Imagine your brain firing off these thoughts after you’ve successfully won a trade:
“Let me trade more often. I’ve been beating the market….”
“I should increase my leverage… just a little more….”
“I’ve got a solid grip on the markets….”
“I don’t need to manage my risk! I know what I’m doing…”
… These thoughts swirl in your mind when you start to get “better at this,” raising the question: Is overconfidence helping you, or stealthily setting you up for failure? Well, the biggest threat to your investments isn’t the economy, your broker, or bad luck—it’s you.
Benjamin Graham notes that “the investor’s chief problem—and even his worst enemy—is likely to be himself."
Let’s take a closer look at this topic.
Barber and Odean’s famous study (2000) empirically supports Benjamin Graham’s opinion. They focused on the returns from common stock investments of 66,465 households at a large discount brokerage firm over a six-year period ending in 1997 and found interesting results: overconfident traders traded too frequently, which hindered their net performance. As shown in Figure 1 below, there is a negative correlation between monthly turnover and net returns. While frequent traders (Group 5 – High Turnover) earned only 11.4% net annually, patient traders (Group 1 – Low Turnover) achieved returns of 18.5%, outperforming a passive investment in the S&P 500 Index Fund, which earned approximately 17.9% over the same period. This suggests that being overconfident endogenously leads to rapid decision-making, which is highly likely to negatively impact your investments.
Could it be revenge trading? Desperation? Well, the most active households had an annual turnover of more than 250%. This suggests that these behavioral patterns are more likely to be the result of overconfidence, reflected in trading too frequently, overestimating one’s knowledge, and ignoring trading costs. Maybe people are trading for entertainment? Not necessarily, as 2,333 of the 66,000 households had at least 50% of their net worth in common stocks at the broker and still recorded a 75% annual turnover.
Moreover, using a multi-period asymmetric Bayesian model, Gervais & Odean (2001) show that overconfidence can be reinforced over time, particularly among traders who experience a few lucky trades over a short period. Such investors and traders suffer from self-serving attribution bias, as Hastorf, Schneider, and Polifka (1970) addressed: “We are prone to attribute success to our own dispositions and failures to external forces.” Usually, after some time, people undergo self-assessment. Likewise, becoming wealthy may reinforce overconfidence, which may act as a hidden tax that erodes one’s wealth over time.
While Barber & Odean (2000) suggest that overconfidence is a negative trait, De Long et al. (1990) conclude that overconfident traders might be winning, at least on a short-term basis. They implemented a two-agent dynamic overlapping generations model, consisting of rational arbitrageurs and “noise” traders, in which each agent lives for two periods. From each agent’s perspective, rational arbitrageurs are risk-averse and base their decisions on fundamentals, while “noise traders” act on non-fundamental information, thereby creating volatility by influencing price movements. As such, arbitrageurs are discouraged from restoring mispriced assets to their fundamental values because of the risk created by “noise” traders. What’s the outcome? Because noise traders bear the risk they created themselves, they earn higher returns than rational investors. It is important to note that this study doesn’t examine the long-term accumulation of wealth for noise traders.
So, what’s the verdict?
Barber & Odean (2000) empirically show that excessive trading depletes net returns. Gervais & Odean (2001) state that as traders accumulate wealth, they tend to get overconfident, enabling them to have more capital than their less confident peers. However, these traders are at greater risk of losing their wealth because their overconfidence will likely lead them to take excessive, uncalculated risks. De Long et al. (1990) demonstrate a “short-horizon” model in which there is limited time to correct mispricing, illustrating how noise traders’ actions affect market outcomes. However, the model falls short of addressing long-term outcomes. Moreover, the authors state that the longer the investment period, the safer arbitrage is for rational investors, enabling them to correct mispriced assets and reduce profits available to noise traders. In conclusion, after assessing the studies above, we can strongly suggest that, in the long run, irrational and overconfident traders lose.
Are you drawn to short-term gains? Not worth it… Invest slowly and steadily. Discipline, rationality, and risk management… yes, they are the drivers of success!