• Title/Summary/Keyword: Volatility

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A Study on the Interregional Relationship of Housing Purchase Price Volatility (지역간 주택매매가격 변동성의 상관관계에 관한 연구)

  • Yoo, Han-Soo
    • Korean Business Review
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    • v.20 no.2
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    • pp.15-27
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    • 2007
  • This paper analyzed the relationship between Housing Purchase Price volatility of Seoul and Housing Purchase Price volatility of local large city. Other studies investigates the effect on the observed volatility Observed volatility consists of fundamental volatility and transitory volatility. Fundamental volatility is caused by information arrival and transitory volatility is caused by noise trading. Fundamental volatility is trend component and is modelled as a random walk with drift. Transitory volatility is cyclical component and is modelled as a stationary process. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Observed volatility is estimated by GJR GARCH(1,1) model. We find that GJH GARCH model is superior to GARCH model and good news is more remarkable effect on volatility than bad news. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. The findings in this paper is as follows. The correlation between Seoul housing price volatility and Busan housing price volatility is high. But, the correlation between Seoul and Daejeon is low. And the correlation between Daejeon and Busan is low. As a distinguishing feature, the correlation between fundamental volatilities is high in the case of all pairs. But, the correlation between transitory volatilities turns out low. The reason is as follows. When economic information arrives, Seoul, Daejeon, and Busan housing markets, all together, are affected by this information.

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The Effect of Institutional Investors' Trading on Stock Price Index Volatility (기관투자자 거래가 주가지수 변동성에 미치는 영향)

  • Yoo, Han-Soo
    • Korean Business Review
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    • v.19 no.1
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    • pp.81-92
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    • 2006
  • This study investigates the relation between institutional investor's net purchase and the volatility of KOSPI. Some portion of volatility in stock prices comes from noise trading of irrational traders. Observed volatility may be defined as the sum of the portion caused by information arrival, fundamental volatility, and the portion caused by noise trading, transitory volatility. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. Most studies investigates the effect on the observed volatility. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Estimation results show that institutional investor's net purchase was not significantly related to all kinds of volatility(observed volatility, fundamental volatility and transitory volatility). This means that institutional investor's net purchase did not increase noise trading.

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A threshold-asymmetric realized volatility for high frequency financial time series (비대칭형 분계점 실현변동성의 제안 및 응용)

  • Kim, J.Y.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.205-216
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    • 2018
  • This paper is concerned with volatility computations for high frequency time series. A threshold-asymmetric realized volatility (T-RV) is suggested to capture a leverage effect. The T-RV is compared with various conventional volatility computations including standard realized volatility, GARCH-type volatilities, historical volatility and exponentially weighted moving average volatility. High frequency KOSPI data are analyzed for illustration.

Cyber Trading and KOSPI Volatility (사이버 주식거래와 주가 변동성)

  • 정군오;유한수
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.5 no.1
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    • pp.78-82
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    • 2004
  • Volatility may be defined as the sum of fundamental volatility caused by information arrival and transitory volatility caused by noise trading. This study decomposes the observed KOSPI volatility into fundamental volatility and transitory volatility using Kalman filtering method. This study investigates the effects of the introduction of cyber trading on the KOSPI volatility. Most studies investigates the effect on the observed volatility. In contrast to other studies, this study investigates the effect on the fundamental volatilty and transitory volatility individually. Analysis showed that observed volatility is increased significantly at 1% level, but transitory volatility is not increased. This means that noise trading by irrational investors is not increased.

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Comparison of the Korean and US Stock Markets Using Continuous-time Stochastic Volatility Models

  • CHOI, SEUNGMOON
    • KDI Journal of Economic Policy
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    • v.40 no.4
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    • pp.1-22
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    • 2018
  • We estimate three continuous-time stochastic volatility models following the approach by Aït-Sahalia and Kimmel (2007) to compare the Korean and US stock markets. To do this, the Heston, GARCH, and CEV models are applied to the KOSPI 200 and S&P 500 Index. For the latent volatility variable, we generate and use the integrated volatility proxy using the implied volatility of short-dated at-the-money option prices. We conduct MLE in order to estimate the parameters of the stochastic volatility models. To do this we need the transition probability density function (TPDF), but the true TPDF is not available for any of the models in this paper. Therefore, the TPDFs are approximated using the irreducible method introduced in Aït-Sahalia (2008). Among three stochastic volatility models, the Heston model and the CEV model are found to be best for the Korean and US stock markets, respectively. There exist relatively strong leverage effects in both countries. Despite the fact that the long-run mean level of the integrated volatility proxy (IV) was not statistically significant in either market, the speeds of the mean reversion parameters are statistically significant and meaningful in both markets. The IV is found to return to its long-run mean value more rapidly in Korea than in the US. All parameters related to the volatility function of the IV are statistically significant. Although the volatility of the IV is more elastic in the US stock market, the volatility itself is greater in Korea than in the US over the range of the observed IV.

A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data

  • Kim, Eun-Young;Park, Jong-Hae
    • The Korean Journal of Financial Management
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    • v.26 no.2
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    • pp.181-201
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    • 2009
  • This study is on the forecasting performance analysis of range volatility estimators(Parkinson, Garman and Klass, and Rogers and Satchell) relative to historical one using two-scale realized volatility estimator as a benchmark. American sub-prime mortgage loan shock to Korean stock markets happened in sample period(January 2, 2006~March 10, 2008), so the structural change somewhere within this period can make a huge influence on the results. Therefore sample was divided into two sub-samples by May 30, 2007 according to Zivot and Andrews unit root test results. As expected, the second sub-sample was much more volatile than the first sub-sample. As a result of forecasting performance analysis, Rogers and Satchell volatility estimator showed the best forecasting performance in the full sample and relatively better forecasting performance than other estimators in sub-samples. Range volatility estimators showed better forecasting performance than historical volatility estimator during the period before the outbreak of structural change(the first sub-sample). On the contrary, the forecasting performance of range volatility estimators couldn't beat that of historical volatility estimator during the period after this event(the second sub-sample). The main culprit of this result seems to be the increment of range volatility caused by that of intraday volatility after structural change.

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A Fractional Integration Analysis on Daily FX Implied Volatility: Long Memory Feature and Structural Changes

  • Han, Young-Wook
    • Asia-Pacific Journal of Business
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    • v.13 no.2
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    • pp.23-37
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    • 2022
  • Purpose - The purpose of this paper is to analyze the dynamic factors of the daily FX implied volatility based on the fractional integration methods focusing on long memory feature and structural changes. Design/methodology/approach - This paper uses the daily FX implied volatility data of the EUR-USD and the JPY-USD exchange rates. For the fractional integration analysis, this paper first applies the basic ARFIMA-FIGARCH model and the Local Whittle method to explore the long memory feature in the implied volatility series. Then, this paper employs the Adaptive-ARFIMA-Adaptive-FIGARCH model with a flexible Fourier form to allow for the structural changes with the long memory feature in the implied volatility series. Findings - This paper finds statistical evidence of the long memory feature in the first two moments of the implied volatility series. And, this paper shows that the structural changes appear to be an important factor and that neglecting the structural changes may lead to an upward bias in the long memory feature of the implied volatility series. Research implications or Originality - The implied volatility has widely been believed to be the market's best forecast regarding the future volatility in FX markets, and modeling the evolution of the implied volatility is quite important as it has clear implications for the behavior of the exchange rates in FX markets. The Adaptive-ARFIMA-Adaptive-FIGARCH model could be an excellent description for the FX implied volatility series

Petroleum Imports and Exchange Rate Volatility (원유수입과 환율변동성)

  • Mo, Soo-Won;Kim, Chang-Beom
    • Environmental and Resource Economics Review
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    • v.11 no.3
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    • pp.397-414
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    • 2002
  • This paper presents an empirical analysis of exchange rate volatility, petroleum's import price and industrial production on petroleum imports. The GARCH framework is used to measure the exchange rate volatility. One of the most appealing features of the GARCH model is that it captures the volatility clustering phenomenon. We found one long-run relationship between petroleum imports, import price, industrial production, and exchange rate volatility using Johansen's multivariate cointegration methodology. Since there exists a cointegrating vector, therefore, we employ an error correction model to examine the short-run dynamic linkage, finding that the exchange rate volatility performs a key role in the short-run. This paper also apply impulse-response functions to provide the dynamic responses of energy consumption to the exchange rate volatility. The results show that the response of energy consumption to exchange rate volatility declines at the first month and dies out very quickly.

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Herd behavior and volatility in financial markets

  • Park, Beum-Jo
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1199-1215
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    • 2011
  • Relaxing an unrealistic assumption of a representative percolation model, this paper demonstrates that herd behavior leads to a high increase in volatility but not trading volume, in contrast with information flows that give rise to increases in both volatility and trading volume. Although detecting herd behavior has posed a great challenge due to its empirical difficulty, this paper proposes a new methodology for detecting trading days with herding. Furthermore, this paper suggests a herd-behavior-stochastic-volatility model, which accounts for herding in financial markets. Strong evidence in favor of the model specification over the standard stochastic volatility model is based on empirical application with high frequency data in the Korean equity market, strongly supporting the intuition that herd behavior causes excess volatility. In addition, this research indicates that strong persistence in volatility, which is a prevalent feature in financial markets, is likely attributed to herd behavior rather than news.

Volatility spillover between the Korean KOSPI and the Hong Kong HSI stock markets

  • Baek, Eun-Ah;Oh, Man-Suk
    • Communications for Statistical Applications and Methods
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    • v.23 no.3
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    • pp.203-213
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    • 2016
  • We investigate volatility spillover aspects of realized volatilities (RVs) for the log returns of the Korea Composite Stock Price Index (KOSPI) and the Hang Seng Index (HSI) from 2009-2013. For all RVs, significant long memories and asymmetries are identified. For a model selection, we consider three commonly used time series models as well as three models that incorporate long memory and asymmetry. Taking into account of goodness-of-fit and forecasting ability, Leverage heteroskedastic autoregressive realized volatility (LHAR) model is selected for the given data. The LHAR model finds significant decompositions of the spillover effect from the HSI to the KOSPI into moderate negative daily spillover, positive weekly spillover and positive monthly spillover, and from the KOSPI to the HSI into substantial negative weekly spillover and positive monthly spillover. An interesting result from the analysis is that the daily volatility spillover from the HSI to the KOSPI is significant versus the insignificant daily volatility spillover of the KOSPI to HSI. The daily volatility in Hong Kong affects next day volatility in Korea but the daily volatility in Korea does not affect next day volatility in Hong Kong.