The behaviour of
sentiment-induced share returns:
Measurement when
fundamentals are observable
Richard Brealey
Ian Cooper
Evi Kaplanis
London Business School
Share prices and sentiment
Many theories about the effect of sentiment on share prices are expressed in terms of deviations from fundamentals
— Daniel, Hirshleifer, and Subrahmanyam (1998),
Barberis, Shleifer, and Vishny (1998)
Barberis et al (2012):
— Sentiment pushes prices away from fundamentals in the
short term
— In the medium-term they mean-revert
The effect should be concentrated in “hard-to-arbitrage” stocks
On the other hand, there is evidence of market-wide sentiment effects (Arif and Lee (2014)) which may affect all stocks
The importance of controlling for fundamentals
Results about sentiment and returns can be different if controls for fundamentals are not included (Barberis, Shleifer, Wurgler (2005))
Our study: Use a sample where we believe we have a good proxy for fundamental value
Our study
Use a sample of firms where we should have an excellent proxy for fundamental value: Upstream oil stocks
— Empirically, oil price explains cross-section of values (Miller and Upton (1985a), (1985b))
– Theory says discount rate uncertainty is not so important for these stocks once the oil price is controlled for (Hotelling)
Split the stock return into the part caused by changes in fundamentals and the part that represents the deviation from fundamentals
Test whether sentiment predicts the behavior of the deviation from fundamentals in the way that theory says it should
Two measures of sentiment:
— Baker-Wurgler index should predict reversion to fundamentals
— Retail investor sentiment index should predict momentum trading
Main results
Sentiment predicts returns in the expected way
a. Baker-Wurgler (“BW”) sentiment predicts mean-reversion
b. Retail “Bullish” sentiment predicts momentum
The effect appears only after the major increase in interest in commodities, particularly oil, in 2000
Only then do fundamentals explain a large part of returns
The effect appears to work via the fundamentals themselves rather than through deviations from fundamentals
Economic size is about 0.3% per month from bullish sentiment and about 0.3% per month from BW sentiment
The effect appears in a Hi-Lo portfolio, but because it has a net exposure to fundamentals
Data
121 US oil exploration and production stocks (SIC 1311)
Monthly data 1983-2011 (CRSP)
Fundamentals measured by spot oil price, spot gas price, oil contango
Equally weighted portfolio of all stocks
Sub-portfolios sorted by variance over prior 60 months
Highest tercile variance portfolio minus lowest tercile variance portfolio (“Hi-Lo”)
BW sentiment
American Association of Individual Investors “bullishness” survey
Serial properties of our data
Our data show standard properties of returns data:
— Short-term momentum
Lehman (1990), Jegadeesh (1990), Jagadeesh and Titman (1993)
— Longer term mean-reversion
Poterba and Summers (1988), Lo and MacKinlay (1998), Cutler, Poterba, and Summers (1991)
— Consistent with excess volatility relative to fundamentals
Shiller (1981), LeRoy and Porter (1981)
Variance ratios of our sample
Variance ratios of the All-stocks portfolio
relative to the 1-month variance rate
Equally-weighted all US oil production and exploration
stocks listed on NYSE (121 stocks)
Sentiment measures
Baker-Wurgler composite index of sentiment (index of IPO volume and returns, market volume, relative pricing of high and low volatility stocks)
Survey data (Qiu and Welch (2004), Brown and Cliff (2004, 20025))
— We use American Association of Individual Investors survey: Proportion who report that they are bullish (“Bullish” sentiment)
Hypothesis is that BW sentiment is an index of the level of mispricing, so returns following high BW sentiment will be low, reflecting reversion to fundamental value, and that this will be more pronounced for hard-to-arbitrage stocks
Hypothesis is that Bullish sentiment picks up momentum trading and high bullish sentiment will be followed by high returns
BW sentiment
monthly serial
correlation
0.96
Bullish
sentiment
monthly serial
correlation
0.45
Monthly
correlation
between them
0.09
Sub-period analysis: Motivation
For our sub-period analysis, we split the period at the end of 2000
Open interest in oil futures (CFTC) and flows into commodity hedge
funds (Managed Futures Funds, TASS data) increased significantly
post-2000
Preliminary results
Across the sample period the fundamentals explain 41% of the
variance in the All-stocks portfolio returns
Hi-Lo portfolio returns are not well hedged against fundamentals, oil
and gas price are highly significant factors for Hi-Lo returns
Correlation between returns and lagged sentiment are larger for high-
variance portfolio and the Hi-Lo portfolio: appears at first sight to be
consistent with hard-to arbitrage hypothesis
Including controls reduces considerably the significance of sentiment
variables are reduced considerably for both portfolios for entire
period and for both sub-periods
Splitting returns
To avoid overfitting the coefficients, each month we split
the returns into fundamentals and non-fundamentals using
lagged parameter values
Estimate fundamentals regression for prior 60 months:
Rit = ai + bi Δ WTIt + ci Δ GASt + di Δ Conti + uit
Fundamentals: Returns to WTI spot price, Gas spot price,
change in Contango of 6th-1st futures price
Use estimated coefficients and actual realizations of{ΔWTIt, ΔGASt, ΔContt}to estimate fundamental return for that month
Remainder of return is non-fundamental
Roll the windows
Regression structure
Fundamental return from t-1 to t is: Ft – Ft-1
Non-fundamental return from t-1 to t is: NFt – NFt-1
Regress Ft – Ft-1 and NFt – NFt-1 on lagged returns and lagged sentiment measures
Include BW sentiment, St, and Bullish sentiment, Bt, in a VAR
VAR Structure and Hypotheses
VAR for entire period: Hi-Lo portfolio
VAR Results: Summary
BW predicts reversion to mean
Bullish predicts momentum
Both effects operate through fundamentals (i.e. oil and gas prices)
Hi-Lo portfolio is exposed to fundamentals
No effect of sentiment through deviations from fundamentals
BW sentiment responds to fundamental return, not non-fundamental return
Sub-period results: Hi-Lo portfolio
Different measurement intervals
Sentiment transmission in the second period
Robustness
Including lagged market return does not change results
Looking only at high variance portfolio alone does not change results
Including 274 NASDAQ exploration and production stocks:- High vol portfolio is almost exclusively NASDAQ
– Hi-Lo is better hedged against fundamentals
– Effect of sentiment still appears only in second period
– Predictability of Hi-Lo return is lower
– Effect of sentiment appears only through fundamentals
when return is split (not in current paper)
What if the oil price is not “fundamental”?
Evidence that oil and gas prices are affected by sentiment (Pindyck (1993))
Regress oil price change on sentiment and “deep” fundamentals
Deep fundamentals are changes in:
– Oil production, oil consumption, gdp, proven oil
reserves (annual data), oil inventories (quarterly)
Low power test, but coefficient on BW is mildly significant and negative, coefficient on bullish is mildly significant and positive
Consistent with channel of influence of sentiment being
through oil price
Regression of changes in the oil price on deep
fundamentals and sentiment
Results: Summary
Sentiment predicts returns in the expected way
a. Baker-Wurgler sentiment predicts mean-reversion
b. Retail bullish sentiment predicts momentum
Economic size is about 0.3% per month from bullish sentiment and about 0.3% per month from BW sentiment
The sentiment effect for these stocks operates through fundamentals(i.e. oil and gas prices)
Significant effects appear only after 2000 when:
– interest in oil as an asset increased considerably
– fundamentals became more important in determining upstream oil stock returns
Inconsistent with theories where sentiment causes deviations from
fundamental value
Inconsistent with with hard-to-arbitrage theories about sentiment
effects
Caveats and issues
Maybe our results are sector-specific because, in this
instance, what we use as fundamentals are themselves
tradeable (Basak and Pavlova (2014))
The highly time-varying effect of sentiment here has a
clear cause that may not be present for other stocks
Our result that that the Hi-Lo portfolio loads on fundamental factors may not apply in other cases
Raises the question of what “fundamental value” means in
this instance
Raises question of why sentiment should predict returns
in “easy-to-arbitrage” assets like oil