the protection of lock-up periods may face severe redemptions leading to severe selling pressure during periods of crisis

  14. Investors’ Horizons and Selling Pressure

  15. Investors Horizons and Selling Pressure • In periods of market turmoil, all institutional investors’ net sales increase by the equivalent of almost 0.3 standard deviations for an investor with average net sales and average churn ratio • The increase in net sales is equivalent to over 0.65 standard deviations for an investor with a churn ratio in the top quartile of the distribution but to less than 0.15 standard deviations for investors with a churn ratio in the lowest quartile

  16. Cumulative Abnormal Returns • Two (main) definitions of normal (expected) returns • Based on the market model • Estimated using weekly returns from the beginning of 2003 until the end of the first quarter of 2008 • Based on contemporaneous returns of 100 portfolios sorted on size and book to market • Ikenberry, Lakonishok and Vermaelen, 1995 • Robustness tests using (two) multifactor models including VIX and Pastor and Stambaugh’s liquidity factor

  17. CARs: Market Model The stocks held to a larger extent by investors with shorter horizons experience more severe price drops and larger price reversals

  18. CARs: Size & Value Portfolios

  19. Economic and Statistical Significance

  20. Innovations in Implied Volatility Innovations in time-varying market volatility, considered to reflect the probability of a market-wide meltdown, may either change the risk-return trade-off, or the expectations of future returns (Campbell (1996) and Chen (2002)) It can be argued that the price dynamics we uncover just reflect differences in the stocks’ exposure to the probability of a meltdown

  21. Innovations in Implied Volatility • Differences in exposure to aggregate volatility risk? • We estimate abnormal returns using Ang, Hodrick, Xing, and Zhang’s (2006) multifactor model • We use changes in aggregate volatility, measured by the VIX, as an additional factor in the computation of normal returns

  22. Exposure to Aggregate Volatility

  23. Exposure to Liquidity Risk • Heterogeneity between the two groups of stocks driven by their differences in the exposure to liquidity risk? • We estimate a multifactor model including the market return and the aggregated liquidity factor as in Pastor and Stambaugh (2003)

  24. Exposure to Liquidity Risk

  25. Rest of Talk • I will try to convince you that the previous striking figure does not depend on • firm heterogeneity • characteristics of the investors trading strategy (other than investor horizon) • i.e., indexers vs active investors; momentum traders

  26. Do Low and High IT Firms Differ? • Low and High IT firms differ along a number of dimensions • High IT firms have lower insider ownership • High IT firms are more liquid and more volatile • High IT firms have lower leverage • Yet, it’s important to notice that: • High IT firms have beta only slightly larger relative to low IT firms

  27. Is it Really Investor Horizon? • Portfolio sorts – looking at subsamples of more homogeneous firms • Our benchmarks already take into account differences in size and book-to market • We find larger drops and reversals for stocks held by short-term investors within portfolio quintiles sorted on • Share turnover Not merely a liquidity effect • Return volatility • Past returns Not merely a momentum effect • Cross-sectional & panel regressions

  28. Portfolio Sorts

  29. Price Drop - Cross-section Analysis

  30. Price Drops – Panel Regressions

  31. Price Reversals

  32. Testing the Mechanisms (I) • Investors with short horizons may sell more for some (unobserved) reason related to returns • Investor portfolio turnover captures • trades whose motivation is to generate profits (or limit losses) • trades forced by other reasons such investor flows • Historicalcorrelationbetween assets under management and pastperformancerelatedtoforcedtrades It can be used as an instrument • Instrumental variableestimatesconfirm the resultsshown so far

  33. Testing the Mechanism (II) • Do short-term investors sell also the stocks mostly held by long-term investors in their portfolios? • If not some stock unobservable characteristics could explain their trades Net Asset Position as % of Total Asset Value (invested in each type of stock)

  34. Other Major Market Shocks • Do we point out something specific to the fall 2008? • Other events during the 2007-2008 crisis • Large mkt declines (15% drop in the S&P500 in one month)

  35. Other Major Market Shocks

  36. Other Major Market ShocksMultivariate Analysis

  37. Conclusions • Evidence that investors’ short trading horizons amplify negative shocks • Future research: What determines investor horizon?

More Related