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    政大機構典藏 > 商學院 > 財務管理學系 > 學位論文 >  Item 140.119/36691


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/36691


    Title: 交易量對於隱含波動度預測誤差之對偶效果-Panel Data的分析
    The Dual Effect of Volume and Volatility Forecasting Error-Panel Data analysis
    Authors: 李政剛
    Lee,Jonathan K.
    Contributors: 杜化宇
    Tu,Anthony H.
    李政剛
    Lee,Jonathan K.
    Keywords: 對偶效果
    交易量
    隱含波動度
    波動度預測
    異質性
    固定效果模型
    隨機效果模型
    dual effect
    volume
    implied volatility
    volatility forecasting
    panel data
    heterogeneity
    fixed effects model
    random effects model
    Date: 2004
    Issue Date: 2009-09-18 19:18:11 (UTC+8)
    Abstract: 本研究探討選擇權交易量之大小對於波動度預測之效率性所造成之對偶效果(dual effect)，驗證〝正常的高交易量〞與〝異常的高交易量〞對於波動度預測能力是否有不同的影響。本研究採用panel data之資料型態，以LIFFE上市的個股買權為對象，資料長度為三年左右。主要欲探討之假說為： 1.一般而言，交易量大的選擇權，其波動度估計誤差較交易量小的選擇權來得小。 2.相對於平日水準而言，某日交易量異常高的選擇權將有較大的波動度估計誤差。
    本研究所使用的波動度預測模型為隱含波動度(ISD)，採用的是最接近到期月份及最接近價平的合約。實證以組合迴歸、固定效果模型、隨機效果模型分別估計之，加以比較。結果發現固定效果模型為較佳之解釋模型，然而結果顯示交易量的對偶效果並不明確影響波動度預測誤差，故推測有某種影響公司間差異的因素，即公司間之異質性，比相對交易量更容易影響波動度預測之誤差。另外，透過組間與組內效果之分析，發現不論是長期還是短期，由於公司間的異質性存在，使得相對交易量對於波動度預測誤差均無明顯影響。
    The purpose of this research is to study the dual effect on the efficiency of volatility forecasting which is caused by the volume of option market, with the intent to test whether〝normal high volume〞and〝abcdrmal high volume〞cause different results on the ability of volatility forecasting. The data used is in the form of panel data. It is drawn from LIFFE, and has a length of about three years. The hypotheses to be examined in this study are：1. High-average-volume options have smaller volatility forecasting errors than low-average-volume options; 2. Options have larger volatility forecasting errors on abcdrmally-high-volume days than on normal-volume days.
    In this research, volatility is forecasted by implied standard deviation (ISD) which is implied in the at-the-money and the nearest expiry month options. Pooled regression、fixed effect model、and random effect model methods were applied. The results show that the fixed effect model made the best analysis amongst the three models. However, the result does not support the hypotheses made above, which means that volume does not have much influence on volatility forecasting error. It is inferred that there exists some other factors which could cause the difference between firms, namely heterogeneity, and these factors have much more powerful influence over volatility forecasting error than volume. Finally, it was found that no matter for long run or short run, because of the existence of heterogeneity, relative volume doesn’t have obvious influence on volatility forecasting errors when analyzing the difference between the between-individual effect and the within-individual effect.
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    Description: 碩士
    國立政治大學
    財務管理研究所
    91357019
    93
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0913570191
    Data Type: thesis
    Appears in Collections:[財務管理學系] 學位論文

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