• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.45-52
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• 2021

Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009-2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.

• Journal of Korea Port Economic Association
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• v.31 no.2
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• pp.103-114
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• 2015

The exchange rate volatility during the global financial crisis in 2007-2009 led Korean shipbuilding companies to face currency risk. The use of foreign currency derivatives to take a risk in financial exposure affects them significantly. This research analyzes how the use of foreign currency derivatives affects the Korean shipbuilding industry in relation to its foreign sales by company type and over time, especially before and after the crisis period. It is based on statistical data presented by KOSHIPA and KOSIC in 2001-2014. The results of the analysis show that there is a significant relationship between foreign currency derivatives and foreign currency exposure for all firm sizes and years, but no relationship between them overtime.

• Journal of Korea Trade
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• v.23 no.6
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• pp.66-92
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• 2019

Purpose - Foreign Exchange Rates (FER) have been one of the most significant factors for both Korean exporters and the economy of Korea. The purpose of this study is to evaluate whether exporters with a high level of Exchange Rate Elasticity of Sales (ERES) make the use of earnings management for Income Smoothing (IS). Design/methodology - Income smoothing was obtained using the methodology suggested by Leuz, Nanda and Wysocki (2003). Accruals-based Earnings Management (AEM) was estimated using Discretionary Accruals (DA) calculated by the operant Jones Model developed by Dechow, Sloan and Sweeney (1995). Real Earnings Management (REM) was obtained using the methodologies suggested by Roychowdhury (2006) and Cohen and Zarowin (2010). Data were 2,402 firm years of public listed companies on the KRX, which were not in the financial industry and had a settlement of accounts in December for the period from 2013 to 2017. Findings - Results of the evaluation are as follows. First, companies with higher levels of ERES have relatively lower levels of smoothing of reported income. This might be because a fluctuation in sales caused by an exchange rate fluctuation has a direct impact on the volatility of the reported income. Second, companies with high levels of both ERES and IS have a positive correlation with both AEM and REM. This might be because companies with high levels of IS engage in earnings management to smooth reported income. Specifically, it is possible to assume that for smoothing the reported income, not only AEM but also REM is practiced. Third, companies with high levels of ERES but low levels of IS have a negative correlation with both AEM and REM. This could be interpreted as companies exhibiting low levels of IS due to higher levels of ERES tend to control IS. In addition, such results were supported by firms relying highly on exporting, and are consequently sensitive to exchange rate fluctuation. Therefore, it may conclude that companies with high levels of ERES make the use of earnings management as a means of IS. Originality/value - This study can find its significance from the fact that it is the first study, empirically verifying that companies of Korea, where exportation is a large part, use both AEM and REM as a means for smoothing reported income upon facing exchange rate fluctuations. In addition, it is highly expected that the results of this study could be useful for participants of financial markets when making IS-related decisions.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.94-108
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• 2021

This study is to identify the internal and external factors of a company that can affect the rate of change in the inventory turnover ratio. In addition, by appropriately managing or responding to these factors, changes in the inventory turnover ratio do not occur abruptly, so that the company's business and financial performance can be improved. To confirm this, factors such as gross profit margin, cash flow volatility, advertising expenses, inflation, exchange rate rise, and leading economic index were selected, and these factors were predicted to affect the change rate of inventory turnover. Data of 85,878 companies were obtained from domestic securities listings, KOSDAQ listings, and externally audited companies, and multiple regression analysis was performed using the data. Gross profit margin and cash flow volatility have a significant positive (+) effect, advertising expenses have a negative (-) significant effect, and inflation and exchange rate rises have a negative (-) significant effect. As an influence, the leading economic index was tested to have a significant positive (+) effect. Through this, it is suggested that manufacturing companies can improve their business performance and achieve operational efficiency by well understanding and appropriately managing factors that can affect the change rate of inventory turnover.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.49-62
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• 2022

Realized volatility is well known to have long memory, strong association with other global financial markets and interdependences among macroeconomic indices such as exchange rate, oil price and interest rates. This paper proposes autoencoder factor-augmented heterogeneous autoregressive (AE-FAHAR) model for realized volatility forecasting. AE-FAHAR incorporates long memory using HAR structure, and exogenous variables into few factors summarized by autoencoder. Autoencoder requires intensive calculation due to its nonlinear structure, however, it is more suitable to summarize complex, possibly nonstationary high-dimensional time series. Our AE-FAHAR model is shown to have smaller out-of-sample forecasting error in empirical analysis. We also discuss pre-training, ensemble in autoencoder to reduce computational cost and estimation errors.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.611-622
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• 2019

This paper considers the estimation of the long memory parameter in nonparametric regression with strongly correlated errors. The key idea is to minimize a unified mean squared error of long memory parameter to select both kernel bandwidth and the number of frequencies used in exact local Whittle estimation. A unified mean squared error framework is more natural because it provides both goodness of fit and measure of strong dependence. The block bootstrap is applied to evaluate the mean squared error. Finite sample performance using Monte Carlo simulations shows the closest performance to the oracle. The proposed method outperforms existing methods especially when dependency and sample size increase. The proposed method is also illustreated to the volatility of exchange rate between Korean Won for US dollar.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• KDI Journal of Economic Policy
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• v.36 no.3
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• pp.1-23
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• 2014

This paper has studied the monetary policy in Korea with a time varying VAR model using four key macroeconomic variables. First, inclusion of the exchange rate was a crucial factor in evaluating Korean monetary policy since the monetary policy demonstrated sensitivity to exchange rate movements during the crisis periods of both the Asian financial crisis of 1997 and the global financial crisis of 2008. Second, a specification of the stochastic volatilities in TVP-VAR model is important in explaining excessive movements of all variables in the sample. The overall moderation of variables in 2000s was more or less due to a reduction of the stochastic volatilities but also somewhat due to the macroeconomic fundamental structures captured by impulse response functons. Third, the degree of the monetary policy effectiveness of inflation was mitigated in recent periods but with increased persistence. Lastly, the monetary policy stance towards inflation stabilization has advanced ever since the inflation targeting scheme was adopted. However, there still seems to be a room for improvement in this aspect since the degree of the monetary policy stance towards inflation stabilization was relatively weaker than to output stabilization.

• Economic Analysis
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• v.25 no.1
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• pp.1-33
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• 2019

This paper examines the economic factors that are related to the dynamics of the variance risk premium, and specially, which economic factors are related to the forecasting power of the variance premium regarding future index returns. Eleven general economic variables, eight interest rate variables, and eleven sentiment-associated variables are used to figure out the relevant economic variables that affect the variance risk premium. According to our empirical results, the won-dollar exchange rates, foreign reserves, the historical/implied volatility, and interest rate variables all have significant coefficients. The highest adjusted R-squared is more than 65 percent, indicating their significant explanatory power of the variance risk premium. Next, to verify the economic variables associated with the predictability of the variance risk premium, we conduct forecasting regressions to predict future stock returns and volatilities for one to six months. Our empirical analysis shows that only the won-dollar exchange rate, among the many variables associated with the dynamics of the variance risk premium, has a significant forecasting ability regarding future index returns. These results are consistent with results found in previous studies, including Londono (2012) and Bollerslev et al. (2014), which show that the variance risk premium is related to global risk factors.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.189-200
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• 2015

Stationary bootstrapping is applied to a Lagrangian multiplier (LM) test to test market microstructure noise (MMN) in financial asset prices. A Monte-Carlo experiment shows that the bootstrapping method improves the size of the original LM test which has some size distortion for conditional heteroscedastic models. The proposed test is illustrated for real data sets like KOSPI index and Won-Dollar exchange rate.