• Title/Summary/Keyword: volatility

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Risk Volatility Measurement: Evidence from Indonesian Stock Market

  • Rahmi, Mustika;Azma, Nurul;Muttaqin, Aminullah Achmad;Jazil, Thuba;Rahman, Mahfuzur
    • The Journal of Asian Finance, Economics and Business
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    • v.3 no.3
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    • pp.57-65
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    • 2016
  • The purpose of this paper is to investigate the volatility of both Islamic and conventional stock market in Indonesia with the aim of identifying the most appropriate model for risk management practice. The study considers GARCH as a genre of model to measure the volatility of stock market movement. The results support the view that each model shows specific volatility from both Islamic and conventional stock market in Indonesia. In Islamic stock market, volatility is affected by exchange rate and money supply (M1) but not interest rate as interest is prohibited in Islam. However, interest rate is found as a principal factor that affects volatility of conventional stock market. The outcomes of this paper are of particular significance to policy makers, as it provides guidelines to maintain economic health. Furthermore, the findings may assist practitioners to understand the consequences of macroeconomic factors such as exchange rate, money supply and interest rate, which are very crucial for the market stability of Indonesian stock market. The paper enhances the understanding of stock market volatility and proposes guidelines risk management practices.

An Empirical Study on the Stock Volatility of the Korean Stock Market (한국 증권시장의 주가변동성에 관한 실증적 연구)

  • Park, Chul-Yong
    • Korean Business Review
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    • v.16
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    • pp.43-60
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    • 2003
  • There are several stylized facts concerning stock return volatility. First, it is persistent, so an increase in current volatility lasts for many periods. Second, stock volatility increases after stock prices fall. Third, stock volatility is related to macroeconomic volatility, recessions, and banking crises. On the other hand, there are many competing parametric models to represent conditional heteroskedasticity of stock returns. For this article, I adopt the strategy followed by French, Schwert, and Stambaugh(1987) and Schwert(l989, 1990). The models in this article provide a more structured analysis of the time-series properties of stock market volatility. Briefly, these models remove autoregressive and seasonal effects from daily returns to estimate unexpected returns. Then the absolute values of the unexpected returns are used in an autoregressive model to predict stock volatility.

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The Causality and Volatility Spillover between Farming fish Species in Consumption Replacement Relation (소비 대체 양식어종 간의 가격 인과성과 변동성 전이에 관한 연구)

  • Kang, Seok-Kyu
    • The Journal of Fisheries Business Administration
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    • v.46 no.3
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    • pp.119-127
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    • 2015
  • This study is to analyse the causality and volatility spillover between farming fish species in consumption replacement relation using flatfish(oliver flounder) and rockfish's wholesale market price data from September 2006 to July 2015. For the analysis, VAR(5) model and bivariate asymmetric GARCH-BEKK model are employed. The empirical results of this study are summarized as follows: First, the price volatility of flatfish and rockfish is very large without the trend during the sample period. Second, the correlation coefficient between flatfish and rockfish wholesale markets has positive 0.1059 value. Third, causality relation is unidirectional from rockfish market to flatfish market. Fourth, conditional volatility spillover effect is unidirectional from rockfish market to flatfish market, but asymmetric volatility effect is bidirectional between flatfish and rockfish markets that implies the bad news arising from flatfish wholesale market impact on rockfish market's volatility and the bad news arising from rockfish wholesale market impact on flatfish market's volaltilty. Consequently, based on the thus results, the volatility spillover effect interacts and is bidirectional between flatfish and rockfish wholesale markets.

Effects of Financial Crises on the Long Memory Volatility Dependency of Foreign Exchange Rates: the Asian Crisis vs. the Global Crisis

  • Han, Young Wook
    • East Asian Economic Review
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    • v.18 no.1
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    • pp.3-27
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    • 2014
  • This paper examines the effects of financial crises on the long memory volatility dependency of daily exchange returns focusing on the Asian crisis in 97-98 and the Global crisis in 08-09. By using the daily KRW-USD and JPY-USD exchange rates which have different trading regions and volumes, this paper first applies both the parametric FIGARCH model and the semi-parametric Local Whittle method to estimate the long memory volatility dependency of the daily returns and the temporally aggregated returns of the two exchange rates. Then it compares the effects of the two financial crises on the long memory volatility dependency of the daily returns. The estimation results reflect that the long memory volatility dependency of the KRW-USD is generally greater than that of the JPY-USD returns and the long memory dependency of the two returns appears to be invariant to temporal aggregation. And, the two financial crises appear to affect the volatility dynamics of all the returns by inducing greater long memory dependency in the volatility process of the exchange returns, but the degree of the effects of the two crises seems to be different on the exchange rates.

Volatility clustering in data breach counts

  • Shim, Hyunoo;Kim, Changki;Choi, Yang Ho
    • Communications for Statistical Applications and Methods
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    • v.27 no.4
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    • pp.487-500
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    • 2020
  • Insurers face increasing demands for cyber liability; entailed in part by a variety of new forms of risk of data breaches. As data breach occurrences develop, our understanding of the volatility in data breach counts has also become important as well as its expected occurrences. Volatility clustering, the tendency of large changes in a random variable to cluster together in time, are frequently observed in many financial asset prices, asset returns, and it is questioned whether the volatility of data breach occurrences are also clustered in time. We now present volatility analysis based on INGARCH models, i.e., integer-valued generalized autoregressive conditional heteroskedasticity time series model for frequency counts due to data breaches. Using the INGARCH(1, 1) model with data breach samples, we show evidence of temporal volatility clustering for data breaches. In addition, we present that the firms' volatilities are correlated between some they belong to and that such a clustering effect remains even after excluding the effect of financial covariates such as the VIX and the stock return of S&P500 that have their own volatility clustering.

The COVID-19 and Stock Return Volatility: Evidence from South Korea

  • Pyo, Dong-Jin
    • East Asian Economic Review
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    • v.25 no.2
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    • pp.205-230
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    • 2021
  • This study examines the impact of the number of coronavirus cases on regime-switching in stock return volatility. This study documents the empirical evidence that the COVID-19 cases had an asymmetric effect on the regime of stock return volatility. When the stock return is in the low volatility regime, the probability of switching to the high volatility regime in the next trading day increases as the number of cumulative cases increases. In contrast, in the high volatility regime, the effect of cumulative cases on the transition probability is not statistically significant. This study also documents the evidence that the government measures against the pandemic contribute to promoting the high volatility regime of the KOSPI during the pandemic. Besides, this study projects future stock prices through the Monte Carlo simulation based on the estimated parameters and the predicted number of the COVID-19 new cases. Under a scenario where the number of new cases rapidly increases, stock price indices in Korea are expected to be in a downward trend over the next three months. On the other hand, under the moderate scenario and the best scenario, the stock indices are likely to continue to rise.

The Stochastic Volatility Option Pricing Model: Evidence from a Highly Volatile Market

  • WATTANATORN, Woraphon;SOMBULTAWEE, Kedwadee
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.2
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    • pp.685-695
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    • 2021
  • This study explores the impact of stochastic volatility in option pricing. To be more specific, we compare the option pricing performance between stochastic volatility option pricing model, namely, Heston option pricing model and standard Black-Scholes option pricing. Our finding, based on the market price of SET50 index option between May 2011 and September 2020, demonstrates stochastic volatility of underlying asset return for all level of moneyness. We find that both deep in the money and deep out of the money option exhibit higher volatility comparing with out of the money, at the money, and in the money option. Hence, our finding confirms the existence of volatility smile in Thai option markets. Further, based on calibration technique, the Heston option pricing model generates smaller pricing error for all level of moneyness and time to expiration than standard Black-Scholes option pricing model, though both Heston and Black-Scholes generate large pricing error for deep-in-the-money option and option that is far from expiration. Moreover, Heston option pricing model demonstrates a better pricing accuracy for call option than put option for all level and time to expiration. In sum, our finding supports the outperformance of the Heston option pricing model over standard Black-Scholes option pricing model.

A Study on Unfolding Asymmetric Volatility: A Case Study of National Stock Exchange in India

  • SAMINENI, Ravi Kumar;PUPPALA, Raja Babu;KULAPATHI, Syamsundar;MADAPATHI, Shiva Kumar
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.4
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    • pp.857-861
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    • 2021
  • The study aims to find the asymmetric effect in National Stock Exchange in which the Nifty50 is considered as proxy for NSE. A return can be stated as the change in value of a security over a certain time period. Volatility is the rate of change in security value. It is an arithmetical assessment of the dispersion of yields of security prices. Stock prices are extremely unpredictable and make the investment in equities risky. Predicting volatility and modeling are the most profuse areas to explore. The current study describes the association between two variables, namely, stock yields and volatility in equity market in India. The volatility is measured by employing asymmetric GARCH technique, i.e., the EGARCH (1,1) tool, which was used in building the study. The closing prices of Nifty on day-to-day basis were used for analysis from the period 2011 to 2020 with 2,478 observations in the study. The model arrests the lopsided volatility during the mentioned period. The outcome of asymmetric GARCH model revealed the subsistence of leverage effect in the index and confirms the impact of conditional variance as well. Furthermore, the EGARCH technique was evidenced to be apt in seizure of unsymmetrical volatility.

Exchange Rate Volatility and FDI Response during the Financial Crisis: Empirical Evidence from Vietnam

  • HUONG, Tram Thi Xuan;NGUYEN, My-Linh Thi;LIEN, Nguyen Thi Kim
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.119-126
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    • 2021
  • This study is to examine the foreign direct investment (FDI) response to real effective exchange rate volatility in Vietnam by using the vector autoregression model. The research data are quarterly frequency data in the period from 2004:Q1 to 2019:Q2. The data on real effective exchange rate were collected from the statistics of Bruegel (Europe) and FDI data were collected from the International Financial Statistics. The quantitative study was conducted with two steps: (1) measuring exchange rate volatility by the GARCH(1,1) method; and (2) examining the impact of exchange rate volatility on FDI in the context of the global financial crisis. The estimation results show that FDI responded significantly to real exchange rate volatility with the lag of 3 periods at the 5% significance level. The FDI response increased after the exchange rate volatility with the lag of 3 periods, and the impact extended to the lag of 6 periods, and then gradually stabilized. The research findings indicate that FDI in Vietnam responds positively and significantly to exchange rate volatility with the lag of 3 periods. Simultaneously, the negative impact of the global financial crisis in 2008 with the lag of 2 periods leads to a slight decrease in FDI inflows into Vietnam.

The Impact of Foreign Ownership on Stock Price Volatility: Evidence from Thailand

  • THANATAWEE, Yordying
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.1
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    • pp.7-14
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    • 2021
  • This paper examines the impact of foreign ownership on stock price volatility in an emerging market, namely, Thailand. The data were obtained from SETSMART, the database of the Stock Exchange of Thailand (SET). After removing financial firms, banks, and insurance companies as well as filtering outliers, the final sample covers 1,755 firm-year observations from 371 nonfinancial firms listed on the SET over the five-year period from 2014 to 2018. The regression model consists of stock price volatility, measured by two methods, as the dependent variable, foreign ownership as the main independent variable, and firm characteristics including firm size, leverage, market-to book ratio, and stock turnover as the control variables. The pooled OLS, fixed effects, and random effects estimations are employed to examine the relationship between foreign ownership and stock price volatility. The results reveal that foreign ownership has a negative and significant impact on stock price volatility. The two-stage least squares (2SLS) are also performed to address potential endogeneity problem. The results still indicate a negative relationship between foreign ownership and stock price volatility. Taken together, the findings of this study suggest that foreign investors help reduce stock price volatility and thus stabilize share price in the Thai stock market.