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Is online trading gambling with peanuts?

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  • Anderson, Anders

Abstract

If individuals derive a small utility from gambling, we should observe high turnover in portfolios that are of only marginal importance to them. By the use of detailed individual financial data, as well as trades from a Swedish online broker, I measure the frequency and cost of online trading in the cross-section, and find the opposite relation. Those who have online portfolios that constitute a large share of risky assets trade more aggressively, but have lower trading performance. These results can be explained by a simple Treynor-Black portfolio model where investors suffer from biased self-assessment, rather than possessing true investment skill. The overall result suggests that the cost of online trading can be substantial. The top quintile of investors who have the highest share of their total financial assets in stocks invested at the brokerage firm under study loose 3.70% of their financial wealth annually, which corresponds to 1.38% of aggregate income within this group. These investors do not only hve lower overall wealth and income, but also have the highest aggregate trading losses. Therefore, trading losses are mainly carried by those who can afford them the least. Across individuals, annual losses for 36% of investors exceed 1% of their financial wealth, and 17% lose more than 5%.

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  • Anderson, Anders, 2006. "Is online trading gambling with peanuts?," Papers 06-02, Sonderforschungsbreich 504.
    • Handle: RePEc:mnh:spaper:2604
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    References listed on IDEAS

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    Cited by:

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    3. Philippe Bernard & Michel Blanchard, 2013. "The performance of amateur traders on a public internet site: a case of a stock-exchange contest," Economics Bulletin, AccessEcon, vol. 33(3), pages 1729-1737.
    4. Anders Anderson, 2007. "All Guts, No Glory: Trading and Diversification among Online Investors," European Financial Management, European Financial Management Association, vol. 13(3), pages 448-471, June.

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    More about this item

    Keywords

    Investor behavior ; performance evaluation ; online trading ; overconfidence;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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