Detecting and Measuring Nonlinearity
AbstractThis paper proposes an approach to measure the extent of nonlinearity of the exposure of a financial asset to a given risk factor. The proposed measure exploits the decomposition of a conditional expectation into its linear and nonlinear components. We illustrate the method with the measurement of the degree of nonlinearity of a European style option with respect to the underlying asset. Next, we use the method to identify the empirical patterns of the return-risk trade-off on the SP500. The results are strongly supportive of a nonlinear relationship between expected return and expected volatility. The data seem to be driven by two regimes: one regime with a positive return-risk trade-off and one with a negative trade-off. View Full-Text
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Kotchoni, R. Detecting and Measuring Nonlinearity. Econometrics 2018, 6, 37.
Kotchoni R. Detecting and Measuring Nonlinearity. Econometrics. 2018; 6(3):37.Chicago/Turabian Style
Kotchoni, Rachidi. 2018. "Detecting and Measuring Nonlinearity." Econometrics 6, no. 3: 37.
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