BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Author
Płuciennik Piotr (Adam Mickiewicz University in Poznań; National Bank of Poland)
Title
Forecasting Financial Processes by Using Diffusion Models
Prognozowanie procesów finansowych za pomocą modeli dyfuzji
Source
Dynamic Econometric Models, 2010, vol. 10, s. 51-60, rys., tab., bibliogr. 30 poz.
Keyword
Symulacja Monte Carlo, Model GARCH, Modele ARIMA, Dyfuzja, Prognozowanie, Szeregi czasowe
Monte Carlo simulation, GARCH model, Autoregressive integrated moving average (ARIMA) models, Diffusion, Forecasting, Time-series
Note
summ., streszcz.
Abstract
Prognozowanie szeregów czasowych jest jednym z najważniejszych zagadnień współczesnej ekonometrii finansowej. W obliczu rosnącego zainteresowania modelami z czasem ciągłym i szybkiego rozwoju metod ich estymacji, podejmujemy w pracy próbę modelowania i prognozowania szeregów czasowych z różnych rynków finansowych za pomocą modeli dyfuzji. Stosujemy w tym celu bazującą na symulacjach Monte-Carlo metodę wprowadzoną przez Cziraky i Kucherenko (2008). Jakość otrzymanych prognoz zostaje skonfrontowana z jakością prognoz otrzymanych za pomocą powszechnie stosowanych parametrycznych modeli szeregów czasowych. (abstrakt oryginalny)

Time series forecasting is one of the most important issues in the financial econometrics. In the face of growing interest in models with continuous time, as well as rapid development of methods of their estimation, we try to use the diffusion models to modeling and forecasting time series from various financial markets. We use Monte-Carlo-based method, introduced by Cziraky and Kucherenko (2008). Received forecasts are confronted with those determined with the commonly applied parametrical time series models. (original abstract)
Accessibility
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of Poznań University of Economics and Business
Full text
Show
Bibliography
Show
  1. Black, F., Scholes, M. (1973), The Pricing of Option and Corporate Liabilities, Journal of Political Economy, 81, 637-659.
  2. Broadie, M., Jain, A. (2008), Pricing and Hedging Volatility Derivatives, Journal of Derivatives, 15, Issue 3, 7-24.
  3. Chan, K. C., Karolyi, G. A., Longstaff, F. A., Sanders, A. B. (1992), An Empirical Comparison of Alternative Models of Short Term Interest Rates, Journal of Finance, 47, 1209-1227.
  4. Cliff, M. T. (2003) GMM and MINZ Program Libraries for Matlab, Krannert Graduate School of Management Purdue University.
  5. Cox, J. C., Ingersoll, J., Ross, S. (1985), A Theory of the Term Structure of Interest Rates, Econometrica, 53, 385-407.
  6. Cziraky, D., Kucherenko, S. (2008), Monte Carlo Forecasting from CIR Square Root Diffusion Models, BRODA Ltd. http://www.broda.co.uk (8.01.2009).
  7. Detemple, J., Osakwe, S. (1999), The Valuation of Volatility Options, CIRANO Paper, Scientific Series.
  8. Doman, M., Doman, R. (2004), Econometric Modeling of Polish Financial Market Dynamic (In Polish), Poznań University of Economics, Poznań.
  9. Engle, R. F. (1982), Autoregressive Conditional Heteroscedacticity with Estimates of the Variance of United Kingsdom Inflation, Econometrica, 50, 987-1007.
  10. Hansen, L. P. (1982), Large Sample Properties of Generalized Method Of Moments Estimators, Econometrica, 50, 1029-1054.
  11. Heston, S. L. (1993), A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options, The Review of Financial Studies, 6, Issue 2, 327-343.
  12. Howison, S., Rafailidis, A., Rasmussen, H. (2004), On the Pricing and Hedging of Volatility Derivatives, Applied Mathematical Finance, 11, Issue 2, 317-346.
  13. Javaheri, A., Wilmott, P., Haug, E. (2002), GARCH and Volatility Swaps, Wilmott Magazine, January, 1-17.
  14. Jagannathan R., Kaplin A., Sun S. G. (2004), An Evaluation of Multi-Factor CIR Models Using Libor, Swap Rates, and Cap and Swaption Prices, Journal of Econometrics, 116, 113-146.
  15. Ljung, G. M., Box, G. E. P. (1978), On a Measure of Lack of fit in Time Series Models, Biometrika, 65, 297-303.
  16. Mannolini, A., Mari, C., Renò, R. (2008), Pricing Caps and Floors with the Extended CIR Model, International Journal of Finance & Economics, 13 (4) 386-400.
  17. McLeod, A. I., Li, W. K. (1983), Diagnostic Checking ARMA Time Series Models Using Squared Residual Autocorrelations, Journal of Time Series Analysis, 4, 269-273.
  18. Merton, R. C. (1973), Theory of Rational Option Pricing, Bell Journal of Economics and Management Science, 4 (1) 141-183.
  19. Merton, R. C. (1974), On The Pricing of Corporate Debt: The Risk Structure of Interest Rates, Journal of Finance, 29, 449-470.
  20. Nelson, D. (1991), Conditional Heteroskedasticity in Asset Returns: A New Approach, Econometrica, 59, 347-370.
  21. Newey, W. K., West, K. D. (1987), A Simple, Positive Semidefinite, Heteroskedasticity and Autocorrelation Consistant Covariance Matrix, Economerica, 59, 347-370.
  22. Phillips, P. C. B., Perron, P. (1988), Testing for a Unit Root in Time Series Regressions, Biometrika, 75, 335-346.
  23. Phillips, P. C. B., Yu, J. (2009), A Two-Stage Realized Volatility Approach to Estimation of Diffusion Processes with Discrete Data, Journal of Econometrics, 150, Issue 2, 139-150.
  24. Psychoyios, D., Skiadopoulos, G. (2006), Volatility Options: Hedging Effectiveness, Pricing, and Model Error, Journal of Futures Markets, 26, 1-31.
  25. Said, E., Dickey, D.A. (1984), Testing for Unit Roots in Autoregressive Moving Average Models of Unknown Order, Biometrika, 71, 599-607.
  26. Sepp, A. (2008), VIX Option Pricing in a Jump-Diffusion Model, Risk, April, 84-89.
  27. Vašiček, O. (1977), An Equilibrium Characterization of the Term Structure, Journal of Financial Economics, 5, 177-188.
  28. Tamba, Y. (2006), Pricing the Bermudan Swaption with the Efficient Calibration, NUCB Journal of Economics and Information Science, 51, Issue 1, 17-31.
  29. Welfe, A. (1998), Econometrics (In Polish), Polskie Wydawnictwo Ekonomiczne, Warszawa.
  30. Yoshida, N. (1992), Estimation for Diffusion Processes From Discrete Observation, Journal of Multivariate Analysis, 41, 220-242.
Cited by
Show
ISSN
1234-3862
Language
eng
URI / DOI
http://dx.doi.org/10.12775/DEM.2010.005
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu