• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.11
• /
• pp.7672-7676
• /
• 2015

This study examines the dynamic relations between housing price and trading volume in a set of apartment markets in Republic of Korea to explore the informational role of trading volume in predicting the price volatility. Using monthly index data, EGARCH model is utilized to test for volume effect. To estimate the EGARCH-based volatility, two different sets of region are applied for the monthly return. Strong evidence has been found towards housing turnover leading price volatility, this supports previous studies on financial sector(s). These findings also support that trading volume in the housing market contains information on investor sentiment which, in turn, has a valuation effect on the price.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.1
• /
• pp.15-22
• /
• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• Asia-Pacific Journal of Business
• /
• v.14 no.4
• /
• pp.37-48
• /
• 2023

Purpose - This study aims to explore the influence of emotional discrepancies among investors on the cryptocurrency market. It focuses on how varying emotions affect market dynamics such as volatility and trading volume in the context of Bitcoin trading. Design/methodology/approach - This study involves analyzing data from Bitcointalk.org, consisting of 57,963 posts and 2,215,776 responses from November 22, 2009, to December 31, 2022. Tools used include the Linguistic Inquiry and Word Count (LIWC) software for classifying emotional content and the Python Pattern library for sentiment analysis. Findings - The results show that heterogeneous emotional feedback, whether positive or negative, significantly influences Bitcoin's intraday volatility, skewness, and trading volume. These findings are more pronounced when the underlying emotion in the feedback is amplified. Research implications or Originality - This study underscores the significance of emotional factors in financial decision-making, especially within the realm of social media. It suggests that investors and market strategists should consider the emotional landscape of online forums when making investment choices or formulating market strategies. The research also paves the way for future studies regarding the behavioral impact of emotions on the cryptocurrency market.

• The Journal of the Korea Contents Association
• /
• v.21 no.11
• /
• pp.320-332
• /
• 2021

This paper investigates the influence of stock-level left-tail risk, which is defined using Value-at-Risk(VaR) estimates of past one-year daily stock returns, in the expected stock returns in the Korean stock market. Our results are summarized as follows: First, monthly-constructed zero-cost portfolios that buy (shortsell) the highest (lowest) left-tail risk decile in the previous month exhibit an average monthly return (called left-tail risk premium) of -2.29%. Second, Fama-MacBeth cross-sectional regressions suggest that left-tail risk in the previous month shows significant and negative explanatory power over return in this month, after controlling for various firm characteristics such as firm size, B/M, market beta, liquidity, maximum daily return, idiosyncratic volatility, and skewness. Third, the stocks with larger recent month loss have lower returns in the next month. Fourth, the magnitude of left-tail risk premium is negatively related with lagged market-level volatility. These results support the hypothesis from a perspective of behavioral finance that the overpricing of stocks with left-tail risk is attributed to the investors' underreaction to it.

• Journal of Korean Society of Forest Science
• /
• v.104 no.2
• /
• pp.248-253
• /
• 2015

This study applied the portfolio approach as a means to provide decision-making information for the establishment of the optimal production plan for non-timber products. The target items of non-timber forest product were Chestnut, Jujube, Walnut and Astringent Persimmon. The data used in this study were the annual report of forestry production cost survey which contains the annual production, annual gross income, and annual product cost from 2008 to 2013. These data were used to calculate the expected return of non-timber forest product. The objective function in the portfolio models was to minimize the expected return volatility, called risk and the constrain was to achieve the minimum expected return rate. Results indicated that the production ratio of the nuts and fruits in 2013 was 7% for Chestnut, 20% for Jujube, 5% for Walnut and 68% for Astringent Persimmon. Furthermore, portfolio presented that the production ratio was 10% for Chestnut, 9% for Jujube, 3% for Walnut and 78% for Astringent Persimmon in the near future. The cause was analyzed due to maintain stable production and income of Astringent Persimmon and Chestnut. Meanwhile, the revenue of Walnuts and Jujube was in great variation with relatively higher revenues.

• The Journal of the Korea Contents Association
• /
• v.17 no.5
• /
• pp.165-173
• /
• 2017

The purpose of this study was to analyze the correlation and volatility of Korea and neighboring East Asia stock markets. East Asian stock markets were selected for Japan, China, Hong Kong and Taiwan by economically and geographically close with Korea. If you understand the volatility and the correlation between Korea and the East Asian stock market, it may be helpful in predicting investment. And It may reduce the risk of investing of asset allocation in global portfolio level. For this using the national monthly return data for the last 163 months, I was calculating and comparison the rate and correlation, and regression analysis. Result of the correlation analysis, Korea have shown a low correlation with China. while showing a high correlation with Taiwan and Hong Kong. China has been forming its own market in East Asia and showing a low correlation with other countries exception Hong Kong. Hong Kong has been determined as the highest harmonization within the East Stock Market.

• International Area Studies Review
• /
• v.12 no.2
• /
• pp.3-26
• /
• 2008

This article investigates the usefulness of the skewed Student-t distribution in modeling the long memory volatility property that might be present in the daily returns of two Australian financial series; the ASX200 stock index and AUD/USD exchange rate. For this purpose we assess the performance of FIGARCH and FIAPARCH Value-at-Risk (VaR) models based on the normal, Student-t, and skewed Student-t distribution innovations. Our results support the argument that the skewed Student-t distribution models produce more accurate VaR estimates of Australian financial markets than the normal and Student-t distribution models. Thus, consideration of skewness and excess kurtosis in asset return distributions provides appropriate criteria for model selection in the context of long memory volatility models in Australian stock and foreign exchange markets.

• Journal of the Korean housing association
• /
• v.14 no.2
• /
• pp.89-100
• /
• 2003

This study is identified the characteristics of housing product through housebuilders' strategies. As a methodology for this study, literature survey and questionnaire survey were used. Questionnaires have been done on mail to 232 housebuilders and return rate was 34.1%. In summary, housing product can be characterized long gestation period, periodically building cycle, future uncertainty of market volatility, maximization of land development gain, utilization of public fund for continuous building activity, moral hazard by accidentally bankrupcy. Therefore private housebuilding could be defined speculative industry.

• Bulletin of the Korean Mathematical Society
• /
• v.53 no.5
• /
• pp.1411-1425
• /
• 2016

We provide a partial differential equation for European options on a stock whose price process follows a general geometric Riemannian Brownian motion. The existence and the uniqueness of solutions to the partial differential equation are investigated, and then an expression of the value for European options is obtained using the fundamental solution technique. Proper Riemannian metrics on the real number field can make the distribution of return rates of the stock induced by our model have the character of leptokurtosis and fat-tail; in addition, they can also explain option pricing bias and implied volatility smile (skew).

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.4
• /
• pp.1027-1036
• /
• 2008

Value at Risk(VaR) is a fundamental tool for managing market risks. It measures the worst loss to be expected of a portfolio over a given time horizon under normal market conditions at a given confidence level. Calculation of VaR frequently involves estimating the volatility of return processes and quantiles of standardized returns. In this paper, we introduced and applied the CreditMetrics model to estimate the credit VaR of Korean Property and Casuality insurers.