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Hybrid versus highbred: combined economic models with time-series analyses

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  • Ming-Yuan Leon Li

Abstract

While incorporating the Markov-switching (MS) mechanism, this work establishes a hybrid model with endogenous and time-varying loading in each economic model and time-series approach. The empirical data include the monthly exchange rates between the U.S. dollar and the currency of four mature economies, those of France, Germany, Japan and U.K., as well as two emerging Asian countries, South Korea and Taiwan, from 1980 to 2000. The empirical findings of this study are consistent with the following notions. First, market investors are more influenced by fundamental variables derived from economic models during volatile periods. Conversely, when markets stabilize, market participants increase the loadings of the values of lagged exchange rates. Second, a hybrid model with time-varying loading outperforms highbred models for each case. However, the performances of hybrid models with constant loadings are trivial. Third, compared with the random walk model, in-sample tests demonstrated the superior performance of the hybrid model with time-varying loading in all cases. Nevertheless, the out-of-sample performance was less promising, particularly in the case of South Korea.

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  • Ming-Yuan Leon Li, 2008. "Hybrid versus highbred: combined economic models with time-series analyses," Quantitative Finance, Taylor & Francis Journals, vol. 8(6), pages 637-647.
  • Handle: RePEc:taf:quantf:v:8:y:2008:i:6:p:637-647
    DOI: 10.1080/14697680701660472
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    Cited by:

    1. Li, Ming-Yuan Leon, 2009. "Could the jump diffusion technique enhance the effectiveness of futures hedging models?," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(10), pages 3076-3088.
    2. Li, Ming-Yuan Leon, 2009. "Value or volume strategy?," Finance Research Letters, Elsevier, vol. 6(4), pages 210-218, December.
    3. Li, Leon, 2022. "The dynamic interrelations of oil-equity implied volatility indexes under low and high volatility-of-volatility risk," Energy Economics, Elsevier, vol. 105(C).

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