Are Stock Markets Efficient? (Price-Earnings Ratio Approach): Korean Stock Market Proxy

2016 ◽  
Author(s):  
Tasoh Martin Toh
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Efficient Price ◽  
Korean Stock Market ◽  
Price Earnings Ratio ◽  
Ratio Approach

scholarly journals Investor Sentiment and Herding Behavior in the Korean Stock Market

2020 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Ki-Hong Choi ◽  
Seong-Min Yoon
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Markets ◽  
Trading Volume ◽  
Investor Sentiment ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Korean Stock Market ◽  
Quantile Regression Method

This paper investigates herding behavior and the connection between herding behavior and investor sentiment. We apply a Cross-Sectional Absolute Deviation (CSAD) approach and the quantile regression method to capture herding behavior in the KOSPI and KOSDAQ stock markets. The analysis results are outlined as follows. First, we find that herding behavior is exhibited during down-market periods in the KOSPI and KOSDAQ stock markets. However, we show that adverse herding behavior occurs in low-trading volume and low-volatility periods. Second, according to the results of the quantile regression, herding behavior is found in the low and high quantiles of the KOSPI and KOSDAQ stock markets. However, adverse herding behavior is also found, which means that investors herd in extreme market conditions. Third, the relationship between investor sentiment and herding behavior is analyzed through regression and quantile regression, and investor sentiment is confirmed to be one of the important factors that can cause herding behavior in the Korean stock market.

Spot Trading Volume Volatility, Futures Trading Volume Volatility, and the Volatility of Korean Stock Market

2011 ◽  
Vol 19 (2) ◽  
pp. 149-173
Author(s):  
Kook Hyun Chang ◽  
Byung Jo Yoon
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Trading Volume ◽  
Relative Importance ◽  
Futures Trading ◽  
Jump Model ◽  
Korean Stock Market ◽  
Transitory Component

This paper tries to investigate whether the information contained in trading volume volatilities of spot and futures may be statistically useful in explaining the volatility of korean stock market. This paper uses both the component-jump model and the bivariate GJR-GARCH type BEKK model to estimate the trading volume volatilities of spot and futures from 1/2/2001 to 9/30/2010. By using the component-jump model, the volume volatility is decomposed into a permanent component and a transitory component. According to this study, the relative importance of permanent component to the transitory component contained in both trading volume volatilities of spot and futures has been more significant in explaining the volatility of the korean stock markets.

scholarly journals The Role of World Oil Price in the Movements of the Asian Stock Market

2020 ◽  
Vol 6 (2) ◽  
pp. 7-18 ◽  
Author(s):  
Le Thi Minh Huong
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Markets ◽  
Oil Prices ◽  
Cross Border ◽  
Korean Stock Market ◽  
Causality Tests ◽  
Research Period ◽  
Insight Into

This article contributed insight into the cross-border role of oil on Asia’s largest stock markets. The research conducted using VAR, GARCH_BEKK (1,1), and related tests such as stationarity, correlation, and causality tests in the analysis. The results obtained suggest that the time series of data ensure conditions for analysis. Asian stock prices are inversely related to oil prices in a correlation. At the same time, in considered stock markets, the Korean stock market and world oil prices appear to have a causal relationship with each other. Moreover, the tests of profitability and volatility in oil prices also indicate a link with the Korean stock market during the research period.

Revisiting the Profitability Premium in the Korean Stock Market

2020 ◽  
Vol 45 (2) ◽  
pp. 247-280
Author(s):  
Su Jeong Lee ◽  
Seunghwan Kim ◽  
Seunghee Yang
Keyword(s):  
Stock Market ◽  
Korean Stock Market ◽  
Profitability Premium

Pemodelan Data Time Series Garch(1,1) Untuk Pasar Saham Indonesia

2015 ◽  
Vol 11 (1) ◽  
pp. 13
Author(s):  
Elfa Rafulta ◽  
Roni Tri Putra
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Markets ◽  
Financial Data ◽  
International Stock Markets

This paper introduced a method pengklusteran for financial data. By using the model Heteroskidastity Generalized autoregressive conditional (GARCH), will be estimated distance between the stock market using GARCH-based distance. The purpose of this method is mengkluster international stock markets with different amounts of data.

Momentum Effect in Stock Market: Empirical Evidence from Pakistan Stock Exchange

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Shahid Rasheed ◽  
Umar Saood ◽  
Waqar Alam
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Stock Markets ◽  
Stock Exchange ◽  
Momentum Effect ◽  
Using Data

This study aims to examine the momentum effect presence in selected stocks of Pakistan stock market using data from Jan 2007 to Dec 2016. This study constructed the strategies includes docile, equal weighted and full rebalancing techniques. Data was extracted from the PSX – 100 index ranging from 2007 to 2016. STATA coding ASM software was used for calculating momentum portfolios, finally top 25 stocks were considered as a winner stocks and bottom 25 stocks were taken as a loser stocks. In conclusion, the results of the study found a strong momentum effect in Pakistan stock exchange PSX 100- index. As by results it has been observed that a substantial profit can earn by the investors or brokers in constructing a portfolio with a short formation period of three months and hold for 3, 6 and 12 months. There is hardly a study is present on the same topic on Pakistan Stock Exchange as preceding studies were only conducted on individual stock markets before merger of stock markets in Pakistan while this study leads the explanation of momentum phenomenon in new dimension i.e. Pakistan Stock Exchange. Keywords: Momentum, Portfolio, Winner Stocks, Loser Stocks

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