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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/87225


    Title: 波動度所含資訊內涵之分析
    Other Titles: The information content of market volatility
    Authors: 顏維德;Yen, Wei-Te
    Contributors: 淡江大學財務金融學系碩士在職專班
    林蒼祥;Lin, William T.
    Keywords: 波動度;跨式;勒式組合交易;知訊交易者;Volatility;straddle;strangle;Informed trader
    Date: 2012
    Issue Date: 2013-04-13 10:52:03 (UTC+8)
    Abstract: 本研究為了解交易人與機構交易人包含造市者在台指選擇權交易市場中何者具有波動度訊息上優勢的地位,研究採用的樣本為2008年1月至2009年3月台指選擇權的每日成交資料,區分交易人身份類別、帳號及其交易策略配對,延用Chang, Hsieh and Wang (2010)及Ni, Pan and Poteshman (2008)計算加權淨vega的方法分別計算其淨vega需求利用迴歸分析來觀察對於未來實際波動度是否有預測能力並觀察不同交易人在資訊優勢領先的狀況,且輔以跨式及勒式組合交易來檢測交易人是否具有優勢的機會。最後,本文以資料樣本時間內所發生之重大事件如:金融海嘯、總統大選 、除權息旺季等事件,以事件前後所發生的衝擊來觀察何者交易人在事件發生的前後期間是否有不一樣資訊優勢的改變。
    研究發現,在樣本這段期間外資、造市者、自營商及散戶在台指選擇權市場皆具有未來波動度的預測能力。外資和自營商應為波動度資訊交易者,造市者可能藉由擔任造市者提供流動性交易時獲得對於波動度資訊內涵掌握之優勢,只在選擇權市場進行波動度交易的散戶是比較在乎市場的波動度而比較不在乎市場的方向性,通常這些人也是比較富有經驗的。至於在金融海嘯、總統大選 、除權息旺季等事件前後期間,除了造市者在金融海嘯後的預測能力有正向顯著的改變外,其餘交易者對於其預測能力並未有所改變。
    In this paper, we use the method of Chang, Hsieh and Wang (2010) and Ni, Pan and Poteshman (2008) to investigate the information content of net vega demand to examine the predictive power of realized volatility of different types of traders in the TAIEX options market. We also examine straddle and strangle strategies and discuss the impact of significant events how to affect the traders, including financial crisis, president election and ex dividend.
    After regression analysis, this paper finds that foreign institutional investors, market maker and dealers have the predictive power on the future volatility. Foreign institutional investors and dealers are the informed traders of volatility. And market makers maybe get the vantage on the information content of volatility by providing liquidity. In the period of significant events, most of investors had been unchanged, just market makers’ predictive power is positive significant after financial crisis.
    Appears in Collections:[財務金融學系暨研究所] 學位論文

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