BOEING's CIO (SCOTT GRIFFIN) INTERVIEW

MOST people think of commercial airplanes when they hear the name Boeing. But the era of a single manufacturer producing an entire airplane has come and gone, and Boeing has changed with the times.
Today, Boeing's capabilities extend beyond commercial airplanes to include integrated military platforms, advanced technology for defense systems, and even electronic enablement of airplanes. In other words, Boeing specializes in wireless connectivity on a grand scale, and technology so advanced as to be almost beyond recognition.

As Boeing's vice president and CIO, Scott Griffin bears responsibility for all I.T. strategy, systems, network operations, architecture, processes, and people.

Boeing is the world's leading aerospace company and the largest manufacturer of commercial jetliners, with capabilities in military aircraft, rotorcraft, missiles, satellites, launch vehicles, and advanced information and communication systems. Its reach extends to customers in 145 countries around the world.

Griffin began his career at Boeing in 1979 and has held a broad range of assignments throughout the company. He became VP and CIO of Commercial Airplanes in October 1997, a position he held until his promotion to Boeing CIO in October 1999. In addition to holding that title, Griffin chairs the company's Information Technology Process Council and is a member of the Boeing Engineering Council.

Born and raised in Fresno, California, Griffin earned an undergraduate degree from Fresno State University and a master's degree in business from the University of Puget Sound.

On the very day Boeing's latest pride and joy -- the Boeing 777-2000LR -- debuted and made a record nonstop flight from Hong Kong to London, Griffin spoke with CIO Today. Exuberant, intelligent, and gregarious, he was delighted to reveal that Boeing's aptitude is for more than just altitude.

CIO Today: What are your top concerns as CIO?

Griffin: Boeing is changing from a manufacturing company to a technology company. Historically, people have thought of Boeing as a manufacturer of aerospace platforms -- aircraft, missiles, spacecraft, and satellites.

But today, more and more of the fabrication of the parts for those products is being done by our partners, and we have become a large-scale systems integrator -- a company focused on integrating and assembling those parts.

Additionally, more and more of our products are services or systems. One example is the U.S. Army's Future Combat System, which will transform how soldiers use communication and information technology in the field to integrate the battlespace. It involves everything from radios to middleware. It's not a traditional manufacturing product, it's a "system of systems."

INTERVIEW OF MICROSOFT's CIO (RON MARKEZICH)

Has the I.T. environment changed from five years ago?

Markezich: Five years ago was kind of the tail-end of the bubble. Money was spent on I.T. just for the sake of spending it -- just not much thought was given to the outcome. After the bubble burst, budgets were slashed just as recklessly. Now we are in the healthiest state I.T. has ever been in. For the first time, I.T. is in a state of balance.

What was promised by the Internet five to seven years ago is finally coming true: the landscape becoming a reality through the low cost of bandwidth, connectivity, and a great deal of innovation. So, I think there is a big change in opportunity and how we think about I.T. overall.

And everything is much more complex than five years ago. The environments were built without a lot of thought around the architecture during the bubble, and now all I.T. departments have to work through that.

Elevating the level of technology to make it more easily searchable and accessible also makes it more complex for a CIO to manage. It used to be you could just lock down the network, but now it is hard to control the network because you want to use it with partners, customers, suppliers, and others. It is a much more complex trend and difficult to manage.

CIO Today: How have new legislative demands affected the I.T. department and the CIO in particular?

Markezich: That is another category of things that have radically changed. I think Sarbanes-Oxley regulation has been great for the industry and for us but it does require a huge time commitment. Even so, I am probably at an advantage because I have the resources to readily comply. It does give us internal controls and great feedback, but the actual scope of the requirement is difficult to nail down.

The biggest challenge is in handling all the different laws in different countries, and even in different regions of the same country. Many of those laws dictate where you can store company data or even employee information. That makes it hard. I.T. loves to standardize, but such a scattering of requirements makes it hard to standardize compliance. Plus, the rules are constantly changing.

At some point, many of us in I.T. would like to see some consistency for managing controls and privacy, like a standards board that sets the bar across industries -- something along the lines of what accounting has in the GAAP, or generally accepted accounting principles.

DESTRUCTIVE CULT

OSHAMA BIN LADEN AS DESTRUCTIVE CULT LEADER

"Destructive cult" is a term used to refer to religions and other groups which have caused harm to their own members or to others. Some researchers define "harm" in this case with a narrow focus, specifically groups which have deliberately physically injured or killed other individuals, while others define the term more broadly and include emotional abuse among the types of harm inflicted. Use of the term has been criticized by some researchers, who assert that it is used to discredit the groups it is applied to, and unfairly compare them with historically more harmful groups and movements. Authors have also compared destructive cults with terrorism, and have used the term to characterize osama bin laden as a destructive cult leader.


Physical harm
"Destructive cult" as applied to physical abuse has generally referred to groups which have, through deliberate action, physically injured or killed members of their own group or other individuals. The ontario consultants on religious tolerence limit use of the term to specifically refer to religious groups that "have caused or are liable to cause loss of life among their membership or the general public."

Emotional harm
Some researchers describe the term "destructive cult" more broadly, and include emotional abuse along with physical abuse as a defining characteristic. Steven Hasan, author of the book Combatting Cult Mind Control, defines the term as such: "A destructive cult is a pyramid-shaped authoritarian regime with a person or group of people that have dictatorial control. It uses deception in recruiting new members (e.g. people are NOT told up front what the group is, what the group actually believes and what will be expected of them if they become members)." Psychologist Michael Langone, executive director of the International Cultic Studies Association, defines a destructive cult as "a highly manipulative group which exploits and sometimes physically and/or psychologically damages members and recruits." In the book Into the Rabbit Hole contributor Randall Waters cites psychiatrist Robert Lifton's Thought Reform and the Psychology of Totalism, specifically Lifton's "Eight Criteria for Thought Reform", as criteria to identify a destructive cult. In Perfected Mind Control - The Unauthorized Black Book of Hypnotic Mind Control author J. K. Ellis also cites Lifton's criteria, writing: "If most of Robert Lifton's eight point model of thought reform is being used in a cult organization, it is most likely a dangerous and destructive cult." In a statement which Congressman Leo J. Ryan later read into the Congressional Record, Dr. John Gordon Clark cited totalitarian systems of governance and an emphasis on money making as characteristics of a destructive cult. Dr. Clark later authored the work Destructive Cult Conversion: Theory, Research and Practice.

In their book Cult and Ritual Abuse, authors Noblitt and Perskin also include the characteristics of "trauma-induced dissociation and programming" in their definition of a destructive cult. In Cults and the Family the authors cite Shapiro, who defines a "destructive cultism" as a sociopathic syndrome, whose distinctive qualities include: "behavioral and personality changes, loss of personal identity, cessation of scholastic activities, estrangement from family, disinterest in society and pronounced mental control and enslavement by cult leaders." In The Ethics of Touch: The Hands-on Practitioner's Guide To Creating a Professional, Safe and Enduring Practice, the authors describe their version of destructive cult characteristics in a section on "Cult Mind Control Abuse." In the book, a destructive cult is seen as being either "religious, political, 'therapeutic' or business" and they state that it can cause trauma-related symptoms such as dissociative disorder. In Dr. Susan Gregg's The Complete Idiot's Guide to Spiritual Healing, she cites three main signs of a destructive cult, including giving up one's individuality, having their relationships with friends and family threatened, and being asked to donate large sums of money to the group. In his work Lethal Violence, the criteria of a destructive cult environment is compared to that of battered woman defence.


Criticism of the term
Some researchers have criticized the usage of the term "destructive cult", writing that it is used to describe groups which are not necessarily harmful in nature to themselves or others. In his book Understanding New Religious Movements, John A. Saliba writes that the term is overgeneralized and equated with the deaths of members of Peoples Temple at Jonestown.Saliba sees this as the "paradigm of a destructive cult," where those that use the term are implying that other new religious movements will have similar outcomes to those of the Peoples Temple at Jonestown. Writing in the book Misunderstanding Cults: Searching for Objectivity in a Controversial Field, contributor Julius H. Rubin complains that the term has been used to discredit certain groups in the court of public opinion.In his work Cults in Context author Lorne L. Dawson writes that though the Unification Church "has not been shown to be violent or volatile," it has been described as a destructive cult by "anticult crusaders."In 2002, the German government was held by Germany's Federal Constitutional Court to have defamed the Osho movement by referring to it, among other things, as a "destructive cult". The court decided that "destructive cult" and other expressions employed by the government to describe the group had no factual basis to justify their use.

Terrorism
In 1984, a group of followers of Osho (then known as Bhagwan Shree Rajneesh) carried out what has come to be known as the first bioterrorism attack in the United States. Over seven hundred and fifty individuals became ill from salmonella poisoning, after the group had deliberately contaminated the salad bars of ten restaurants. After epidemiological research, law enforcement isolated the source of the contamination as a clinical laboratory operated by members of the Rajneesh movement.They had intended to influence voter turnout in an upcoming election.The March 1995 sarin gas attack on the Tokyo subway by the Aum Shinrikyo movement, as well as their prior experiments with anthrax, were also seen as bioterrorism events.

Since the September 11, 2001 attacks and the prevalence of the War on Terrorism in society, researchers have begun to use the term "destructive cult" to compare and contrast certain characteristics of terrorist organizations with those of other religious groups previously characterized as such. In the book Jihad and Sacred Vengeance: Psychological Undercurrents of History, psychiatrist Peter A. Olsson compares Osama bin Laden to other religious leaders including Jim Jones, David Koresh, Shoko Asahara, Marshall Applewhite, Luc Jouret and Joseph Di Mambro, in a section of the book called: "The Psychology of Destructive Cult Leaders".Olsson asserts that each of these individuals fit at least eight of the nine criteria for Narcissistic Personality Disorder. Olsson goes into some of these issues in more depth in his work Malignant Pied Pipers of Our Time: A Psychological Study of Destructive Cult Leaders from Rev. Jim Jones to Osama bin Laden. In the book Seeking the Compassionate Life: The Moral Crisis for Psychotherapy and Society authors Goldberg and Crespo also refer to Osama bin Laden as a "destructive cult leader."

At a 2002 meeting of the American Psychological Association (APA), Steven Hassan asserted that Al Qaeda fulfills the characteristics of a destructive cult. Panelists at the convention asked the APA to investigate mind control among destructive cults.Hassan spoke of the commonalities between researching destructive cults, and the war on terrorism: "We need to apply what we know about destructive mind-control cults, and this should be a priority with the war on terrorism. We need to understand the psychological aspects of how people are recruited and indoctrinated so we can slow down recruitment. We need to help counsel former cult members and possibly use some of them in the war against terrorism."

In an article on Al Qaeda published in The Times, Mary Ann Sieghart wrote that al-Qaeda resembles a "classic cult", commenting: "Al-Qaeda fits all the official definitions of a cult. It indoctrinates its members; it forms a closed, totalitarian society; it has a self-appointed, messianic and charismatic leader; and it believes that the ends justify the means."A similar comparison was made by former UK Home Secretary Charles Clarke, as well as UK Home Secretary John Reid, who stated that "..fanatics are looking to groom and brainwash children, including your children, for suicide bombings, grooming them to kill themselves in order to murder others."

Although not specifically mentioning al Qaeda, former Mujaheddin member and now author and academic Dr. Masoud Banisadr stated in a May 2005 speech in Spain :

If you ask me: are all cults a terrorist organisation? My answer is no as there are many peaceful cults at present around the world and in the history of mankind. But if you ask me are all terrorist organisations, some sort of cult? my answer is yes. Even if they start as ordinary modern political party or organisation, to prepare and force their members to act without asking any moral question and act selflessly for the cause of the group and ignore all the ethical, cultural, moral or religious code of the society and humanity, those organisations have to change into a cult. Therefore to understand an extremist or a terrorist organisation one has to learn about a Cult.

ON DIWALI AND DHANTERAS

MAY YOU BE BLESSED WITH SUCCESS,PROSPERITY,HAPPINESS AND WEALTH AS YOU JOURNEY TOWARDS GREATER SUCCESS !!!

!! SHUBH DIWALI AND DHANTERAS !!

BUSINESS ANALYTICS ??

It has been suggested that Analytics be merged into this article or section.

Business analytics is how organizations gather and interpret data in order to make better business decisions and to optimize business processes. Analytical activities are expanding fast in businesses, government agencies and not-for-profit organizations.

Analytics are defined as the extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based decision-making.
Analytics may be used as input for human decisions; however, in business there are also examples of fully automated decisions that require minimal human intervention. In businesses, analytics (alongside data access and reporting) represents a subset of business intelligence.

The Age of Analytics may be thought of as a new subcategory of the Information Age,with the key difference that the early years of the Information Age were a time when information was a scarce resource, whereas today there is an abundance of information. The Age of Analytics therefore represents another way to think of the activities necessary for success in a knowledge economy or increasingly typical of a modern information society.
Contents

Application of analytics

Many organizations already use analytics in some form. Operating metrics and performance gauges such as the balanced scorecard are familiar to most managers. For instance, a manufacturer may track, interpret and use data to improve how it manages product quality, and a marketing group might base decisions on the long-term analysis of different customer segments. Businesses as diverse as global cement giant CEMEX, California winemaker E & J Gallo Winery, industrial equipment maker John Deere, retailer Tesco, and Bank of America are regularly applying analytics to achieve advantage. For example, Gallo, operating in a business built on using intuition to gauge unpredictable consumer preferences, now quantitatively analyzes and predicts the appeal of its wines. Between 2002 and 2005, John Deere saved more than $1 billion by employing a new analytical tool to better optimize inventory.
However, only a handful of companies are using analytics as a foundation for their business strategies. Capital One is among those full-fledged analytical competitors. The financial services provider is very open about its use of data analysis to differentiate among customers based on credit risk, usage and other characteristics, and to match customer characteristics with appropriate product offerings. Harrah’s, the world’s largest gaming firm, is another aggressive analytical competitor, particularly in the area of customer loyalty.
Research by global management consultancy Accenture found that high-performance businesses — those that substantially outperform competitors over the long term and across economic, industry and leadership cycles — are twice as likely to use analytics strategically compared with the overall sample, and five times more likely to do so than low performers.
Common to all those aspiring to that level of competitiveness is the need to focus on developing four fundamental assets:
Committed senior executives: Taking a broad analytical approach to business calls for big changes in culture, process, behavior and skills for many employees. Such changes must be spearheaded by senior executives who are passionate about analytics and fact-based decision-making.
A strong base of skills in use of data: It is very important to have a broad base of employees who are data-savvy — or who can quickly become data-savvy. This calls for hiring, training and rewarding for analytical skills, especially at management levels. It also highlights the need to understand where those skills matter most and where they will matter most in the future.
Fact-driven business processes: Analytical competitors begin with “a single version of the truth” — not the conflicting views of the same metrics that stymie other companies. What’s needed is an integrated, cross-enterprise view of the data — a state that may require business process redesign on a broad scale.
Technology to capture, sort, and make sense of the data: The processing power to support an analytics thrust is readily available. There is wider use of dedicated “business intelligence appliances” — supercomputer — like machines that can quickly find and sort data in large databases and analyses. Much of the necessary analytical software is also available. “Real-time BI,” in which automated decisions are embedded in operational business processes, is gaining ground.

Example

Netflix, the movie rental company, relies on analytics to drive its growth. At the heart of its business is a movie-recommendation “engine” based on proprietary software. Cinematch, as the tool is called, analyzes customers’ choices and feedback on the movies they have rented — more than a billion ratings of movies they have liked, loved, or hated — and then recommends movies in ways that optimize both the customer’s taste and Netflix’s inventory.
Analytics also help Netflix decide what to pay for the distribution rights to DVDs, essentially giving the company a powerful information advantage during negotiations. For example, when Netflix bought rights to Favela Rising, a documentary about Rio de Janeiro musicians, company executives knew that a million customers had rented 2003’s City of God, also set in Rio. About half a million had rented the Oscar-winning documentary Born Into Brothels, and 250,000 had seen both. So Netflix paid a fee based on 250,000 rentals. If it rents more than that number of copies of Favela Rising, the film’s producers and Netflix split the upside.

History

Data analysis has been used in business since the dawn of the industrial era — from the time management exercises initiated by Frederick Winslow Taylor in the late 19th century to the measured pacing of the mechanized assembly lines developed by Henry Ford. But it began to command more attention in the late 1960s when computers were used in experiments to aid decision-making. These earliest “decision support systems” addressed repetitive and non-strategic activities such as financial reporting. (One notable exception was at American Airlines, which depended on Sabre, its breakthrough yield management system, to beat its competitors.) Analysis of statistics became more routine in the 1970s with the arrival of packaged computer applications. But few executives embraced the strategic use of data; number-crunching was left largely to the statisticians.
Since then, analytics have evolved with the development of enterprise resource planning (ERP) systems, data warehouses, and a wide variety of other hardware and software tools and applications. But until recently, companies have focused on analyzing historical data rather than developing predictive analytics for decision-making.
Many companies today are collecting and storing a mind-boggling quantity of data. In just a few years, the common terminology for data volumes has grown from megabytes to gigabytes to terabytes (TB) — a trillion bytes. Some corporate databases are even approaching one petabyte — a quadrillion bytes — in size. The 583 TB in Wal-Mart’s data warehouse, for example, is far more than the digital capacity needed if all 17 million of the books in the U.S. Library of Congress were fully formatted. Gargantuan storage facilities are not the only technological frontier: statistical software, high-end 64-bit processors, and specialty “data appliances” can quickly churn through enormous amounts of data—and do so with greater sophistication.

Awareness of analytics

Executives are increasingly aware of the power of information technology to help make better decisions. More than 30 percent of senior managers polled in a 2006 study by Accenture said they use their enterprise systems for “significant decision support or analytical capability”; four years earlier, only 19 percent agreed with that statement.
There is also growing sensitivity among executives to the relevance and utility of business intelligence. A 2007 Gartner survey of chief information officers found that BI is the top technology priority for IT organizations for the second year in a row. Only 36 percent of CIOs surveyed by Gartner believe that management is using the right information to run the business.
Gartner has identified four strategies that CIOs should pursue: technical excellence; enterprise agility; information effectiveness; and innovation. The third strategy involves using analytics and applying information to how business decisions are made, rather than how information is moved around a company’s computer systems.
In most cases, the top performers have already mastered those strategies. As they develop their analytical capabilities further, they are increasingly migrating toward more powerful techniques such as predictive modeling, forecasting and optimization

Challenges of analytics

Analytics is dependent on data. If there is no data, there can be no analytics. However, if data is sparse or non-existent, an organization can conduct surveys or a census to obtain data. In many cases to save expenses, organizations can look for data obtained from situations that are similar but not quite meet the current requirements, and make minor modifications (i.e.,a company trying to introduce an energy drink for the first time in a town can use existing data from a survey of athletes that drink carbonated beverages). However, in these cases, businesses should be aware of the risks inherent in using data obtained in such manner.
For many organizations aspiring to be analytical competitors, the primary problem is not that they lack data. It is that they must contend with dirty data. The challenge is that they do not know which data is trustworthy — “clean” — and which contains duplicates, outdated records and erroneous data entries.
According to Gartner, an alarming proportion of all business data is inaccurate. The research firm estimates that at least 25 percent of critical data within Fortune 1,000 companies will continue to be inaccurate through 2007. In a separate study by a leading accounting firm, only a little more than a third of executives were “very confident” in the quality of their corporate data.
A company that finds it has poor-quality data should postpone any plans to compete on analytics and instead should fix its data first. UPS demonstrates the patience that is often necessary. Although the delivery company has been collecting customer information for more than five years, it took more than half that time to validate that data before it was usable.
Unlike mature economies, in some of the fastest growing developing economies, such as India and China, analytics has to contend with "noisy" data wherein the data is incomplete (e.g. credit rating of a customer) or suspect (e.g. demographic information of a mobile telecom customer) or plain missing. A new generation of analytical algorithms that compensates for this "noise" appropriately helps in deployment of analytics solutions without the need to rely on fixing data - something that may never be possible in the near future. Such innovative algorithms are an example of technology innovations in developing markets that promise to leapfrog existing methods that have been developed primarily for mature markets and not easily transposable given constraints such as data sanctity

Companies Providing Analytics Services

Providers of Analytics services are focused on extracting information by looking at the data in many different ways. Companies pay extra attention to results when they are supported by data. Data Analysis answers the "What happened?" but not the "Why did it happen" question. "What" question is answered by the experts within the industry who understand the data side as well the Business and Customer side. "Why" question is answered by talking to the customer.

BEHAVIORAL ECONOMICS AND FINANCE !!! ???

Behavioral economics and behavioral finance are closely related fields which apply scientific research on human and social, cognitive and emotional factors to better understand economic decisions and how they affect market prices, returns and the allocation of resources. The fields are primarily concerned with the bounds of rationality (selfishness, self-control) of economic agents. Behavioral models typically integrate insights from psychology with neo-classical economic theory.
Academics are divided between considering Behavioral Finance as supporting some tools of technical analysis by explaining market trends, and considering some aspects of technical analysis as behavioral biases (representativeness heuristic, self fulfilling prophecy).[1]
Behavioral analysts are mostly concerned with the effects of market decisions, but also those of public choice, another source of economic decisions with some similar biases.
Contents

History

During the classical period, economics had a close link with psychology. For example, Adam Smith wrote The Theory of Moral Sentiments, an important text describing psychological principles of individual behavior; and Jeremy Bentham wrote extensively on the psychological underpinnings of utility. Economists began to distance themselves from psychology during the development of neo-classical economics as they sought to reshape the discipline as a natural science, with explanations of economic behavior deduced from assumptions about the nature of economic agents. The concept of homo economicus was developed, and the psychology of this entity was fundamentally rational. Nevertheless, psychological explanations continued to inform the analysis of many important figures in the development of neo-classical economics such as Francis Edgeworth, Vilfredo Pareto, Irving Fisher and John Maynard Keynes.
Although psychology had nearly disappeared from economic discussions by the mid 20th century, it somehow managed to stage a resurgence, and certain factors were responsible for this resurgence in the continued development of behavioral economics. Expected utility and discounted utility models began to gain wide acceptance, generating testable hypotheses about decision making under uncertainty and intertemporal consumption respectively. Soon a number of observed and repeatable anomalies challenged those hypotheses. Furthermore, during the 1960s cognitive psychology had begun to shed more light on the brain as an information processing device (in contrast to behaviorist models). Psychologists in this field such as Ward Edwards,[2] Amos Tversky and Daniel Kahneman began to compare their cognitive models of decision making under risk and uncertainty to economic models of rational behavior. In Mathematical psychology, there is a longstanding interest in the transitivity of preference and what kind of measurement scale utility constitutes (Luce, 2000).[3]
An important paper in the development of the behavioral finance and economics fields was written by Kahneman and Tversky in 1979. This paper, 'Prospect theory: An Analysis of Decision Under Risk', used cognitive psychological techniques to explain a number of documented divergences of economic decision making from neo-classical theory. Over time many other psychological effects have been incorporated into behavioral finance, such as overconfidence and the effects of limited attention. Further milestones in the development of the field include a well attended and diverse conference at the University of Chicago,[4] a special 1997 edition of the Quarterly Journal of Economics ('In Memory of Amos Tversky') devoted to the topic of behavioral economics and the award of the Nobel prize to Daniel Kahneman in 2002 "for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty".[5]
Prospect theory is an example of generalized expected utility theory. Although not commonly included in discussions of the field of behavioral economics, generalized expected utility theory is similarly motivated by concerns about the descriptive inaccuracy of expected utility theory.
Behavioral economics has also been applied to problems of intertemporal choice. The most prominent idea is that of hyperbolic discounting, proposed by George Ainslie (1975), in which a high rate of discount is used between the present and the near future, and a lower rate between the near future and the far future. This pattern of discounting is dynamically inconsistent (or time-inconsistent), and therefore inconsistent with some models of rational choice, since the rate of discount between time t and t+1 will be low at time t-1, when t is the near future, but high at time t when t is the present and time t+1 the near future. As part of the discussion of hypberbolic discounting, has been animal and human work on Melioration theory and Matching Law of Richard Herrnstein. They suggest that behavior is not based on expected utility rather it is based on previous reinforcement experience.

Methodology

At the outset behavioral economics and finance theories had been developed almost exclusively from experimental observations and survey responses, although in more recent times real world data have taken a more prominent position. Functional magnetic resonance imaging fMRI has complemented this effort through its use in determining which areas of the brain are active during various steps of economic decision making. Experiments simulating market situations such as stock market trading and auctions are seen as particularly useful as they can be used to isolate the effect of a particular bias upon behavior; observed market behavior can typically be explained in a number of ways, carefully designed experiments can help narrow the range of plausible explanations. Experiments are designed to be incentive-compatible, with binding transactions involving real money being the "norm".

Key observations

There are three main themes in behavioral finance and economics:[6]
Heuristics: People often make decisions based on approximate rules of thumb, not strictly rational analysis. See also cognitive biases and bounded rationality.
Framing: The way a problem or decision is presented to the decision maker will affect his action.
Market inefficiencies: There are explanations for observed market outcomes that are contrary to rational expectations and market efficiency. These include mis-pricings, non-rational decision making, and return anomalies. Richard Thaler, in particular, has described specific market anomalies from a behavioral perspective.
Recently, Barberis, Shleifer, and Vishny (1998),[7] as well as Daniel, Hirshleifer, and Subrahmanyam (1998)[citation needed] have built models based on extrapolation (seeing patterns in random sequences) and overconfidence to explain security market over- and underreactions, though such models have not been used in the money management industry. These models assume that errors or biases are correlated across agents so that they do not cancel out in aggregate. This would be the case if a large fraction of agents look at the same signal (such as the advice of an analyst) or have a common bias.
More generally, cognitive biases may also have strong anomalous effects in the aggregate if there is a social contamination with a strong emotional content (collective greed or fear), leading to more widespread phenomena such as herding and groupthink. Behavioral finance and economics rests as much on social psychology within large groups as on individual psychology. However, some behavioral models explicitly demonstrate that a small but significant anomalous group can also have market-wide effects (eg. Fehr and Schmidt, 1999).[citation needed]

Behavioral finance topics

Some central issues in behavioral finance include "Why investors and managers (lenders and borrowers as well) make systematic errors". It shows how those errors affect prices and returns (creating market inefficiencies). It also shows what managers of firms, other institutions and financial players might do to take advantage of market inefficiencies (arbitrage behavior).
Behavioral finance highlights certain inefficiencies and among these inefficiencies are underreactions or overreactions to information, as causes of market trends and in extreme cases of bubbles and crashes). Such misreactions have been attributed to limited investor attention, overconfidence / overoptimism, and mimicry (herding instinct) and noise trading.
Other key observations made in behavioral finance literature include the lack of symmetry (disymmetry) between decisions to acquire or keep resources, called colloquially the "bird in the bush" paradox, and the strong loss aversion or regret attached to any decision where some emotionally valued resources (e.g. a home) might be totally lost. Loss aversion appears to manifest itself in investor behavior as an unwillingness to sell shares or other equity, if doing so would force the trader to realise a nominal loss (Genesove & Mayer, 2001). It may also help explain why housing market prices do not adjust downwards to market clearing levels during periods of low demand.
Benartzi and Thaler (1995), applying a version of prospect theory, claim to have solved the equity premium puzzle, something conventional finance models have been unable to do so far.
Some current researchers in experimental finance use the experimental method, e.g. creating an artificial market by some kind of simulation software to study people's decision-making process and behavior in financial markets.

Behavioral finance models

Some financial models used in money management and asset valuation use behavioral finance parameters, for example:
Thaler's model of price reactions to information, with three phases, underreaction-adjustment-overreaction, creating a price trend
One characteristic of overreaction is that the average return of asset prices following a series of announcements of good news is lower than the average return following a series of bad announcements. In other words, overreaction occurs if the market reacts too strongly or for too long (persistent trend) to news that it subsequently needs to be compensated in the opposite direction. As a result, assets that were winners in the past should not be seen as an indication to invest in as their risk adjusted returns in the future are relatively low compared to stocks that were defined as losers in the past.
The stock image coefficient
[edit]Criticisms of behavioral finance
Critics of behavioral finance, such as Eugene Fama, typically support the efficient market theory (though Fama may have reversed his position in recent years). They contend that behavioral finance is more a collection of anomalies than a true branch of finance and that these anomalies will eventually be priced out of the market or explained by appealing to market microstructure arguments. However, a distinction should be noted between individual biases and social biases; the former can be averaged out by the market, while the other can create feedback loops that drive the market further and further from the equilibrium of the "fair price".
A specific example of this criticism is found in some attempted explanations of the equity premium puzzle. It is argued that the puzzle simply arises due to entry barriers (both practical and psychological) which have traditionally impeded entry by individuals into the stock market, and that returns between stocks and bonds should stabilize as electronic resources open up the stock market to a greater number of traders (See Freeman, 2004 for a review). In reply, others contend that most personal investment funds are managed through superannuation funds, so the effect of these putative barriers to entry would be minimal. In addition, professional investors and fund managers seem to hold more bonds than one would expect given return differentials.

Quantitative behavioral finance

Quantitative behavioral finance is a new discipline that uses mathematical and statistical methodology to understand behavioral biases in conjunction with valuation. Some of this endeavor has been lead by Gunduz Caginalp (Professor of Mathematics and Editor of Journal of Behavioral Finance during 2001-2004) and collaborators including Vernon Smith (2002 Nobel Laureate in Economics), David Porter, Don Balenovich,[8] Vladimira Ilieva, Ahmet Duran,[9] Huseyin Merdan). Studies by Jeff Madura,[10] Ray Sturm[11] and others have demonstrated significant behavioral effects in stocks and exchange traded funds.
The research can be grouped into the following areas:
Empirical studies that demonstrate significant deviations from classical theories
Modeling using the concepts of behavioral effects together with the non-classical assumption of the finiteness of assets
Forecasting based on these methods
Studies of experimental asset markets and use of models to forecast experiment

Behavioral economics topics

Models in behavioral economics are typically addressed to a particular observed market anomaly and modify standard neo-classical models by describing decision makers as using heuristics and being affected by framing effects. In general, economics sits within the neoclassical framework, though the standard assumption of rational behaviour is often challenged.