English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 111321/142230 (78%)
Visitors : 48402185      Online Users : 830
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/77626


    Title: 跳躍風險與隨機波動度下溫度衍生性商品之評價
    Pricing Temperature Derivatives under Jump Risks and Stochastic Volatility
    Authors: 莊明哲
    Chuang, Ming Che
    Contributors: 林士貴
    Lin, Shih Kuei
    莊明哲
    Chuang, Ming Che
    Keywords: 日均溫
    冷氣指數/暖氣指數衍生性商品
    風險中立評價法
    隨機波動度
    跳躍風險
    粒子濾波演算法
    期望最大演算法
    daily average temperature index
    CDD/HDD derivatives
    risk-neutral pricing method
    stochastic volatility
    jump risk
    particle filter algorithm
    expectation-maximization algorithm
    Date: 2015
    Issue Date: 2015-08-17 15:02:39 (UTC+8)
    Abstract: 本研究利用美國芝加哥商品交易所針對 18 個城市發行之冷氣指數/暖氣指數衍生性商品與相對應之日均溫進行分析與評價。研究成果與貢獻如下:一、延伸 Alaton, Djehince, and Stillberg (2002) 模型,引入跳躍風險、隨機波動度、波動跳躍等因子,提出新模型以捕捉更多溫度指數之特徵。二、針對不同模型,分別利用最大概似法、期望最大演算法、粒子濾波演算法等進行參數估計。實證結果顯示新模型具有較好之配適能力。三、利用 Esscher 轉換將真實機率測度轉換至風險中立機率測度,並進一步利用 Feynman-Kac 方程式與傅立葉轉換求出溫度模型之機率分配。四、推導冷氣指數/暖氣指數期貨之半封閉評價公式,而冷氣指數/暖氣指數期貨之選擇權不存在封閉評價公式,則利用蒙地卡羅模擬進行評價。五、無論樣本內與樣本外之定價誤差,考慮隨機波動度型態之模型對於溫度衍生性商品皆具有較好之評價績效。六、實證指出溫度市場之市場風險價格為負,顯示投資人承受較高之溫度風險時會要求較高之風險溢酬。本研究可給予受溫度風險影響之產業,針對衍生性商品之評價與模型參數估計上提供較為精準、客觀與較有效率之工具。
    This study uses the daily average temperature index (DAT) and market price of the CDD/HDD derivatives for 18 cities from the CME group. There are some contributions in this study: (i) we extend the Alaton, Djehince, and Stillberg (2002)`s framework by introducing the jump risk, the stochastic volatility, and the jump in volatility. (ii) The model parameters are estimated by the MLE, the EM algorithm, and the PF algorithm. And, the complex model exists the better goodness-of-fit for the path of the temperature index. (iii) We employ the Esscher transform to change the probability measure and derive the probability density function of each model by the Feynman-Kac formula and the Fourier transform. (iv) The semi-closed form of the CDD/HDD futures pricing formula is derived, and we use the Monte-Carlo simulation to value the CDD/HDD futures options due to no closed-form solution. (v) Whatever in-sample and out-of-sample pricing performance, the type of the stochastic volatility performs the better fitting for the temperature derivatives. (vi) The market price of risk differs to zero significantly (most are negative), so the investors require the positive weather risk premium for the derivatives. The results in this study can provide the guide of fitting model and pricing derivatives to the weather-linked institutions in the future.
    Reference: [1] Alaton, P., B. Djehince, and D. Stillberg, 2002, "On Modelling and Pricing Weather Derivatives," Applied Mathematical Finance, Vol. 9, 1-20.
    [2] Andricopoulos, A. D., M. Widdicks, P. W. Duck, and D. P. Newton, 2003, "Universal Option Valuation Using Quadrature Methods," Journal of Financial Economics, Vol. 67, 447-471.
    [3] Andricopoulos, A. D., M. Widdicks, D. P. Newton, and P. W. Duck, 2007, "Extending Quadrature Methods to Value Multi-Asset and Complex Path Dependent Options," Journal of Financial Economics, Vol. 83, 471-499.
    [4] Bates, D. S., 2001, "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," Review of Financial Studies, Vol. 9, 69-107.
    [5] Barndorff-Nielsen, O. E. and N. Shephard, 2001, "Non-Gaussian Ornstein-Uhlenbeck-Based Models and Some of Their Uses in Financial Economics," Journal of the Royal Statistical Society. Series B, Vol. 63, 167-241.
    [6] Bellini, F., 2005, "The Weather Derivatives Market: Modelling and Pricing Temperature," Ph.D. thesis, University of Lugano.
    [7] Benth, F. E. and J. Saltyte-Benth, 2005, "Stochastic Modelling of Temperature Variations with a View Towards Weather Derivatives," Applied Mathematical Finance, Vol. 12, 53-85.
    [8] Benth, F. E. and J. Saltyte-Benth, 2007, "The Volatility of Temperature and Pricing of Weather Derivatives," Quantitative Finance, Vol. 7, 553-561.
    [9] Benth, F. E. and J. Saltyte-Benth, 2011, "Weather Derivatives and Stochastic Modelling of Temperature," International Journal of Stochastic Analysis, Vol. 2011, 1-21.
    [10] Bibby, B. M., and M. Sorensen, 1995, "Martingale Estimation Functions for Discretely Observed Diffusion Processes," Bernoulli, Vol. 1, 17-39.
    [11] Black, F. and M. Scholes, 1973, "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, Vol. 81, 637-654.
    [12] Bollerslev, T, 1986, "Generalized Autoregressive Conditional Heteroscedasticity," Journal of Econometrics, Vol. 31, 307-327.
    [13] Brody, D. C., J. Syroka, and M. Zervos, 2002, "Dynamical Pricing of Weather Derivatives," Quantitative Finance, Vol. 2, 189-198.
    [14] Campbell, S. D. and F. X. Diebold, 2005, "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, Vol. 100, 6-16.
    [15] Cao, M. and J. Wei, 1999, "Pricing Weather Derivatives: An Equilibrium Approach," Working Paper, Rotman Graduate School of Management, The University of Toronto.
    [16] Cao, M. and J. Wei, 2000, "Pricing the Weather," Risk Weather Risk Special Report, Energy Power Risk Manage, 67-70.
    [17] Cao, M. and J. Wei, 2004, "Weather Derivatives Valuation and Market Price of Weather Risk," Journal of Futures Markers, Vol. 24, 1065-1089.
    [18] Carpenter, J., P. Clifford, and P. Fearnhead, 1999, "Improved Particle Filter for Nonlinear Problems," Radar, Sonar and Navigation, IEE Proceedings, Vol. 46, 2-7.
    [19] Chen, D., H. J. Harkonen, and D. P. Newton, 2014, "Advancing the Universality of Quadrature Methods to any Underlying Process for Option Pricing," Journal of Financial Economics, Vol. 114, 600-612.
    [20] Christoffersen, P., K. Jacobs, and K. Mimouni, 2010, "Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns, and Option Prices," Review of Financial Studies, Vol. 23, 3141-3189.
    [21] Cox, J. C., J. E. Ingersoll, and S. A. Ross , 1985, "A Theory of the Term Structure of Interest Rates," Econometrica, Vol. 53, 385-408.
    [22] Davis, M., 2001, "Pricing Weather Derivatives by Marginal Value," Quantitative Finance, Vol. 1, 1-4.
    [23] Diebold, F. X., 2001, "Modeling the Persistence of Conditional Variances: A Comment," Econometric Reviews, Vol. 5, 51-56.
    [24] Doucet, A., S. Godsill, and C. Andrieu, 2000, "On Sequential Monte Carlo Sampling Methods for Bayesian Filtering," Statistics and Computing, Vol. 10, 197-208.
    [25] Duan, J. C., P. Ritchken, and Z. Sun, 2004, "Jump Starting GARCH: Pricing and Hedging Options with Jumps in Returns and Volatilities," Working Paper, University of Toronto and Case Western Reserve University.
    [26] Duan, J. C., P. Ritchken, and Z. Sun, 2006, "Approximating GARCH-Jump Models, Jump-Diffusion Processes, and Option Pricing," Mathematical Finance, Vol. 16, 21-52.
    [27] Duffie, D., J. Pan, and K. Singleton, 2000, "Transform Analysis and Asset Pricing for Affine Jump-Diffusions," Econometrica, Vol. 68, 1343-1376.
    [28] Engle, R. F, 1990, "Stock Volatility and the Crash of `87: Discussion," Review of Financial Studies, Vol. 3, 103-106.
    [29] Engle, R. F. and T. Bollerslev, 1986, "Modelling the Persistence of Conditional Variances," Econometric Reviews, Vol. 5, 1-50.
    [30] Feller, W, 1951, "Two Singular Diffusion Problems," Annals of Mathematics, Vol. 54, 173-182.
    [31] Geweke, J., 1986, "Modeling the Persistence of Conditional Variances: A Comment," Econometric Review, Vol. 5, 57-61.
    [32] Glosten, L., R. Jagannathan, and D. Runkle, 1993, "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, Vol. 48, 1779-1801.
    [33] Godsill, S. J., A. Doucet, and M. West, 2004, "Monte Carlo Smoothing for Nonlinear Time Series," Journal of the American Statistical Association, Vol. 99, 156-168.
    [34] Gordon, N. J., D. J. Salmond, and A. F. M. Smith, 1993, "Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation," Radar and Signal Processing, IEE Proceedings F, Vol. 140, 107-113.
    [35] Heston, S. L, 1993, "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Vol. 6, 327-343.
    [36] Heston, S. L. and S. Nandi, 2000, "The Closed-Form GARCH Option Valuation Model," Review of Financial Studies, Vol. 13, 585-625.
    [37] Huang, H. H., Y. M. Shiu, and P. S. Lin, 2008, "HDD and CDD Option Pricing with Market Price of Weather Risk for Taiwan," Journal of Futures Markets, Vol. 28, 790-814.
    [38] Hull, J. and A, White, 1990, "Pricing Interest-Rate-Derivative Securities," Review of Financial Studies, Vol. 3, 573-592.
    [39] Lau, K. M. and H.Weng, 1995, "Climate Signal Detection UsingWavelet Transform: How to Make a Time Series Sing," Bulletin of the American Meteorological Society, Vol. 76, 2391-2402.
    [40] Liu, J. S., R. Chen, and W. H. Wong, 1998, "Rejection Control For Sequential Importance Sampling," Journal of the American Statistical Association, Vol. 93, 1022-1031.
    [41] Lucas, R. E., 1978, "Asset Prices in an Exchange Economy," Econometrica, Vol. 46, 1429-1445.
    [42] Morlet, J., 1983, "Sampling Theory and Wave Propagation," NATO ASI Series, Vol. 1, Springer, 233-261.
    [43] Nelson, D., 1990, "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Vol. 59, 347-370.
    [44] Nelson, D. B. and S. P. Foster, 1994, "Asymptotic Filtering Theory for Univariate Arch Models," Econometrica, Vol. 62, 1-41.
    [45] Pillaya, E. and J.G. O`Hara, 2011, "FFT Based Option Pricing under A Mean Reverting Process with Stochastic Volatility and Jumps," Journal of Computational and Applied Mathematics, Vol. 235, 3378-3384.
    [46] Pitt, M. K. and N. Shephard, 1999, "Filtering via Simulation: Auxiliary Particle Filters," Journal of the American Statistical Association, Vol. 94, 590-599.
    [47] Schwert, G. W, 1990, "Stock Volatility and the Crash of `87," Review of Financial Studies, Vol. 3, 77-102.
    [48] Sentana, E., 1995, "Quadratic ARCH Models," Review of Economic Studies, Vol. 62, 639-661.
    [49] Vasicek, O. A., 1977, "An Equilibrium Characterization of the Term Structure," Journal of Financial Economics, Vol. 5, 177-188.
    [50] Wong, H. Y. and Y. W. Lo, 2009, "Option Pricing with Mean Reversion and Stochastic Volatility," European Journal of Operational Research, Vol. 197, 179-187.
    [51] Zakoian, J., 1994, "Threshold Heteroskedastic Models," Journal of Economic Dynamics and Control, Vol. 18, 931-955.
    [52] Zapranis, A. and A. Alexandridis, 2008, "Modelling the Temperature Time Dependent Speed of Mean Reversion in the Context of Weather Derivatives Pricing," Applied Mathematical Finance, Vol. 15, 355-368.
    [53] Zapranis, A. and A. Alexandridis, 2009a, "Modeling and Forecasting CAT and HDD Indices For Weather Derivative Pricing," In: EANN 2009, London, Springer, 210-222.
    [54] Zapranis, A. and A. Alexandridis, 2009b, "Weather Derivatives Pricing: Modeling the Seasonal Residual Variance of an Ornstein-Uhlenbeck Temperature Process with Neural Networks," Neurocomputing, Vol. 73, 37-48.
    Description: 博士
    國立政治大學
    金融研究所
    100352503
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0100352503
    Data Type: thesis
    Appears in Collections:[Department of Money and Banking] Theses

    Files in This Item:

    File SizeFormat
    250301.pdf4929KbAdobe PDF2105View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback