an examination of the relationship between the disposition effect and gender age and product type n.
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  1. An Examination of the Relationship between the Disposition Effect and Gender, Age, and Product Type Presenter: Teng Yuan Cheng

  2. Abstract • We analyze how internal characteristics and an external factor are related to the disposition effect • Internal characteristics: • one is gender, remains fixed over the lifetime. • The other is age that changes over the lifetime. • External factor is product type: electronic- and financial-sector index futures contract.

  3. Abstract • Electronic sector: ever-changing nature, compete with the world-wide competitor. • Financial sector: more conservative investors, compete mostly domestically.

  4. Abstract • We show that women and mature traders, compared with their male and younger counterparts, exhibit a stronger disposition effect. • The effect is also stronger among traders who trade the financial-sector futures contract than those who trade the electronic- sector futures contract.

  5. Internal biological characteristics: gender and age Behavioral bias: disposition effect External factor: two specific types of futures products

  6. Introduction • Rules from Commodity Research Bureau (CRB), the most familiar ones for the successful traders are “cut your losses short” and “let profits run. • But most of investors behave just the opposite. They exhibit the disposition effect, the tendency to hold onto losses too long but realize gains too readily.

  7. Introduction • Going beyond the aggregate investor approach, we track the trade-by-trade history of each individual, • How variations in internal biological characteristics such as gender and age affect trader’s behavior

  8. Introduction • We further investigate how external factors also play a role in the disposition effect. • The electronic sector index versus financial sector index futures —with different volatility nature and attract different traders.

  9. Literature Review • Disposition Effect (in stock market) • Kahneman and Tversky (1979) • Shefrin and Stateman (1985) • Odean (1998), Barber and Odean (2000), and Dhar and Zhu (2006) look at retail investors of a US discount brokerage house • Garvey and Murphy (2004) examine 15 proprietary stock traders, • Feng and Seasholes (2005): individual level • Barber et al. (2007) analyze four types of investors (individuals, corporations, dealers, and foreign investors) in Taiwan;

  10. Literature Review • Disposition Effect • Relatively few in futures market: • Heisler (1994) (retail), Locke and Mann (2005) (professional floor) and Frino et al. (2004) (local traders) • Frino et al. (2004), Locke and Mann (2005),

  11. Literature Review • Gender issue: • Barber and Odean (2001) and Agnew et al. (2003) that men trade more actively than women, • A large amount of research in sociology and psychology has revealed gender differences in the perception of risk associated with risky behaviors, various hazards, and dangerous activities (e.g., Spigner et al. (1993), Flynn et al. (1994), Boverie et al. (1995) etc. • Campbell (2006) for an extensive review of the literature on gender differences in investor behavior.

  12. Literature Review • Age issue: • Risk tolerance decreases with age, Mclnish (1982) and Hallahan et al. (2004). • Xiao and Anderson (1997) and Donkers and Van Soest (1999) find a positive relationship. • Many other studies (e.g., Cutler (1995), Sunden and Surette (1998), and Van de Venter and Michayluk (2009) find little or no relationship

  13. Data • Tracking the trade-by-trade transaction histories, individual traders on the Taiwan Futures Exchange. • Two different characteristic underlying assets: Electronic and Financial Sectors, mature between January 2003 and December 2004.

  14. Data • In total, there are 65,631 traders trading TE and 71,896 trading TF. • We further require that the traders trade more than ten days over the sample period and have more than ten roundtrips. • 18,172 TE traders and 22,950 TF traders meet these criteria.

  15. Methodology • We calculate, after each trade, all the necessary statistics such as the open interests (OIs), weighted average costs, and realized and unrealized gains/losses. • We exclude institutional and proprietary traders and focus only on trades that are executed by individual traders.

  16. Methodology • Originate from Odean (1998) proportion of gains realized (PGR) and proportion of losses realized (PLR) • We construct the proportion of offsets that result in a realized gain, called proportion of positive offset (PPO), • and proportion of offsets that lead to a realized loss, called proportion of negative offset (PNO).

  17. Methodology • By examining PPO and PNO at individual level we can further investigate whether and how it varies among traders. • If PPO>PNO,the disposition effect exists, the trader is more inclined to offset her position when doing so results in a realized gain while loath to offset if it leads to a realized loss.

  18. when there is a realized gain at t when there is a realized loss at t

  19. 2/30=0.067

  20. 1/130=0.008

  21. Result • Female traders show stronger disposition effect tendency than male traders • Mature traders show stronger disposition effect tendency than younger traders • Financial futures traders show stronger disposition effect tendency than electronic futures traders

  22. Regression Tests of the Relationship between Disposition Effect and Trader’s Characteristics and External Factor Model: Disposition_effect=β0+∑βi*trading_variable +∑δj*internal_characteristics+∑ηk*product_type

  23. Variables • Note: • Disposition Effect = PPO – PNO. • Profit Per Contract = Cumulative net trading profit ( after transaction cost) over total trading volume • Volume Per Day = Total trading volume over trading days • Tenure = last trading date less open account date (by months) • Age = trader’s age in years from birth date to the last trading date in years • Gender = 0 for male; 1 for female. • DTE-TF =0 for trading TE; 1, TF • DBoth= 0 for trading only TE or TF; 1 for trading both TE and TF • Dprofit=0 for profitable traders; 1, loss traders

  24. Result • Volume per day: negative impact on disposition effect • Tenure is not a significant factor in this test. • Age: Mature traders show stronger disposition effect tendency than younger traders • Gender: Female traders show stronger disposition effect tendency than male traders

  25. Result • DTE-TF : Financial futures traders show stronger disposition effect tendency than electronic futures traders • Dboth: Traders who trade both electronic and financial futures show stronger disposition effect tendency than those who trade only one futures

  26. Thank you for your listening.