Ornstein-Uhlenbeck process and GARCH model for temperature forecasting in weather derivatives valuation

1. Alaton, P., Djehiche, B., Stillberger, D. (2002). On Modelling and Pricing of Weather Derivatives. Applied mathematical finance journal, Vol. 9, No. 1, pp- 1-20.10.1080/13504860210132897Search in Google Scholar

2. Alexandridis, A. K., Zapranis, A. D. (2007). Wavelet Neural Networks for Weather Derivatives Pricing. 6th Hellenic Finance and Accounting Association Conference, Patra.Search in Google Scholar

3. Bahovec, V., Erjavec, N. (2009). Uvod u ekonometrijsku analizu. Element, Zagreb.Search in Google Scholar

4. Baković, T., Lazibat, T., Štulec, I. (2011). Specifičnosti trgovanja vremenskim derivativema ovisno o organiziranosti terminskog tržišta. Zbornik Ekonomskog fakulteta u Zagrebu, Vol. 9, No. 1, pp. 1-16.Search in Google Scholar

5. Benth, F. E., Benth, J. Š. (2007). The volatility of temperature and pricing of weather derivatives. Journal of Quantitative Finance, Vol. 7, No. 5, pp. 553-561.10.1080/14697680601155334Search in Google Scholar

6. Berliner, L. M. (2001). Monte Carlo Based Ensemble Forecasting. Statistics in Computing, Vol. 11, No. 3, pp. 269-275.10.1023/A:1016656422040Search in Google Scholar

7. Buizza, R., Taylor J. W. (2004). A Comparison of Temperature Density Forecast from GARCH and Atmospheric Models. Journal of forecasting, Vol. 23, No. 5, pp. 337-355.Search in Google Scholar

8. Campbell, S. D., Diebold F. X. (2005). Weather Forecasting for Weather Derivatives. Journal of American Statistical Association, March 2005, pp. 1-11.10.1198/016214504000001051Search in Google Scholar

9. Cao, M., Li, A. (2003). Weather derivatives: New Class of Financial Instruments. Rotman School of Management.10.2139/ssrn.1016123Search in Google Scholar

10. Chai, T, Draxler, R. R. (2014). Root mean square error (RMSE) or mean absolute error (MAE)?. Geoscientific Model Development, Vol. 7, No. 1, pp. 1247-1250.10.5194/gmd-7-1247-2014Search in Google Scholar

11. Considine, J. (2000). Introduction to Weather Derivatives. Agroinsurance, pp. 1-10.Search in Google Scholar

12. Dall’Amico, M., Hornsteiner, M. (2006). A Simple Method for Estimating Daily and Monthly Mean Temperatures from Daily Minima and Maxima. International Journal of Climatology, Vol. 26, No. 1, pp. 1930-1936.10.1002/joc.1363Search in Google Scholar

13. Frances, H. P., Dijk, D. (1996). Forecasting Stock Market Volatility Using (Non-Linear) Garch Model. Journal of Forecasting, Vol. 15, No. 1, pp. 229-235.10.1002/(SICI)1099-131X(199604)15:3<229::AID-FOR620>3.0.CO;2-3Search in Google Scholar

14. Gilks, W. R., Richardson, S., Spiegelhalter, D. J. (1996). Markov Chain Monte Carlo in Practice. Chapman & Hall, London.Search in Google Scholar

15. Gillespie, D. T. (1990). Exact Numerical Simulation of the Ornstein-Uhlenbeck Process and its Integral. Physical review, Vol. 4, No. 2, pp. 1-8.Search in Google Scholar

16. Hanke, J. E., Witchern, D. (2014). Business Forecasting. Pearson Education Limited, Essex.Search in Google Scholar

17. Kӧlbl, F. (2016). Aggregation of AR (2) process. Diplomarbeit. Technische Universität Graz.Search in Google Scholar

18. Lazibat, T., Županić, I. (2010). Vremenske izvedenice kao instrument upravljanja vremenskim rizikom. Poslovna izvrsnost, Vol. 4, No. 2, pp. 93-105.Search in Google Scholar

19. Lewis, C.D. (1982). Industrial and business forecasting methods. Butterworths, London.Search in Google Scholar

20. Manikandan, S. (2011). Measures of central tendency: Median and mode. Journal of Pharmacology and Pharmacotherapeutics, Vol. 2, No. 3, pp. 214-215.10.4103/0976-500X.83300Search in Google Scholar

21. Ornstein, L. S., Uhlenbeck, G. E. (1930). On the Theory of the Brownian Motion. Physical review, Vol. 36, No. 1, pp. 1-19.Search in Google Scholar

22. Orsag, S. (2011). Vrijednosni papiri: Investicije i instrumenti financiranja. Revicon, Sarajevo.Search in Google Scholar

23. Samso, J. (2018). New weather supercomputer to be installed in Bologna. Available at: https://www.euronews.com/2018/11/14/new-weather-supercomputer-to-be-installed-in-bologna [13 August 2019].Search in Google Scholar

24. Schiller, F., Seidler, G., Wimmer, M. (2012). Temperature Models for Pricing Weather Derivatives. Quantitative Finance Journal, Vol. 12, No. 3, pp. 489-500.10.1080/14697681003777097Search in Google Scholar

25. Till, H. (2015). Why Haven’t Weather Derivatives been more Successful as Futures Contracts? A Case Study. Journal of Governance and Regulation, Vol. 4, No. 4, pp. 367-371.10.22495/jgr_v4_i4_c3_p1Search in Google Scholar

26. Vidić, S. (2019). Zagreb Maksimir Temperature 2000-2018. E-mail.Search in Google Scholar