Post on 03-Jan-2016
description
transcript
Buy and Sell Timing Decisions by Mutual Fund Managers
Rajiv D. BankerJanice Chen
Fox School of BusinessTemple 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 AbilityBased on only fund-level data
• Treynor and Mazuy (1966)
• Henriksson and Merton (1981)
• Jiang et al. (2007) Artificial timing bias: time-varying parameter problem
pmpmppp RcRR 2**
pmpmppp RcRR ),0max(**
),cov()()()( 111 mtptmtptpt rrEErE
√
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 Transactions Sell Transactions
Number % Number %
Growth 5,399 45% 4,019 47%
Value 6,203 52% 4,171 49%
Large cap 7,929 67% 5,483 65%
Small cap 3,673 31% 2,707 32%
Over-weighted 10,194 86% 6,050 71%
Under-weighted 1,712 14% 2,402 28%
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 TransactionsMedian Excess Returns
-6 -3 +3
-7
-6
-5
-4
-3
-2
-1
0
1
2
med
ian
exce
ss re
turn
s -6 -3 0 +3 +6
-2.17
-5.90
1.44
0.31
√
Sell Transactions Median Excess Returns
-6 -3
-4
-2
0
2
4
6
8
10
med
ian
exce
ss r
etur
ns
-6 -3 0 +3 +6
4.05
8.78
-1.98
1.48
√
Buy Sub-Sample AnalysisMedian Excess Returns
Pre6-3 Pre3-0 Post0-3 Post3-6
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 -2.45 -5.83*** 1.92*** -1.92
Small Cap -0.34*** -4.87*** 0.27*** 4.37***
Overweighted -2.54 -6.31*** 1.56*** 0.15***
Underweighted 0.02*** -3.54 0.59*** 1.19***
√
Sell Sub-Sample AnalysisMedian Excess Returns
Pre6-3 Pre3-0 Post0-3 Post3-6
Full Sample 4.05*** 8.78*** -1.98*** 1.48***
Growth 10.94*** 14.76*** -2.66 2.86***
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*** -1.41 -0.54***
√
Paired TestsPre-Trade Minus Post-Trade Median Excess Returns
Buy Sample Sell Sample
Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -5.23*** -4.53*** 9.67*** 7.63***
Pre6-3 -2.49*** -1.99*** 5.55*** 2.70***
√
Buy Sample Paired TestsPre-Trade Minus Post-Trade Median Excess Returns
Buy
-6
-5
-4
-3
-2
-1
0
Post0-3 Post0-3
Pre3-0
Pre6-3
Sell Sample Paired TestsPre-Trade Minus Post-Trade Median Excess Returns
sell
0
2
4
6
8
10
12
Post0-3 Post0-3
Pre3-0
Pre6-3
Growth vs. ValuePaired Test
Buy Sample Sell Sample
Growth Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -0.82*** 2.90*** 16.00*** 12.06***
Pre6-3 -1.82 3.96*** 12.99*** 7.69***
Buy Sample Sell Sample
Value Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -8.63*** -9.99*** 5.26*** 1.71***
Pre6-3 -2.57*** -5.46*** -0.54 -0.82
Large Cap vs. Small CapPaired Test
Buy Sample Sell Sample
Large Cap Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -6.57*** -1.87*** 7.19*** 4.90***
Pre6-3 -2.50*** 0.15 4.68*** 3.09***
Buy Sample Sell Sample
Small Cap Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -1.33** -9.41*** 17.02*** 12.82***
Pre6-3 -1.71 -5.36*** 7.93*** 2.70***
Overweighted vs. UnderweightedPaired Test
Buy Sample Sell Sample
Overweighted Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -5.88*** -4.77*** 12.70*** 10.84***
Pre6-3 -3.28*** -2.90*** 6.89*** 2.71***
Buy Sample Sell Sample
Underweighted Post0-3 Post3-6 Post0-3 Post3-6
Pre3-0 -1.03 -1.90 4.02*** 1.27**
Pre6-3 1.64 2.48 2.47*** 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
Mean Median
Diff_Ret Mean p-value Median p-value
Buy Sample 1.53 0.03 1.57 0.015
Sell Sample -2.13 0.03 -2.16 0.001
√
Comparison with Contrarian Strategy
Excess returns of actual strategy – Excess returns of contrarian strategy
Mean Median
Diff_Ret Mean p-value Median p-value
Buy Sample 1.37 0.075 1.26 0.03
Sell Sample -1.97 0.01 -1.85 0.003
√
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
√