1. Practical Lessons from 20 Years of Bubble Experiments

2. Overview of the Experimental Environment The basic experimental set-up has the following features 15 period asset Dividend uncertainty Initial cash and shares Double Auction or Call market trading mechanism Trader experience

3. The Basic Result The graph charts the average contract price each period for the same cohort of subjects that participated in three sessions (inexperienced, once-experienced and twice-experienced) of an asset market. The trade volume each period is given by the number next to the contract price symbol. Dividends of 0, 8, 28, 60 cents are equally likely. Hence expected one period dividend is 24, and share value is 15 x 24 = 360 in period 1 and declines by 24 cents each period thereafter.

4. What Might be Causing This? The subject pool is not representative

5. Short Selling is Required Shorts had to be covered before period 15

6. Insiders Will Take Hold Experienced traders – grad students

7. Expectations Need to Unravel Future on the 8 period spot

8. “Circuitbreakers” will help Limit price change rule imposed

9. Understanding Expectations Formation What generates the bubbles? Home grown expectations Forecasting abilities Forecasts lag behind significant changes in the trend Forecasts miss turning points Prices converge faster than forecasts Past market experience has a strong effect on forecasts

10. Momentum Trading Trade is influenced by price changes. Positive changes brings in more buy orders and pushes prices up This continues until the momentum traders become cash constrained and then fundamentals push prices down Momentum traders then sell-off causing the violent crash

11. Implications from Momentum At the initial throws of price increase, the further price is from fundamentals the larger the bubble will be Cash to Asset Value is crucial to the bubble size and path The higher the cash infusion the bigger the bubble

12. Cash is King

13. Momentum Model Results Momentum model underestimates price in early periods and overestimates price in later periods

14. Momentum vs Fundamental Traders

15. Leopard that Changes Spots

16. Who Forecasts Better? ARIMA Random Walk Random Walk and Pure Momentum combined Momentum Recalculate F 1 and F 2 based on past and current data Excess Bids Bids minus Asks Model Humans

17. Predictors Battle Royal For one-period ahead predictions Excess Bids wins, followed by humans. Momentum and ARIMA (1,1,1) are similar in 1- period accuracy For two-period ahead predictions momentum model is the most accurate All other models fail in longer horizon prediction

18. Is Experience Enough?

19. What Might Cause a Bubble to Rekindle? Great stock market booms as driven by waves of new technology such environments introduce new sources of unpredictable yield uncertainty parallel with this development we see much new liquidity attracted into equity investment Can structural changes in the environment reignite what was a converging market

20. Baseline vs Rekindle Environments Dividends {0,8,28,60} Initial Portfolios Average Portfolio is 4 shares and 720 cents in cash Twice Experienced Same cohort Dividends {0,1,8,28,98} Initial Portfolios Average Portfolio is 2 shares and 1530 cents in cash Twice Experienced Mixed traders

21. The graph charts the difference between fundamental value and the market price each period of the twice-experienced subjects in the replication and rekindle experiments

22. Do Speculative Stocks Influence Value Stock Behavior? An overreaction in the speculative stock tends to divert investment capital away from value stocks Trading prices of value stocks are generally lower and more volatile when one of the assets is a speculative stock. In addition, the temporal minimum price of the value stock during the last phase of the experiment is lower in the presence of the speculative stock (when the trading price of the speculative asset is declining sharply). suggesting that the psychological impact of rapidly falling prices in the speculative asset lead to more conservative bidding and aggressive selling of the value asset, even though the latter does not suffer negative earnings updates during this period (affect heuristic).

23. Overreaction and Information Groups with disparate beliefs about the fundamentals of a stock Each group has information that the asset will be worth either 10 or 100  Group 1 has information that leads to a 25% chance of 10 and a 75% chance that it is 100  Group 1 has information that leads to a 75% chance of 10 and a 25% chance that it is 100 Trading continues with this information for 10 minutes New information is revealed to one for the gropus that aligns with the other group  For example, Group 1 is told there is new information that determines that there is a 75% chance of 10 and a 25% chance that it is 100

24. Overreaction and Information

25. Traders underreact to the updated valuation Price and valuation history have a significant effect on trader behavior  Traders tend to “anchor” their price expectations to the pre-existing prices and/or valuations News causes an immediate increased variance Trend is not effected

26. Irrationality? Capital gains expectations are not the base cause Irrationality via probability judgment errors (low-probability high-payoff outcomes) induces more bubbles Speculation multi-period versus single period markets. The combination of probability judgment error and speculation increases the probability that bubbles will occur.

27. The Effect of Noise and Liquidity Traders Noise traders push stocks away from fundamentals They trend chase They increase volatility The effect of noise traders is mitigated through call markets Liquidity traders are no harmed Volatility significantly reduced

28. Recap Bubbles are pervasive and persistence Attempts to moderate bubbles through institutional changes do not work or exacerbate the price bubbles Bubbles a very dependant on the underlying environment Bubbles are fueled by excess cash Uncertainty in dividends that create probability judgment error ignites bubbles Reignite

29. Recap Timing the market from all of the tested models is not possible Chasing the market can leave you holding the bag Forecasts lag the market and miss turning points The combination of probability judgment error and speculation increases the probability that bubbles will occur.

30. Recap There are spillovers from speculation in one stock to another Volatility begets volatility Crash in one market can have a affect heuristic in another There is an underreaction to expectations alignment Traders anchor on the price trend The presence of noise traders increase the bubble characteristics and price volatility