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Combining Forecasts with Missing Data: Making Use of Portfolio Theory

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  • Björn Fastrich
  • Peter Winker

Abstract

In this work we propose the construction of optimized forecast-portfolios where analysts are thought of as “assets” with specific characteristics that may be combined in portfolios. The analysts’ forecasts were made about the German stock market index DAX on a 6-month horizon as provided by the ZEW Financial Market Survey. A Differential Evolution algorithm is applied that is flexible enough to work with the holey structure of the survey dataset, as it allows for the introduction of a weights-shifting scheme that prevents the exclusion of analysts with missing data and the resulting loss of information. The method is implemented for each of three objective functions that translate ideas from financial management into the forecast-portfolio framework: the mean–variance, the Value-at-Risk, and an asymmetric target strategy. With a backtest we show that weighting several individual forecasts with a forecast-portfolio can indeed improve the forecast quality. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.
    • Handle: RePEc:kap:compec:v:44:y:2014:i:2:p:127-152
    DOI: 10.1007/s10614-013-9401-z
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    Cited by:

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    2. Gong, Xiao-li & Zhuang, Xin-tian, 2016. "Option pricing and hedging for optimized Lévy driven stochastic volatility models," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 118-127.
    3. Brückbauer Frank & Schröder Michael, 2023. "The ZEW Financial Market Survey Panel," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(3-4), pages 451-469, June.
    4. Gong, Xiaoli & Zhuang, Xintian, 2017. "American option valuation under time changed tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 57-68.
    5. D. Th. Vezeris & C. J. Schinas & Th. S. Kyrgos & V. A. Bizergianidou & I. P. Karkanis, 2020. "Optimization of Backtesting Techniques in Automated High Frequency Trading Systems Using the d-Backtest PS Method," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 975-1054, December.

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