• International conference on construction engineering and project management
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• 2013.01a
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• pp.151-157
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• 2013

Since the sub-prime mortgage crisis from the US in 2008, the Korean housing market has plummeted. However, the deposit prices of the Korean local lease contract, Chonsei, had been increasing. This increase of Chonsei prices can be a threat to low-income people, most of whom prefer to live in houses with a Chonsei contract. In the housing and Chonsei market, there are many stakeholders with their own interest, hence, simple thoughts about housing and Chonsei market, such as more house supply, will decrease house price, would not work in a real complex housing market. In this research, we suggests system dynamics conceptual model which consists of causal-loop-diagrams for the Chonsei market as well as the housing market. In conclusion, the Chonsei price has its own homeostasis characteristics and different price behavior with housing price in the short and long term period. We found that unless government does not have a structural causation mind in implementing policies in the real estate market, the government may not attain their intended effectiveness on both markets.

• 한국벤처창업학회:학술대회논문집
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• 2018.04a
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• pp.187-190
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• 2018

The study examines the effects of the regulation on cryptocurrency market, investigating a case in South Korea. As South Korea has one of the largest market share of the cryptocurrency market for the time being, its regulation in South Korea affected the entire markets around the World. This research in progress will use the method of difference-in-differences to assess the effects of regulation to the market. The findings indicate that there is a significant reduction of the Bitcoin price and the price volatility was significantly reduced by about 58% after the regulation of the cryptocurrency market. More so the trading activity indicates a huge decline after regulation was implemented.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• Culinary science and hospitality research
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• v.23 no.2
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• pp.126-134
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• 2017

The purpose of this paper was to examine the dynamics of the price discovery function between lean hog futures and spot markets using the vector error correction model (VECM). The researcher also investigated the existence of the long-run equilibrium relationship between the lean hog futures and spot markets. Daily time series data of lean hog futures and spot observed in the Korean market during the period from 5 Jan. 2011 to 28 Dec. 2012 were analyzed. To examine the price discovery, this study employed the Gonzalo and Granger's (1995) information ratio and Hasbrock's (1995) information ratio measurement method. The significant findings of the study are summarized as follows. First, lean hog futures and spot market are significantly correlated. Secondly, the lean hog future market plays a more dominant role in price discovery than the spot market. Finally, price discovery measures based on the VECM suggested that the lean hog future market plays a more dominant role in price discovery than the lean hog spot market. This is the important systematic empirical work to find the relationship between the lean hog future and spot market.

• Journal of Distribution Science
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• v.11 no.10
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• Korean Management Science Review
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• v.33 no.4
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• pp.65-75
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• 2016

We study limit pricing in a price-based duopoly market under asymmetric information on the demand state. An incumbent, who is a monopolist in the initial period, has complete information on the size of a market, while a potential entrant only knows it partially. After observing the sales price of the incumbent in the first period, the entrant decides whether to enter a duopoly market and the sales price if she chooses to. We present a separating perfect Bayesian equilibrium, which indicates that limit pricing can deter the entry of a potential entrant under price competition when there is information asymmetry about the demand state.

• Journal of the Korean Society of Costume
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• v.58 no.7
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• pp.92-103
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• 2008

The purpose of this study was to subdivide the shoes market in Korea and to evaluate the size and competitive strength of each segment. In order to implement the purpose of this study, the data of 300 respondents were analyzed using CBC(Choice-Based Conjoint measurement) and mixture model. The part-worth utilities were then used to predict the impact of price change on the choice probability using the legit model. As a result, the mixture model showed the optimal segments number and the shoes market in Korea was divided into 4 segments. Each segment was identified by distinctive characteristics such as brands, price and demand for comfortable shoes. Also, as a result of grasping the competitive structure and the competitive strength by sub-markets, one group was sensitive to price according to each competitive situation, whereby the choice probability was greatly influenced, and the other group on the contrary. This study made it clear that discrimination between brands whose profits Increase sharply if price is lowered and brands whose profits do not increase even if price is lowered can help brand managers with their decision-making on price lowering.

• Journal of the Korean Home Economics Association
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• v.40 no.9
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• pp.1-15
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• 2002

The multi-faceted influence of price on consumers' purchasing process of apparel products: Relationships with attitudinal and behavioral variables Price has a significant relationship to clothing products not only because of its practical, emotional and symbolic attributes but also because of its wide range and frequent changes. The purpose of this study was to identify the multi-faceted influence of price on consumers' purchasing process of clothing products. Six types of price-perceptions were related to various attitudinal and behavioral variables in a clothing purchase. A questionnaire was developed and data were collected from 720 adult women living in Seoul. Factor analysis, multiple regression, t-test and canconical correlation were employed to analyze the data. Low price consciousness was negatively related to product-oriented aspects of clothing and effected the one-price sale, visiting public markets and using interpersonal sources of price information. Value for money consciousness was positively related to product-oriented aspects of clothing and consumers' age or marriage and effected price considerations at the on-purchase and post-purchase stage. Price-quality inference was related to product-oriented and market-oriented aspects of clothing while price-prestige inference was related to visual and symbolic aspects of clothing and effected normal-price purchasing. Sale proneness was related to market-oriented aspects of clothing and effected seasonal sale price purchasing and price mavenism was related to market-oriented and visual aspects of clothing and effected price considerations at the pre-purchase stage.

• Land and Housing Review
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• v.9 no.4
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• pp.1-9
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• 2018

Since year 2000, French housing and rent prices rose at a rapid rate and the housing market has been overheated. Face to this phenomena, the French government enacted a new law Alur which is a legislatif tool to control the private housing rent price for the cities, where the tension of the housing market is very high. This new law has impacted the housing market in two major ways. First, for the 38 cities designated by this law, the rent price's increase rate can not rise above the IRL, which is the rent reference index. Secondly, this law also permits local authorities to control the housing rent's price following the concrete price guidance. Especially in Paris, the city applicated this method for private rental housing since 2015. This city classified its own area by 14 zones. Based on the market surveys of each sector, local authority made a guidance for private housing rent's price. The guideline is consisted of average prices, maxima and minima price by types, which is classified by the construction year, number of rooms and furnished or not. Therefore, this study aims to understand french housing rent's price control system and draw implementation for korean housing rent policies. This research is meaningful for it introduces recent foreign regislations which could be helpful to control the housing market in Korea.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.143-150
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• 2020

This study aims to investigate the effect of oil price and exchange rate on the two Vietnamese stock market indices: VN index and HXN index. This study uses the daily data from August 1^st 2000 to October 25^th 2019 of the two Vietnamese stock indices: VN index and HNX index, the two oil price indices: BRENT and WTI, and the two exchange rates: US dollar to Vietnamese dong and Euro to Vietnamese dong. Due to the presence of heteroskedasticity in our data, we use GARCH (1,1) regression model to perform our analysis. Our findings show that the oil price has a significant positive effect on the two Vietnamese stock market indices. In terms of the stock index volatility, both the VN index and HNX index volatilities are negatively impacted by the return of oil price. While the conclusion about the impact of oil price remained consistent through all three robustness tests, the effect of exchange rate on Vietnamese stock market indices is not consistent. We find thatchanges of the USD/VND exchange rate significantly impact the return and volatility of HNX index only in GARCH (1,1) setting. Our analysis also survives a number of robustness tests.