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題名 天氣事件對台灣不同產業股價報酬率的影響
The Impacts of Weather Events on the Taiwan Stock Returns of Different Industries
作者 賴穎緻
貢獻者 徐燕山
賴穎緻
關鍵詞 颱風
異常報酬
事件研究法
符號檢定
日期 2012
上傳時間 22-Jul-2013 11:13:15 (UTC+8)
摘要 近年來氣候變遷議題興起，天氣災害對於實體經濟的影響也愈來愈嚴重，因此相關研究也開始在國際間出現，使用許多不同的角度來審視氣候變遷與天氣事件對經濟的影響。
以台灣而言，最明顯的天氣事件便是颱風，而在近幾年因為氣候變遷，導致颱風降雨型態變化，水文災害有愈來愈嚴重的趨勢，本研究的目的在研究台灣重大氣候事件對於台灣產業的影響，以極端降雨前十名的颱風為事件，使用事件研究法來確認颱風事件對股價報酬率的衝擊。選定的九個產業分別為水泥工業、食品工業、航運業、營建業、汽車工業、觀光業、鋼鐵工業、油電燃氣業和貿易百貨業。若以整體事件期間來看，食品工業、觀光業和油電燃氣業、貿易百貨業的影響較大。分個別產業以t統計量檢定之，發現大部分股價報酬率在颱風警報發布日加計前後三個交易日並未出現顯著的異常報酬，只有汽車工業的受到較為明顯的負向影響。而如果以符號檢定來進行檢定，則可以發現顯著性較t統計檢定來得高上許多，其中食品工業所受衝擊，無論在事件日前後皆呈現明顯的負向影響，顯示颱風可能造成食品工業負向的異常報酬率；航運業、營建業、和鋼鐵工業則出現了在事件日之前顯著偏正、事件日之後顯著偏負的情形。水泥工業、汽車工業、觀光業、油電燃氣業與貿易百貨業相比起來則相對比較輕微。兩種檢定結果相差甚多，可能是因為極端值的存在所造成的影響。
從結果來看，颱風事件對於台灣股市確實存在其影響力，但效果在各個產業間有所不同，並且隨著時間點的變化，可能會出現正負反轉的現象，也因此可能造成在整體來看顯著性並不強烈的現象。以迴歸模式診斷，發現特定產業的異常報酬率的確可以由雨量解釋之。
Recently, the concern about climate change has become one of the hottest issues around the world. There are more and more related researches published, using different dimensions to evaluate the impacts of climate change and weather events on economy.
In Taiwan, the most frequent weather event is typhoon. In addition, due to the climate change, the modes of typhoons’ rainfalls have changed drastically, making the damages and losses become worse and worse. This paper uses top-10 heavy-rainfall typhoons to identify whether there exists impact of typhoon on the stock returns of different industries in Taiwan. Industries include Cement, Food, Transport, Construction, Automobile, Tourism, Iron and Steel, Energy and Trading and department store, totaling nine industries. According to the sign test results, the impact of typhoons on stock returns is different from industry to industry. Food industry is affected negatively in the whole period. Transport, Construction, and Iron and steel industry have similar pattern, showing positive before the events and reversing to negative after the events. Other five industries present relatively small impacts.
All in all, we can say typhoons do have impact on stock returns in Taiwan, but different industries are affected differently. Yet there is no statistical evidence shows that the abnormal returns may differ because of the strength of typhoons, and neither does the time. Using the regression model, we discover that “rainfall” is able to explain some specific industries.
參考文獻 1. Andresen, J. A., G. Alagarswamy, C. A. Rotzc, J. T. Ritchie, A. W. LeBaron, 2001, “Weather Impacts on Maize, Soybean, and Alfalfa Production in the Great Lakes Region, 1895-1996,” Argon. Journal, Vol. 93, pp. 1059-1070.

2. Anthony O. S., C. L. Susan, W. Koko, C. Cosmin, Y. Kristina, 2012, “Addressing Loss and Damage in the Context of Social Vulnerability and Resilience,” The United Nation University Institute for Environmental and Human Society.

3. Briones R. M., D. M. Alvaro, J. W. Eric, C. C. Eddie, 2012, “Climate Change and Price Volatility: Can We Count on the ASEAN Plus Three Emergency Rice Reserve,” Asian Development Bank, NO. 24.

4. Buchner B., A. Falconer, M. H. Mignucci, C. Trabacchi, 2012, “The Landscape of the Climate Finance 2012,” Climate Policy Initiative.

5. Crain S. J. and J. H. Lee, 1996, “Volatility in Wheat Spot and Futures Markets, 1950-1993: Government Farm Programs, Seasonality, and Causality,” The Journal of Finance, Vol. 51, NO. 1, pp. 325-343.

6. Deschênes, O., M. Greenstone, 2007, “The Economic Impacts of Climate Change: Evidence from Agricultural Output and random Fluctuations in Weather,” American Economic Review, Vol. 97, pp. 354-385.

7. Drabo A., L. M. Mbaye, 2011, “Climate Change, Natural Disasters and Migration: An Empirical Analysis in Developing Countries,”, IZA.

8. Dutton, J. A., 2002, “Opportunity and Priorities in a New Era for Weather and Climate Services,” Bulletin of the American Meteorological Society, Vol. 83, pp. 1303-1311.

9. Hallegatte S., 2012, “An Exploration of the Link between Development, Economic Growth, and Natural Risk,”, The World Bank.

10. Härdle W. K. and O. Maria, 2012, “Spatial Risk Premium on Weather Exposure in Electricity,” The Energy Jouranl.

11. Harmeling S. and D. Eckstein, 2012, “Global Climate Risk Index 2013,” Germanwatch.

12. Kane S., J. Reilly, J. Tobey, 1992, “An Empirical Study of the Economic Effects of Climate Change on World Agriculture,” United States Department of Agriculture (USDA).

13. Lazo J. K., M. Lawson, P. H. Larsen, D. M. Waldman, 2011, “U.S. Economic Sensitivity to Weather Variability,” American Meteorological Society.

14. Richard S. J., 2008, “The Economic Impact of Climate Change,” The Economic and Social Research Institute (ESRI).

15. Saunders E. M. JR., 1993, “Stock Prices and Wall Street Weather,” The American Economic Review, Vol. 83, pp. 1337-1345.

16. Schlenker W. and M. J. Roberts, 2006, “Nonlinear Effects of Weather on Corn Yields,” Review of Agricultural Economics, Vol. 28, NO.3, pp. 391-398.

17. Warner K., S. Kreft, M. Zissener, P. Hőppe, C. Bals, T. Loster, J. L. Bayer, S. Tschudi, E. Gurenko, A. Haas, S. Young, P. Kovacs, A. D. Lecki, A. Oxley, 2012, “Insurance Solutions in the Context of Climate Change-Related Loss and Damage,” The United Nation University Institute for Environmental and Human Society , Munich Climate Insurance Initiative.
描述 碩士
國立政治大學
財務管理研究所
100357002
101
資料來源 http://thesis.lib.nccu.edu.tw/record/#G1003570021
資料類型 thesis
dc.contributor.advisor 徐燕山zh_TW
dc.contributor.author (Authors) 賴穎緻zh_TW
dc.creator (作者) 賴穎緻zh_TW
dc.date (日期) 2012en_US
dc.date.accessioned 22-Jul-2013 11:13:15 (UTC+8)-
dc.date.available 22-Jul-2013 11:13:15 (UTC+8)-
dc.date.issued (上傳時間) 22-Jul-2013 11:13:15 (UTC+8)-
dc.identifier (Other Identifiers) G1003570021en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/58933-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 財務管理研究所zh_TW
dc.description (描述) 100357002zh_TW
dc.description (描述) 101zh_TW
dc.description.abstract (摘要) 近年來氣候變遷議題興起，天氣災害對於實體經濟的影響也愈來愈嚴重，因此相關研究也開始在國際間出現，使用許多不同的角度來審視氣候變遷與天氣事件對經濟的影響。
以台灣而言，最明顯的天氣事件便是颱風，而在近幾年因為氣候變遷，導致颱風降雨型態變化，水文災害有愈來愈嚴重的趨勢，本研究的目的在研究台灣重大氣候事件對於台灣產業的影響，以極端降雨前十名的颱風為事件，使用事件研究法來確認颱風事件對股價報酬率的衝擊。選定的九個產業分別為水泥工業、食品工業、航運業、營建業、汽車工業、觀光業、鋼鐵工業、油電燃氣業和貿易百貨業。若以整體事件期間來看，食品工業、觀光業和油電燃氣業、貿易百貨業的影響較大。分個別產業以t統計量檢定之，發現大部分股價報酬率在颱風警報發布日加計前後三個交易日並未出現顯著的異常報酬，只有汽車工業的受到較為明顯的負向影響。而如果以符號檢定來進行檢定，則可以發現顯著性較t統計檢定來得高上許多，其中食品工業所受衝擊，無論在事件日前後皆呈現明顯的負向影響，顯示颱風可能造成食品工業負向的異常報酬率；航運業、營建業、和鋼鐵工業則出現了在事件日之前顯著偏正、事件日之後顯著偏負的情形。水泥工業、汽車工業、觀光業、油電燃氣業與貿易百貨業相比起來則相對比較輕微。兩種檢定結果相差甚多，可能是因為極端值的存在所造成的影響。
從結果來看，颱風事件對於台灣股市確實存在其影響力，但效果在各個產業間有所不同，並且隨著時間點的變化，可能會出現正負反轉的現象，也因此可能造成在整體來看顯著性並不強烈的現象。以迴歸模式診斷，發現特定產業的異常報酬率的確可以由雨量解釋之。		zh_TW
dc.description.abstract (摘要) Recently, the concern about climate change has become one of the hottest issues around the world. There are more and more related researches published, using different dimensions to evaluate the impacts of climate change and weather events on economy.
In Taiwan, the most frequent weather event is typhoon. In addition, due to the climate change, the modes of typhoons’ rainfalls have changed drastically, making the damages and losses become worse and worse. This paper uses top-10 heavy-rainfall typhoons to identify whether there exists impact of typhoon on the stock returns of different industries in Taiwan. Industries include Cement, Food, Transport, Construction, Automobile, Tourism, Iron and Steel, Energy and Trading and department store, totaling nine industries. According to the sign test results, the impact of typhoons on stock returns is different from industry to industry. Food industry is affected negatively in the whole period. Transport, Construction, and Iron and steel industry have similar pattern, showing positive before the events and reversing to negative after the events. Other five industries present relatively small impacts.
All in all, we can say typhoons do have impact on stock returns in Taiwan, but different industries are affected differently. Yet there is no statistical evidence shows that the abnormal returns may differ because of the strength of typhoons, and neither does the time. Using the regression model, we discover that “rainfall” is able to explain some specific industries.		en_US
dc.description.tableofcontents 第一章 緒論 1
第一節 研究動機與背景 1
第二節 研究問題目的 6
第三節 研究架構 7
第二章 文獻回顧 9
第三章 研究方法 13
第一節 樣本選取 13
第二節 模型設定 15
第三節 報酬指數與加權股價指數 20
第四節 異常報酬率迴歸模型 25
第四章 研究結果 26
第一節 不同產業異常報酬率 26
第二節 t統計檢定 30
第三節 符號檢定 36
第四節 迴歸分析 45
第五章 結論 47
參考文獻 49
附錄 51		zh_TW
dc.format.extent 1436729 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1003570021en_US
dc.subject (關鍵詞) 颱風zh_TW
dc.subject (關鍵詞) 異常報酬zh_TW
dc.subject (關鍵詞) 事件研究法zh_TW
dc.subject (關鍵詞) 符號檢定zh_TW
dc.title (題名) 天氣事件對台灣不同產業股價報酬率的影響zh_TW
dc.title (題名) The Impacts of Weather Events on the Taiwan Stock Returns of Different Industriesen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 1. Andresen, J. A., G. Alagarswamy, C. A. Rotzc, J. T. Ritchie, A. W. LeBaron, 2001, “Weather Impacts on Maize, Soybean, and Alfalfa Production in the Great Lakes Region, 1895-1996,” Argon. Journal, Vol. 93, pp. 1059-1070.

2. Anthony O. S., C. L. Susan, W. Koko, C. Cosmin, Y. Kristina, 2012, “Addressing Loss and Damage in the Context of Social Vulnerability and Resilience,” The United Nation University Institute for Environmental and Human Society.

3. Briones R. M., D. M. Alvaro, J. W. Eric, C. C. Eddie, 2012, “Climate Change and Price Volatility: Can We Count on the ASEAN Plus Three Emergency Rice Reserve,” Asian Development Bank, NO. 24.

4. Buchner B., A. Falconer, M. H. Mignucci, C. Trabacchi, 2012, “The Landscape of the Climate Finance 2012,” Climate Policy Initiative.

5. Crain S. J. and J. H. Lee, 1996, “Volatility in Wheat Spot and Futures Markets, 1950-1993: Government Farm Programs, Seasonality, and Causality,” The Journal of Finance, Vol. 51, NO. 1, pp. 325-343.

6. Deschênes, O., M. Greenstone, 2007, “The Economic Impacts of Climate Change: Evidence from Agricultural Output and random Fluctuations in Weather,” American Economic Review, Vol. 97, pp. 354-385.

7. Drabo A., L. M. Mbaye, 2011, “Climate Change, Natural Disasters and Migration: An Empirical Analysis in Developing Countries,”, IZA.

8. Dutton, J. A., 2002, “Opportunity and Priorities in a New Era for Weather and Climate Services,” Bulletin of the American Meteorological Society, Vol. 83, pp. 1303-1311.

9. Hallegatte S., 2012, “An Exploration of the Link between Development, Economic Growth, and Natural Risk,”, The World Bank.

10. Härdle W. K. and O. Maria, 2012, “Spatial Risk Premium on Weather Exposure in Electricity,” The Energy Jouranl.

11. Harmeling S. and D. Eckstein, 2012, “Global Climate Risk Index 2013,” Germanwatch.

12. Kane S., J. Reilly, J. Tobey, 1992, “An Empirical Study of the Economic Effects of Climate Change on World Agriculture,” United States Department of Agriculture (USDA).

13. Lazo J. K., M. Lawson, P. H. Larsen, D. M. Waldman, 2011, “U.S. Economic Sensitivity to Weather Variability,” American Meteorological Society.

14. Richard S. J., 2008, “The Economic Impact of Climate Change,” The Economic and Social Research Institute (ESRI).

15. Saunders E. M. JR., 1993, “Stock Prices and Wall Street Weather,” The American Economic Review, Vol. 83, pp. 1337-1345.

16. Schlenker W. and M. J. Roberts, 2006, “Nonlinear Effects of Weather on Corn Yields,” Review of Agricultural Economics, Vol. 28, NO.3, pp. 391-398.

17. Warner K., S. Kreft, M. Zissener, P. Hőppe, C. Bals, T. Loster, J. L. Bayer, S. Tschudi, E. Gurenko, A. Haas, S. Young, P. Kovacs, A. D. Lecki, A. Oxley, 2012, “Insurance Solutions in the Context of Climate Change-Related Loss and Damage,” The United Nation University Institute for Environmental and Human Society , Munich Climate Insurance Initiative.		zh_TW