If you would believe everything you read in social media, trading forums and financial news, you would be misled to believe that the majority of traders are rational, risk-minimizing, sophisticated and consistently profitable human beings. In the following, we summarize the findings of 20 economic research journals about traders’ overconfidence, the effect of stop loss and round numbers, media, attention-grabbing events, technical analysis and many more trading related fields that have been scientifically examined. Besides feeling entertained, a trader would do well by checking whether he can find himself in the following statements and think about his own trading behavior.
Over Confidence – What Traders Think About Themselves
1. Three-quarters of dealers rated themselves above average, which is consistent with results from other psychological studies of overconfidence. Statistically, only 50% should have rated themselves as above average without the effect of overconfidence. 1
2. Dealers also overestimate their professional success, an effect known as the “better-than-average-effect”. 1
3. Trading experience eliminates the reluctance to realize losses. 1
4. Individual investors who think that their investment skills or past performance are above trade more frequently. 2
5. By examining over 400 traders with trading experience over 12 years at a bank, currency dealers show two types of overconfidence. They tend to overestimate the precision of their information and their personal competence. 3
6. The most senior traders are no less overconfident than their more junior colleagues. 3
7. In theory, irrational traders will be driven out of asset markets by trading losses. However, the examination of 400 experienced traders indicates that overconfident currency traders are not driven out of the market despite losses. 3
8. Overconfidence among foreign exchange dealers could affect equilibrium exchange rates. 3
9. Chinese investors make trading mistakes (selling winners and hold on to losers), they are reluctant to realize their losses, they tend to be under-diversified, they seem to trade often and they show a representativeness bias. 4
10. Middle-aged investors, active investors, wealthier investors, experienced investors and those living in urban cities are often unable to overcome behavioral biases. 4
11. Investors who were successful before trading online believed that their successes are due to their own investment abilities and become overconfident. Once individuals start trading online, investors have access to vast amount of data which can lead to the illusion of knowledge. Furthermore, managing their own trades by the click of a mouse leads to the illusion of control. All of these factors lead to increased overconfidence. 11
The Effects Of Stop Loss Orders And Round Numbers
12. The response of exchange rates to stop-loss orders is larger, and lasts longer, than the response to take-profit orders. 5
13. Stop-loss orders are sometimes triggered in waves. 5
14. The reversal frequency at round numbers is greater than the reversal frequency at arbitrary price levels in 79% of examined 10 day periods. 5
15. Exchange rates trend faster after crossing round numbers which suggest that stop-loss orders propagate trends. 5
16. Large stop-loss orders are tightly clustered near rates ending in 00. In contrast, very large take-profit orders are not clustered. 5
What Does Research Say About Technical Analysis
17. Adding technical analysis, like moving averages to investment rules, can outperform other trading strategies. 6
18. Significant excess returns are possible using technical analysis in foreign exchange markets. 7
19. Technical trading rules exist for NASDAQ Composite and Russell 2000 but not for DJIA and S&P 500. Rules of technical analysis even generate significant profits and improve unprofitable trading rules. 8
20. Technical trading profits have gradually declined over time in 12 futures markets. 9
The Impacts Of Big Events And Financial Media
21. Stock prices temporarily rise following widely talked about events before reversing to pre-event levels over the next five days. On average, individuals lose 0.88% when prices reverse. 10
22. Attention-grabbing events lead active individual investors to be net buyers of stocks. 10
23. Individual investors who currently hold a company’s share, sell as prices increase during upper price limit events. 10
24. Individual investors are more likely to trade an S&P 500 index stock after an earnings announcement if that announcement was covered in the investor’s local newspaper. 18
25. The presence or absence of local media coverage is strongly related to the probability and magnitude of local trading. 18
26. On days of extreme weather events, which are likely to disturb the regular delivery of daily newspapers, the relationship between media coverage and trading is broken. 18
27. Trading patterns are strongly related to the local patterns of media coverage. 18
28. The portion of negative words in firm-specific news stories forecasts low firm earnings. Furthermore, negative words in stories about fundamentals are particularly useful predictors of both earnings and returns. 20
29. Investors who have never previously owned a stock are more likely to buy when stocks reach upper price limits such as all-time highs. Other rational investors can profit at the expense of the attention driven individual investors. 19
Random Findings Of Trading And Investing
30. After news events, traders tend to trade in parallel with their “friends”. Traders with more friends are more profitable, which suggests that traders share perspectives with each other. 12
31. Currency exchange rate dealers widened bid-ask spreads from December 1999 to January 2000 as the uncertainty surrounding the year 2000 lead to increased “safe-haven” flows. 13
32. Interdealer spreads widened on the day of the 9/11 attacks as uncertainty and volatility both rose significantly. Notably, interdealer spreads came back to normal figures the next day. 14
33. Investors are more likely to increase trade size after successful trades and more likely to decrease trade size or quit trading after unsuccessful trades. 15
34. Due to the disposition effect, day traders are more likely to close profitable positions. 15
35. The response of trading to performance depends on trader experience. The difference between profitable and unprofitable traders, for traders with less than 12 months trading experience, is nearly twice as high as for those of all day traders. 15
36. Day traders are not standard risk-averse; they may be risk-seeking or attracted to investments with highly skewed investments, that have negative expected returns but a small probability of a large payoff. 16
Awareness, and especially self-awareness, is one of the most important premises on the path to becoming a consistently profitable trader. Although the presented statistics and findings won’t make you a better trader at the first glance, waking your awareness of potential shortfalls, certain market anomalies or negative psychological effects, a trader is able to avoid costly mistakes and evolve. If you want to read more, check out our first article about economic research facts about trading.
1) Alicke, M.D., & Govorun, O. (2005). The better-than-average effect. In M.D. Alicke, D.A. Dunning, & J. I. Krueger, (Eds.), The self in social judgment. New York: Psychology Press.
2) Glaser and Weber (2007), “Overconfidence and Trading Volume,” Forthcoming, Geneva Risk and Insurance Review.
3) Thomas Oberlechner and Carol Osler (2008): OVERCONFIDENCE IN CURRENCY MARKETS. SSRN Working Paper #1108787
4) Gong-Meng Chena, Kenneth A. Kimb, John R. Nofsingerd, Oliver M. Ruie (2005):Behavior and performance of emerging market investors: Evidence from China,
5) C. L. Osler (March 2003): STOP-LOSS ORDERS AND PRICE CASCADES IN CURRENCY MARKETS, Graduate School of International Economics and Finance; Brandeis University.
6) (Yingzi Zhu, Guofu Zhou 2009: Technical analysis: An asset allocation perspective on the use of moving averages, Journal of Financial Economics)
7) Neely, Weller, Dittmar (1997): Is Technical Analysis in the Foreign Exchange Market Profitable?, Federal Reserve Bank of St. Louis)
8) Hsu, Kuan: Re-Examining the Profitability ofTechnical Analysis with White’s Reality Check
9) Park, Irwin (2005): The Profitability of Technical Trading Rules in US Futures Markets: A Data Snooping Free Test)
10) Mark S. Seasholes, Guojun Wu (2006): Predictable behavior, profits, and attention. Journal of Empirical Finance
11) Barber B., Odean T. (2002): Online Investors: Do the slow die first, The Review of Financial Studies 2002 Vol 15, No.2, pp 445 – 487
12) Michael R. King, Carol Osler and Dagfinn Rime (2013): The market microstructure approach to foreign exchange: Looking back and looking forward, Norges Bank Research Working Paper
13) Kaul, Aditya and Stephen Sapp (2006): Y2K fears and safe haven trading of the U.S. dollar, Journal of International Money and Finance, 25(5), pp. 760–779.:
14) Mende, Alexander (2006): 09/11 on the USD/EUR foreign exchange market. Applied Financial Economics, 16(3), pp. 213–222.
15) Barber, Lee, Odeon, Liu (2010): Do Day Traders Rationally Learn About Their Ability?
16) Kumar, Alok, (2009): Who Gambles in the Stock Market, Journal of Finance, 64, 1889- 1933.
18) Engelberg, J., & Parsons, C. (2011). The causal impact of media in financial markets. Journal of Finance, 66, 67–97.
19) Seasholes, M. S., & Wu, G. (2007). Predictable behavior, profits, and attention. Journal of Empirical Finance, 15, 590–610.
20) Tetlock, Paul, Maytal Saar-Tsechansky, and Sofus Macskassy, 2008, More than words: Quantifying
language to measure firms’ fundamentals, Journal of Finance 63, 1437-1467.