Psychology of Commodity Trading: Behavioral Biases That Move Markets
Book: Commodities: Markets, Performance, and Strategies
Editors: H. Kent Baker, Greg Filbeck, Jeffrey H. Harris
Publisher: Oxford University Press, 2018
ISBN: 9780190656010
Even the Pros Get It Wrong
You might think that commodity markets are dominated by rational professionals who have their emotions under control. Chapter 4, by John Nofsinger, Pattanaporn Chatjuthamard, and Xu Dai, shows that this is not the case. Even seasoned market makers, floor traders, and hedge fund managers fall prey to the same psychological biases that trip up regular investors.
The fast-paced environment of futures trading actually makes things worse. Quick decisions under pressure are exactly the conditions where behavioral errors thrive.
The Big Biases
The chapter organizes behavioral biases into three categories: biases (overconfidence, confirmation bias), heuristics (mental shortcuts like anchoring), and framing effects (loss aversion, prospect theory).
Overconfidence
People generally think they are above average. Traders are no different. They overestimate the precision of their knowledge and their ability to time the market. This leads to excessive trading, which racks up costs and reduces profits.
A good example from the chapter: many grain producers are overconfident about future prices. They expect prices higher than what futures markets reflect. This overconfidence actually leads them to underuse futures for hedging. They think they know better than the market, so they skip the hedge and take on unnecessary risk.
Prospect Theory
Daniel Kahneman and Amos Tversky’s prospect theory is one of the most important ideas in behavioral finance. It says three things:
- People feel losses more strongly than gains. Losing $100 feels roughly twice as bad as gaining $100 feels good.
- Loss aversion makes people behave oddly. Rather than take a small certain loss, people will gamble on a bigger potential loss for a chance to break even.
- Reference points matter. People do not evaluate outcomes in absolute terms. They measure gains and losses relative to some reference point, like the price they paid for an asset.
In commodity markets, this plays out in interesting ways. Research by Narayan, Narayan, and Popp (2011) found significant price clustering in oil futures around whole dollar amounts. Traders anchor on these round numbers, and they become psychological barriers that influence behavior.
The Disposition Effect
Prospect theory leads directly to what researchers call the disposition effect: the tendency to sell winners too quickly and hold losers too long.
When a trade is profitable, people feel the pull to lock in the gain and avoid the risk of it disappearing. When a trade is losing money, people hold on because selling would make the loss feel real. They hope it will come back.
Terrance Odean (1998) documented this extensively in stock markets. Choe and Eom (2009) found the same pattern in the Korean stock index futures market. Individual investors were much more susceptible than institutional investors, though even professionals showed the effect.
Here is the thing: holding losers and selling winners is usually the wrong move. The losers tend to keep losing, and the winners tend to keep winning. Plus, delaying the sale of a loser postpones a tax deduction you could use.
Loss Aversion in the Futures Pit
The chapter has some fascinating studies on how loss aversion plays out among professional futures traders.
Locke and Mann (2005) studied CME floor traders in 1995 and found they held losing positions longer than winning ones. But interestingly, this behavior was not always costly for professionals. Some floor traders had enough information and skill to ride out losses that eventually turned profitable.
Locke and Mann (2009) found an even more specific pattern. They looked at how morning gains and losses affected afternoon trading behavior. Traders who had morning losses traded more aggressively in the afternoon, taking bigger risks to try to get back to breakeven. This is the classic “break-even effect,” which is loss aversion in action.
Soybean producers showed similar patterns. Mattos, Garcia, and Pennings (2008) found that loss aversion affected hedging decisions, though the impact was relatively small in a static context. What mattered more was how prior outcomes affected risk attitudes going forward.
Reference Points and Price Clustering
People are attracted to round numbers. This creates price clustering in futures markets, where trading activity bunches up around whole dollar amounts.
This happens in sophisticated markets too, not just among small retail investors. Research shows price clustering in foreign exchange, gold futures, and energy markets. These round numbers become psychological reference points that traders use to frame their decisions.
Emotions on the Trading Floor
The chapter makes a quick but important point about emotions. Day traders who showed more intense emotional responses to market events had significantly worse trading performance (Lo, Repin, and Steenbarger, 2005).
Even weather affects trading. Limpaphayom, Locke, and Sarajoti (2007) found that Chicago floor traders bought more on calm, sunny days and earned less on windy days. Sunshine makes people happier and more optimistic. Wind apparently does not help.
Trend Chasing and Momentum
Positive feedback trading means buying after prices go up and selling after prices go down. It is basically trend chasing. And it is everywhere in commodity markets.
DeLong, Shleifer, Summers, and Waldmann (1990) showed that even rational speculators can amplify the effects of positive feedback trading rather than correcting them. When enough traders chase momentum, prices can get pushed far from fundamental values.
Tokic (2011) argued that this is exactly what happened during the 2008 oil price bubble. Commercial hedgers engaged in positive feedback trading, bidding prices higher and contributing to the bubble.
Momentum strategies get interesting when you look at intraday data. Chen (2013) found that the first five minutes of the trading day in Taiwan stock index futures actually predicted the rest of the day’s returns. If the opening was bullish, institutional traders increased their positions and the momentum continued.
Different Traders, Different Biases
One of the chapter’s best insights is that behavioral biases vary by trader type.
Market makers tend to take bigger risks after losses (trying to break even) and reduce risk after gains (trying to stay ahead). Coval and Shumway (2005) documented this pattern clearly.
Floor traders show the disposition effect, but it is not always irrational. Some professional floor traders ride losses because they have informational advantages. Their losing positions come back to profitability more often than those of less informed traders. So what looks like a behavioral bias might partly be informed trading.
Individual investors are the most susceptible to behavioral biases. They are more prone to the disposition effect than institutional investors, and their risk-seeking behavior after large losses actually affects market volatility and liquidity.
Institutional investors and fund managers are more sophisticated but still not immune. Haigh and List (2005) ran experiments with both undergraduate students and professional futures traders from the Chicago Board of Trade. The professionals actually showed more myopic loss aversion than the students. Experience does not always protect you.
My Take
This chapter is a reality check for anyone who thinks commodity markets are run by perfectly rational actors. They are not. Even the most experienced traders hold losers too long, chase trends, anchor on round numbers, and let morning losses push them into reckless afternoon bets.
The practical takeaway is that understanding your own biases is as important as understanding the market. If you know that you are likely to hold losers and dump winners, you can set rules to counteract that. If you know that a bad morning might push you to take bigger risks in the afternoon, you can take a step back.
The market does not care about your feelings. But your feelings absolutely affect your trading.