• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.747-757
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• 2021

The primary purpose of the study is to investigate the volatility spillover from financial uncertainty (FU) of the United States (US) to the stock markets of SAARC member countries including India, Sri-Lanka, Pakistan, and Bangladesh. The empirical literature overlooked SAARC countries and the FU index. Based on the estimation method, the data of FU is available for three different forecast horizons including 1-month, 3-months, and 12-months. For empirical analysis, monthly data is used from February 2013 to September 2019. EGARCH model is employed to investigate the volatility spillover effects. The findings of the study show that the spillover effect of FU varies with the forecast horizon. The FU with a higher forecast horizon has a significant spillover effect on more countries. The spillover effect of US financial uncertainty is negative in most of the SAARC countries. Bangladesh stock market is influenced by FU with all three forecast horizons whereas the volatility of the Pakistan stock market is not influenced by FU with any forecast horizon. The findings are consistent with the concept of "limited trade openness" in the financial markets of emerging economies. The emerging economies avoid financial market openness to minimize the risk of spillover of other countries.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.296-309
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• 2022

Timer options are one of the contingent claims that, for given the variance budget, its payoff depends on a random maturity in terms of the realized variance unlike the standard European vanilla option with a fixed time maturity. Since it was first launched by Société Générale Corporate and Investment Banking in 2007, the valuation of the timer options under several stochastic environment for the volatility has been conducted by many researches. In this study, we propose the pricing of timer power options combined with standard timer options and the index of the power to the underlying asset for the investors to actualize lower risks and higher returns at the same time under the uncertain markets. By using the asymptotic analysis, we obtain the first-order approximation of timer power options. Moreover, we demonstrate that our solution has been derived accurately by comparing it with the solution from the Monte-Carlo method. Finally, we analyze the impact of the stochastic volatility with regards to various parameters on the timer power options numerically.

• Economic Analysis
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• v.25 no.3
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• pp.70-99
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• 2019

Using a stochastic volatility-in-mean VAR model consisting of the KOSPI index, the foreign exchange rate, the government bond rate, and the credit spread, this study investigates the effects of financial market uncertainty on financial markets. We find that higher uncertainty has recessionary effects on financial markets. The effects are especially stronger in equity markets and in won-dollar exchange markets. We also find that the effects of uncertainty become stronger during times of financial market stress compared to normal times. Finally, the results imply that financial market uncertainty may potentially affect the real sector, too.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.27-34
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• 2020

The study investigates herding behavior in cryptocurrencies in different situations. This study employs daily returns of major cryptocurrencies listed in CCI30 index and sub-major cryptocurrencies and major stock returns listed in Dow-Jones Industrial Average Index, from 2015 to 2018. Quantile regression method is employed to test the herding effect in market asymmetries, inter-dependency and intra-dependency cases. Findings confirm the presence of herding in cryptocurrency in upper quantiles in bullish and high volatility periods because of overexcitement among investors, which lead to high volume trading. Major cryptocurrencies cause herding in sub-major cryptocurrencies, but it is a unidirectional relation. However, no intra-dependency effect among cryptocurrencies and equity market is observed. Results indicate that in the CKK model herding exists at upper quantile in market that may be due when the market is moving fast, continuously trading, and bullish trend are prevailing. Further analysis confirms this narrative as, at upper quantile, the beta of bullish regime is negative and significant, meaning the main source of market herding is a bullish trend in investment, which increases market turbulence and gives investors opportunity to herd. Also, we found that herding in cryptocurrencies exits in high volatility periods, but this herding mostly depends on market activity, not market movement.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.85-97
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• 2018

This paper investigates factors underlying a decrease in trading values in KOSPI 200 futures/options market on the basis of the current state of the markets. Among the factors that could affect trading values in KOSPI 200 derivatives market, we focus on the market activity of underlying assets as it has an impact on the trading of financial derivatives. Trading value and volatility are designated as market activity and the empirical results confirm that the market activity of the underlying assets is significant in explaining the decrease in trading values in KOSPI 200 futures/options market. To figure out fundamental reasons of the decrease in trading values in this market, we examine mitigation of home bias and decrease in leverage incentives as they are presumed to have influence on KOSPI 200 index market. As the global and local financial environment is time-varying, the degree of home bias and the leverage demand also changes. It implies that institutional change and/or policy effort to promote the trading of KOSPI 200 financial derivatives should be made taking into account the fact that considerable portion of the change in trading values in financial derivatives market depends on the state of the market.

• The Korean Journal of Financial Management
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• v.25 no.2
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• pp.69-101
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• 2008

We empirically investigate the option leverage property that should be priced under much more general conditions than the Black-Scholes assumptions and the option redundancy property that is based on the assumption that the underlying asset price follows a one-dimensional diffusion process and examine the systematic risk factors implied in the return dynamics of KOSPI 200 index options. We find that the option leverage pattern is similar to the theoretical result but the options are not redundant securities and in the nonlinear structure of option payoffs, the traders of KOSPI 200 index options price the systematic higher-moments and the negative volatility risk premium significantly affects delta-hedged gains, even after accounting for jump fears. But the empirical evidence on jump risk preference is less conclusive.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.91-131
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• 2007

In the paper, the effects of sidecar on index arbitrage trading and non-index arbitrage trading in the Korean stock market are examined. The analyses of return, volatility, and liquidity dynamics illustrate that there are no distinct differences for index arbitrage group and non-index arbitrage group surrounding the sidecar events. For further analysis, we construct pseudo-sidecar sample and analyse the effects of the actual sidecar and pseudo-sidecar on arbitrage sample and non-index arbitrage sample. The result of analysis using pseudo-sidecar shows that the differences between index arbitrage group and non-index arbitrage group are larger in pseudo-sidecar sample than in actual sidecar sample. This means that former results can be explained by temporary order clustering in one side before and after the event. Sidecar has little effect on non-index arbitrage group, however, it has relatively large effect on arbitrage group. These results imply that it needs to redesign the sidecar system of the Korean stock market which applies for all program trading including arbitrage and non-index arbitrage trading.

• International Area Studies Review
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• v.12 no.2
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• pp.3-26
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• 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 Digital Convergence
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• v.15 no.2
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• pp.135-144
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• 2017

This study is to identify the growth rate and volatility of logistics related firms in the stock market. To do this, we used monthly data for 197 years from June 2000 to October 2016 by selecting KOSPI and Transport & Storage(T&S), KOSDAQ, Transportation(TRANS) index. The purpose of this study is to compare the T&S and TRANS stock index returns with the KOSPI and KOSDAQ index. And we are to judge whether the development potential of the logistics industry and the value of the investment of related companies in the future is high. For this purpose, we will analyze the basic statistics, correlation and growth rate of each index, and compare T&S and TRANS with market returns. Analysis result, for the past 197 months logistics related T&S and TRANS have been higher than market returns. The correlation was highly related to TRANS and T & S in KOSPI, but it was not related to KOSDAQ. TRANS represents high risk and high return, while KOSDAQ represents high risk and low return market. TRANS is considered to be an efficient investment. We expect the future development of logistics related industries and T & S and TRANS to show a high rate of increase compared to the market returns.

• Information Systems Review
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• v.23 no.1
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• pp.23-43
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• 2021

Recently, many studies have been conducted to increase the accuracy of stock price prediction by analyzing candlestick charts using artificial intelligence techniques. However, these studies failed to consider the time-series characteristics of candlestick charts and to take into account the emotional state of market participants in data learning for stock price prediction. In order to overcome these limitations, this study produced input data by combining volatility index and candlestick charts to consider the emotional state of market participants, and used the data as input for a new method proposed on the basis of combining variantion autoencoder (VAE) and attention mechanisms for considering the time-series characteristics of candlestick chart. Fifty firms were randomly selected from the S&P 500 index and their stock prices were predicted to evaluate the performance of the method compared with existing ones such as convolutional neural network (CNN) or long-short term memory (LSTM). The results indicated the method proposed in this study showed superior performance compared to the existing ones. This study implied that the accuracy of stock price prediction could be improved by considering the emotional state of market participants and the time-series characteristics of the candlestick chart.