Author: Lai, Wai Man
Title: A test on a stock return forecast model : evidence from the Hong Kong market
Advisors: Tong, Wilson (AF)
Degree: D.B.A.
Year: 2014
Subject: Stock price forecasting.
Investment analysis.
Hong Kong Polytechnic University -- Dissertations
Department: Faculty of Business
Pages: vii, 123 leaves : color illustrations ; 30 cm
Language: English
Abstract: In this study, I examine whether the expected return forecast model developed by Haugen and Baker (hereafter 'the HB model', 1996), which applies a broad set of variables including the factor categories of risk, liquidity, price level, profitability, and price history to a newly augmented investor sentiment factor can collectively identify mispriced stocks in Hong Kong. I also construct a long-short equity portfolio that generates beta-adjusted excess return. Significant positive payoffs are found in the factor categories of risk, price level, profitability, medium-term price history and investor sentiment, while significant negative payoffs are observed in the factor categories of liquidity and short-and long-term price history. The long-short portfolios examined under the Base and Extended models exhibit significant beta-adjusted excess portfolio returns of 2.036% and 1.711% per month, respectively. The inclusion of the investor sentiment factor in the HB model improves its explanatory power by over 10%. Inconsistent with the findings in the HB model, the long (short) portfolio in this study contains smaller (larger) value (growth) stocks with lower (higher) liquidity, higher (lower) volatility of return, higher (lower) leverage and positive (negative) momentum but cheaply (dearly) priced. The profile of the long portfolio is associated with the small firm effect, which coincides with the unique characteristics of the Hong Kong equity market; that is, small firm dominance, high ownership concentration, high proportion of retail investors and high volatility.
Rights: All rights reserved
Access: restricted access

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/7983