BTCUSD
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.
2. Dealers also overestimate their professional success, an effect known as the “better-than-average-effect”.
3. Trading experience eliminates the reluctance to realize losses.
4. Individual investors who think that their investment skills or past performance are above trade more frequently.
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.
6. The most senior traders are no less overconfident than their more junior colleagues.
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.
8. Overconfidence among foreign exchange dealers could affect equilibrium exchange rates.
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.
10. Middle-aged investors, active investors, wealthier investors, experienced investors and those living in urban cities are often unable to overcome behavioral biases.
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.
12. The response of exchange rates to stop-loss orders is larger, and lasts longer, than the response to take-profit orders.
13. Stop-loss orders are sometimes triggered in waves.
14. The reversal frequency at round numbers is greater than the reversal frequency at arbitrary price levels in 79% of examined 10 day periods.
15. Exchange rates trend faster after crossing round numbers which suggest that stop-loss orders propagate trends.
16. Large stop-loss orders are tightly clustered near rates ending in 00. In contrast, very large take-profit orders are not clustered.
17. Adding technical analysis, like moving averages to investment rules, can outperform other trading strategies.
18. Significant excess returns are possible using technical analysis in foreign exchange markets.
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.
20. Technical trading profits have gradually declined over time in 12 futures markets.
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.
23. Individual investors who currently hold a company’s share, sell as prices increase during upper price limit events.
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.
25. The presence or absence of local media coverage is strongly related to the probability and magnitude of local trading.
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