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Les strategies de "Stop Loss" : Theorie et application au contrat notionnel du MATIF

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  • Bensaid, B.
  • De Bandt, O.

Abstract

Pour expliquer l'existence de règles de «stop-loss» dans les institutions financières, nous développons un modèle principal-agent, où une firme d'investissement (le principal) doit faire appel à l'expertise d'un opérateur (l'agent) pour investir dans un actif risqué et sophistiqué (par exemple, un contrat à terme). Quand l'opérateur a une «responsabilité limitée», nous montrons que la firme d'investissement peut accroître ses gains en s'engageant à mettre en place des règles de «stop-loss», c'est-à-dire a liquider la position de l'opérateur quand ses résultats sont mauvais. En utilisant des données journalières sur les positions individuelles sur le Contrat Notionnel du Matif, nous trouvons certains éléments en faveur d'une des conclusions testables du modèle, à savoir que les positions sont plus souvent liquidées lorsque les pertes sont importantes. Il ressort de l'analyse empirique que plus de 20 % des comptes utilisent des stratégies de ce type.

Suggested Citation

  • Bensaid, B. & De Bandt, O., 1996. "Les strategies de "Stop Loss" : Theorie et application au contrat notionnel du MATIF," Working papers 36, Banque de France.
  • Handle: RePEc:bfr:banfra:36
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    1. Krugman, Paul & Miller, Marcus, 1993. "Why have a target zone?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 38(1), pages 279-314, June.
    2. Gennotte, Gerard & Leland, Hayne, 1990. "Market Liquidity, Hedging, and Crashes," American Economic Review, American Economic Association, vol. 80(5), pages 999-1021, December.
    3. Grossman, Sanford J, 1988. "An Analysis of the Implications for Stock and Futures Price Volatility of Program Trading and Dynamic Hedging Strategies," The Journal of Business, University of Chicago Press, vol. 61(3), pages 275-298, July.
    4. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
    5. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    6. Shiller, 021Robert J. & Pound, John, 1989. "Survey evidence on diffusion of interest and information among investors," Journal of Economic Behavior & Organization, Elsevier, vol. 12(1), pages 47-66, August.
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    Cited by:

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    2. Carol L. Osler, 2001. "Currency orders and exchange-rate dynamics: explaining the success of technical analysis," Staff Reports 125, Federal Reserve Bank of New York.
    3. Carol L. Osler, 2006. "Macro lessons from microstructure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(1), pages 55-80.
    4. John A. Carlson & Christian M. Dahl & Carol L. Osler, 2008. "Short-run Exchange-rate Dynamics: Theory And Evidence," Working Papers 39, Brandeis University, Department of Economics and International Businesss School.
    5. Carol L. Osler, 2003. "Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis," Journal of Finance, American Finance Association, vol. 58(5), pages 1791-1820, October.

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    More about this item

    Keywords

    Information ; Institutions financières;

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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