Information Asymmetry and the Cross-Sectional Profitability of Technical Analysis

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洪嘉佑(Chia-yu Hung) 查詢紙本館藏

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財務金融學系

論文名稱

(Information Asymmetry and the Cross-Sectional Profitability of Technical Analysis)

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摘要(中)

本文的重點是檢驗技術分析的獲利能力。本文將PIN作為與信息不對稱相關的代理變數，依照PIN大小分為10個分組的投資組合作為投資標的，並使用技術分析中的移動平均指標作為投資的依據。本文記錄了移動平均策略的應用，該策略產生的投資組合基本上優於買入持有策略。對於高PIN的投資組合，資本資產定價模型（CAPM）和Fama-French 3因子模型的超額報酬皆具有經濟以及統計顯著。在使用了移動平均策略後，高信息不對稱投資組合的表現明顯優於低信息不對稱投資組合，而且超額報酬與資訊不對稱程度呈正相關。此外，按照信息不對稱和信息不確定性代理變數排序的其他投資組合也有類似的結果。

摘要(英)

The key of this paper is to examine the profitability of technical analysis. This paper regard PIN as the main variable related to information asymmetry. Then, applying the moving average indicator with the portfolios sorted by PIN. This paper documents that the application of moving average timing strategy portfolios which generate investment timing portfolios, is substantially outperforming the buy-and-hold strategy. For high-PIN portfolios, the abnormal returns, relative to the capital asset pricing model (CAPM) and the Fama-French 3-factor models, are of great economic significance. Additionally, high-information-asymmetry portfolios perform better than low-information-asymmetry portfolios by technical analysis, and the abnormal returns are likely an increasing function across deciles. Last but not least, other portfolios sorted by variables related to information asymmetry and information uncertainty have similar results.

關鍵字(中)

★ 技術分析
★ 信息不對稱
★ 信息不確定性

關鍵字(英)

★ Technical analysis
★ Information asymmetry
★ Information uncertainty

論文目次

摘要 i
Abstract ii
Contents iii
List of table: iv
1. Introduction 1
2. Literature review 4
3. Data 5
I. Variable Definition 5
II. Sample Data 8
4. The Moving Average Timing Strategies 9
5. Profitability of the Moving Average Portfolios 11
I. Summary Statistics 11
II. Alpha 12
III. PIN derivations variables decile portfolios 14
IV. Alternative decile portfolios 15
6. Additional test 18
I. Alternative lag length 18
II. Alternative trading day 18
7. Conclusion 19
Reference 21

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指導教授

賴弘能(Hung-Neng Lai)

審核日期

2020-1-7

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