Academic journal article ASBM Journal of Management

Behavioural Vectors of Soy Oil Futures Traders in India

Academic journal article ASBM Journal of Management

Behavioural Vectors of Soy Oil Futures Traders in India

Article excerpt


With the availability of internet trading terminals, the number of small traders operating independently in commodity market has increased manifold. These traders frequently subscribe to several trading advisory services, which provide vanilla trade alerts. As the traders belong to different categories, have different risk return perceptions, different trading horizons and behavioural biases, there is a need to customize the advisory as per the trading profiles of the traders. Behavioural profiling of traders is essential for custom designing of trading portfolios for the clients as per their risk-return profile.

To the best of available knowledge, behavioural profiling of traders in equity or commodity markets has not been studied so far in India. Therefore, this study attempts a trader profiling based on their behavioural biases, with the objective of identifying the latent vectors responsible for the trading behaviour, with a specific focus on soy oil traders.

Soy oil is the largest traded edible oil in India forming approximately a third of daily trade value in agricultural commodities on three of the major commodity exchanges namely National Commodity and Derivatives Exchange (NCDEX), ACE Commodity exchange (ACE) and Indian Commodity Exchange (ICEX). Refined, bleached, and degummed soy oil is traded on these exchanges as Refined Soy Oil (RSO). Soy oil also has the largest trading footprint across global commodity markets.

This paper is organised as follows. Section 2 covers the relevant literature survey to identify the behavioural biases affecting the trading decisions. Section 3 describes the methodology and theoretical framework. Section 4 presents the findings, discussions and limitations and, section 5 concludes.

Review of Literature

Behavioural finance literature demonstrates that the individual investor behaviour and the decision making process are being affected by various psychological factors.

Odean (1998) states that traders, insiders and market makers may unconsciously overestimate the precision of their information and rely on it more than warranted. The traders receiving a better than average return may perceive their performance better than the peers, and may trade aggressively. This is known as overconfidence bias. Daniel, Hirshleifer and Subrahmanyam (1998), highlight that investors exhibit overconfidence and biased self attribution, i.e., people attribute more credit to their own success. The overconfident investors, according to Glaser and Weber (2007), at the individual level, trade more aggressively. As overconfident traders increase both trading volume and volatility, Gervais and Odean (2001) find that these traders realize, on average, lower gains. Hirshleifer and Luo (2001) explain the persistence of overconfidence in the market by the fact that overconfident traders are more aggressive than their rational counterparts in exploiting mispricing brought about by noise traders or market makers.

Stratman, Thorley, and Vorkink (2006) argue that investor overconfidence is a driver of the disposition effect, which refers to an investor's willingness to hold on to a losing trade and close a winning trade. Unlike the overconfidence effect, which affects the market in general and explains both sides of a given transaction, the disposition effect explains the motivation for only one side of the trade. Chou and Wang (2011), using a unique dataset from Taiwan futures exchange which recorded all account level trades and orders, differentiate empirically between overconfidence and disposition effect. Prosad, Kapoor, and Sengupta (2013) find that disposition and overconfidence prevail in the Indian equity market and can lead to an increase in trading volume at market level as well as at individual security level.

Herding or the actions of individuals in a group is another commonly studied and documented bias. Greed in uptrending and fear in downtrending markets drive the herding behaviour. …

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