• Title/Summary/Keyword: volatility clustering

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Detection of Atrial Fibrillation Using Markov Regime Switching Models of Heart Rate Intervals (심박간격의 마코프 국면전환 모형화를 통한 심방세동 탐지)

  • Jung, Yonghan;Kim, Heeyoung
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.4
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    • pp.290-295
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    • 2016
  • This paper proposes a new method for the automatic detection of atrial fibrillation (AF), using Markov regime switching GARCH (1, 1) model. The proposed method is based on the observation that variability patterns of heart rate intervals during AF significantly differ from regular patterns. The proposed method captures the different patterns of heart rate intervals between two regimes : normal and AF states. We test the proposed method using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) atrial fibrillation database, and demonstrate the effectiveness of the proposed method.

An Analysis of Stock Return Behavior using Financial Big Data (금융 빅 데이터를 이용한 주식수익률 행태 분석)

  • Jung, Heon-Yong;Kim, Sang-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.708-710
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    • 2014
  • 최근 금융 분야에서는 빅 데이터를 이용하여 주가예측 모형을 만들어내고 있으며, 특히 금융 시계열 자료의 변동성 집중 현상을 금융 빅 데이터를 이용하여 분석함으로써 세계 주식시장의 동조화 현상을 분석하고 있다. 본 논문에서는 한국과 중국의 일별 주가지수수익률과 일중 주가지수수익률을 이용하여 이들 2개 국가의 대표적인 주가지수 시계열 데이터에 변동성 집중 현상이 존재하는지를 보다 세밀하게 추적하여 양국 주식시장의 동조화 현상을 분석한다. 분석 결과, 한국의 KOSPI와 중국의 Shanghai 종합주가지수의 지수수익률 시계열 자료는 단위근이 존재하지 않으며, 변동성 집중 현상을 보이는 것으로 나타났다. 또한 한국보다는 중국 주식시장의 변동성 집중현상이 보다 강하게 나타나며, 이러한 현상은 일중 주가지수수익률 시계열 자료에서 보다 두드러지게 나타났다.

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Hedging effectiveness of KOSPI200 index futures through VECM-CC-GARCH model (벡터오차수정모형과 다변량 GARCH 모형을 이용한 코스피200 선물의 헷지성과 분석)

  • Kwon, Dongan;Lee, Taewook
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1449-1466
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    • 2014
  • In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.

A recent overview on financial and special time series models (금융 및 특수시계열 모형의 조망)

  • Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.1-12
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    • 2016
  • Contrasted with the standard linear ARMA models, financial time series exhibits non-standard features such as fat-tails, non-normality, volatility clustering and asymmetries which are usually referred to as "stylized facts" in financial time series context (Terasvirta, 2009). We are accordingly led to ad hoc models (apart from ARMA) to accommodate stylized facts (Andersen et al., 2009). The paper aims to give a contemporary overview on financial and special time series models based on the recent literature and on the author's publications. Various models are illustrated including asymmetric models, integer valued models, multivariate models and high frequency models. Selected statistical issues on the models are discussed, bringing some perspectives to the future works in this area.

The Effects of Sidecar on Index Arbitrage Trading and Non-index Arbitrage Trading:Evidence from the Korean Stock Market (한국주식시장에서 사이드카의 역할과 재설계: 차익거래와 비차익거래에 미치는 효과를 중심으로)

  • Park, Jong-Won;Eom, Yun-Sung;Chang, Uk
    • 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.

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