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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 王耀輝 | |
dc.contributor.author | Hui-Yu Chen | en |
dc.contributor.author | 陳蕙妤 | zh_TW |
dc.date.accessioned | 2021-05-17T09:19:03Z | - |
dc.date.available | 2012-07-18 | |
dc.date.available | 2021-05-17T09:19:03Z | - |
dc.date.copyright | 2012-07-18 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-07-09 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/6831 | - |
dc.description.abstract | 在這篇論文中,我們使用Google搜尋量作為測量散戶投資者注意的媒介,來探討在不同的國家中,搜尋量和股票市場波動率之間的動態關係,以及檢驗搜尋量是否可以幫助預測波動率。我們發現搜尋量對預測未來實現波動率(realized volatility)一般是有用的。當有一個正的搜尋量衝擊,波動率並不會立即的反應而是在之後有正向的移動,但是波動率卻可以立即地影響搜尋量。當建立波動率預測的模型,搜尋量增加了有價值的信息,並且正面地影響未來的波動率。它還可以顯著地增進預測波動率的預測能力在樣本內,樣本外也可以但比較不顯著。在新興市場(emerging markets) 和新領域市場(frontier markets),搜尋量可以增進預測波動率的現象變得較不明顯。而在我們的實證當中,有些國家沒有這個現象的可能原因除了市場的開發程度,還有較低頻率的資料、意義較不明確單一的搜尋關鍵字、較低的Google市佔率、國家的所在位置、較低的網路使用者普及率和較低的散戶投資者的比例。 | zh_TW |
dc.description.abstract | In this paper, we use Google search volume as proxy of retail investors’ attention to study the dynamic relationship with stock market volatility and examine if it can help to forecast volatility in different countries. We find search volume is useful to predict future realized volatility generally. When there is a positive shock of search volume, realized volatility wouldn’t react immediately but have positive movement later, while volatility can affect search volume immediately. Search volume adds valuable information for modeling volatility and influences future volatility positively. Search volume also can improve volatility forecasting in- and out-of-sample. But it becomes much more insignificantly in out-of-sample forecast evaluation. The phenomenon that search volume can improve volatility forecasting becomes more unobvious when turning to emerging markets and frontier markets. Besides the developed level of markets, there are some possible reasons, like lower frequency of data, less univocal search terms, lower market shares of Google, locations of countries, smaller penetration rate of internet users and lesser market shares of retail investors, can explain why this phenomenon becomes unobvious for some countries from our empirical results. | en |
dc.description.provenance | Made available in DSpace on 2021-05-17T09:19:03Z (GMT). No. of bitstreams: 1 ntu-101-R99723033-1.pdf: 732634 bytes, checksum: 43fd23a88279da8b335e50c42789b338 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | Contents
誌謝 II 摘要 III ABSTRACT IV 1. INTRODUCTION 1 2. DATA 6 2.1 STOCK INDEX VOLATILITY 6 2.2 INTERNET SEARCH VOLUME 10 2.3 SUMMARY STATISTICS 17 3. METHODS 27 3.1 VECTOR AUTOREGRESSIVE MODEL (VAR MODEL) 27 3.1.1 Granger causality test 28 3.1.2 Impulse response function (IRF) 28 3.1.3 Variance decomposition 29 3.2 REGRESSION MODELS 29 3.3 VOLATILITY FORECASTS 30 4. EMPIRICAL RESULTS 32 4.1 DYNAMICS OF SEARCH VOLUME AND VOLATILITY (VAR MODEL) 32 4.1.1 Whether search volume is useful in forecasting volatility? 33 4.1.2 How volatility reacts over time to shock of search volume and vice versa? 36 4.1.3 How much of volatility can be explained by search volume? 38 4.2 WHETHER SEARCH VOLUME HAS VALUABLE INFORMATION FOR MODELING VOLATILITY? 40 4.3 DOES SEARCH VOLUME HELP TO IMPROVE VOLATILITY FORECASTS? 43 4.3.1 In-sample forecast evaluation 43 4.3.2 Out-of-sample forecast evaluation 50 4.4 WHY SEARCH VOLUME CAN’T HELP TO FORECASTING VOLATILITIES IN SOME COUNTRIES? 57 5. CONCLUSION 60 REFERENCE 62 | |
dc.language.iso | zh-TW | |
dc.title | 網路搜尋量是否可以增進股票市場波動率的預測?國際實證 | zh_TW |
dc.title | Can internet search volume improve volatility forecasting for the stock markets? International Evidence | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 張森林,徐之強 | |
dc.subject.keyword | 實現波動率,預測,散戶投資者,網路搜尋量, | zh_TW |
dc.subject.keyword | realized volatility,forecasting,retail investor,internet search volume, | en |
dc.relation.page | 64 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2012-07-09 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
顯示於系所單位: | 財務金融學系 |
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