An Appraisal of Composite Forecasting Methods

Park, David W.; Tomek, William G.

doi:10.1093/aepp/10.1.1

Cited by 9 publications

(7 citation statements)

References 6 publications

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“…Along the same lines Park and Tomek (1989) evaluated several forecast models (including ARIMA, VectorAutoregression and OLS for their variances) and concluded in favour of the composite approach. Combining several forecast models gave the lowest MSE when compared to the same models not being combined.…”

Section: Composite Forecast Modelsmentioning

confidence: 99%

“…Just to mention a few see for example, Engle (1982), Taylor (1985) Bollerslev et al (1992), , Susmel and Thompson (1997), Wei and Leuthold (1998), Engle (2000), Manfredo et al (2001). However, there is less evidence that ARCH models give reliable forecasts of commodity price volatility for out-of-sample evaluation (Park and Tomek, 1989, Schroeder et al, 1993, Manfredo et al, 2001. All of them found that the explanatory power of these out-of-sample forecasts is relatively low.…”

Section: Historical Volatility Modelsmentioning

confidence: 99%

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Predictive Accuracy of Futures Options Implied Volatility: The Case of the Exchange Rate Futures Mexican Peso-Us Dollar

Benavides¹

2017

PE-IPN

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RESUMENExiste una cantidad substancial de investigación destinada a pronosticar la volatilidad de los rendimientos de precios de futuros de activos financieros. Una parte significativa de la literatura muestra que pronosticar la mencionada volatilidad con certeza no es una tarea fácil, independientemente del modelo de pronóstico utilizado. En el presente trabajo de investigación se analiza el poder predictivo de varios modelos de pronósticos de volatilidad diaria para los rendimientos de los futuros del tipo de cambio Peso Mexicano-Dólar Estadounidense. Los modelos que se utilizan son: univariado GARCH; multi-variado GARCH (modelo BEKK); dos modelos de volatilidad implícita de opciones; y, un modelo de pronóstico compuesto. Diferente a otros trabajos en la literatura, ABSTRACTThere has been substantial research effort aimed to forecast futures price return volatilities of financial assets. A significant part of the literature shows that volatility forecast accuracy is not easy to estimate regardless of the forecasting model applied. This paper examines the volatility accuracy of several volatility forecast models for the case of the Mexican peso-USD exchange rate futures returns. The models applied here are a univariate GARCH, a multivariate ARCH (the BEKK model), two option implied volatility models and a composite forecast model. The composite model includes time-series (historical) and option implied volatility forecasts. Different to other works in the literature, in this paper there is a more rigorous analysis of the option implied volatilities calculations. The results show that the option implied models are superior to the historical models in terms of accuracy and that the composite forecast model was the most accurate one (compared to the alternative models) having the lowest mean-squared-errors. However, the results should be taken with caution given that the coefficient of determination in the regressions was relatively low. According to these findings it is recommended to use a composite forecast model if both types of data are available i.e. the time-series (historical) and the option implied.

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Section: Composite Forecast Modelsmentioning

confidence: 99%

Section: Historical Volatility Modelsmentioning

confidence: 99%

Predictive Accuracy of Futures Options Implied Volatility: The Case of the Exchange Rate Futures Mexican Peso-Us Dollar

Benavides¹

2017

PE-IPN

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“…(2001), among others. 7 However, the out-of-sample forecasting accuracy of these types of non-linear models could be, in some cases, questionable (see Park and Tomek: 1989, Schroeder et. al.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective

Benavides

2006

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Banco de MéxicoAbstract: In this research paper ARCH-type models are applied in order to estimate the Value-at-Risk (VaR) of an inflation-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures traded at the Mexican Derivatives Exchange (MEXDER). To analyze the VaR with time horizons of more than one trading day bootstrapping simulations were applied. The results show that these models are relatively accurate for time horizons of one trading day. However, the volatility persistence of ARCH-type models is reflected with relatively high VaR estimates for longer time horizons. These results have implications for short-term inflation forecasts. By estimating confidence intervals in the VaR, it is possible to have certain confidence about the future range of inflation (or extreme inflation values) for a specified time horizon. Keywords: Bootstrapping, inflation, inflation-indexed futures, Mexico, Value at Risk, volatility persistence. JEL Classification: C15, C22, C53, E31, E37.Resumen: En el presente documento de investigación modelos tipo-ARCH se utilizan para estimar el Valor-en-Riesgo (VaR) de un portafolio de futuros indizados a la inflación para distintos horizontes en el tiempo. El análisis empírico se realiza para los futuros indizados a la inflación en México los cuales son negociados en la Bolsa Mexicana de Derivados (MEXDER). Para analizar el VaR con horizontes en el tiempo de más de un día de negociación simulaciones de remuestreo fueron utilizadas. Los resultados muestran que ese tipo de modelos son relativamente certeros para horizontes en el tiempo de un día de negociación. Sin embargo, la persistencia en la volatilidad de los modelos tipo-ARCH se ve reflejada con estimados relativamente altos de VaR para horizontes en el tiempo más largos. Estos resultados tienen implicaciones para pronósticos de volatilidad de la inflación de corto plazo. Al estimar intervalos de confianza en el VaR, es posible tener cierta confianza sobre el rango de posibles valores de la inflación (ó valores de inflación extremos) para un horizonte del tiempo específico. Palabras Clave: Remuestreo, inflación, futuros indizados a la inflación, México, Valor en Riesgo, persistencia en la volatilidad.* I appreciate the comments from José

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“…(2001). However, there is less evidence that ARCH models give reliable forecasts of commodity price volatility for out-of-sample evaluation (Park and Tomek: 1989, Schroeder et. al.…”

Section: Historical Volatility Modelsmentioning

confidence: 99%

“…They created the weights for the composite forecast model based upon the forecast ability of each individual model in terms of their Mean-Squared-Errors (MSE). Along the same lines Park and Tomek (1989) evaluated several forecast models (including ARIMA, Vector-Autoregression and OLS for their variances) and concluded in favour of the composite approach. Combining several forecast models gave the lowest MSE when compared to the same models not being combined.…”

Section: Composite Forecast Modelsmentioning

confidence: 99%

Predictive Accuracy of Futures Options Implied Volatility: The Case of the Exchange Rate Futures Mexican Peso-U.S. Dollar

Benavides

2004

SSRN Journal

View full text Add to dashboard Cite

There has been substantial research effort aimed to forecast futures price return volatilities of financial assets. A significant part of the literature shows that volatility forecast accuracy is not easy to estimate regardless of the forecasting model applied. This paper examines the volatility accuracy of several volatility forecast models for the case of the Mexican peso-USD exchange rate futures returns. The models applied here are a univariate GARCH, a multivariate ARCH (the BEKK model), two option implied volatility models and a composite forecast model. The composite model includes time-series (historical) and option implied volatility forecasts. Different to other works in the literature, in this paper there is a more rigorous analysis of the option implied volatilities calculations. The results show that the option implied models are superior to the historical models in terms of accuracy and that the composite forecast model was the most accurate one (compared to the alternative models) having the lowest mean-squared-errors. However, the results should be taken with caution given that the coefficient of determination in the regressions was relatively low. According to these findings it is recommended to use a composite forecast model if both types of data are available i.e. the time-series (historical) and the option implied.

show abstract

An Appraisal of Composite Forecasting Methods

Cited by 9 publications

References 6 publications

Predictive Accuracy of Futures Options Implied Volatility: The Case of the Exchange Rate Futures Mexican Peso-Us Dollar

Predictive Accuracy of Futures Options Implied Volatility: The Case of the Exchange Rate Futures Mexican Peso-Us Dollar

Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective

Predictive Accuracy of Futures Options Implied Volatility: The Case of the Exchange Rate Futures Mexican Peso-U.S. Dollar

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