• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.247-262
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• 2022

Purpose - The purpose of this study is to examine the impact of the Pandamic Declaration on 'untact firms' listed in KOSPI and KOSDAQ market in order to verify Investor Mania Hypothesis. Design/methodology/approach - This study collected financial data for 44 untact firms in KOSPI and KOSDAQ market. Then, we employed ESM(Event Study Methodology), EGARCH model and DID(Difference-In-Difference) for analysis. Findings - First, in contrast with the benchmarking index, KOSPI 200 which shows a negative (-) abnormal return trend, the untact firms have positive abnormal return trend consistently. Second, after the Pandemic Declaration, the variability of abnormal return for the untact firms is found to be significantly positive. Third, we find that the cumulative abnormal return and volatility of the untact firms significantly increase after the Pandemic Declaration. Research implications or Originality - Based on the Investor Mania Hypothesis, we confirm that the market potential of untact firms after the Pandemic Declaration is observed when compared with the KOSPI 200.

• Korea Trade Review
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• v.47 no.2
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• pp.133-154
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• 2022

The Baltic Capesize Index (BCI), which is used as an indicator for marine transportation of steel raw materials, is one of the key economic indexes for managing the risk of loss due to rapid market fluctuations when steel companies establish business strategies and procuring plans for raw materials. Still, the conditions of supply and demand of steel raw materials has been extremely affected by volatility shocks from drastic events like the financial crisis such as the Lehman Brothers incident and changes in the external environment such as COVID-19. And, especially since the 2008 financial crisis, endeavors to predict the market conditions of the steel raw material is becoming more and more arduous for the deepening uncertainty and increased volatility of BCI, which has been used as a leading indicator of the real economy. This study investigates the correlation between the steel raw material market and the marine transportation market by estimating the spillover effect of information between markets. The vector error correction model (VECM) was used to analyze information transfer based on the correlation between the BCI and crude steel production, capesize fleet supply, raw material price, and cargo volume.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.71-88
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• 2024

Purpose - This study provides an overview of existing research and practices related to market risk premiums(MRP), and empirically estimates the MRP in Korea, particularly using the related option prices. We also seek to improve the current MRP practices and explore alternative solutions. Design/methodology/approach - We present the option price-based MRP estimation method, as proposed by Martin (2017), and implement it within the context of the Korean stock market. We then juxtapose these results with those derived from other methods, and compare the characteristics with those of the United States. Findings - We found that the lower limit of the MRP in the Korean stock market shows a much lower value compared to the US. There seems to be the possibility of a market crash, exchange rate volatility, or a lack of option trading data. We investigated the predictive power of the estimated values and discovered that the weighted average of the results of various methodologies using the Principal Component Analysis (PCA) is superior to the individual method's results. Research implications or Originality - It is required to explore various methods of estimating MRP that are suitable for the Korean stock market. In order to improve the estimation methodology based on option prices, it is necessary to develop the methods using the higher-order(third order or above) moments, or consider additional risk factors such as the possibility of a crash.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.109-118
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• 2019

As a result of the United States (U.S) -China trade conflict, the recent instability of the stock market has led many people to invest in Bitcoin, a commodity that many previous studies have interpreted as a safe asset. However, recent Bitcoin market price fluctuations suggest that the asset's stability stems from speculative purchasing trends. Therefore, classifying the characteristics of Bitcoin assets can be an important reference point in analyzing relevant accounting information. To determine whether Bitcoin is a safe asset, this study analyzed the correlation between Bitcoin and economic indicators to verify whether gold and Bitcoin responded similarly in time series analyses. These show that the regression explanatory power between the price of gold and bitcoin is low, thus no relation between the two assets could be drawn. Additionally, the Granger causality analyses of six individual economic variables and Bitcoin did not establish any notable causality. This can be interpreted that short-term price fluctuations have a significant impact on the nature of Bitcoin as an asset.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.249-264
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• 2009

Equity-indexed annuities(EIAs) provide their customers with the greater of either the return linked to the underlying index or the minimum guaranteed return. Insurance companies have developed EIAs to attract customers reluctant to buy traditional fixed annuities because of low returns and also reluctant to buy mutual funds for fear of the high volatility in the stock market. This paper proposes a new type of EIA embedded with an outside barrier option with flexible monitoring period in order to increase its participation rate. It also derives an explicit pricing formula for this proposed product, and discusses numerical examples to show relationships among participation rate, barrier level, index volatility and correlation.

• Asia-Pacific Journal of Business
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• v.11 no.2
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• pp.159-172
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• 2020

Purpose - The purpose of this study is to investigate economic variables which have impact on the prices and returns of preferred stocks and to provide investors, underwriters, and policy makers with information regarding correlations and causal relations between them. Design/methodology/approach - This study collected 98 monthly data from Korea Exchange and Bank of Korea. The Granger causal relation analysis, unit-root test and the multiple regression analysis were hired in order to analyze the data. Findings - First, our study derives the economic variables affecting the prices and returns of preferred stocks and their implications, while previous studies focused mainly on the differential characteristics and related economic factors between common and preferred stocks. Empirical results show that the significant variables influencing the prices and returns of preffered stocks are consumer sentiment index, consumer price index, industrial production index, KOSPI volatility index, and exchange rate between Korean won and US dollar. Second, consumer sentiment index, consumer price index, and industrial production index have significant casual relations with the returns of preferred stocks, providing market participants with important information regarding investment in preferred stocks. Research implications or Originality - This study is different from previous studies in that preferred stocks themselves are investigated rather than the gap between common stocks and preferred stocks. In addition, we derive the major macro variables affecting the prices and returns of preferred stocks and find some useful causal relations between the macro variables and returns of preferred stocks. These findings give important implications to market participants, including stock investors, underwriters, and policy makers.

• East Asian Economic Review
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• v.27 no.3
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• pp.213-242
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• 2023

This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.85-98
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• 2016

This study makes an empirical comparison of various realized volatilities (RVs) in terms of overnight returns. In financial asset markets, during overnight or holidays, no or few trading data are available causing a difficulty in computing RVs for a whole span of a day. A review will be made on several RVs reflecting overnight return variations. The comparison is made for forecast accuracies of several RVs for some financial assets: the US S&P500 index, the US NASDAQ index, the KOSPI (Korean Stock Price Index), and the foreign exchange rate of the Korea won relative to the US dollar. The RV of a day is compared with the square of the next day log-return, which is a proxy for the integrated volatility of the day. The comparison is made by investigating the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE). Statistical inference of MAE and RMSE is made by applying the model confidence set (MCS) approach and the Diebold-Mariano test. For the three index data, a specific RV emerges as the best one, which addresses overnight return variations by inflating daytime RV.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.87-106
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• 2022

Uncertainties in the energy market are increasing due to technology developments (shale revolution), trade wars, COVID-19, and the Russia-Ukraine war. Especially, since 2020, the risk of international trade in the energy market has increased significantly due to changes in the supply chain of transportation and due to prolonged demand reduction because of COVID-19 and the Russian-Ukraine war. Considering these points, this study analyzed connectedness between energy price, tanker index, and uncertainty to understand the connectedness between international trade in the energy market. Main results are summarized as follows. First, as a result of analyzing stable period and unstable period of the energy price model using the MS-VAR model, it was confirmed that both the crude oil market model and the natural gas market model had a higher probability of maintaining stable period than unstable period, increasing volatility by specific events. Second, looking at the results of the analysis of the connectedness between stable period and unstable period of the energy market, it was confirmed that in the case of total connectedness, connectedness between variables was increased in the unstable period compared to the stable period. In the case of the energy market stable period, considering the degree of connectedness, it was confirmed that the effect of the tanker freight index, which represents the demand-side factor, was significant. Third, unstable period of the natural gas market model increases rapidly compared to the crude oil market model, indicating that the volatility spillover effect of the natural gas market is greater when uncertainties affecting energy prices increase compared to the crude oil market.