On the behaviour of financial markets:
Fluctuations and Sentiment
Khurshid Ahmad,
Chair of Computer Science
Trinity College, Dublin, IRELAND
11-13th November 2013
Price Discovery in Spot
Markets
A method of determining the price for a specific
commodity or security through basic supply and
demand factors related to the market.
Price discovery is the general process used in
determining spot prices. These prices are dependent
upon market conditions affecting supply and demand.
For example, if the demand for a particular
commodity is higher than its supply, the price will
typically increase (and vice versa).
http://www.investopedia.com/terms/p/pricediscovery.asp#axzz2KmoENsz7
Price Discovery in Futures
Markets
Garbade and Silber have noted that:
Risk transfer and price discovery are two of the major
contributions of futures markets to the organization of
economic activity […]
Risk transfer refers to hedgers using futures contracts to shift
price risk to others.
Price discovery refers to the use of futures prices for pricing
cash market transactions.
The significance of both contributions depends upon a close
relationship between the prices of futures contracts and cash
commodities.
Kenneth D. Garbade and William L. Silber (1983). Price Movements and Price Discovery in Futures and Cash
Markets. The Review of Economics and Statistics, Vol. 65, No. 2 (May, 1983), pp. 289-297Published
Economics, Finance and Behaviour
Individual and Institutional Investor Sentiment
The Investor Behavior Project at Yale University, has been
collecting questionnaire survey data on the behavior of US
investors since 1984. The questionnaire is sent to individual
investors and to institutional investors.
One of the longest-running effort to measure investor
confidence and related investor attitudes.
The differences amongst the individuals and institutions is
quite remarkable. This is perhaps one of first systematic field
studies to have identified information asymmetry in financial
trading.
Institutional Investors shown in blue, Individual Investors shown in red.
Economics, Finance and Behaviour
Individual and Institutional Investor Sentiment
Institutional Investors shown in blue,
Individual Investors shown in red.
Confidence that the stock market will
go up in the succeeding year rose fairly
steadily over the years from 1989 to
2004, both for institutional and for
individual investors. At the peak of
One-Year Confidence, as of December
2003, 92.52% of institutional investors
expected the market to go up over the
succeeding year, and as of January 2004
95.62% of individual investors thought
the same. After that, there was a brief
moment of high confidence among
institutional investors in 2006.
Individual investor confidence
bottomed in April 2008, just before the
subprime crisis, and, surprisingly,
improved with as the crisis worsened.
http://icf.som.yale.edu/stock-market-confidence-indices-united-states-yearindex
Economics, Finance and Behaviour
Individual and Institutional Investor Sentiment
Institutional Investors shown in blue,
Individual Investors shown in red.
Confidence that there will be no stock market
crash in the succeeding six months generally
declined (though with a lot of ups and downs)
over the years since 1989 until the stock market
bottomed out in late 2002. Just after the terrorist
attacks of September 11, 2001, Crash Confidence
actually rose a little. But Crash Confidence
reached its lowest point at 20.79% for
institutional investors and 28.95% for individual
investors as of November 2002. Crash confidence
reached its all-time low, both for individual and
institutional investors, in early 2009, just months
after the Lehman crisis, reflecting the turmoil in
the credit markets and the strong depression fears
generated by that event, and is plausibly related
to the very low stock market valutions then. The
recovery of crash confidence starting in 2009
mirrors the strong recovery in the stock market.
http://icf.som.yale.edu/stock-market-confidence-indices-united-states-crashindex
Economics, Finance and Behaviour
Individual and Institutional Investor Sentiment
Institutional Investors shown in blue,
Individual Investors shown in red.
Confidence that there will be no stock market
crash in the succeeding six months generally
declined (though with a lot of ups and downs)
over the years since 1989 until the stock market
bottomed out in late 2002. Just after the terrorist
attacks of September 11, 2001, Crash Confidence
actually rose a little. But Crash Confidence
reached its lowest point at 20.79% for
institutional investors and 28.95% for individual
investors as of November 2002. Crash confidence
reached its all-time low, both for individual and
institutional investors, in early 2009, just months
after the Lehman crisis, reflecting the turmoil in
the credit markets and the strong depression fears
generated by that event, and is plausibly related
to the very low stock market valutions then. The
recovery of crash confidence starting in 2009
mirrors the strong recovery in the stock market.
http://icf.som.yale.edu/stock-market-confidence-indices-united-states-crashindex
Economic Cycles
Complex physical systems exhibit repetitive behaviour or
cycles: Periodic arrangements of atoms in a crystalline
structure leads to robust and elastic materials; a lack of
periodicity is regarded as crystal defect.
We have weather changes – spring in May, snowfall in
December in the Northern Hemisphere- but the ‘early’ onset of
spring/summer/winter, or the more/less than average
rainfall/snowfall, or the more/less frequent floods, is variously
attributed to the disastrous global warming/cooling.
Any deviation from the periodic behaviour is described through
terms of negative affect – defects, disasters, spikes, and crash of
or in the system.
Economic Cycles
Prices and traded volumes of shares, bonds and
commodities, for instance, show a cyclical
behaviour over a period of time–Jugular (1862)
noted a 10 year cycle, then there are 20 year
Kuznet swings and 50 year Kondratieff cycle
(Solumu 1998); and for the chaos theorist
Benoit Mandelbrot there are 5 year cycles. The
unexpected surges and devastating downturns
in prices remain largely unexplained
Economic Cycles
The cyclical behaviour of prices suggests that when an
object is underpriced by its seller, a buyer rush
towards it and competition encourages the seller to
reach the correct price; similarly for an overpriced
object, buyers shy away and the seller is forced to sell
the object at its true value.
Prices move towards an equilibrium value, much like
the physical systems where forces of nature (atomic,
molecular, gravitational and so on) help the systems to
move towards a settled price.
Economic Cycles
It has been argued that there are market forces that
help to realize the optimum prices – and this has lead
to the so-called rational market theories, especially the
efficient market hypothesis which had dominated the
pre-2007/08 credit crunch.
Market forces will discount all irrationality and the
lender-of-last-resort will be there only to discourage
criminal manipulation of prices. However, this
(constructivist) Cartesian world of rationally behaved
trinity of buyers/sellers/regulators also discounted
three well documented observations
Disruption to the economic
cycles
The three well documented observations:
(a) framing –presentation format of a proposition
effects the perception what is being proposed
(Kahnemann 2000);
(b) human herd behaviour in financial markets
(Cipriani and Guarino 2009);
and
(c) areas of human brain dedicated to seeking risk
unnecessarily and avoiding plausible risk (Porcelli and
Delgado 2009).
PS: Mandelbrot has only 3 states of matter and three
states of randomness; I have added the fourth!
Disruption to economic cycles
Four states of matter: solid,
liquid, gases and plasma;
Four kinds of randomness:
mild, slow, wild, furious.
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour
of Markets. London: Profile Books (Paperback edition printed in 2005)
Economics and Finance
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London: Profile Books
(Paperback edition printed in 2005)
Disruption to economic cycles
Stable economic systems are like solids, mean
reversion of returns and minimal volatility. As the
economic systems become more and more unstable
prices change much more rapidly, reversion to mean
is delayed, or indeed disappears altogether and
volatility of returns dramatically.
The ‘liquid’ state shows local failure but globally the
economic system remains stable. In the gaseous
state, large components of the system fail and have to
be repaired and/or replaced.
The plasma state is the state of total meltdown.
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London: Profile Books
(Paperback edition printed in 2005)
Disruption to economic cycles
Stable Economy:
full employment
Local Shocks but
otherwise stable
economy
Major Shocks
and fragile
economy
Economy in total
meltdown
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London: Profile Books
(Paperback edition printed in 2005)
Disruption to economic cycles
Ever since Maynard Keynes suggestion
that there are “animal spirits” in the
market, “economists have devoted
substantial attention to trying to
understand the determinants of wild
movements in stock market prices that
are seemingly unjustified by
fundamentals”
Ontological commitments in BLUE & terminological conventions in RED
Tetlock, Paul C. (2008). Giving Content to Investor Sentiment: The Role of Media in the StockMarket. Journal of Finance.
Paul C. Tetlock , Saar-Tsechansky, Mytal, and Mackskassy, Sofus (2005). More Than Words: Quantifying Language to Measure Firms’
Fundamentals. (http://www.mccombs.utexas.edu/faculty/Paul.Tetlock/papers/TSM_More_Than_Words_09_06.pdf )
Disruption to economic cycles
Market Type
Rational
Market
(‘Traditional’ View)
Exuberant
Market
('Alternative' view)
Why prices change?
Role of sentiment?
The current price of a stock
closely reflects the present
value of its future cash
flows. The correlations in
the returns of two assets
arise from correlations in
the changes in the assets’
fundamental values
Demand shocks or shifts in
investor sentiment plays no
role [in price changes]
because the actions of
arbitrageurs readily offset
such shocks.
The dynamic interplay
between noise traders and
rational arbitrageurs
establishes prices.
The correlated trading
activities of noise traders
may induce co-movements
and arbitrage forces may not
fully absorb these correlated
demand shocks.
Kumar, Alok., and Lee, Charles, M.C. (2007). Retail Investor Sentiment and Return Comovements. Journal
of Finance. Vol 59 (No.5), pp 2451-2486
Randomness of price
variation
Three states of matter: solid, liquid and gases;
Three kinds of randomness: mild, slow, and wild.
Mandelbrot: Conventional finance theory
assumes that the variation of prices can be
modeled by random processes that, in
effect, follow the simplest ‘mild’ pattern, as
if each uptick and downtick were
determined by the toss of a coin
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour
of Markets. London: Profile Books (Paperback edition printed in 2005)
Randomness of price
variation
Three states of matter: solid, liquid and gases;
Three kinds of randomness: mild, slow, and wild.
Mandelbrot: Investigations based on the
fractals of mathematics indicate that
standard, real prices ‘misbehave’ very
badly.
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour
of Markets. London: Profile Books (Paperback edition printed in 2005)
Randomness of price
variation
Three states of matter: solid, liquid and gases;
Three kinds of randomness: mild, slow, and wild.
August 1998 should not have happened: Random
walk theory (mild randomness) suggests that
chances of August 31, 1998 collapse was 1 in 20
million (trade for 100,000 years to encountyer
such an event; odds of THREE such declines in one
month  one in 500 billion. (Mandelbrot and
Hudson 2004:4)
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour
of Markets. London: Profile Books (Paperback edition printed in 2005)
Randomness of price
variation
Three states of matter: solid, liquid and gases;
Three kinds of randomness: mild, slow, and
wild.
In October 198, DJIA fell by 29.2% (1 in 1050)
In August 1997, DJIA fell by 7.7% (1 in 50 billion chances);
STUFF happens?
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour
of Markets. London: Profile Books (Paperback edition printed in 2005)
Randomness of price
variation
Investor sentiment & stock market bubbles
has some causal relationship with:
1961
-tronics mania
1967
franchise and computer ‘crazies’
1983
high tech issues
2001
dot.com
Baker, M., & Wurgler, J. (2003). ‘Investor sentiment and cross-section of stock returns. Proc.
Conf on Investor Sentiment.
Randomness of price
variation
In his book Irrational Exuberance Robert
Shiller (2000) mentions the mass media
as an important factor in the generation
of overreactions: Due to their capacity to
arouse attention the media can create
positive feedback and reinforce existent
trends – and contribute to the
reinforcement of speculative price
movements and financial bubbles.
Flightiness of price change
Benoit Mandelbrot (1963) has argued that the rapid rate of
change in prices (the flightiness in the change) can and should be
studied and not eliminated – ‘large changes [in prices] tend to be
followed by large changes –of either sign- and small changes tend
to be followed by small changes’.
The term volatility clustering is attributed to such clustered
changes in prices.
Mandelbrot’s paper drew upon the behaviour of commodity prices
(cotton, wool and so on), but volatility clustering’ is now used in
for almost the whole range of financial instruments (see Taylor
2007 for an excellent and statistically well-grounded, yet readable,
account of this subject).
Flightiness of price change
There is a realisation that the various stakeholders in financial
markets across the world that we do not understand fully how
prices of financial instruments change with time.
This realisation is more worrying in that many of the regulators
of financial markets have doubts about the ability of the markets
to apply endogenous corrections.
Somehow it appears that stakeholders – investors, traders,
regulators- behave in an irrational manner and their subjective
feelings have (indirect) impact on the markets.
Flightiness of price change
The ability to estimate the changes in prices of an
asset – asset price dynamics to be more precise- is
critical for an estimation of risk associated with that
asset.
The efficient market hypothesis – that gives credence to the selfcorrecting markets hypothesis- is based on a random walk model of the
prices where the changes in prices are assumed to be distributed
according to a normal distribution: 68% of the changes will be within
one standard deviation from the mean value, and 99.5% within three
standard deviation from the mean.
The efficient market hypothesis suggested that price
changes are statistically independent.
Flightiness of price change
Not-so random walk of price changes
Benoit Mandelbrot (2005) notes that ‘the bell curve [normal
distribution] fits reality very poorly. Form 1916 to 2003, the daily
index movements of the Dow Jones Industrial Average do not
spread out on a graph paper like a simple bell curve. […] Theory
[bell curves] suggests that over that time [97 years] there should
be fifty eight days when the Dow moved more than 3.4 percent; in
fact there were 1,001 [such days]. Theory predicts six days of
index swings beyond 4.5 percent; in fact there were 366. And index
swings of more than 7 percent should come once every 300,000
years; in fact twentieth century saw forty eight such days. Truly, a
calamitous era that insists on flaunting all predictions. Or,
perhaps, our assumptions are wrong’ (pp 13)
Mandelbrot, Benoit B., and Hudson, Richard L. (2005), The (Mis)behaviour of
Markets – A Fractal View of risk, Ruin and Reward. London: Profile Books
Flightiness of price change
Not-so random walk of price changes
Normal Distribution
Deviation from the mean Probability Cumulative Value
0
39.89%
50.00%
0.25
38.67%
59.87%
0.5
35.21%
69.15%
1
24.20%
84.13%
1.5
12.95%
93.32%
2
5.40%
97.72%
3
0.44%
99.87%
4
0.01%
100.00%
5
0.00%
100.00%
6
0.00%
100.00%
7
0.00%
100.00%
Flightiness of price change
Movement of daily price changes – actually return of prices
 r=log(pt/pt-1) on three stock exchanges between 1996-2005.
You can see ‘mild’, slow and wild movements
Not-so random walk of price changes
Once Every
Year
Once Every
1,000 Years
Once Every
1,000,000 Years
Price
Changes
Theory
(Days)
Observation
(Days)
3.4%
Once in 1.65 yrs
10.3
4.5%
Once in 16.5 yrs
3.8
7% Once in 300K yrs
Once in 2 yrs
Price
Changes
Theory
(Days)
Observation
(Days)
3.4%
60
1032
4.5%
6
377
7% Once in 300K yrs
49
Price
Changes
Theory
(Days)
Observation
(Days)
3.4%
597938
10319588
4.5%
61856
3773196
7%
3
494845
ot-so random walk of price changes
Prices Change and Traded
Volumes Fluctuate
Prices Change and Traded
Volumes Fluctuate
Financial Times, Saturday 21, March 2009
Main Headline: ‘Banker fury over tax ‘witch hunt’
Back Page: The Week in Numbers:
300 bn
20%
5
Federal Reserve US equities
Norwegian Kr
The [Fed] stunned the
market by […buying]
$300bn of longer-term
Treasury bonds. The yield
on 10-year Treasury bonds
fell 50 basis points
The Norwegian krone
touched a five month
high against the dollar
as investors sought
safer alternatives to the
US currency [Oct
2008:7.2 NKr/$; Mar
2009: ~6.4 NKr/$]
The [S&P 500]
benchmark set an
intraday high of 802.34,
marking a rise of more
than 20% from a 12
year low of 669.2 struck
just nine days earlier
Prices Change and Traded
Volumes Fluctuate
Why do markets (mis)behave?
‘Empirical observation of finance markets has often revealed
that large movements occur more frequently than would be
xpected if returns were normally distributed. For instance, the
1987 equity crash recorded negative returns that were over 20
standard deviations from the mean […] In addition, most return
distributions are also skewed, meaning there is a greater
likelihood of the portfolio yielding either higher or lower returns
than would be expected under normal distributions’ (Lhabitant
2004:47)
Lhabitant, François-Serge. (2004). Hedge Funds: Quantitative Insights.
Chichester: John Wiley & Sons, Ltd.
Prices Change and Traded
Volumes Fluctuate
Why do markets (mis)behave?
The MSCI (Morgan Stanley Capital Investment) World
is a stock market index of 'world' stocks. L’habitant
(2004) has argued that ‘only when we remove some
outliers’ the normality assumption is usually not
rejected. But even when as much as 2% outliers are
excluded, returns on many hedge funds still do not
conform to normal distribution (ibid:48-49)
Lhabitant, François-Serge. (2004). Hedge Funds: Quantitative Insights.
Chichester: John Wiley & Sons, Ltd.
Prices Change and Traded
Volumes Fluctuate
Why do markets (mis)behave?
We can tell that markets misbehave because (a) prices do
correlate and exhibit flightiness – or volatility; and (b) the
underlying distribution of changes – or returns- does not obey
the normal distribution.
But why is there the flightiness and non-normality? Because it is
Nature’s law – Zipf’s Law; Pareto Distribution; Cauchy’s
Distributions, and Mandelbrot’s fractal theory of behaviour. In
all these cases, the largest observed value can and does change
the averages and standard deviations.
Mandelbrot, Benoit B., and Hudson, Richard L. (2005), The (Mis)behaviour of
Markets – A Fractal View of risk, Ruin and Reward. London: Profile Books
Economics and Finance
Dan Nelson (1992) ‘recognized that
volatility could respond asymmetrically
to past forecast errors. In a financial
context, negative returns seemed to be
more important predictors of volatility
than positive returns. Large price
declines forecast greater volatility than
similarly large price increases. This is
an economically interesting effect that
has wide ranging implications’
Economics and Finance
‘Why it is natural for news to be clustered in time, we must be more
specific about the information flow’ (Engle 2003:330)
Volatility Clustering
Type
Clustering Cycle
Slow
Several years
or longer.
Single inventions or unique
events that may benefit firms in
Few days or
minutes
Price Discovery: When agents
High Frequency
Medium Duration Weeks or
Volatility
Months
Information Flow
the longer term
fail to agree on a price and suspect
that other agents have
insights/models better than his or
her. Prices are revised upwards or
downwards quite rapidly.
Clustered events: Many
inventions streaming in; global
summits; governmental inquiries;
Robert F. Engle III (2003). RISK AND VOLATILITY: ECONOMETRIC MODELS AND FINANCIAL
PRACTICE. Nobel Lecture, December 8, 2003
Economics and Finance
Board of Governors of the Federal Reserve
System
The January 2008 Senior Loan Officer
Opinion Survey on Bank Lending Practices
The [..] Survey addressed changes in the
supply of, and demand for, bank loans to
businesses and households over the past
three months. Special questions in the
survey queried banks about changes in
terms on commercial real estate loans
during 2007, expected changes in asset
quality in 2008, and loss-mitigation
strategies on residential mortgage loans. In
addition, the survey included a new set of
recurring questions regarding revolving
home equity lines of credit. This article is
based on responses from fifty-six domestic
banks and twenty-three foreign banking
institutions.
Economics, Finance and
Behaviour
Tighten
Belt
Market
Forces
Economics, Finance and
Behaviour: The recurrent ‘moral hazard’
For many thinkers, language is a communications system used to represent reality without
interfering with the message. For others, contrarily, language shapes the message and
becomes part of the message; language constitutes the message rather merely representing it.
A multi-sensory world
Multisensory Processing
is an emergent property
of the brain that distorts
the neural
representation of reality
to generate adaptive
behaviors.
Economics, Finance and
Behaviour
John R. Nofsinger (2005) Social Mood and Financial Economics. The Journal of
Behavioral Finance Vol. 6, No. 3, 144–160
Economics, Finance and
Behaviour
• ‘The ability to forecast financial market
volatility is important for portfolio selection
and asset management as well for the pricing
of primary and derivative assets’.
• The asymmetric or leverage volatility
models: good news and bad news have
different predictability for future
volatility.
Engle, R. F. and Ng, V. K (1993). Measuring and testing the impact of news on volatility, Journal of
Finance Vol. 48, pp 1749—1777.
Economics and Finance
As time goes by, we get more information
on these future events and re-value the
asset. So at a basic level, financial price
volatility is due to the arrival of new
information. Volatility clustering is simply
clustering of information arrivals. The fact
that this is common to so many assets is
simply a statement that news is typically
clustered in time.
Robert F. Engle III (2003). RISK AND VOLATILITY: ECONOMETRIC MODELS AND FINANCIAL
PRACTICE. Nobel Lecture, December 8, 2003
Economics and Finance
Volatility and Information Arrivals
• ‘The ability to forecast financial market
volatility is important for portfolio selection
and asset management as well for the pricing
of primary and derivative assets’.
• The asymmetric or leverage volatility
models: good news and bad news have
different predictability for future
volatility.
Engle, R. F. and Ng, V. K (1993). Measuring and testing the impact of news on volatility,
Journal of Finance Vol. 48, pp 1749—1777.
Economics and Finance
Griffin concludes that ‘the most likely reason why
the stockholder held on to their ENRON positions
long after the erosion of firm value became
evident is that senior management made several
strong endorsements and recommendations as to
the holding of ENRON common equity.
Management insistence to maintain and even to
increase the size of their positions temporarily
assuaged investor’s fears and protected their ego.’
(2006:127)
Harry F. Griffin. (2006). Did Investor Sentiment Foretell the Fall of ENRON? The Journal of
Behavioral Finance 2006, Vol. 7, No. 3, 126–127
Economics, Finance and
Behaviour
John R. Nofsinger (2005) Social Mood and Financial Economics. The Journal of Behavioral
Finance 2005, Vol. 6, No. 3, 144–160
Economics and Finance
•
A financial economist can analyse quantitative data using a large body
of methods and techniques in statistical time series analysis on
“fundamental data”, related, for example, to fixed assets of an
enterprise, and on “technical data”, for example, share price
movement;
•
The economist can study the behaviour of a financial instrument, for
example individual shares or currencies, or aggregated indices
associated with stock exchanges, by looking at the changes in the value
of the instrument at different time scales – ranging from minutes to
decades;
•
Financial investors/traders are trying to discover the market
sentiment, looking for consensus in expectations, rising prices on
falling volumes, and information/assistance from back-office analysts;
•
The efficient market hypothesis suggests that quirks caused by
sentiments can be rectified by the supposed inherent rationality of the
majority of the players in the market
Economics and Finance
 Firm-level Information Proxies:
•
•
•
•
•
•
•
•
Closed-end fund discount (CEFD);
Turnover ratio (in NYSE for example) (TURN)
Number of Initial Public Offerings (N-IPO);
Average First Day Returns on R-IPO
Equity share S
Dividend Premium
Age of the firm, external finance, ‘size’(log(equity))…….
Each sentiment proxy is likely to include a sentiment component and as
well as idiosyncratic or non-sentiment-related components. Principal
components analysis is typically used to isolate the common component.
 A novel composite index built using Factor Analysis:
•
Sentiment = -0.358CEFDt+0.402TURNt-1+0.414NIPOt
+0.464RIPOt+0.371 St-0.431Pt-1
Baker, M., and Wurgler, J. (2004). "Investor Sentiment and the Cross-Section of Stock Returns,"
NBER Working Papers 10449, Cambridge, Mass National Bureau of Economic Research, Inc.
Economics and Sociology
• Of all the contested boundaries that define the discipline of sociology,
none is more crucial than the divide between sociology and economics
[…] Talcott Parsons, for all [his] synthesizing ambitions, solidified the
divide. “Basically,” […] “Parsons made a pact ... you, economists, study
value; we, the sociologists, will study values.”
• If the financial markets are the core of many high-modern economies,
so at their core is arbitrage: the exploitation of discrepancies in the
prices of identical or similar assets.
• Arbitrage is pivotal to the economic theory of financial markets. It
allows markets to be posited as efficient without all individual investors
having to be assumed to be economically rational.
MacKenzie, Donald. 2000b. “Long-Term Capital Management: a Sociological
Essay.” In (Eds) in Okönomie und Gesellschaft, Herbert Kaltoff, Richard
Rottenburg and Hans-Jürgen Wagener. Marberg: Metropolis. pp 277-287.
Defining Rationality
Method
Systematic study of
archives detailed
observations
Techniques
Mathematical/
Statistical Models
Defining Rationality
Instances
Data
Characteristics
Econometrics Large data
esp. asset
sets of
dynamics
quantitative
variables
Economics and Psychology
Bounded Rationality
Herbert Simon(Nobel Prize in Economics 1978)
Rational Decision Making in Business Organisations:
Mechanisms of Bounded Rationality –failures of knowing all of the
alternatives, uncertainty about relevant exogenous events, and inability to
calculate consequences .
Daniel Kahneman (Nobel Prize in Economics 2002)
Maps of bounded rationality –intuitive judgement & choice:
Two generic modes of cognitive function: an intuitive mode: automatic and
rapid decision making; controlled mode deliberate and slower.
Economics, Finance and
Behaviour
The Journal of Behavioral Finance
2004,Vol. 5,No. 2, 70-74
Economics, Finance and
Behaviour
Rumors and the Financial Marketplace
In the contemporary financial marketplace, the consequences of
speculation and decision making based on unfounded assertions
and false rumors can be especially potent and undeniably
dangerous. With the emergence of the Internet and other new
communication technologies that facilitate the spread of
misinformation, it has become essential for managers, investors,
and other stakeholders to acquire a better understanding of the
forces that give rise to rumors and the most effective strategies
for dealing with them. [….] Although relatively little research
attention has been paid to the particularities of financial rumors,
[…] some key characteristics that appear to distinguish financial
rumors from rumors about other aspects of business operations,
such as greater conciseness, a shorter life cycle, and the potential
for significant economic consequences.
Editorial (2004). The Journal of Behavioral Finance 2004,Vol. 5,No. 3, 134-141
Economics, Finance and
Behaviour
There is a constant stream of news and e-mails in a
dealing room. Some directly from news agencies
(*) and some annotated items based on the news
Hardie, Iain & MacKenzie, Donald. (July 2005). An Economy of Calculation: Agencement and
Distributed Cognition in a Hedge Fund (available from D.MacKenzie@ed.ac.uk)
Economics, Finance and
Behaviour
Floyd Norris, of New York Times and Int. Herald Tribune
Online Editions, writes acerbically on finance and economics,
on a near daily basis. His column attracts bloggers and he
replies occasionally and then the bloggers write even more.
Norris on March 2,
2007, 2:31 pm
Bloggers start on March 2,
2007 at 5.27
My column today warns of the
risks involved in tightening
subprime credit now, as home
prices are falling. In tomorrow’s
Times, I will discuss how home
prices are falling in many regions
………………………..
5.27 pm: I agree that tardy regulators can
often make a bad situation worse. Posted by
Jonsson
6.00 pm: Floyd to Blogger: Mr.Jonsson: No, I
do not think we would be better off without
them.
Economics, Finance and
Behaviour
Date
Blogs
Lead
Sentence
Excerpt
Apr. 4
19
A Search for
Scapegoats
The most amazing diversion now appearing in the
credit crisis is the search for scapegoats. [..]. My
column today criticizes regulators, who [] did
nothing to halt the flurry of highly leveraged
products. […]
Apr. 2
14
Does Wall
Street Trust
Wall Street?
Is it all over? The big rally in stocks this week may be
a sign that traders believe that governments
now stand behind investment banks, as they
do commercial banks:
Apr. 1
19
Nail the
RumorMongers
Have you noticed that financial regulators are all
investigating to see who is spreading rumors
that financial institutions are less than healthy?
Mar 31
107
Market
Plunges, Fed
Acts
Say this for the Fed. It pays attention to what Wall
Street wants. [..] Alan Greenspan fought to keep
regulation away from that market,
Economics, Finance and Behaviour
Financial
News
write
Financial
Reporters
use
restrict
Financial
Language
analyse
communicate
survey
report
describe
Financial
Markets
affect
Financial
Traders
Economics, Finance and Behaviour
Financial
News
Bloggers
Bloggers
write
Financial
Reporters
use
restrict
Financial
Language
analyse
communicate
Financial
Traders
survey
report
describe
Bloggers
affect
Bloggers
Financial
Markets
Economics, Finance and Behaviour
• News Effects
• I: News Announcements Matter, and Quickly;
• II: Announcement Timing Matters
• III: Volatility Adjusts to News Gradually
• IV: Pure Announcement Effects are Present in
Volatility
• V: Announcement Effects are Asymmetric –
Responses Vary with the Sign of the News;
• VI: The effect on traded volume persists longer
than on prices.
Andersen, T. G., Bollerslev, T., Diebold, F X., & Vega, C. (2002). Micro effects of macro announcements: Real time
price discovery in foreign exchange. National Bureau of Economic Research Working Paper 8959,
http://www.nber.org/papers/w8959
Economics, Finance and
Neuroscience
Peterson has argued ‘that investors’ undisciplined
decisions may be biased in a way that furthers the
development of bull and bear markets. When the
stock market is rising and most people are
experiencing paper gains, many feel hypomanic, they
ignore risks, and they overemphasize potential
returns. Consequently, the market risk premium
tends to decline and stocks rise further, generating
more upward movements in the bull market.’
Richard L. Peterson (2007). Affect and Financial Decision-Making: How Neuroscience
Can Inform Market Participants. The Journal of Behavioral Finance 2007, Vol. 8 (no.
2), pp 70–78
Economics, Finance and
Neuroscience
Evidence indicates the
existence of separate brain
systems, linked to affect
[moods, attitudes, and
emotions] processing, that
are responsible for risktaking and risk-avoiding
behaviors in financial
settings. Excessive
activation or suppression
of either system can lead to
errors in investment
choices and trading
behaviors.
Richard L. Peterson (2007). Affect and Financial Decision-Making: How Neuroscience Can Inform
Market Participants. The Journal of Behavioral Finance 2007, Vol. 8 (no. 2), pp 70–78
Economics, Finance and
Behaviour
Proponents of behavioural finance have
posited that (a) optimism and/or
pessimism within groups in a society, or
even a society itself, is ‘reflected by the
emotions of financial decision-makers.’;
and (b) emotions of one participant or
group may effect emotions of the other –
the emotions may correlate (Nofsinger
2005:144). This leads authors like
Nofsinger to make three major claims
John R. Nofsinger (2005) Social Mood and Financial Economics. The Journal of
Behavioral Finance 2005, Vol. 6, No. 3, 144–160
Economics, Finance and
Behaviour
Proponents of behavioural finance, like Nofsinger claim that:
1.
Social mood determines the types of decisions made by consumers,
investors, and corporate managers alike. Extremes in social mood are
characterized by optimistic (pessimistic) aggregate investment and
business activity.
2. Due to the efficient and emotional nature of stock transactions, the stock
market itself is a direct measure or gauge of social mood.
3. Since the tone and character of business activity follows, rather than
leads, social mood, stock market trends help forecast future financial and
economic activity. Specific predictions about stock market levels and
trading volume, market volatility, firm expansion, leverage use, and IPO
and M&A activity are also given.
John R. Nofsinger (2005) Social Mood and Financial Economics. The Journal of
Behavioral Finance 2005, Vol. 6, No. 3, 144–160
Economics, Finance and
Behaviour
A fundamental question for any discipline
that studies financial markets is how we
should theorise actors and action in those
markets. Dominant approaches in financial
economics – and also, for example, in
psychology-based ‘behavioural finance’ –
explicitly or implicitly theorise actors as
equivalent to individual human beings,
whether rational, as orthodoxy posits, or
subject to systematic biases as behavioural
finance suggests.
Iain Hardie and Donald MacKenzie. (2007). Assembling an economic actor: the
agencement of a Hedge Fund. Sociological Review. Vol. 77, pp 55-80.
Economics and Psychology?
‘Economics and psychology offer contrasting
perspectives on the question of how people
value things. The economic model of choice is
concerned with a rational agent whose
preferences obey a tight web of logical rules,
formalized in consumer theory and in models
of decision making under risk’ (Kahneman,
Ritov and Schkade 1999:203)
Kahneman, Daniel., Ilana Ritov and David Schkade. (1999). ‘Economic Preferences or Attitude
Expressions? An Analysis of Dollar Responses to Public Issues’. Journal of Risk and Uncertainty.
Vole 19 (Nos.1-3), pp 203-235; Reprinted in Kahneman and Tversky (Eds.) (2000), pp 642-671.
Economics and Psychology?
‘Economics and psychology offer contrasting
perspectives on the question of how people
value things. [….] The tradition of psychology,
in contrast [to the tradition of economics] is
not congenial that a logic of rational choice can
serve double duty as a model of actual decision
behavior.’ (Kahneman, Ritov and Schkade
1999:203)
Kahneman, Daniel., Ilana Ritov and David Schkade. (1999). ‘Economic Preferences or Attitude
Expressions? An Analysis of Dollar Responses to Public Issues’. Journal of Risk and Uncertainty.
Vole 19 (Nos.1-3), pp 203-235; Reprinted in Kahneman and Tversky (Eds.) (2000), pp 642-671.
Economics and Psychology?
What is important is the ‘power and generality
of psychological principles’ and not the
‘limitations of rational choice theory’.
Phenomena that appears anomalous from the
‘perspective of standard preference models
are, in fact, predictable –indeed, inevitable –
consequences of well-established rules of
judgment and valuation (Kahneman, Ritov
and Schkade 1999:233)
Kahneman, Daniel., Ilana Ritov and David Schkade. (1999). ‘Economic Preferences or Attitude
Expressions? An Analysis of Dollar Responses to Public Issues’. Journal of Risk and Uncertainty.
Vole 19 (Nos.1-3), pp 203-235; Reprinted in Kahneman and Tversky (Eds.) (2000), pp 642-671.
Notes on Prospect Theory
According to conventional financial
theory, the world and its participants
are, for the most part, rational "wealth
maximizers". However, there are
many instances where emotion and
psychology influence our decisions,
causing us to behave in unpredictable
or irrational ways.
http://www.investopedia.com/university/behavioral_finance/default.asp
Notes on Prospect Theory
A method for comparing asset dynamics and ‘affect’ changes (Ahmad 2008a, 2008b)
rt

asset
asset
p
 log( t )
p
t 1
1 n asset asset 2

( rt k  r
)
n  1 k 1

rt

affect
affect
 log(
f
t )
f
t 1
1 n affect affect 2

( rt k  r
)
n  1 k 1

Ahmad K. (2011) The ‘return’ and ‘volatility’ of sentiments: An attempt to quantify the behaviour of the markets? In: Ahmad K. (ed).