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 The 2007-08 Financial Crisis: A Behavioral Finance Approach Isabelle Bajeux-Besnainou April, 5 th , 2012 GWSB, The Geor

 The 2007-08 Financial Crisis: A Behavioral Finance Approach Isabelle Bajeux-Besnainou April, 5 th , 2012 GWSB, The George Washington University.

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 The 2007-08 Financial Crisis: A Behavioral Finance Approach Isabelle Bajeux-Besnainou April, 5 th , 2012 GWSB, The Geor

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  1.  The 2007-08 Financial Crisis:A Behavioral Finance ApproachIsabelle Bajeux-BesnainouApril, 5th, 2012GWSB, The George Washington University

  2. What caused the 2007-2008 Financial Crisis?According to Chairman Bernanke’s presentation, we can identify:Vulnerabilities before the crisis in particular, bad mortgage products and practicesAmplification mechanisms – Large failures

  3. Today, we concentrate on Behavioral Finance Aspects Where Psychology and Finance meet… Reference: “Psychology and the Financial Crisis of 2007-2008,” by Nicholas Barberis.

  4. Pillar of Standard Finance:Assumption of Efficient markets Financial theory is based on the assumption that: “Prices fully reflect all relevant information”

  5. Are markets always efficient?Are investors always rational?In April 1997, Financial Times ran a contest suggested by Richard Thaler: Readers were told to choose a number between 0 and 100. The winning entry would be the integer closest to 2/3 of the average entry.If markets were efficient, what number should everybody pick?

  6. The case against market efficiencyStock prices are too volatileStock market bubbles existInvestor’s mood may drive prices away from their fair value… and so many others…

  7. Today’s questions: How to explain market bubbles? Why financial institutions had such large risky positions? What are the amplification mechanisms? Regulation and behavioral issues.

  8. 1. Market bubblesFirst belief-based theory Example: Suppose a stock is currently traded only by the students in this class. Half of the class believes the price should be $50, the other half believes it should be $30. Short sales are not allowed. What will probably be the “equilibrium” price?

  9. 1. Market bubblesFirst belief-based theory The price will then reflect the views of the Bullish investors only! This is a “rational” explanation of Market bubbles.

  10. 1. Market BubbleSecond belief-based explanation What is the number of countries in Africa as a percentage of all UN countries? • More than 7.5% • Less than 7.5% a or b?

  11. 1. Market BubbleSecond belief-based explanation What is the number of countries in Africa as a percentage of all UN countries?

  12. 1. Market BubbleSecond belief-based explanation The answer is about 24% ANCHORING Mental attachment to a specific number or price

  13. 1. Market BubbleSecond belief-based explanation Another example: Coin flipping contest 6 billion people pay $1 each to join Heads you stay in, tails you are out Play until less than 2 people remain and then share the gains. • After one round, 3 billion are still in • After ten rounds, about 6 million are still in Imagine, flipping 10 heads in a row! People begin to believe they are good at flipping, not lucky. • After 20 rounds, around 6,000 people are left Locals become heroes! But half of these falter in the next round

  14. 1. Market BubbleSecond belief-based explanation Another example: Coin flipping contest • After 25 rounds, 180 flippers remain If the game stopped now, each would receive $33.3 million These people write books about their flipping techniques and strategy • It would probably take 32 rounds to end with a a maximum of two winners The odds of flipping heads 32 times in a row is roughly one in six billion. Is the winner good at flipping? Lucky?

  15. 1. Market BubbleSecond belief-based explanation Anchoring Over-extrapolation House prices keep going up forever? Came from Home buyers, banks, rating agencies.

  16. 1. Market BubbleThird belief-based explanation The DJIA closed 2003 at 10,454. As a price index, it does not include reinvested dividends. If it was redefined to reflect the reinvestment of all dividends since January 1929, when its value was 300, what should its value have been at the end of 2003?Write down your best guess, a low guess and a high guess, so that you are 90% confident that the answer lies between your low and high guesses.

  17. 1. Market BubbleThird belief-based explanation Answer: 251,046 Most people are not well calibrated AND are overconfident. Another example: How good of a driver are you Above average or below average?

  18. 1. Market BubbleThird belief-based explanation Overconfidence. Overestimation of precision of forecasts.

  19. 1. Market BubbleFirst preference-based explanation Consider the following situations:1. Toss a coin. Heads, you win $200, tails, you lose $200. Would you take this gamble?2. You won $1000 earlier and now you face the same coin toss. Would you take the gamble? Did your answer change?

  20. 1. Market BubbleFirst preference-based explanation After experiencing gains Most people are willing to take MORE risks.

  21. 1. Market BubbleSecond preference-based explanation Lottery ticket costs $1 Probability of winning 1/(100 million) If you win, you get $60M Should anybody buy lottery tickets?

  22. 1. Market BubbleSecond preference-based explanation The brain over-weights low probabilities Another example: tech stock bubble in late 90s

  23. 1. Market BubbleThird preference-based explanation Lottery example:You have been selecting the same lottery ticket numbers every week for months. You have not won yet. A friend suggests a different set of numbers. Do you change numbers?

  24. 1. Market BubbleThird preference-based explanation Fear of REGRET- Regret of omission (stick with the old numbers and the new ones win)- Regret of commission (switch to the new numbers and the old ones win)Regret of commission is more painful

  25. 2. Huge Bank exposuresFirst “rational” explanation “Bad Incentives” reason Incentives for traders, executives are to take as much risk as possible. Lack of proper compensation scheme

  26. 2. Huge Bank exposuresSecond “rational” explanation “Bad Models” reason The models are not well designed The quants are accused Too much opacity Too little understanding Ratings of exotic securities

  27. 2. Huge Bank exposuresThird “rational” explanation “Bad Luck” reason Probability of these events happening were so low… It is called a “black swan” event or the impact of the highly improbable, by Nassim Taleb.

  28. 2. Huge Bank exposuresBehavioral explanation COGNITIVE DISSONANCE Advertising campaign http://www.youtube.com/watch?v=JNTZxcKP1dc

  29. 2. Huge Bank exposuresBehavioral explanation Cognitive Dissonance – Definition: Feeling of discomfort that comes from 2 INCONSISTENT thoughts or ideas.

  30. 2. Huge Bank exposuresBehavioral explanation Cognitive Dissonance Most standard example: I like to smoke I know that smoking is bad

  31. 2. Huge Bank exposuresBehavioral explanation Traders or Bankers “knew” that their positions were very very risky. They liked making lots of money. Rating agencies “knew” that their AAA ratings were not appropriate. They also wanted to have a good self-image and be valuable to society. These two thoughts were contradictory

  32. 2. Huge Bank exposuresBehavioral explanation Cognitive Dissonance between Greed and Moral principles. How do people deal with it? Beliefs manipulation Made easier with subprime-linked products because of the complexity of these products.

  33. 3. Amplification mechanismsThe Ellsberg’s paradox Draw a ball from a bag containing 50 Red balls and 50 Black balls Red ball => $1,000 Black ball => $0 How much are you willing to pay to play this game?

  34. 3. Amplification mechanismsThe Ellsberg’s paradox Draw a ball from a bag containing 100 balls. Some are red, others are black but you do not know how many are red or black. The number of red and black balls is random. Red ball => $1,000 Black ball => $0 How much are you willing to pay to play this game?

  35. 3. Amplification mechanismsThe Ellsberg’s paradox Difference between Risk and Uncertainty Risk is quantifiable Uncertainty is not When uncertainty becomes more important on Financial markets, people tend to FREEZE AMBIGUITY AVERSION

  36. 3. Amplification mechanisms Suppose you face a choice between:1.   accepting a sure loss of $7,5002.   taking a chance where there is 75% chance you will lose $10,000 and 25% chance you will lose nothing

  37. 3. Amplification mechanisms Most people choose (2)LOSS AVERSION Becoming more and more important after suffering losses

  38. 4. Regulation and Behavioral issues Regulators are subject to the same behavioral biases but in general are better educated than the general public! Regulators need to be aware of these behavioral biases to understand better how to design efficient regulations.

  39. Conclusion – What did we learn today? Market bubbles Restrictions on short sales Anchoring; Over-extrapolation Overconfidence; over estimation of forecasts The brain over-weights very low probability Fear of regret Bank large exposures Bad incentives; Bad models; Bad luck Cognitive dissonance - Greed Amplification Mechanisms Ellsberg’s paradox; Ambiguity aversion Loss aversion

  40. Conclusion You understood from the four lectures of Chairman Bernanke the importance of the Fed’s decisions on monetary policies for economic stability and for financial crisis situations. Chairman Bernanke can infuse optimism in the markets through announcements. The markets are listening.

  41. Conclusion Chairman Bernanke also said that Financial crises were unavoidable and that we should prepare to probably have more…

  42. Thank you

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