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題名 考量環境保護下能源產業之財務風險管理：煉油廠實證
Financial risk management in energy industry under the environmental protection: evidence from refinery作者 王品昕
Wang, Pin Hsin貢獻者 林士貴
Lin, Shih Kuei
王品昕
Wang, Pin Hsin關鍵詞 均數回復過程
均數回復跳躍擴散過程
季節性
風險值
能源
碳權
mean-reverting process
mean-reverting jump diffusion process
seasonality
Value-at-Risk
energy
emission certificate日期 2011 上傳時間 30-Oct-2012 10:15:00 (UTC+8) 摘要 Schwarz (1997)提出均數回復過程（Mean-Reverting Process, MR）捕捉能源價格的動態過程，而Lucia and Schwarz (2002)將此模型結合確定季節性函數，並推導出期貨價格封閉解。然而，能源價格常會因為未預期事件的發生而產生大幅度的變動，為了描述價格跳躍的現象，Clewlow and Strickland (2000)延伸Schwarz的模型提出均數回復跳躍擴散模型（Mean-reverting jump diffusion process, MRJD），此模型除了保留均數回復模型對能源價格會回復至長期水準的描述外，再加上跳躍項來描述價格的異常變動。而Cartea and Figueroa (2005)則同時考慮季節性和跳躍因子，並推導出期貨價格封閉解。另外，雖然台灣目前並非京都議定書所規範的國家，但環境保護是未來的趨勢，故在衡量能源產業財務風險時，除了考慮相關原料和產品，應考慮碳權交易之影響。為了探討財務風險管理在能源產業之應用，本文以煉油廠為例，將其表示成特定期貨部位的投資組合，並透過計算投資組合風險值來衡量煉油廠的財務風險。文中使用結合季節性的均數回復過程、均數回復跳躍擴散過程進行模型配適。實證結果顯示，均數回復跳躍擴散模型在回溯測試下表現最佳；另外，考慮碳權交易後會使得煉油廠的財務風險上升。
Schwarz (1997) proposes the mean-reverting process (MR) to model energy spot price dynamics, and Lucia and Schwarz (2002) extend this model by including mean reversion and a deterministic seasonality. This model can capture the mean-reversion of energy price, but fail to account for the huge and non-negligible price movement in the market. Clewlow and Strickland (2000) extend Schwarz’s model to mean-reverting jump diffusion process (MRJD). Cartea and Figueroa (2005) present a model which captures the most importance characteristics of energy spot prices such as mean reversion, jumps and seasonality, and provide a closed-form solution for the forward. Although Taiwan is not the member of Kyoto Protocol, but Environmental Protection is a trend in the future. In order to measure the financial risk induced by energy industries, we should consider the effect of emission trading. In this paper, we discuss the implication of financial risk management in energy industries by analyzing the exposure of refinery which represented certain energy futures portfolios. We use MR and MRJD process with seasonality to model energy spot price dynamics, and calibrate the parameters to historical data. And, we consider the interaction of all of positions and calculate the Value-at-Risk of portfolios. The results show that among various approaches the MRJD presents more efficient results in back-testing, and emission trading poses additional risk factors which will increase the financial risk for refineries.參考文獻 Alberola, E., Chevallier J. and Chèze, B. (2008), “Price drivers and structural breaks in European carbon price 2005-2007,” Energy Policy 36, 787-797.Andriosopoulos, K. and Nomikos, N. (2011), "Risk management in the energy markets and Value-at-Risk modeling: a Hybrid approach,” 1st Conference of Financial Engineering and Banking Society.Ball, C. A. and Torous, W. N. (1983), “A simplified jump process for common stock returns,” Journal of Financial and Quantitative Analysis 18, 53-65.Ball, C. A. and Torous, W. N. (1985), “On jumps in common stock prices and their impact on call option pricing,” Journal of Finance 40, 155-173.Basle Committee on Banking Supervision (1996), “Supervisory framework for the use of backtesting in conjunction with the internal models approach to market risk capital requirements,” Basle: Bank for International Settlement.Bhanot, K. (2000), “Behavior of power prices: implications for the valuation and hedging of financial contracts,” Journal of Risk 2, 43-62.Black, F. and Scholes, M. (1973), “The pricing of options and corporate liabilities,” Journal of Political Economy 81, 637-654.Boerger, R. H., Cartea, Á., Kiesel, R. and Schindlmayr, G. (2009), “Cross-commodity analysis and applications to risk Management,” Journal of Futures Markets 29, 197-217. Cartea, Á. and Figueroa, M. G. (2005), “Pricing in electricity markets: a mean reverting jump diffusion model with seasonality,” Applied Mathematical Finance 12, 313-335.Christoffersen, P. (1998), “Evaluating interval forecasts,” International Economic Review 39, 841-862.Clewlow, L., and Strickland, C. (2000), “Energy derivatives: pricing and risk management,” Lacima Publications.Coase, R. (1960), “The problem of social coast,” Journal of Law and Economics 3, 1-44.Daskalakis, G., Psychoyios, D. and Markellos., R.N. (2009), “Modeling CO2 emission allowance prices and derivatives: evidence from the European trading scheme,” Journal of Banking and Finance 33, 1230-1241.Dixit, A. K. and Pindyck R. S. (1994), “Investment under uncertainty,” Princeton University Press, Princeton, NJ.Haldrup, N. and Nielsen, M. O. (2006), “A regime switching long memory model for electricity prices,” Journal of Econometrics 135, 349-76.Jorion, P. (2007), “Value at risk: The new benchmark for managing financial risk," 3rd edition, McGraw-Hill.JP Morgan (1996), “Risk Metrics,” Technical Document, New York.Kupiec, P. H. (1995), “Techniques for verifying the accuracy of risk measurement models,” Journal of Derivatives 3, 73-84. Lin, S. K., Chen, S. N. and Li, C. Y. (2012), “Valuation of CO2 emission allowance and derivatives using a regime switch jump diffusion model: evidence from the European trading scheme,” Working paper.Lucia, J. J. and Schwartz, E. S. (2002), “Electricity prices and power derivatives: Evidence from the Nordic power exchange,” Review of Derivatives Research 5, 5-50.Mauro, A. (1999), “Price risk management in the energy Industry: The value at risk approach,” Proceedings of the XXII Annual International Conference of the International Association for Energy Economics, 9-12.Marimoutou, V., Raggad, B. and Trabelsi, A. (2009), “Extreme value theory and value at risk: application to oil market,” Energy Economics 31, 519-530.Mayer, K., Schmid, T. and Weber, F. (2011), “Modeling electricity spot prices: combining mean-reversion, spikes and stochastic volatility,” Working paper.Merton, R. C. (1976), “Option pricing when underlying stock returns are discontinuous,” Journal of Financial Economics 3, 125-144.Pilipovic, D. (1997), “Energy risk: valuing and managing energy derivatives,” McGraw-Hill.Sadeghi, M. and Shavvalpour, S. (2005), “Energy risk management and value at risk modeling,” Energy policy 34, 3367-3373.Samuelson, P. A. (1965),“Proof that properly anticipated prices fluctuate randomly,” Industrial Management Review 6, 41-49.Schwartz, E. S. (1997), “The stochastic behavior of commodity prices: implications for valuation and hedging,” Journal of Finance 52, 923-973.Seifert, J., Uhig-Homburg, M. and Wanger, M. (2008), “Dynamic behavior of CO2 spot prices,” Journal of Economics and Management 56, 180-194.Weron, R. (2006), “Modeling and forecasting electricity loads and prices: a statistical approach,” Wiley Finance.Zhang, Z. (2000), “The economics of energy policy in China: implication for global climate change,” New York: Edward Elgar. 描述 碩士
國立政治大學
金融研究所
99352022
100資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099352022 資料類型 thesis dc.contributor.advisor 林士貴 zh_TW dc.contributor.advisor Lin, Shih Kuei en_US dc.contributor.author (Authors) 王品昕 zh_TW dc.contributor.author (Authors) Wang, Pin Hsin en_US dc.creator (作者) 王品昕 zh_TW dc.creator (作者) Wang, Pin Hsin en_US dc.date (日期) 2011 en_US dc.date.accessioned 30-Oct-2012 10:15:00 (UTC+8) - dc.date.available 30-Oct-2012 10:15:00 (UTC+8) - dc.date.issued (上傳時間) 30-Oct-2012 10:15:00 (UTC+8) - dc.identifier (Other Identifiers) G0099352022 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/54185 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 金融研究所 zh_TW dc.description (描述) 99352022 zh_TW dc.description (描述) 100 zh_TW dc.description.abstract (摘要) Schwarz (1997)提出均數回復過程（Mean-Reverting Process, MR）捕捉能源價格的動態過程，而Lucia and Schwarz (2002)將此模型結合確定季節性函數，並推導出期貨價格封閉解。然而，能源價格常會因為未預期事件的發生而產生大幅度的變動，為了描述價格跳躍的現象，Clewlow and Strickland (2000)延伸Schwarz的模型提出均數回復跳躍擴散模型（Mean-reverting jump diffusion process, MRJD），此模型除了保留均數回復模型對能源價格會回復至長期水準的描述外，再加上跳躍項來描述價格的異常變動。而Cartea and Figueroa (2005)則同時考慮季節性和跳躍因子，並推導出期貨價格封閉解。另外，雖然台灣目前並非京都議定書所規範的國家，但環境保護是未來的趨勢，故在衡量能源產業財務風險時，除了考慮相關原料和產品，應考慮碳權交易之影響。為了探討財務風險管理在能源產業之應用，本文以煉油廠為例，將其表示成特定期貨部位的投資組合，並透過計算投資組合風險值來衡量煉油廠的財務風險。文中使用結合季節性的均數回復過程、均數回復跳躍擴散過程進行模型配適。實證結果顯示，均數回復跳躍擴散模型在回溯測試下表現最佳；另外，考慮碳權交易後會使得煉油廠的財務風險上升。 zh_TW dc.description.abstract (摘要) Schwarz (1997) proposes the mean-reverting process (MR) to model energy spot price dynamics, and Lucia and Schwarz (2002) extend this model by including mean reversion and a deterministic seasonality. This model can capture the mean-reversion of energy price, but fail to account for the huge and non-negligible price movement in the market. Clewlow and Strickland (2000) extend Schwarz’s model to mean-reverting jump diffusion process (MRJD). Cartea and Figueroa (2005) present a model which captures the most importance characteristics of energy spot prices such as mean reversion, jumps and seasonality, and provide a closed-form solution for the forward. Although Taiwan is not the member of Kyoto Protocol, but Environmental Protection is a trend in the future. In order to measure the financial risk induced by energy industries, we should consider the effect of emission trading. In this paper, we discuss the implication of financial risk management in energy industries by analyzing the exposure of refinery which represented certain energy futures portfolios. We use MR and MRJD process with seasonality to model energy spot price dynamics, and calibrate the parameters to historical data. And, we consider the interaction of all of positions and calculate the Value-at-Risk of portfolios. The results show that among various approaches the MRJD presents more efficient results in back-testing, and emission trading poses additional risk factors which will increase the financial risk for refineries. en_US dc.description.tableofcontents 1 緒論 11.1 研究動機與背景 11.2 研究目的 31.3 研究架構 32 文獻回顧 42.1 能源價格動態模型回顧 42.2 能源投資組合之風險管理 62.3 碳權交易市場 82.3.1 京都議定書之彈性減量機制與碳排放市場 92.3.2 碳權相關文獻 103 模型與期貨理論價格 123.1 對數價格模型 123.1.1 季節性 133.1.2 均數回復過程 143.1.3 均數回復跳躍擴散過程 153.2 期貨理論價格 163.2.1 MR期貨理論價格 163.2.2 MRJD期貨理論價格 173.2.3 波動度 184 估計與檢定 194.1 估計 194.1.1 估計季節性函數 194.1.2 估計MR模型 204.1.3 估計MRJD模型 224.1.4 估計風險溢酬 244.2 概似度比檢定 245 實證分析 265.1 研究樣本 275.2 資料分析與參數估計 285.2.1 敘述統計 285.2.2 季節性 285.2.3 參數估計與檢定 305.3 煉油廠投資組合 305.4 風險值 326 結論 34參考文獻 35附錄A：證明MRJD模型的期貨價格封閉解 38 zh_TW dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099352022 en_US dc.subject (關鍵詞) 均數回復過程 zh_TW dc.subject (關鍵詞) 均數回復跳躍擴散過程 zh_TW dc.subject (關鍵詞) 季節性 zh_TW dc.subject (關鍵詞) 風險值 zh_TW dc.subject (關鍵詞) 能源 zh_TW dc.subject (關鍵詞) 碳權 zh_TW dc.subject (關鍵詞) mean-reverting process en_US dc.subject (關鍵詞) mean-reverting jump diffusion process en_US dc.subject (關鍵詞) seasonality en_US dc.subject (關鍵詞) Value-at-Risk en_US dc.subject (關鍵詞) energy en_US dc.subject (關鍵詞) emission certificate en_US dc.title (題名) 考量環境保護下能源產業之財務風險管理：煉油廠實證 zh_TW dc.title (題名) Financial risk management in energy industry under the environmental protection: evidence from refinery en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) Alberola, E., Chevallier J. and Chèze, B. (2008), “Price drivers and structural breaks in European carbon price 2005-2007,” Energy Policy 36, 787-797.Andriosopoulos, K. and Nomikos, N. (2011), "Risk management in the energy markets and Value-at-Risk modeling: a Hybrid approach,” 1st Conference of Financial Engineering and Banking Society.Ball, C. A. and Torous, W. N. (1983), “A simplified jump process for common stock returns,” Journal of Financial and Quantitative Analysis 18, 53-65.Ball, C. A. and Torous, W. N. (1985), “On jumps in common stock prices and their impact on call option pricing,” Journal of Finance 40, 155-173.Basle Committee on Banking Supervision (1996), “Supervisory framework for the use of backtesting in conjunction with the internal models approach to market risk capital requirements,” Basle: Bank for International Settlement.Bhanot, K. (2000), “Behavior of power prices: implications for the valuation and hedging of financial contracts,” Journal of Risk 2, 43-62.Black, F. and Scholes, M. (1973), “The pricing of options and corporate liabilities,” Journal of Political Economy 81, 637-654.Boerger, R. H., Cartea, Á., Kiesel, R. and Schindlmayr, G. (2009), “Cross-commodity analysis and applications to risk Management,” Journal of Futures Markets 29, 197-217. Cartea, Á. and Figueroa, M. G. (2005), “Pricing in electricity markets: a mean reverting jump diffusion model with seasonality,” Applied Mathematical Finance 12, 313-335.Christoffersen, P. (1998), “Evaluating interval forecasts,” International Economic Review 39, 841-862.Clewlow, L., and Strickland, C. (2000), “Energy derivatives: pricing and risk management,” Lacima Publications.Coase, R. (1960), “The problem of social coast,” Journal of Law and Economics 3, 1-44.Daskalakis, G., Psychoyios, D. and Markellos., R.N. (2009), “Modeling CO2 emission allowance prices and derivatives: evidence from the European trading scheme,” Journal of Banking and Finance 33, 1230-1241.Dixit, A. K. and Pindyck R. S. (1994), “Investment under uncertainty,” Princeton University Press, Princeton, NJ.Haldrup, N. and Nielsen, M. O. (2006), “A regime switching long memory model for electricity prices,” Journal of Econometrics 135, 349-76.Jorion, P. (2007), “Value at risk: The new benchmark for managing financial risk," 3rd edition, McGraw-Hill.JP Morgan (1996), “Risk Metrics,” Technical Document, New York.Kupiec, P. H. (1995), “Techniques for verifying the accuracy of risk measurement models,” Journal of Derivatives 3, 73-84. Lin, S. K., Chen, S. N. and Li, C. Y. (2012), “Valuation of CO2 emission allowance and derivatives using a regime switch jump diffusion model: evidence from the European trading scheme,” Working paper.Lucia, J. J. and Schwartz, E. S. (2002), “Electricity prices and power derivatives: Evidence from the Nordic power exchange,” Review of Derivatives Research 5, 5-50.Mauro, A. (1999), “Price risk management in the energy Industry: The value at risk approach,” Proceedings of the XXII Annual International Conference of the International Association for Energy Economics, 9-12.Marimoutou, V., Raggad, B. and Trabelsi, A. (2009), “Extreme value theory and value at risk: application to oil market,” Energy Economics 31, 519-530.Mayer, K., Schmid, T. and Weber, F. (2011), “Modeling electricity spot prices: combining mean-reversion, spikes and stochastic volatility,” Working paper.Merton, R. C. (1976), “Option pricing when underlying stock returns are discontinuous,” Journal of Financial Economics 3, 125-144.Pilipovic, D. (1997), “Energy risk: valuing and managing energy derivatives,” McGraw-Hill.Sadeghi, M. and Shavvalpour, S. (2005), “Energy risk management and value at risk modeling,” Energy policy 34, 3367-3373.Samuelson, P. A. (1965),“Proof that properly anticipated prices fluctuate randomly,” Industrial Management Review 6, 41-49.Schwartz, E. S. (1997), “The stochastic behavior of commodity prices: implications for valuation and hedging,” Journal of Finance 52, 923-973.Seifert, J., Uhig-Homburg, M. and Wanger, M. (2008), “Dynamic behavior of CO2 spot prices,” Journal of Economics and Management 56, 180-194.Weron, R. (2006), “Modeling and forecasting electricity loads and prices: a statistical approach,” Wiley Finance.Zhang, Z. (2000), “The economics of energy policy in China: implication for global climate change,” New York: Edward Elgar. zh_TW
