On the behaviour of financial markets: Fluctuations and Sentiment Khurshid Ahmad, Chair of Computer...
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On the behaviour of financial markets: Fluctuations and Sentiment Khurshid Ahmad, Chair of Computer Science Trinity College, Dublin, IRELAND 11-13 th November
On the behaviour of financial markets: Fluctuations and
Sentiment Khurshid Ahmad, Chair of Computer Science Trinity
College, Dublin, IRELAND 11-13 th November 2013
Slide 2
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
Slide 3
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
Slide 4
Economics, Finance and Behaviour Individual and Institutional
Investor Sentiment Institutional Investors shown in blue,
Individual Investors shown in red. 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.
Slide 5
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
Slide 6
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
Slide 7
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
Slide 8
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.
Slide 9
Economic Cycles Prices and traded volumes of shares, bonds and
commodities, for instance, show a cyclical behaviour over a period
of timeJugular (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
Slide 10
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.
Slide 11
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
Slide 12
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).
Slide 13
Four states of matter: solid, liquid, gases and plasma; Four
kinds of randomness: mild, slow, wild, furious. Disruption to
economic cycles Mandelbrot, Benoit, B., & Hudson, Richard L.
(2004). The (Mis)Behaviour of Markets. London: Profile Books
(Paperback edition printed in 2005) PS: Mandelbrot has only 3
states of matter and three states of randomness; I have added the
fourth!
Slide 14
Economics and Finance Mandelbrot, Benoit, B., & Hudson,
Richard L. (2004). The (Mis)Behaviour of Markets. London: Profile
Books (Paperback edition printed in 2005)
Slide 15
Disruption to economic cycles Mandelbrot, Benoit, B., &
Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London:
Profile Books (Paperback edition printed in 2005) 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.
Slide 16
Disruption to economic cycles Mandelbrot, Benoit, B., &
Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London:
Profile Books (Paperback edition printed in 2005) Stable Economy:
full employment Local Shocks but otherwise stable economy Major
Shocks and fragile economy Economy in total meltdown
Slide 17
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 Disruption to economic cycles 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
) Ontological commitments in BLUE & terminological conventions
in RED
Slide 18
Disruption to economic cycles Market TypeWhy prices change?Role
of sentiment? Rational Market (Traditional View) 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. Exuberant Market ('Alternative' view) 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
Slide 19
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 Randomness of price variation Mandelbrot, Benoit, B., &
Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London:
Profile Books (Paperback edition printed in 2005)
Slide 20
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. Randomness of price variation Mandelbrot,
Benoit, B., & Hudson, Richard L. (2004). The (Mis)Behaviour of
Markets. London: Profile Books (Paperback edition printed in
2005)
Slide 21
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) Randomness of price variation Mandelbrot, Benoit, B., &
Hudson, Richard L. (2004). The (Mis)Behaviour of Markets. London:
Profile Books (Paperback edition printed in 2005)
Slide 22
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 10 50 ) In August 1997, DJIA fell by 7.7% (1 in 50
billion chances); STUFF happens? Randomness of price variation
Mandelbrot, Benoit, B., & Hudson, Richard L. (2004). The
(Mis)Behaviour of Markets. London: Profile Books (Paperback edition
printed in 2005)
Slide 23
Investor sentiment & stock market bubbles has some causal
relationship with: Baker, M., & Wurgler, J. (2003). Investor
sentiment and cross-section of stock returns. Proc. Conf on
Investor Sentiment. 1961-tronics mania 1967franchise and computer
crazies 1983high tech issues 2001dot.com Randomness of price
variation
Slide 24
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.
Slide 25
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. Mandelbrots 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).
Slide 26
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.
Slide 27
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 self-
correcting 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.
Slide 28
Flightiness of price change 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 Not-so random walk of price changes
Slide 29
Flightiness of price change Not-so random walk of price changes
Normal Distribution Deviation from the meanProbabilityCumulative
Value 039.89%50.00% 0.2538.67%59.87% 0.535.21%69.15% 124.20%84.13%
1.512.95%93.32% 25.40%97.72% 30.44%99.87% 40.01%100.00%
50.00%100.00% 60.00%100.00% 70.00%100.00%
Slide 30
Flightiness of price change Movement of daily price changes
actually return of prices r=log(p t /p t-1 ) on three stock
exchanges between 1996-2005. You can see mild, slow and wild
movements
Slide 31
Prices Change and Traded Volumes Fluctuate Not-so random walk
of price changes Once Every Price Changes Theory (Days) Observation
(Days) Year3.4%Once in 1.65 yrs10.3 4.5%Once in 16.5 yrs3.8 7%Once
in 300K yrsOnce in 2 yrs Once Every Price Changes Theory (Days)
Observation (Days) 1,000 Years3.4%601032 4.5%6377 7%Once in 300K
yrs49 Once Every Price Changes Theory (Days) Observation (Days)
1,000,000 Years3.4%59793810319588 4.5%618563773196 7%3494845 Not-so
random walk of price changes
Slide 32
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 bn20%5 Federal Reserve The
[Fed] stunned the market by [buying] $300bn of longer-term Treasury
bonds. The yield on 10-year Treasury bonds fell 50 basis points US
equities The [S&P 500] benchmark set an intraday high of
802.34, marking a rise of more than 20% from a 12 year low of 669.2
struck just nine days earlier Norwegian Kr The Norwegian krone
touched a five month high against the dollar as investors sought
safer alternatives to the US currency [Oct 2008:7.2 NKr/$; Mar
2009: ~6.4 NKr/$]
Slide 33
Prices Change and Traded Volumes Fluctuate 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,
Franois-Serge. (2004). Hedge Funds: Quantitative Insights.
Chichester: John Wiley & Sons, Ltd. Why do markets
(mis)behave?
Slide 34
Prices Change and Traded Volumes Fluctuate The MSCI (Morgan
Stanley Capital Investment) World is a stock market index of
'world' stocks. Lhabitant (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, Franois-Serge. (2004). Hedge
Funds: Quantitative Insights. Chichester: John Wiley & Sons,
Ltd. Why do markets (mis)behave?
Slide 35
Prices Change and Traded Volumes Fluctuate 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 Natures
law Zipfs Law; Pareto Distribution; Cauchys Distributions, and
Mandelbrots 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 Why do markets (mis)behave?
Slide 36
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
Slide 37
Economics and Finance Volatility Clustering Type Clustering
CycleInformation Flow SlowSeveral years or longer. Single
inventions or unique events that may benefit firms in the longer
term High FrequencyFew days or minutes Price Discovery : When
agents 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. Medium Duration Volatility Weeks or
Months Clustered events : Many inventions streaming in; global
summits; governmental inquiries; Why it is natural for news to be
clustered in time, we must be more specific about the information
flow (Engle 2003:330) Robert F. Engle III (2003). RISK AND
VOLATILITY: ECONOMETRIC MODELS AND FINANCIAL PRACTICE. Nobel
Lecture, December 8, 2003
Slide 38
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.
Slide 39
Economics, Finance and Behaviour Tighten Belt Market
Forces
Slide 40
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.
Slide 41
A multi-sensory world Multisensory Processing is an emergent
property of the brain that distorts the neural representation of
reality to generate adaptive behaviors.
Slide 42
Economics, Finance and Behaviour John R. Nofsinger (2005)
Social Mood and Financial Economics. The Journal of Behavioral
Finance Vol. 6, No. 3, 144160
Slide 43
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
17491777.
Slide 44
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
Slide 45
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 17491777.
Slide 46
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 investors 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, 126127
Slide 47
Economics, Finance and Behaviour John R. Nofsinger (2005)
Social Mood and Financial Economics. The Journal of Behavioral
Finance 2005, Vol. 6, No. 3, 144160
Slide 48
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
Slide 49
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 = -0.358CEFD t +0.402TURN t -1+0.414NIPO t +0.464RIPO t
+0.371 S t -0.431P t-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.
Slide 50
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 Oknomie und
Gesellschaft, Herbert Kaltoff, Richard Rottenburg and Hans-Jrgen
Wagener. Marberg: Metropolis. pp 277-287.
Slide 51
Defining Rationality MethodTechniques Systematic study of
archives detailed observations Mathematical/ Statistical
Models
Slide 52
Defining Rationality InstancesData Characteristics Econometrics
esp. asset dynamics Large data sets of quantitative variables
Slide 53
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.
Slide 54
Economics, Finance and Behaviour The Journal of Behavioral
Finance 2004,Vol. 5,No. 2, 70-74
Slide 55
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
Slide 56
Economics, Finance and Behaviour Hardie, Iain & MacKenzie,
Donald. (July 2005). An Economy of Calculation: Agencement and
Distributed Cognition in a Hedge Fund (available from
[email protected]) 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
Slide 57
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
tomorrows 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.
Slide 58
Economics, Finance and Behaviour DateBlogsLead Sentence Excerpt
Apr. 419 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. 214 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.
119 Nail the Rumor- Mongers Have you noticed that financial
regulators are all investigating to see who is spreading rumors
that financial institutions are less than healthy? Mar 31107 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,
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 Behaviour
Slide 62
Economics, Finance and Neuroscience 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 7078 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.
Slide 63
Economics, Finance and Neuroscience Evidence indicates the
existence of separate brain systems, linked to affect [moods,
attitudes, and emotions] processing, that are responsible for risk-
taking 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 7078
Slide 64
John R. Nofsinger (2005) Social Mood and Financial Economics.
The Journal of Behavioral Finance 2005, Vol. 6, No. 3, 144160
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 Economics,
Finance and Behaviour
Slide 65
John R. Nofsinger (2005) Social Mood and Financial Economics.
The Journal of Behavioral Finance 2005, Vol. 6, No. 3, 144160
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. Economics, Finance and
Behaviour
Slide 66
Iain Hardie and Donald MacKenzie. (2007). Assembling an
economic actor: the agencement of a Hedge Fund. Sociological
Review. Vol. 77, pp 55-80. 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. Economics, Finance and Behaviour
Slide 67
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?
Slide 68
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?
Slide 69
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.
Economics and Psychology?
Slide 70
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. Notes on Prospect Theory
http://www.investopedia.com/university/behavioral_finance/default.asp
Slide 71
Notes on Prospect Theory A method for comparing asset dynamics
and affect changes (Ahmad 2008a, 2008b) Ahmad K. (2011) The return
and volatility of sentiments: An attempt to quantify the behaviour
of the markets? In: Ahmad K. (ed).