Abstract
The aim of this study is to model steel price returns by Lévy process. The daily
LME Steel Billets Spot Prices between 04.01. 2010 and 31.10.2011 are analyzed
and AR[1] ~ GARCH[1,1] discrete model is found to be the best candidate taking
all indicators into account. Then the continuous analogue of the discrete model is
derived from the discrete model parameters. During the overall study, time
(pathwise), distributional and spectral analysis performed. Finally, it is shown that
the volatility simulated from both discrete and continuous models shows similar
volatility patterns. The results of the study could be utilized to predict the
behavior of future steel prices’ moves. In addition, the finding could be a good
reference specialist and researchers who are interested in steel market.
Keywords
Steel Modelling ARMA GARCH COGARCH Lévy Processes Discrete Time Models Continuous Time Models Stochastic Modelling
References
- Barndorff-Nielsen, Ole E., Neil Shepherd (2001), “Non-Gaussian Ornstein
- Uhlenbeck Based Models and some of their Use in Financial Economics (with discussion)”, Journal of Royal Statistics Society Series B, Vol. 63, pp.167-241. Christian Kleiber and Samuel Kotz (2003), “Statistical Size Distributions in
- Economics and Actuarial Sciences”, Wiley Series in Probability and Statistics. Duan, Jin Chuan (1997), “Augmented GARCH (p,q) Process and Its Diffusion
- Limit”, Journal of Econometrics, Vol. 79, pp.97-127. Geman Hélyette (2005), “Commodities and Commodity Derivatives: Modelling and Pricing for Agriculturals, Metals and Energy”, Wiley Finance.
- Klüppelberg Claudia, Alexander Lindner and Ross Maller (2004), “A Continuous
- Time GARCH Process Driven by a Lévy Process: Stationary and Second Order Behaviour”, Journal of Applied Probability, Vol. 41, pp.601-622. Klüppelberg Claudia, Alexander Lindner and Ross Maller (2006), “Continuous
- Time Volatility Modelling: COGARCH versus Ornstein-Uhlenbeck Models”,(in: Yuri Kabanov, Robert Lipster and Jordan Stoyanov-Eds, From Stochastic Calculus to Mathematical Finance), Springer:Berlin, pp.393-419. Nelson, Daniels B. (1990), “ARCH Models as Diffusion Approximation”, Journal of Econometrics, Vol. 45, pp.7-38.
- Ross A. M., Gernot M. and Alex S. (2008), “GARCH Modelling in Continuous
- Time for Irregular Spaced Time Series Data”, Bernoulli, Vol. 14, pp.519-542. Ross A. Maller, Gernot Müller and Alex Szimayer (2009), “Ornstein-Uhlenbeck
- Processes and Extensions”, Handbook of Financial Time Series. Tim Heteroscedasticity”, Journal of Econometrics, Vol. 31, pp.307-327. (1986), “Generalized Autoregressive Conditionally
Abstract
References
- Barndorff-Nielsen, Ole E., Neil Shepherd (2001), “Non-Gaussian Ornstein
- Uhlenbeck Based Models and some of their Use in Financial Economics (with discussion)”, Journal of Royal Statistics Society Series B, Vol. 63, pp.167-241. Christian Kleiber and Samuel Kotz (2003), “Statistical Size Distributions in
- Economics and Actuarial Sciences”, Wiley Series in Probability and Statistics. Duan, Jin Chuan (1997), “Augmented GARCH (p,q) Process and Its Diffusion
- Limit”, Journal of Econometrics, Vol. 79, pp.97-127. Geman Hélyette (2005), “Commodities and Commodity Derivatives: Modelling and Pricing for Agriculturals, Metals and Energy”, Wiley Finance.
- Klüppelberg Claudia, Alexander Lindner and Ross Maller (2004), “A Continuous
- Time GARCH Process Driven by a Lévy Process: Stationary and Second Order Behaviour”, Journal of Applied Probability, Vol. 41, pp.601-622. Klüppelberg Claudia, Alexander Lindner and Ross Maller (2006), “Continuous
- Time Volatility Modelling: COGARCH versus Ornstein-Uhlenbeck Models”,(in: Yuri Kabanov, Robert Lipster and Jordan Stoyanov-Eds, From Stochastic Calculus to Mathematical Finance), Springer:Berlin, pp.393-419. Nelson, Daniels B. (1990), “ARCH Models as Diffusion Approximation”, Journal of Econometrics, Vol. 45, pp.7-38.
- Ross A. M., Gernot M. and Alex S. (2008), “GARCH Modelling in Continuous
- Time for Irregular Spaced Time Series Data”, Bernoulli, Vol. 14, pp.519-542. Ross A. Maller, Gernot Müller and Alex Szimayer (2009), “Ornstein-Uhlenbeck
- Processes and Extensions”, Handbook of Financial Time Series. Tim Heteroscedasticity”, Journal of Econometrics, Vol. 31, pp.307-327. (1986), “Generalized Autoregressive Conditionally
Details
| Other ID | JA74SE56HH |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | June 1, 2012 |
| Published in Issue | Year 2012 Volume: 4 Issue: 1 |