Buy and Sell Timing Decisions by Mutual Fund Managers Rajiv D. Banker Janice Chen Fox School of Business Temple University √

Slides:



Advertisements
Similar presentations
1 Behavioural Slides 2007 Behavioral Corporate Finance.
Advertisements

Presented by: Bhavin Gandhi Jaime Tibaduiza Althea Lim Sean Findley.
Chapter 3 Market Efficiency
A test of the free cash flow hypothesis: The case of bidder returns Larry H.P. Lang Rene M. Stulz Ralph A. Walkling (Journal of Financial Economics 29,
Contrarian & Momentum Strategies in Japan Amitabh Agrawal Karim Fahim Bernard Muller Shawn Ramsey Jason Takata Global Investment Management.
1 Quantitative Portfolio Management Dr. B. Swaminathan, PhD Partner & Director, Research LSV Asset Management Professor of Finance Cornell University.
Behavioral Finance Ahmed Elshahat October 27 th 2006 CPE.
Vicentiu Covrig 1 The Efficient Capital Markets (chapter 12 Jones)
Why “Bigger” Isn’t Better Liquidity in the Canadian Equity Market.
Week-6 Stock Market, Rational Expectations and Financial Structure Money and Banking Econ 311 Tuesdays 7 - 9:45 Instructor: Thomas L. Thomas.
Market Efficiency Chapter 10.
© 2008 Pearson Education Canada7.1 Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Markets Hypothesis.
Market Efficiency Chapter 12. Do security prices reflect information ? Why look at market efficiency - Implications for business and corporate finance.
Asset Management Lecture 19. Agenda Behavioral finance (Chapter 12) Challenges to market efficiency Limits to arbitrage Irrational investors.
INVESTOR BEHAVIOUR AND BENCHMARKS Presentation to Finansmarkedsfondet Executive Board Sari Carp Norwegian School of Management (BI) 8 December 2005.
Judgment in Managerial Decision Making 8e Chapter 9 Common Investment Mistakes Copyright 2013 John Wiley & Sons.
1 Business System Analysis & Decision Making - Lecture 8 Zhangxi Lin ISQS 5340 July 2006.
Chapter 7 The Stock Market, The Theory of Rational Expectations, and the Efficient Market Hypothesis.
The Security Market Line (SML) aka The Capital Asset Pricing Model (CAPM) The Capital Asset Price Model is E(R A ) = R f + [E(R M ) - R f ] x A Expected.
Efficient Capital Markets Objectives: What is meant by the concept that capital markets are efficient? Why should capital markets be efficient? What are.
McGraw-Hill/Irwin © 2007 The McGraw-Hill Companies, Inc., All Rights Reserved. Behavioral Finance and Technical Analysis CHAPTER 19.
CHAPTER 19 Behavioral Finance and Technical Analysis.
1 Why your behaviour may dramatically reduce your returns What evidence do we have? Frank Ashe July 2005.
Experience Schulich 2010 Mini-lecture: Finance. S As Far as Investors were concerned… the last decade was a miss!
Pauline Shum Schulich School of Business York University
Behavioral finance is an approach to finance, not a sub-field.
Chapter 12 The Efficient Market Hypothesis. McGraw-Hill/Irwin © 2004 The McGraw-Hill Companies, Inc., All Rights Reserved. Random Walk - stock prices.
1 BM410: Investments Portfolio Construction 2: Market Anomalies and Portfolio Tilts.
Size Effect Matthew Boyce Huibin Hu Rajesh Raghunathan Lina Yang.
Behavioural Finance and Investment Beliefs. Twin Peaks 1 1.
Investment and portfolio management MGT 531.  MGT 531   Lecture # 16.
Copyright © 2010 Pearson Addison-Wesley. All rights reserved. Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market.
Chapter 8 The Efficient Market Hypothesis. McGraw-Hill/Irwin © 2004 The McGraw-Hill Companies, Inc., All Rights Reserved. Efficient Market Hypothesis.
McGraw-Hill/Irwin © 2007 The McGraw-Hill Companies, Inc., All Rights Reserved. Efficient Markets & The Behavioral Critique CHAPTE R 8.
McGraw-Hill/Irwin Copyright © 2005 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 12 Market Efficiency and Behavioral Finance.
The Efficient Market Hypothesis. Any informarion that could be used to predict stock performance should already be reflected in stock prices. –Random.
McGraw-Hill/Irwin Copyright © 2001 by The McGraw-Hill Companies, Inc. All rights reserved Market Efficiency Chapter 11.
Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
1 MBF 2263 Portfolio Management & Security Analysis Lecture 7 Efficient Market Hypothesis.
CHAPTER 19 Behavioral Finance. McGraw-Hill/Irwin © 2004 The McGraw-Hill Companies, Inc., All Rights Reserved. Behavioral Finance Traditional financial.
 The McGraw-Hill Companies, Inc., 1999 INVESTMENTS Fourth Edition Bodie Kane Marcus Irwin/McGraw-Hill 12-1 Market Efficiency Chapter 12.
BEHAVIORAL FINANCE.
High Momentum and Traditional Momentum Strategies: Evidence from China Traditional Momentum (Jegadeesh and Titman, 1993)  A self-financing strategy that.
McGraw-Hill/Irwin © 2007 The McGraw-Hill Companies, Inc., All Rights Reserved. Efficient Markets & The Behavioral Critique CHAPTER 8.
Chapter 10 Market Efficiency.
The Case For Passive Investing: Active investor track records Aswath Damodaran.
1 Lecture 12 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Essentials of Investments © 2001 The McGraw-Hill Companies, Inc. All rights reserved. Fourth Edition Irwin / McGraw-Hill Bodie Kane Marcus 1 Chapter 9.
2016 CIFR Conference 1 Uncommon Value: The Investment Performance of Contrarian Funds Kelsey Wei, University of Texas, Dallas Russ Wermers, University.
Behavioral Finance Economics 437.
Chapter 7 the Stock Market and Market Efficiency.
Chapter 11 Investment Companies. Closed-end Open-end (commonly called a mutual fund)
Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Behavioral Finance and Technical Analysis
Chapter 9 Market Efficiency.
Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Are Financial Markets Efficient ?
Behavioral Finance.
Momentum, contrarian, and the January seasonality
Multifactor Models and Market Efficiency (BKM 11, 12, 13) BUFN 741: Advanced Capital Markets Topic 4.
Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Chapter 7 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Behavioral Finance Economics 437.
Behavioral Finance Economics 437.
Behavioral Finance Economics 437.
Market Efficiency and Behavioral Finance
How Efficient Is the Market?
Lectures 11 and 12 The Stock Market, the Theory of Rational Expectations, and the Efficient Market Hypothesis.
Behavioral Finance Economics 437.
Presentation transcript:

Buy and Sell Timing Decisions by Mutual Fund Managers Rajiv D. Banker Janice Chen Fox School of Business Temple University √

Theme of the Paper Job security and compensation incentives imply that active fund managers have superior ability to time the market in buy or sell trades Psychological biases, such as disposition or endowment effects, may inhibit efficient timing Data on 18 fund managers at one firm spanning one year (2005) We find fund managers exhibit good buy and sell timing ability Actual trading strategy outperforms both momentum and contrarian strategies √

Mutual Funds A mutual fund is a trust that pools the savings of a number of investors In end 2007, the combined assets of mutual funds in the U.S. were $12 trillion In early 2008, the worldwide value of all mutual funds totaled more than $26 trillion Mutual fund companies competed vigorously to attract investor funds

Stock Picking Ability Market Timing Ability Fama (1972) Wermers (1997)Jiang et al. (2007) Bollen and Busse (2001) Grinblatt and Titman (1989, 1993) Fund Manager Performance

Principal Hypothesis Fund managers have the ability to time their buy and sell trades efficiently Timing ability is critical for fund managers: High liquidity and frequent trading activities Replacement of less successful fund managers High investment turnover rate Bonuses based on fund performance √

Measures of Timing Ability Based on only fund-level data Treynor and Mazuy (1966) Henriksson and Merton (1981) Jiang et al. (2007) Artificial timing bias: time-varying parameter problem √

Behavioral Finance Studies Psychological biases inhibit performance Overconfidence explains reduction in investors’ performance due to excessive trading (Barber and Odean 2000, 2001, 2002) Fund managers exhibit herding behavior (Grinblatt et al. 1995) Disposition effect (Shefrin and Statman 1985) Endowment effect ( Thaler, 1980) √

Prospect Theory Kahneman and Tversky 1979 VALUE LOSSES

Disposition Effect Disposition effect is an implication of prospect theory (Kahneman and Tversky 1979) applied to investment decisions Disposition effect reflects the tendency of investors to sell winners too early and hold on to losers too long (Shefrin and Statman 1985)

Disposition Effects on Trading Individual investors sell winners early and hold on to losers (Odean 1998) Professional managers also exhibit disposition bias (Grinblatt and Keloharju 2001, Scherbina and Jin 2005) Disposition effect may lead to inefficient timing decisions for buy and sell trades √

Endowment Effect People often demand much more to give up an object Tversky and Kahneman (1991) attribute this phenomenon to loss aversion (tendency to strongly prefer avoiding losses than acquiring gains) Endowment effect may lead to inefficient timing decisions for buy and sell trades √

Alternative Trading Strategies Contrarian Strategy Buying losers and selling winners (De Bondt and Thaler 1985, 1987) Momentum Strategy Buying winners and selling losers (Jegadeesh and Titman, 1993) If fund managers are good at timing their trades, they should outperform these simple strategies √

Hypothesis 2 The actual trading strategy of fund managers outperforms both the contrarian strategy and the momentum strategy trading the same stocks

Sample Data Transaction-based datasets 11,906 buy transactions 8,465 sell transactions Each transaction has trading volume (quantity), market value, cumulative excess returns (3, 6 month pre-trade returns and 3, 6 month post-trade returns). There are 18 fund managers Our transaction dataset is proprietary and spans one calendar year 2005 √

Four Time Periods for Annualized Excess Returns All 4 time periods are calibrated relative to the date of trade √

Types of Traded Stocks Buy TransactionsSell Transactions Number% % Growth5,39945%4,01947% Value6,20352%4,17149% Large cap7,92967%5,48365% Small cap3,67331%2,70732% Over-weighted10,19486%6,05071% Under-weighted1,71214%2,40228%

Empirical Results Buy sample: The medians of annualized excess returns are significantly negative in pre-trade periods while significantly positive in post-trade periods Sell sample: The medians of annualized excess returns are significantly positive in pre-trade periods while significantly negative in a post-trade period

Buy Transactions Median Excess Returns √

Sell Transactions Median Excess Returns √

Buy Sub-Sample Analysis Median Excess Returns Pre6-3Pre3-0Post0-3Post3-6 Full Sample -2.17**-5.90***1.44***0.31*** Growth 0.39***-0.35***3.42***-1.18*** Value -4.18***-9.44***-0.13***0.97*** Large Cap ***1.92*** Small Cap -0.34***-4.87***0.27***4.37*** Overweighted ***1.56***0.15*** Underweighted 0.02*** ***1.19*** √

Sell Sub-Sample Analysis Median Excess Returns Pre6-3Pre3-0Post0-3Post3-6 Full Sample 4.05***8.78***-1.98***1.48*** Growth 10.94***14.76*** *** Value -0.26***2.52***-1.26***0.29*** Large Cap 3.64***6.08*** -2.25**0.19*** Small Cap 5.87***15.89***-1.31***4.14*** Overweighted 4.78***12.27***-2.15***2.43*** Underweighted 2.20***2.19*** *** √

Paired Tests Pre-Trade Minus Post-Trade Median Excess Returns Buy SampleSell Sample Post0-3Post3-6Post0-3Post3-6 Pre ***-4.53***9.67***7.63*** Pre ***-1.99***5.55***2.70*** √

Buy Sample Paired Tests Pre-Trade Minus Post-Trade Median Excess Returns

Sell Sample Paired Tests Pre-Trade Minus Post-Trade Median Excess Returns

Growth vs. Value Paired Test Buy SampleSell Sample GrowthPost0-3Post3-6Post0-3Post3-6 Pre ***2.90***16.00***12.06*** Pre ***12.99***7.69*** Buy SampleSell Sample ValuePost0-3Post3-6Post0-3Post3-6 Pre ***-9.99***5.26***1.71*** Pre ***-5.46***

Large Cap vs. Small Cap Paired Test Buy SampleSell Sample Large CapPost0-3Post3-6Post0-3Post3-6 Pre ***-1.87***7.19***4.90*** Pre *** ***3.09*** Buy SampleSell Sample Small CapPost0-3Post3-6Post0-3Post3-6 Pre **-9.41*** 17.02***12.82*** Pre *** 7.93***2.70***

Overweighted vs. Underweighted Paired Test Buy SampleSell Sample OverweightedPost0-3Post3-6Post0-3Post3-6 Pre ***-4.77***12.70***10.84*** Pre ***-2.90*** 6.89*** 2.71*** Buy SampleSell Sample Underweighted Post0-3Post3-6Post0-3Post3-6 Pre ***1.27** Pre *** 2.69*

Momentum and Contrarian Strategies Winners are stocks with positive excess returns in 3 months preceding trade date Losers are stocks with negative excess returns in 3 months preceding trade date Momentum strategy mimicking portfolios buy winners and sell losers Contrarian strategy mimicking portfolios buy losers and sell winners √

Comparison with Momentum Strategy Excess returns of actual strategy – Excess returns of momentum strategy MeanMedian Diff_RetMeanp-valueMedianp-value Buy Sample Sell Sample √

Comparison with Contrarian Strategy Excess returns of actual strategy – Excess returns of contrarian strategy MeanMedian Diff_RetMeanp-valueMedianp-value Buy Sample Sell Sample √

Robustness Check Results survive when performance of trading strategies is evaluated relative to distribution of simulated excess returns (Kothari and Warner, 2001) drawn from the CRSP population of stocks √

Conclusion Managers have a good market timing ability to buy stocks at a low price and sell at a high price Fund managers are not overly influenced by psychological biases such as the endowment effect or the disposition effect Fund managers outperform both the momentum strategy and the contrarian strategy Caveat: Data for only one company for one year √