John Maynard Keynes (1936) argued that markets can fluctuate wildly under the influence of investors' “animal spirits,” which move prices in a way unrelated to fundamentals.
After
Keynes, many other authors have considered the possibility that a significant
presence of sentiment-driven investors can cause prices to depart from
fundamental values.
The classic
argument against sentiment effects is that they would be eliminated by rational
traders seeking to exploit the profit opportunities created by mispricing.
If rational
traders cannot fully exploit such opportunities, however, then sentiment
effects become more likely.
Thus, we
can easily say that sentiment plays an important role in asset pricing and it
can affect the market.
“Nowadays the
question is no longer, as it was a few decades ago, whether investor sentiment
affects stock prices, but rather how to measure investor sentiment and quantify
its effects.” (Baker, Wurgler 2007)
Measure the investor sentiment: some approaches.
Measuring
the sentiment might be a difficult task. There are various indicators and
studies that assess markets, individual investors, and macroeconomic factors and
that try to understand the feelings of specific markets.
Hereby I
present some of the most popular approaches used by researches to measure the
Bull and the Bear.
Financial
market-based measures
Under the
first approach, empiricists proxy for investor sentiment with market-based
measures such as trading volume, closed-end fund discount, initial public
offering (IPO) first-day returns, IPO volume, option implied volatilities
(VIX), or mutual fund flows.
Baker and
Wurgler (2007) offers one of the most influential models based on financial
markets’ data:
·
trading volume
as measured by NYSE turnover (TURN)
·
dividend premium (PDND)
· closed-end fund discount (CEFD)
· the number of IPOs (NIPO)
· first-day returns on IPOs (RIPO)
·
the
equity share in new issues (S)
One of
the key points is that waves of sentiment have clearly discernible, important, and regular effects
on individual firms and on the stock market as a whole.
Although
market-based measures have the advantage of being readily available at a
relatively high frequency, they have the disadvantage of being the equilibrium
outcome of many economic forces other than investor sentiment. Qiu and Welch
(2006) put it succinctly: “How does one test a theory that is about inputs →
outputs with an output measure?”
Survey-based
sentiment indexes
Perhaps just by asking investors how optimistic they are, we can gain insight into the marginal irrational investor.
One of the most known
indexes is the UBS/Gallup survey, in which a randomly-selected sample of 1000
households with total investments equal or higher than $10,000 are interviewed
to construct Index of Investor Optimism. Another famous index is the “University of Michigan Consumer Sentiment
Index” based on at least 500 telephone interviews with fifty core questions. Brown and Cliff (2005) use the
latter to forecast market returns.
However,
according to Da et al. (2014), using such sentiment indexes can have
significant restrictions.
First, most
of the survey-based data sets are available at weekly or monthly frequency.
Second,
there is a little incentive for respondents to answer question in such surveys
carefully and truthfully (Singer (2002).
Thus,
survey-based sentiment indexes can be helpful in predicting financial
indicators. However, the usage of such indexes has specific drawbacks and can
be limited in some cases.
Textual sentiment
data from specialized on-line resources
Researchers
propose to use text mining and sentiment
analysis algorithms to extract information about investors’ mood from
social networks, media platforms, blogs, newspaper articles, and
other relevant sources of textual data. A precious source of information
can be Twitter for example. Zhang et al. (2011) found that emotional tweet
percentage is significantly negatively correlated with Dow Jones, NASDAQ and
S&P 500, but displayed significant positive correlation to VIX. It
therefore seems that just checking on Twitter for emotional outbursts of any
kind gives a predictor of how the stock market will be doing the next day.
However,
important to notice that it is relatively more difficult to collect such type
of data (in most cases a researcher needs a special software to “scrape the
web”)
Internet search
behavior
Herbert Simon
in 1955 was already claiming that “people start their decision making process
by gathering relevant information”.
Can we use Households
Internet Search Behavior to predict market sentiment? Dimpf and Jank (2012),
for example, find a strong co-movement of the Dow Jones’ realized volatility
and the volume of search queries for its name.
Search data
has the potential to objectively and directly reveal to empiricists the
underlying beliefs of an entire population of households. Internet search
behavior of households is relatively new and promising proxy for investor sentiment:
such type of data does not require additional information from other sources
and can be used in scientific studies independently.
Non-economic
factors
Many other
factors may affect our everyday mood, which is then reflected into the stock
market.
For
example, given that psychological evidence and casual intuition predict that
sunny weather is associated with upbeat mood, Hirshleifer and Shumway (2003) show
that stock returns are affected by the weather across the world.
Edmans,
Garcia, and Norli (2007) associate the outcomes of sporting events, such as the
World Cup, to drops in the stock market when the country loses a game.
There might
be many other non-economic factors, even though in this cases a question naturally
arises: does correlation always mean causation? Many of these non-economic
factors does not seem to have a sufficient economic rationale to support them.
Conclusion
Investor
sentiment is not straightforward to measure, but there is no fundamental reason
why one cannot find imperfect proxies that remain useful over time.
Such
considerations suggest that the practical approach is to combine several
imperfect measures.
It should
also be recognized that investor sentiment is only one of many forces on the
market. Stock prices are of course determined by supply and demand, and there
are numerous factors that affect these, such as fundamental factors, legal,
tax-related, demographic, technological, international, as well as other
psychological factors related to attention, regret, anchoring, and
availability.
Indexes of
stock market senitment can only play a supportive role in trying to understand
market events.
References
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