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Forecasting stock market returns:Application of the Sum-of-the-Parts method in Korean stock market

DC Field Value Language
dc.contributor.advisor조성욱-
dc.contributor.author장세연-
dc.date.accessioned2017-07-14T04:50:43Z-
dc.date.available2017-07-14T04:50:43Z-
dc.date.issued2013-08-
dc.identifier.other000000013427-
dc.identifier.urihttps://hdl.handle.net/10371/124450-
dc.description학위논문 (석사)-- 서울대학교 대학원 : 경영학과(재무금융전공), 2013. 8. 조성욱.-
dc.description.abstractIn this paper, I undertake an extensive analysis of out-of-sample tests of stock return predictability in an effort to identify predictive approaches that best forecast stock return in Korean stock market. Following approaches of Goyal and Welch (2008) and Ferreira and Santa-Clara (2011), I compare out-of-sample R-squares for traditional predictive regressions with macroeconomic and financial variables that are known to exhibit return predictability in extant literature, and the sum-of-the-parts method. I forecast separately the three components of stock market returns – dividend-price ratio, equity growth, and price-to-book ratio growth – the sum of the parts (SOP) method. Modifying the original SOP method from Ferreira and Santa-Clara (2011) by substituting earnings to equity and price-earnings ratio to price-to-book ratio, I show that the new method produces annual out-of-sample R-squares (compared with the historical mean) of more than 12% with 5-year horizon and 7% with 10-year horizon at an index level. This has a significant comparability with most negative R-squares obtained in the predictive regressions. The SOP method, on the other hand, produces negative out-of-sample R-squares of -3% and -1% with 5-year and 10-year horizon respectively at individual stock level. Constructing portfolios by individual firms market capitalization size and book-to-market ratio, I find that the SOP approach predicts annual returns for relatively small and undervalued firms. The use of SOP method as a trading strategy also generates yearly economic profits of 9.53% using return estimates at 5-year horizon and 9.49% with 10-year horizon measured by certainty equivalent. This also compares with most negative returns of trading strategies using various factors of the predictive regressions. Given that I obtain evidence of predictability in Korean stock market, my out-of-sample results strengthen the superiority of the sum-of-the-parts (SOP) method in stock return predictability to the case of Korea.-
dc.description.tableofcontentsCONTENTS

I. Introduction............... 1
Extant literature and previous studies..........1
Research Objective..........3
Composition of the paper..........7

II. Research design and data...............8
2-1. Methodology
2-1.1. Return components..........8
2-1.2. The Sum-of-the-Parts method ..........10
2-1.3. Predictive regressions and out-of-sample tests..........12
2-1.4. Evaluation of return predictability..........13
2-2. Data collection and sample period..........15

III. Empirical results...............23
3-1. Return predictability test..........23
3-2. Performance evaluation of trading strategies..........29
3-2.1. Certainty Equivalent..........31
3-2.2. Sharpe ratio..........34

IV. Extension and Robustness test...............38
4-1. The SOP extension: Multiple reversion approach..........38
Return predictability test for the SOP extension..........38
4-2. The SOP with earnings..........44
4-2.1. Return predictability test..........45
4-2.2. Performance evaluation..........48

V. Conclusion...............50

Reference...............53

Abstract...............57
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dc.formatapplication/pdf-
dc.format.extent1279828 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectreturn predictability-
dc.subjectstock returns-
dc.subjectpredictive regressions-
dc.subjectSum-of-the-Parts method-
dc.subjecttrading strategies-
dc.subject.ddc658-
dc.titleForecasting stock market returns:Application of the Sum-of-the-Parts method in Korean stock market-
dc.typeThesis-
dc.description.degreeMaster-
dc.citation.pagesvi, 58-
dc.contributor.affiliation경영대학 경영학과-
dc.date.awarded2013-08-
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