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Investor Sentiment from Internet Message Postings and Predictability of Stock Returns
Dongcheol Kim,Soon-Ho Kim 한국재무학회 2012 한국재무학회 학술대회 Vol.2012 No.05
There has been interest in the literature on whether investor sentiment as expressed in messages posted on Internet message boards has predictive power for stock returns. To study this issue, we use more than 32 million messages on 91 firms posted on the Yahoo! Finance message board in the period January 2005 to December 2010. What distinguishes our study is the use of sentiment information explicitly revealed by retail investors for individual firms and a longer sample period relative to other studies that use similar sentiment information source. As a proxy for investor sentiment, we use investor sentiment indexes constructed from sentiment explicitly revealed by retail investors and as classified by a machine learning classification algorithm. In intertemporal and cross-sectional regression analyses, we find no evidence that investor sentiment forecasts future stock returns at either the aggregate or individual firm level. Rather, we find evidence that investor sentiment is positively affected by prior stock price performance. We also find no evidence that investor sentiment from Internet postings has predictability for volatility and trading volume. We find no significant predictive ability for retail investor sentiment for the direction of the next period’s stock price movement across demographic characteristics such as gender, age, and professionality.
Time-Varying Expected Momentum Profits
Dongcheol Kim,Tai-Yong Roh,Suk-Joon Byun,Byoung-Kyu Min 한국재무학회 2012 한국재무학회 학술대회 Vol.2012 No.05
We examine time variations of the expected momentum profits using a two-state Markov switching model with time-varying transition probabilities to evaluate the empirical relevance of recent rational theories of the momentum profits. We find that in the expansion state the expected returns of winner stocks are more affected by aggregate economic conditions than those of loser stocks, while in the recession state the expected returns of loser stocks are more affected than those of winner stocks. Consequently, the expected momentum profits display strong procyclical variations. We argue that the observed momentum profits are realizations of such expected returns and can be interpreted as the procyclicality premium. We also find the economic significance of out-of-sample predictability of the momentum profits particularly for loser stocks and during the recession states.
Effects of different stocking density in lairage of fattening pigs in high temperatures
Dongcheol Song,Seyeon Chang,Jaewoo An,Sehyun Park,Kyeongho Jeon,Hyuck Kim,Jinho Cho 충남대학교 농업과학연구소 2023 Korean Journal of Agricultural Science Vol.50 No.4
Lairages serve several functions, such as providing post-mortal inspections and providing a reservoir of animals to ensure the slaughter line runs efficiently. High stress lairage conditions can contribute to the accumulation of transport stress in pigs, causing poor pork quality and still stressed pigs at slaughter. The objective of this study was to investigate meat quality, blood profile and behavior changes according to lairage stocking density in in high temperature. Density treatments were as follows: LD, low density (lower than 0.5 m2/100 kg); ND, normal density (0.5 m2/100 kg to 0.83 m2/100 kg); HD, high density (higher than 0.83 m2/100 kg). Air temperature treatment was as follows: HT, high temperature (higher than 24℃). Pigs stocked with LD showed lower pH, WHC (water holding capacity), and higher DL (drip loss) and CL (cooking loss) than those stocked with HD. Pigs stocked with LD showed lower cortisol level than those stocked with HD. Therefore, Pigs exposed to high stock density (lower than 0.5 m2/100 kg) in high air temperature during pre-slaughter caused acute stress and lead to PSE (pale, soft, exudative) pork incidence. Based on obtained results, stocking of too high (lower than 0.5 m2/100 kg) density is generally not good for meat quality and animal welfare at high temperatures.
Investor Sentiment, Anomalies, and the Macroeconomy
Dongcheol Kim,Haejung Na 한국재무학회 2015 한국재무학회 학술대회 Vol.2015 No.05
This paper examines whether the results supporting a recent story that sentiment-related overpricing is the source of a variety of asset pricing anomalies are still maintained after separating out the effect of macroeconomic conditions. We find that after adjusting for the effect of several macroeconomic variables in the proxy for investor sentiment, the results are no longer consistent with the sentimentrelated overpricing story. These results indicate that the anomalies are not necessarily attributed to sentiment-related overpricing but rather to macroeconomic conditions.
Evaluating Asset Pricing Models in the Korean Stock Market
Dongcheol Kim,Soon-Ho Kim,Hyun-Soo Shin 한국재무학회 2011 한국재무학회 학술대회 Vol.2011 No.05
This paper evaluates and compares asset pricing models in the Korean stock market. The asset pricing models considered are the CAPM, APT-motivated models, the Consumptionbased CAPM, Intertemporal CAPM-motivated models, and the Jagannathan and Wang conditional CAPM model. By using various test portfolios as well as individual stocks, we conduct time-series tests and cross-sectional regression tests based on individual t-tests, the joint F-tests, the Hansen and Jagannathan (1997) distance, and R-squares. Overall, the Fama and French (1993) five-factor model performs most satisfactorily among the asset pricing models considered in explaining the intertemporal and cross-sectional behavior of stock returns in Korea. The Fama and French (1993) three-factor model, the Chen, Novy-Marx, and Zhang (2010) three-factor model, and the Campbell (1996) model are the next. The results indicate that the two bond portfolios, term spread and default spread, play an important role in explaining stock returns in Korea.
Dongcheol Kim,Haejung Na 한국재무학회 2014 한국재무학회 학술대회 Vol.2014 No.11
Previous researches focus on examining only the relation between cross-sectional earnings forecast dispersion and stock returns and on providing explanations for the negative dispersionreturn relation. This paper attempts to examine how time-series mean forecast dispersion is distinct in the relation to stock returns from the cross-sectional forecast dispersion effect. We find that contrary to the standard analyst dispersion effect, there is a strong positive relation between time-series mean forecast dispersion and stock returns. We also find that time-series mean forecast dispersion apparently contains systematic risk components and that such risk is priced in stock returns.
Investor Sentiment from Internet Message Postings and Predictability of Stock Returns
Dongcheol Kim,Soon-Ho Kim 한국재무학회 2012 한국재무학회 학술대회 Vol.2012 No.09
There has been interest in the literature on whether investor sentiment as expressed in messages posted on Internet message boards has predictive power for stock returns. To study this issue, we use more than 32 million messages on 91 firms posted on the Yahoo! Finance message board in the period January 2005 to December 2010. What distinguishes our study is the use of sentiment information explicitly revealed by retail investors for individual firms and a longer sample period relative to other studies that use similar sentiment information source. As a proxy for investor sentiment, we use investor sentiment indexes constructed from sentiment explicitly revealed by retail investors and as classified by a machine learning classification algorithm. In intertemporal and cross-sectional regression analyses, we find no evidence that investor sentiment forecasts future stock returns at either the aggregate or individual firm level. Rather, we find evidence that investor sentiment is positively affected by prior stock price performance. We also find no evidence that investor sentiment from Internet postings has predictability for volatility and trading volume. We find no significant predictive ability for retail investor sentiment for the direction of the next period’s stock price movement across demographic characteristics such as gender, age, and professionality.