Trading indicators with information-gap uncertainty
Colin J. Thompson
Anthony J. Guttmann
Ben J.P. Thompson
Purpose – This paper aims to provide a new quantitative methodology for predicting turning points and trends in financial markets time series based on information-gap decision theory. Design/methodology/approach – Uncertainty in future returns from financial markets is modeled using information-gap decision theory. The robustness function, which measures immunity to uncertainty, yields an additional time series whose turning points anticipate and reflect those of the underlying financial market time series. Findings – The robustness function falling above or below certain thresholds is shown to provide a new reliable technical indicator for predicting highs and lows in financial markets. In addition, iterates of the robustness function are shown in certain cases to predict trends in financial markets. Research limitations/implications – In the analysis and application presented here the authors have only considered a special case of the robustness function. Stricter performance requirements and alternative process model estimates for future returns could be included in the information-gap model formulation and analysis. Practical implications – An additional technical trading tool for applying Information-Gap theory to financial markets has been provided. Originality/value – This paper provides a new reliable methodology for constructing technical indicators for use by traders and fund managers in financial markets. Originality/value – The study serves as an information source for investors in the insurance industry.
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