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Testing for linear autoregressive dynamics under heteroskedasticity
Hafner, Christian M.; Herwartz, Helmut - Sonderforschungsbereich 373, Quantifikation und … - 1998
the volatility process we assume GARCH, TGARCH and stochastic volatility. The results indicate that standard QML inference …
Persistent link: https://www.econbiz.de/10010956379
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Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis
Hafner, Christian M.; Herwartz, Helmut - Sonderforschungsbereich 373, Quantifikation und … - 1999
suggest that a non-zero autoregression coefficient tends to increase the deviation of option prices from Black & Scholes …
Persistent link: https://www.econbiz.de/10010956419
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Testing for linear autoregressive dynamics under heteroskedasticity
HAFNER, CHRISTIAN M.; HERWARTZ, HELMUT - In: Econometrics Journal 3 (2000) 2, pp. 177-197
the volatility process we assume GARCH, TGARCH and stochastic volatility. The results indicate that standard quasi …
Persistent link: https://www.econbiz.de/10005243397
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Asymptotic and Bootstrap Inference for AR(∞) Processes with Conditional Heteroskedasticity
Goncalves, Silvia; Kilian, Lutz - In: Econometric Reviews 26 (2007) 6, pp. 609-641
The main contribution of this paper is a proof of the asymptotic validity of the application of the bootstrap to AR(∞) processes with unmodelled conditional heteroskedasticity. We first derive the asymptotic properties of the least-squares estimator of the autoregressive sieve parameters when...
Persistent link: https://www.econbiz.de/10005511987
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Adaptive Estimation and Prediction of Univariate Vehicular Traffic Condition Series
Guo, Jianhua - 2005
two conditional moments of univariate traffic flow series can be modeled as a SARIMA+GARCH structure, based on which an … smoothing; the local variation is processed using Kalman filter by constructing a state space model. Afterwards, GARCH model is … processed using Kalman filter based on the recognition that GARCH has an equivalent representation as ARMA in the sense of …
Persistent link: https://www.econbiz.de/10009431160
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A GRAS VARIANT SOLVING FOR MINIMUM INFORMATION LOSS
Lemelin, Andre - In: Economic Systems Research 21 (2009) 4, pp. 399-408
The fundamental idea in Junius and Oosterhaven (2003) is to break down the information contained in the a priori data into two parts: algebraic signs, and absolute values. This approach is well grounded in information theory, and provides a basis on which to solve the problem of adjusting...
Persistent link: https://www.econbiz.de/10009223057
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An introduction to maximum entropy and minimum cross-entropy estimation using Stata
Wittenberg, Martin - In: Stata Journal 10 (2010) 3, pp. 315-330
Maximum entropy and minimum cross-entropy estimation are applica- ble when faced with ill-posed estimation problems. I introduce a Stata command that estimates a probability distribution using a maximum entropy or minimum cross-entropy criterion. I show how this command can be used to calibrate...
Persistent link: https://www.econbiz.de/10008677211
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The Relationship Between Energy Spot And Futures Prices: Evidence From The Australian Electricity Market
Worthington, Andrew C.; Higgs, Helen - 2004
conditional heteroskedasticity (GARCH) model is used to identify the magnitude and significance of mean and volatility spillovers … of strong ARCH and GARCH effects. Contrary to evidence from studies in North American electricity markets, the results …
Persistent link: https://www.econbiz.de/10009437450
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Market, interest rate and foreign exchange rate risk in Australian banking: A GARCH-M approach
Ryan, Suzanne K.; Worthington, Andrew C. - 2004
This study employs an extended version of the Generalised Autoregressive Conditional Heteroskedasticity in Mean (GARCH …
Persistent link: https://www.econbiz.de/10009437451
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Multivariate GARCH hedge ratios and hedging effectiveness in Australian Futures Markets
Yang, Wenling; Allen, David E - 2005
vector autoregression, a vector error-correction model and a diagonal-vec multivariate generalized autoregressive conditional …
Persistent link: https://www.econbiz.de/10009440863