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Leithner, S., Spahn, C. Konvexe Strategien im Devisenmarkt: Vorhersagekraft und ökonomischer Wert. Credit and Capital Markets – Kredit und Kapital, 24(2), 212-234. https://doi.org/10.3790/ccm.24.2.212
Leithner, Stephan and Spahn, Cornelius "Konvexe Strategien im Devisenmarkt: Vorhersagekraft und ökonomischer Wert" Credit and Capital Markets – Kredit und Kapital 24.2, 1991, 212-234. https://doi.org/10.3790/ccm.24.2.212
Leithner, Stephan/Spahn, Cornelius (1991): Konvexe Strategien im Devisenmarkt: Vorhersagekraft und ökonomischer Wert, in: Credit and Capital Markets – Kredit und Kapital, vol. 24, iss. 2, 212-234, [online] https://doi.org/10.3790/ccm.24.2.212

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Konvexe Strategien im Devisenmarkt: Vorhersagekraft und ökonomischer Wert

Leithner, Stephan | Spahn, Cornelius

Credit and Capital Markets – Kredit und Kapital, Vol. 24 (1991), Iss. 2 : pp. 212–234

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Stephan Leithner, St. Gallen

Cornelius Spahn, St. Gallen

References

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  36. Hull, J. (1989): „Options, Futures and other Derivative Securities“, Englewood Cliffs, NJ: Prentice- Hall.  Google Scholar
  37. Ibbotson Assoc. (1989): „Stocks, Bonds, Bills, and Inflation 1989 Yearbook“, Chicago, Olinois: Ibbotson Associates. – Kaufmann, P. J. (1987): „Commodity Trading Systems and Methods“, New York: John Wiley and Sons.  Google Scholar
  38. König, P. and J. Möller (1989): „Exchange Rates, Forward Rates and Interest Differentials“ Geld und Währung (Monetary Affairs), 2/3, S. 5 – 29.  Google Scholar
  39. Kritzman, M. (1989): „Serial dependence in currency returns: Investment implications“, Journal of Portfolio Management, Fall 1989, S. 96 – 102.  Google Scholar
  40. Lo, A. und A. MacKinlay (1988): „Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test.“, Review of Financial Studies, 1,1,S. 41 – 66.  Google Scholar
  41. Lo, A. und A. MacKinlay (1989): „The Size and Power of the Variance Ratio Test in Finite Samples. A Monte Carlo Investigation“, Journal of Economics, 4, S. 203 – 238.  Google Scholar
  42. Mark, N. C. (1988): „Time-Varying Betas and Risk Premia in the Pricing of Forward Foreign Exchange Contracts“, Journal of Financial Economics, 22, S. 335 – 354.  Google Scholar
  43. MacDonald, R. (1988): „Floating Exchange Rates: Theories and Evidence“, London: Unwin Hyman.  Google Scholar
  44. Merton, R. (1981): „On Market Timing and Investment Performance. I. An Equilibrium Theory of Value for Market Forecasts“, Journal of Business, 54, 3, S. 363 – 406.  Google Scholar
  45. Perold, A. und W. F. Sharpe (1988): „Dynamic Strategies for Asset Allocation“, Financial Analysts Journal, Jan./Feb., S. 16 – 27.  Google Scholar
  46. Pfeifer, P. E. (1985): „Market Timing and Risk Reduction“, Journal of Financial and Quantitative Analysis, 20, 4, S. 451 – 459.  Google Scholar
  47. Siebert, A. (1989): „The Risk Premium in the Foreign Exchange Market“, Journal of Money, Credit and Banking, 21, 1, S. 49 – 65.  Google Scholar
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Abstract

Convex Strategies on the Exchange Market: Forecasting Ability and Economic Value

The subject of this empirical study is the predictability of deviations, defined as yield on foreign exchange transactions, from the forward rate parity for five rates of exchange in the period 1977/88. Starting from the question whether such deviations are predictable and not random in character, this paper analyzes the yield on foreign exchange transactions for regularity. The following shows that, where foreign exchange transaction yields auto-correlate in a positive sense, a convex investment behaviour is advantageous and that the Trading Rules set out in the “technical analysis” may be referred to as convex in nature. The forecasting value of the strategies examined has been analyzed on the basis of both the Henriksson/Merton and the Cumby/ Modest tests. On this basis, the economics element involved in the forecasting value is ascertained with the help of the options price theory. Simulation runs covering the period 1977/1988 have confirmed the results obtained. It is subsequently -shown that optimal strategy implementation by investors depends not only on the quality of the forecasts made, but also on individual risk aversion.