Prospect theory holds that people are risk-averse toward gains but risk-seeking toward losses, a pattern known as the reflection effect. In "Prospect Theory for Online Financial Trading," Liu et al. (2014) studied an online social trading platform for foreign exchanges and commodities. The dataset covers over 28.5 million trades by 81.3 thousand traders, June 2010 to October 2012. Mirror trades won positive returns about 83% of the time, the highest share of any trade type, but averaged only 0.03% ROI.
What the Study Found
All three trade types showed a win rate above 50%, with mirror trades highest at about 83%. Only mirror trades averaged positive ROI, at about 0.03%, while single and copy trades did not. Mirror trades' winning positions earned just about 0.177% ROI, lower than single and copy trades' winning positions. Mirror trades' losing positions lost about 0.9% ROI on average, worse than single and copy trades' losing positions. Losing traders made up 85.2% of all traders, versus 14.7% who were net winners.
Methodology
The data come from an online social trading platform for foreign exchanges and commodities trading, where traders can copy or mirror others' trades. The sample includes over 28.5 million trades placed by 81.3 thousand traders using real money. Trades were recorded from June 2010 to October 2012, a period of about 28 months. The study compares single, copy, and mirror trades, and separates traders into winning and losing groups by final net profit.
Key Statistics
| Metric | Finding | Context |
|---|---|---|
| Win rate, mirror trades | ≈83% | Highest among single, copy, and mirror trades |
| Average ROI, mirror trades | ≈0.03% | Only trade type with positive average ROI |
| Average ROI, winning mirror positions | ≈0.177% | Lower than single and copy trades' winning positions |
| Average ROI, losing mirror positions | ≈-0.9% | Higher negative ROI than single and copy trades' losing positions |
| Winning vs. losing traders | 14.7% vs. 85.2% | Share of traders with net profit vs. net loss |
| Risk-reward ratio threshold | r* = 4 | Above this, winning traders dominate the P(r) distribution |
| Win-loss duration ratio threshold | s* = 100 | Above this, winning traders dominate the P(s) distribution |
| Win-loss ROI ratio threshold | u* = 2 | Above this, winning traders dominate the P(u) distribution |
| Risk-reward ratio formula | r := ⟨p+⟩ / ⟨|p−|⟩ | Average profit of winning trades over average loss of losing trades, per trader |
Why This Matters
Behavioral metrics like the risk-reward and win-loss ROI ratios can flag potential winning traders before raw performance data would. Traders who copy or follow others based on short-term performance may be copying decisions driven by loss aversion rather than skill. For online social trading platforms, adjusting for these behavioral patterns could improve how gurus or trade leaders are selected. Reducing the emotional impact of the reflection effect may help individual traders avoid the outsized losses common among losing traders.