橙汁期貨謎題再探

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：34

、訪客IP：18.189.143.150

姓名

戴吟蓁(Yin-Chen Tai) 查詢紙本館藏

畢業系所

財務金融學系

論文名稱

橙汁期貨謎題再探
(The FCOJ Puzzle Revisited)

相關論文

★ 避險基金之績效評估	★ 展望理論與共同基金績效
★ 生命週期基金 :行為財務學觀點	★ 行為特性與投資績效相關性之研究
★ 專業投資人行為特性探討	★ 中小型企業融資缺口與資訊不對稱之探討
★ 九型人格特質與理財偏誤行為之相關性研究	★ 銀行通路轉型策略個案研究
★ 銀行財富管理行銷策略分析-以兩家在台外商銀行為例	★ 羅盤玫瑰可預測型態之探討
★ 巢式與非巢式資產定價理論之比較與檢定	★ 投資者情緒與市場報酬
★ 資產定價模型樣本外績效之檢定	★ 規模效果和元月效應之微觀
★ 因子或特徵:全球觀點	★ 特徵與因子：日本證據

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本文重新探究冷凍柳橙汁(FCOJ)期貨的謎團。在冷凍柳橙汁期貨價格中有許多未能被解釋的價格變動，儘管氣溫被視為最該具有解釋潛力的基本面因素，但檢測出來的解釋能力雖顯著卻極低。我們拉長樣本時間，並比較全期間，以及用2010年劃分出的兩個樣本區間之間的差異。本研究使用了佛羅里達州最靠近生產區域的一週最低氣溫，共識看漲情緒指數 (CBSI)作為機構情緒指標，以及由美國個人投資協會編制的投資人情緒指數(AAII)作為個別投資人情緒指標。與先前研究樣本不同的是，現今美國柳橙產量已不像從前獨佔市場，因此我們更預測基本面的影響應該降低。實證結果顯示，在極端氣候條件下，溫度提供了極少的解釋能力，而CBSI提供出最高近30%的解釋能力。隨後，我們使用GARCH模型來檢視CBSI指數的性質。發現在2010年前，CBSI指數可以理性反映出FCOJ期貨報酬的波動度與風險。然而2010年後則與先前的文獻有一致的結果，反映出聰明錢假說的特性：CBSI指數顯示看漲時，會伴隨著FCOJ期貨價格的增長與報酬波動度的減少；相反地，CBSI指數顯示看跌時，FCOJ期貨價格會降低、報酬波動度相對增加。因此我們仍認為CBSI有領先預測FCOJ期貨價格的能力，再次佐證聰明錢假設的有效性。

摘要(英)

The purpose of this study is to reexamine the mysteries surrounding Frozen Concentrated Orange Juice (FCOJ) futures. There are numerous unexplained price movements in frozen orange juice futures prices, and despite temperature being considered a fundamental factor with potential explanatory power, the detected explanatory ability is significant yet remarkably low. We extend the sample period, comparing the entire duration and differences between two sample intervals delineated by the year 2010. This study utilizes the weekly minimum temperatures closest to the production area in Florida, the Consensus Bullish Sentiment Index (CBSI) as an institutional sentiment indicator, and the Investor Sentiment Index compiled by the American Association of Individual Investors (AAII) as an individual investor sentiment indicator.
Unlike previous research samples, the current orange production in the United States is no longer monopolizing the market, leading us to anticipate a reduction in the impact of fundamental factors. Empirical results show that under extreme weather conditions, temperature provides minimal explanatory power, while CBSI offers the highest explanatory power, reaching nearly 30%. Subsequently, we use a GARCH model to examine the nature of the CBSI index. It is found that before 2010, the CBSI index could rationally reflect the volatility and risk of FCOJ futures returns. However, after 2010, consistent with previous literature, it reflects the characteristics of the smart money hypothesis: when the CBSI index indicates bullish sentiment, it is accompanied by an increase in FCOJ futures prices and a decrease in return volatility; conversely, when the CBSI index indicates bearish sentiment, FCOJ futures prices decrease, and return volatility relatively increases. Therefore, we still believe that CBSI has the ability to lead and predict FCOJ futures prices, further supporting the effectiveness of the smart money hypothesis.

關鍵字(中)

★ 氣溫
★ 情緒指數
★ 冷凍柳橙汁期貨
★ 聰明錢

關鍵字(英)

★ Temperature
★ Sentiment index
★ FCOJ futures
★ Smart money

論文目次

摘要 i
ABSTRACT ii
致謝 iv
目錄 v
表目錄 vi
第一章緒論 1
第二章文獻回顧 4
第三章樣本與敘述統計 7
第四章實證結果 10
第五章穩健性測試 13
第六章結論 18
參考文獻 20

參考文獻

(1) Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The journal of Finance, 61(4), 1645-1680.
(2) Boudoukh, J., Richardson, M., Shen, Y. J., & Whitelaw, R. F. (2007). Do asset prices reflect fundamentals? Freshly squeezed evidence from the OJ market. Journal of Financial Economics, 83(2), 397-412.
(3) Brown, G. W., & Cliff, M. T. (2005). Investor sentiment and asset valuation. The Journal of Business, 78(2), 405-440.
(4) Canoles, W. B., Thompson, S., Irwin, S., & France, V. G. (1998). An analysis of the profiles and motivations of habitual commodity speculators. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 18(7), 765-801.
(5) Cao, M., & Wei, J. (2005). Stock market returns: A note on temperature anomaly. Journal of Banking & Finance, 29(6), 1559-1573.
(6) Chou, P. H., Hsieh, C. H., & Shen, C. H. H. (2016). What explains the orange juice puzzle: Sentiment, smart money, or fundamentals?. Journal of financial Markets, 29, 47-65.
(7) Cumby, R. E., & Modest, D. M. (1987). Testing for market timing ability: a framework for forecast evaluation. Journal of Financial Economics, 19(1), 169-189.
(8) Campbell, J. Y., & Kyle, A. S. (1993). Smart money, noise trading and stock price behaviour. The Review of Economic Studies, 60(1), 1-34.
(9) Daniel, K., Hirshleifer, D., & Teoh, S. H. (2002). Investor psychology in capital markets: Evidence and policy implications. Journal of monetary economics, 49(1), 139-209.
(10) De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of political Economy, 98(4), 703-738.
(11) Draper, D. W. (1985). The small public trader in futures markets. Futures Markets: Regulatory Issues, 211S269.
(12) Dow, J., & Gorton, G. (2008). Noise traders. Chapter in The new Palgrave: A dictionary of economics.
(13) Fama, E. F. (1991). Efficient capital markets: II. The journal of finance, 46(5), 1575-1617.
(14) Fisher, K. L., & Statman, M. (2003). Consumer confidence and stock returns. Journal of Portfolio Management, 30(1), 115-127.
(15) Fisher, K. L., & Statman, M. (2000). Investor sentiment and stock returns. Financial Analysts Journal, 56(2), 16-23.
(16) Granger, C. W. J. (1969). Investigating Causal Relationby Econometric and Cross-sectional Method. Econometrica.
(17) Hirshleifer, D. (2001). Investor psychology and asset pricing. The journal of Finance, 56(4), 1533-1597.
(18) Lee, W. Y., Jiang, C. X., & Indro, D. C. (2002). Stock market volatility, excess returns, and the role of investor sentiment. Journal of banking & Finance, 26(12), 2277-2299.
(19) Newey, Whitney K. , and Kenneth D. West, (1987), A simple, positive semi-positive, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica 55, 703-708
(20) Roll, R. (1984). Orange juice and weather. The American Economic Review, 74(5), 861-880.
(21) Sanders, D. R., Irwin, S. H., & Leuthold, R. M. (2003). The theory of contrary opinion: a test using sentiment indices in futures markets. Journal of Agribusiness, 21(345-2016-15207), 39-64.
(22) Saunders, E. M. (1993). Stock prices and Wall Street weather. The American Economic Review, 83(5), 1337-1345.
(23) Shleifer, A., & Vishny, R. W. (1997). A survey of corporate governance. The journal of finance, 52(2), 737-783.
(24) Shleifer, A. (2000). Inefficient markets: An introduction to behavioural finance. Oup Oxford.
(25) Schmeling, M. (2007). Institutional and individual sentiment: smart money and noise trader risk?. International Journal of Forecasting, 23(1), 127-145.
(26) Tsai,Cheng-Fang.,2013.探討情緒指標對柳橙汁期貨報酬的影響

指導教授

周賓凰

審核日期

2024-1-22

推文