• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.769-775
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• 2021

The objective of this research was to analyze the factors influencing the farm-gate shrimp prices in Thailand using monthly time series from January 2001 to December 2019. The econometric methodology was employed to satisfy the purpose, consisting of the cointegration test for revealing the long-run relationship and equilibrium elasticity between the variables as well as the error correction model for detecting speed adjustment to shock responses. The empirical results revealed that (1) the export shrimp prices, shrimp production in the country, and shrimp export volume indicated a long-run relationship running to the farm-gate shrimp prices in Thailand with the size of equilibrium elasticity equal to 1.083%, -0.256%, and 0.123, respectively, and (2) the farm-gate shrimp prices in Thailand would adjust to the equilibrium line with a speed equal to 20.147% if there was any kind of incident or shock which caused the relationship to deviate from the equilibrium point. There was no relationship in terms of global shrimp prices and the exchange rate for farm-gate shrimp prices in Thailand. The recommendations should emphasize the varieties of shrimp products for export to other countries beyond the main trading markets nowadays to reduce risks and fluctuations in the export prices of shrimp products.

• International Area Studies Review
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• v.12 no.3
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• pp.171-194
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• 2008

This paper analysis the long-run demand for monetary indicator M2 and Liquidity indicator L in Korea in the period from 1980:1 to 2006:3 by cointegration and error correction models. The empirical evidence that M2, L in Korea is meaningfully cointegrated with income, interest rate, exchange rate, inflation uncertainty, real effective exchange rate, exchange rate uncertainty and LIBOR, thus showing the existence of long-run demand function under open-economy framework.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.405-421
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• 2019

Predicting how much energy to use is an important issue in society. However, it is more difficult to capture the usage characteristics of residential buildings than other buildings. This paper provides time series analysis methods for electricity consumption in a residential building. Temperature is closely related to electricity demand. An error correction model, which is a method of adjusting the error with time, is applied when a cointegration relation is established between variables. Therefore, we analyze data via ECMs with consideration of the temperature effect.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.65-75
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• 2021

This study analyzes the validity of the Phillips curve with regards to Turkey. The existence and direction of the causality relationship (reason-outcome relationship) between unemployment and inflation is investigated using inflation and unemployment data for the period 1980-2019. Unit root tests were utilized to evaluate the stationarity of the series. In line with the Zivot-Andrews unit root test, which was developed in response to the criticism of the failure of studies that presented macro-variables like inflation to consider traditional unit root tests, in this research, the Engle-Granger cointegration test was implemented to check whether the series could perform a joint action, and, finally, the Granger causality relationship was explored. According to the results of the analysis, over the relevant period there was a single directional causality relationship from inflation toward unemployment in Turkey. The importance of this relationship at the 10% significance level indicates the existence of many different factors that affect inflation and unemployment. Given the existence of a cointegration and causality relationship between inflation and unemployment, it can be said that, in Turkey, the Phillips curve is valid for the period 1980-2019 and that an increase of 1% in inflation will reduce the unemployment rate by 0.028%.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.93-104
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• 2021

In recent years, there has been a substantial theoretical and empirical study on the role that financial market development has significantly played in promoting economic growth and development in the world. The development of an economy requires the financial industry to be developed. In the context of rapid economic development, global warming has become a serious problem with issues such as rising average temperatures, climate change, rising sea level, and increasing carbon dioxide emissions. This study aims to examine the influence of economic growth, financial development, transportation capacity, and environmental degradation. Using time-series data from 1986 to 2019 and environmental degradation being measured by CO2 emissions, the study employs a quantity of ample unit root tests, the structural break unit root tests, Autoregressive Distributed Lag (ARDL), and cointegration bounds test. The results show that there is a significant long-term cointegration among study variables. Empirical findings also indicate that an increase in per capita GDP and financial development worsens environmental quality whereas transportation capacity and foreign investment can improve environmental quality.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.311-324
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• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.27-39
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• 2022

The exchange rate is an important macroeconomic variable that influences internal and external balances. Nepal follows a dual exchange rate such that the Nepali rupee (NPR) is pegged with the Indian rupee (INR) but floats with the United States dollar (USD) and all other currencies. There have been very few studies on the exchange rate of Nepal, of which the majority focus on the bivariate relationship between exchange rate and another variable. However, this paper analyses the multivariate relationship between the USD-NPR exchange rate and major macroeconomic variables. Determinants of Nepal's exchange rate have been derived with multiple regression using the ordinary least square (OLS) approach. Since the explanatory variables could not significantly capture the movement of the dependent variable, a long-run relationship between Nepal and India's exchange rate has been analyzed using Engle-Granger cointegration to establish a relationship as suggested by a graphical representation. This explains that Nepal's exchange rate long run is determined by India's exchange rate than its own fundamentals. In addition, the macro-linkages of Nepal's macroeconomic variables have been analyzed using Standard Vector Autoregressive models followed by impulse response analysis which is useful for policy decisions. Some policy implications indicating the sustainability of Nepal's pegged regime have been drawn based on the empirical analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.123-130
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• 2022

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.1-9
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• 2022

The study examines stock prices (LOGKSE) and exchange rate (LOGPK)-Pakistani Rupee vis-à-vis US Dollar- interactions in Pakistan. This study employs a multivariate VAR-GARCH model using monthly data from January 2012 to October 2020. The results of the Johansen cointegration test show that there is no relationship between Foreign Exchange Market and Stock Market in the long run. In the short-run, stock exchange returns are affected slightly negatively by the changes in the foreign exchange market, but the foreign exchange market does not seem to be affected by the ups and downs of the stock exchange. The VAR model and Granger Causality show that both markets are strongly influenced by their own lagged values rather than by the lagged values of one another and show weak or no correlation between the two markets. Volatility persistence is observed in both the stock and foreign exchange markets, implying that shocks and past period volatility are major drivers of future volatility in both markets. Thus greater uncertainties today will induce panic and consequently generate higher volatility in the future period. This phenomenon has been observed many times on Pakistan Stock Exchange especially. The results have important implications for local international investors in portfolio diversification decisions and risk hedging strategies.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.