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Consultiva Internacional, Inc. Third Annual Investment Management Conference November 15, 2002
The Human Element… How it affects Individual and Institutional Investing Decisions Javier Rubio, CFA Mario Iturrino
<ul><li>The Human Element  in: </li></ul><ul><ul><li>1) Individual Investors </li></ul></ul><ul><ul><li>2) Institutional I...
1) The Human Element in Individual Investors: <ul><li>The following three elements have a significant effect on individual...
<ul><li>Risk Profiles  ( Loss Aversion )   </li></ul><ul><li>1) You Receive $1000 </li></ul><ul><li>2) Now Choose Between ...
<ul><li>1) You Receive $2000 </li></ul><ul><li>2) Now Choose Between </li></ul><ul><ul><li>a) A sure loss of $500 </li></u...
<ul><li>Loss Aversion     Gamblers’ Results: </li></ul><ul><li>A) 84% Choose the Sure Thing: </li></ul><ul><ul><li>$1000 +...
a) Loss Aversion   Utility Function <ul><li>Paul Samuelson’s wager: </li></ul><ul><ul><li>Coin toss: win $200, lose $100 <...
b) Over-confidence…  <ul><li>“ Some people will have accidents,  </li></ul><ul><li>but not us.” </li></ul><ul><li>90% of D...
b) Over-confidence   “What is the Expected Return of Stocks?” (High expected returns follow high realized returns) Source:...
b) Over-confidence “What is the Expected Return of YOUR Stocks?”   (I will do better than the market) Sept. 1999 Sept. 200...
b) Over-confidence   “Is the market overvalued?” An overvalued market offers higher expected returns…. Source: Gallup Sept...
b) Over-confidence   “Is this a good time to invest?” Yes …but the market is overvalued Sept. 1999 Sept. 2001 49% 27% 72% ...
c) Regret Why didn’t I sell when the NASDAQ was at 5,000?
What do investors want?   <ul><li>Investors are:  </li></ul><ul><li>Rational  </li></ul><ul><li>consider portfolios as a w...
2) The Human Element in Institutional Investors: <ul><li>Overconfidence </li></ul><ul><ul><li>Pattern Recognition </li></u...
a) Over-confidence:   Pattern Recognition
a) Over-confidence:   Pattern Recognition
Touch a button, S or B You win (money or food) if the choice is right. a) Ov er-confidence:   Pattern Recognition   Human ...
0% 20% 40% 60% 80% 100% 1 2 3 4 5 Men Rats Time Touching Button S 4/5 chance of winning 1/5 chance of winning a) Ov er-con...
<ul><li>Overconfidence  Barron’s Annual Roundtable*   </li></ul><ul><li>Wall Street Super-stars </li></ul><ul><li>24 years...
b) Traps in Active Management
b) Other Traps <ul><li>Are We too Greedy? </li></ul><ul><ul><li>Assets Under Management… </li></ul></ul><ul><li>Data Overl...
3) The Human Element in Investment Committees: <ul><li>The Beauty Contest  </li></ul><ul><li>Following the Crowd </li></ul...
a) The Beauty Contest
<ul><li>Match client needs with agent skills </li></ul><ul><li>Agents acting wholly on behalf of principals </li></ul><ul>...
XYZ Company Pension Fund Investment Board (Onlookers?) Beneficiaries c) Agent Risks  Evaluation versus Planning Horizons M...
c) Agent Risks  Myopic Loss Aversion: <ul><li>Evaluation Horizon drives Asset Allocation… </li></ul><ul><ul><li>Not the Pl...
c) Agent Risks &  The “Prudent Man Rule” Gain (loss) Undisclosed Perceptions, Inc. Crispy Cream Diet Centers Harley Safety...
d) Overconfidence vs Random Events 4 in a row   50% 5 in a row    25% 6 in a row   20%   20 Coin Flips Heads or Tails % Ch...
d) Overconfidence  vs Random Events <ul><li>Prescription: </li></ul><ul><li>Result: </li></ul><ul><li>Compare to: </li></u...
d) Overconfidence vs Random Events 1 3 2 4 Where did first quartile managers come from? QUARTILE Where did first quartile ...
d) Overconfidence vs Random Events   The Search for Skill 100 Dart Throwers 100 Unskilled Managers 100 Skilled Managers St...
d) Overconfidence vs Random Events   Excess Returns are Variable  (Alpha = 3%, Std Dev 6%, Info Ratio 0.50) <ul><li>Contin...
Conclusion <ul><li>Human predispositions interfere with sound investment decision at all levels, including: </li></ul><ul>...
Recommendations <ul><li>Be aware of potential pitfalls and traps </li></ul><ul><ul><li>Have a well thought out long-term i...
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Behavioral Finance

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  • To examine risk seeking and risk avoidance, consider the following gamble: First you receive $1000. Next you are asked to choose between a sure gain of $500 and a 50:50 chance to either win $1000 or nothing. Which do you choose?
  • Here is a separate gamble: First you receive $2000. Next you are asked to choose between a sure loss of $500 and a 50:50 chance to either lose nothing or lose $1000. Which do you choose this time?
  • Studies have found that 84% of people choose the “sure thing” in the first gamble, whereas most people (69%) chose the risky option in the second gamble. In fact, the outcome of both the first and the second gamble are the same when the initial amounts received are considered. However, the difference in behavior reflects two human characteristics: 1) People hate loses more than they like gains. They would rather gamble to avoid a loss than to make a profit. 2) People do not frame portfolios as a whole. They consider the amount they have as history and irrelevant in making a risky choice.
  • This risk seeking and risk avoiding behavior leads to the concept of the utility function, a curve which converts financial payoffs into emotional payoffs. Professor Paul Samuelson once offered a colleague a wager on a coin toss: heads win $200, tails lose $100. The colleague’s response was “no” for one toss, but “yes” for a hundred tosses. This is completely logical if we construct a utility function where losses could for 2.5 times as much as gains. In this case, the formula for a wager on one toss is as follows: 1 toss Utility = 50%*1*200 + 50%*2.5*(-100) = -25 On the other hand, the formula for two tosses results in positive utility: 25%*win both+50%*split+25%*lose both = .25*400 + .5*100 + .25*2.5*(-100) = +25
  • Similar optimism applies to our investment portfolios. Gallup surveys done in September 1999, when the market was rising sharply, and in September 2001, after six months of steep declines showed interesting results. The expected return on the market, for example, is strongly related to its recent return, with investors expecting a 13.2% return after a 39.8% gain in the prior twelve months, but only a 6.3% return after a 24.4% year-over-year drop.
  • In both surveys, however, investors were expecting superior returns from their own portfolios than those of the market as a whole.
  • Interestingly, although people expected higher returns from the market in September 1999 than they did a year later, more people felt the market was overvaluesd then too….
  • Yet while more people felt the market was overvalued in September 1999, more people also felt that it was a good time to invest….
  • While in finance theory, investors are rational and seek optimized portfolios which minimize risk and maximize expected returns, in practice, investors keep different portfolios in separate mental accounts, holding both insurance and lottery portfolios. Some money is kept safe for a “rainy day” and some is to “play” with.
  • Pick several times for reward S=stocks, B= bonds men &amp; women just can’t believe it can be that simple, rats get it fast. We’re too clever by half!
  • If we take the trend out of stock prices over time, what remains is like a sin curve. When a stock has risen faster than the market, investors’ interest grows, reaching greatest conviction and even love just as the fundamentals start to deteriorate. On the downside, concern grows. By the time general opinion has passed from panic to hate, there are probably no sellers left.
  • One problem for institutional investors is the failure to recognize diminishing returns to scale. While management fees rise with assets under management, the cost of trading rises inexorably with trade size. As firms get larger, their size can overwhelm their potential for excess returns. Another problem is the challenge of separating actionable information on a stock from the overwhelming flow of data. With newsfeeds, databases and e-mails, investors today are overwhelmed with information but may know less about what to do. As T.S. Elliot wrote: “Where is the knowledge we have lost in information, where is the wisdom we have lost in knowledge…”
  • Manager selection…the hot dot! Card trick demonstrates you can’t discern what is / what is not valuable: Coffee cup routine. Tickets to Super Bowl (value is greater if you’re endowed with it). If you’ve picked a card, it’s more valuable to you. On airplane: read this in pouch..then in practice everyone fights to get out….. Miss Iowa the current (overshadowed by 9/11)
  • For a corporate pension plan, the planning horizon of the beneficiaries extends into their retirement, on the order of 30 years. The ultimate guarantor of their benefits is the company itself, which has a planning horizon extending indefinitely, assuming the company succeeds in its primary objective of staying in business. Administering the pension plan, however, are several levels of agents whose time horizons are shorter. In many corporations, the pension officer is on a career path within the Treasury Department and hopes to move on in three to five years. The same time frame may represent the tenure of members of the investment oversight board, who are further hampered by challenged of getting a large group to agree on strategies which might be upsetting to the most conservative members. Consultants can provide an important stabilizing and educational influence, but sometimes they are only present to offer a convenient target for blame when results are disappointing. Finally, the money managers are reviewed monthly, quarterly and annually under investment guidelines that often require out-performance relative to benchmarks over three to five years. The result of this hierarchy of agents is that the long term planning horizon is subordinated to short term evaluation horizons.
  • Benartzi and Thayler drew 100,000 simulations of returns for stocks, bonds and T-bills from the CRSP tapes and examined the relative utility of holding different asset mixed over different evaluation periods. They found that investors’ utility would be maximized by holding fewer stocks at shorter evaluation periods and more stocks at longer periods, because the higher volatility of stocks is smoothed over a longer time frame. A 50:50 asset mix between stocks and bonds is consistent with an evaluation period of one year. If investors used a longer period, they would choose to hold more stocks. Another way of looking at this result is to say that investors with a one year horizon require that stocks have a risk premium of 6.5%. The authors go on to say: “Someone with a twenty-yeaqr horizon would be indifferent between stocks and bonds if the equity premium were only 1.4%,and the remaining 5.1% differential is potential rents payable to those who are able to resist the temptation to count their money so often. In a sense, 5.1% is the price of excessive vigilance.”
  • People focus on the losses…. Put in RED! People harp on losses, no concept of correlations, portfolio concept, balance of risk &amp; return.. Then they try to take control of manager. This is why talking about individual stocks works with committees. But you don’t really know if mgr is good with limited data (prior slide).
  • Tod Petzel How do we know which are going where? Beauty contest (done well recently)
  • Information ratio = -0.1 after one year, 46 of unskilled managers will outperform, 34 will still outperform after 3 years, 41 after 5 years!
  • Transcript of "Behavioral Finance"

    1. 1. Consultiva Internacional, Inc. Third Annual Investment Management Conference November 15, 2002
    2. 2. The Human Element… How it affects Individual and Institutional Investing Decisions Javier Rubio, CFA Mario Iturrino
    3. 3. <ul><li>The Human Element in: </li></ul><ul><ul><li>1) Individual Investors </li></ul></ul><ul><ul><li>2) Institutional Investors </li></ul></ul><ul><ul><li>3) Investment Committees </li></ul></ul>
    4. 4. 1) The Human Element in Individual Investors: <ul><li>The following three elements have a significant effect on individual decision making process </li></ul><ul><ul><li>Preferences (Risk Profiles) </li></ul></ul><ul><ul><li>Over-confidence </li></ul></ul><ul><ul><li>Regret </li></ul></ul>
    5. 5. <ul><li>Risk Profiles ( Loss Aversion ) </li></ul><ul><li>1) You Receive $1000 </li></ul><ul><li>2) Now Choose Between </li></ul><ul><ul><li>a) A sure gain of $500 </li></ul></ul><ul><ul><li>b) A 50% chance to win $1000 and 50% chance of $0 </li></ul></ul>
    6. 6. <ul><li>1) You Receive $2000 </li></ul><ul><li>2) Now Choose Between </li></ul><ul><ul><li>a) A sure loss of $500 </li></ul></ul><ul><ul><li>b) A 50% chance of no loss and 50% to lose $1000 </li></ul></ul><ul><li>Risk Profiles ( Loss Aversion ) </li></ul>
    7. 7. <ul><li>Loss Aversion Gamblers’ Results: </li></ul><ul><li>A) 84% Choose the Sure Thing: </li></ul><ul><ul><li>$1000 + $500 = $1500, zero variance </li></ul></ul><ul><li>B) 69% Choose to Gamble: </li></ul><ul><ul><li>$2000 less either $0 or $1000 = $2000 or $1000 </li></ul></ul><ul><li>Conclusions: </li></ul><ul><ul><li>People hate losses more than they like gains </li></ul></ul>
    8. 8. a) Loss Aversion Utility Function <ul><li>Paul Samuelson’s wager: </li></ul><ul><ul><li>Coin toss: win $200, lose $100 </li></ul></ul><ul><ul><ul><li>Probability: (.5 x 200) + (.5 x –100) = $50 </li></ul></ul></ul><ul><ul><li>Colleague’s response: “no” </li></ul></ul>Myopic Loss Aversion and the Equity Premium Puzzle, Shlomo Benartzi and Richard Taylor, Quarterly Journal of Economics 1998
    9. 9. b) Over-confidence… <ul><li>“ Some people will have accidents, </li></ul><ul><li>but not us.” </li></ul><ul><li>90% of Drivers in Sweden “Above Average” </li></ul><ul><li>Some people will have stupid kids, “but ours will be gifted.” </li></ul>
    10. 10. b) Over-confidence “What is the Expected Return of Stocks?” (High expected returns follow high realized returns) Source: Gallup Sept. 1999 Sept. 2001 15% 40% 39.8% -24.4% 13.2% 6.3% Expected Return on Market S&P Return during the preceding 12 months
    11. 11. b) Over-confidence “What is the Expected Return of YOUR Stocks?” (I will do better than the market) Sept. 1999 Sept. 2001 14.9% 13.2% 6.3% 7.9% Own portfolio Stock Market Source: Gallup
    12. 12. b) Over-confidence “Is the market overvalued?” An overvalued market offers higher expected returns…. Source: Gallup Sept. 1999 Sept. 2001 50 15% 49 27 13.2% 6.3% Expected Return on Market Overvalued
    13. 13. b) Over-confidence “Is this a good time to invest?” Yes …but the market is overvalued Sept. 1999 Sept. 2001 49% 27% 72% 53% Overvalued Good Time to Invest Source: Gallup
    14. 14. c) Regret Why didn’t I sell when the NASDAQ was at 5,000?
    15. 15. What do investors want? <ul><li>Investors are: </li></ul><ul><li>Rational </li></ul><ul><li>consider portfolios as a whole: </li></ul><ul><li>Standard (mean-variance) Portfolio </li></ul><ul><li>Investors are: </li></ul><ul><li>Emotional </li></ul><ul><li>- risk-averse AND risk-seeking </li></ul><ul><li>portfolios as mental accounts: </li></ul>
    16. 16. 2) The Human Element in Institutional Investors: <ul><li>Overconfidence </li></ul><ul><ul><li>Pattern Recognition </li></ul></ul><ul><li>Following the Crowd </li></ul><ul><li>Style Traps </li></ul>
    17. 17. a) Over-confidence: Pattern Recognition
    18. 18. a) Over-confidence: Pattern Recognition
    19. 19. Touch a button, S or B You win (money or food) if the choice is right. a) Ov er-confidence: Pattern Recognition Human vs Rat Intelligence: S B
    20. 20. 0% 20% 40% 60% 80% 100% 1 2 3 4 5 Men Rats Time Touching Button S 4/5 chance of winning 1/5 chance of winning a) Ov er-confidence: Pattern Recognition Never 4/5 Always Rats Humans B S
    21. 21. <ul><li>Overconfidence Barron’s Annual Roundtable* </li></ul><ul><li>Wall Street Super-stars </li></ul><ul><li>24 years, 1751 recommendations </li></ul><ul><li>1599 buys, 152 sells </li></ul><ul><li>Buys </li></ul><ul><ul><ul><li>+1.9% Before Publication </li></ul></ul></ul><ul><ul><ul><li>0.0% After Publication </li></ul></ul></ul><ul><li>Sells </li></ul><ul><ul><ul><li>– 1.2% Before Publication </li></ul></ul></ul><ul><ul><ul><li>-8.1% After Publication </li></ul></ul></ul>Journal of Finance, Sept 1995, H. Desai and P.C. Jain
    22. 22. b) Traps in Active Management
    23. 23. b) Other Traps <ul><li>Are We too Greedy? </li></ul><ul><ul><li>Assets Under Management… </li></ul></ul><ul><li>Data Overload </li></ul><ul><li>What’s Already in the Price? </li></ul>
    24. 24. 3) The Human Element in Investment Committees: <ul><li>The Beauty Contest </li></ul><ul><li>Following the Crowd </li></ul><ul><li>Agent Risks & The Prudent Man Rule </li></ul><ul><li>Over-confidence vs Random Events </li></ul><ul><ul><li>The Hot Hand </li></ul></ul><ul><ul><li>The Search for Skill </li></ul></ul>
    25. 25. a) The Beauty Contest
    26. 26. <ul><li>Match client needs with agent skills </li></ul><ul><li>Agents acting wholly on behalf of principals </li></ul><ul><li>Avoiding potential for divergent motives </li></ul>c) Agent Risks & The “Prudent Man Rule”
    27. 27. XYZ Company Pension Fund Investment Board (Onlookers?) Beneficiaries c) Agent Risks Evaluation versus Planning Horizons Money Managers Horizon = Forever CFO Pension Staff Horizon = 3-5 Years Horizon = Forever Horizon = 3-5 Years Horizon = 30 Years Consultants (Education…Blame?)
    28. 28. c) Agent Risks Myopic Loss Aversion: <ul><li>Evaluation Horizon drives Asset Allocation… </li></ul><ul><ul><li>Not the Planning Horizon (Portfolio Life) </li></ul></ul><ul><li>Longer Evaluation Horizon… </li></ul><ul><ul><li>More Stocks </li></ul></ul><ul><ul><li>More willingness to assume risk </li></ul></ul>Aspects of Investor Psychology Daniel Kahneman & Mark Riepe, Journal of Portfolio Management, Summer 1998
    29. 29. c) Agent Risks & The “Prudent Man Rule” Gain (loss) Undisclosed Perceptions, Inc. Crispy Cream Diet Centers Harley Safety Equipment Boston Red Sox B Shares New Orleans Health Foods TOTAL 200,000 200,000 200,000 200,000 200,000 1,000,000 300,000 310,000 280,000 120,000 260,000 1,270,000 100,000 110,000 80,000 (80,000) 60,000 270,000 Cost Market
    30. 30. d) Overconfidence vs Random Events 4 in a row 50% 5 in a row 25% 6 in a row 20% 20 Coin Flips Heads or Tails % Chance
    31. 31. d) Overconfidence vs Random Events <ul><li>Prescription: </li></ul><ul><li>Result: </li></ul><ul><li>Compare to: </li></ul><ul><li>On Jan. 1, 1991 select last years top performing newsletter in Hulbert’s Digest. Invest $100,000. Follow advice for 1 year. Repeat process on each Jan. 1 st investing assets at previous year’s end in hottest newsletter of previous year. </li></ul><ul><li>10 years ending December 31, 2000 </li></ul><ul><li>Your money = $70,752 (-3.4%/year) </li></ul><ul><li>S&P 500 = $497,371 (17.4%/year) </li></ul>*Source: Mark Hulbert, New York Times, Sunday, Jan 21, 2001
    32. 32. d) Overconfidence vs Random Events 1 3 2 4 Where did first quartile managers come from? QUARTILE Where did first quartile managers go? Universe consisted of 162 institutional managers in Russell’s Growth, Market-Oriented, and Value universes with 8 years of history ending 1998. Example: Of the 41 managers in the top quartile for years 1991-1994, only 8 remained in the first quartile in years 1995-1998. Source: Frank Russell Company 8 8 11 14 41 8 16 11 6 41 1991-94 1995-98 1991-94 1995-98
    33. 33. d) Overconfidence vs Random Events The Search for Skill 100 Dart Throwers 100 Unskilled Managers 100 Skilled Managers Statistically, how many managers will outperform the market? (Assume skilled and skilled have mirror image +/- IRs) 1 year 5 years 3 years 50 46 54 50 43 57 50 41 59
    34. 34. d) Overconfidence vs Random Events Excess Returns are Variable (Alpha = 3%, Std Dev 6%, Info Ratio 0.50) <ul><li>Continuous Underperformance for: </li></ul><ul><ul><li>3 years: 20 times </li></ul></ul><ul><ul><li>4 years: 8 times </li></ul></ul><ul><ul><li>5 years: 3 times </li></ul></ul><ul><li>Underwater vs Benchmark (DrawDown) for: </li></ul><ul><ul><li>3 years: 66 times </li></ul></ul><ul><ul><li>10 years: 10 times </li></ul></ul><ul><ul><li>23 years: 1 time </li></ul></ul>
    35. 35. Conclusion <ul><li>Human predispositions interfere with sound investment decision at all levels, including: </li></ul><ul><ul><li>Individual decisions </li></ul></ul><ul><ul><li>Institutional investment strategies </li></ul></ul><ul><ul><li>Investment committee decisions </li></ul></ul>
    36. 36. Recommendations <ul><li>Be aware of potential pitfalls and traps </li></ul><ul><ul><li>Have a well thought out long-term investment plan </li></ul></ul><ul><ul><li>Although adjustments are recommended, stick to your plan </li></ul></ul><ul><ul><li>Make rational decisions, avoid emotional interference </li></ul></ul><ul><ul><li>Always make decisions on a portfolio context </li></ul></ul>
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