• 제목/요약/키워드: Stochastic volatility

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Development of Dam Inflow Simulation Method Based on Bayesian Autoregressive Exogenous Stochastic Volatility (ARXSV) model

  • 파멜라 파비안;김호준;김기철;권현한
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.437-437
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    • 2022
  • The prediction of dam inflow rate is crucial for the management of the largest multi-purpose dam in South Korea, the Soyang Dam. The main issue associated with the management of water resources is the stochastic nature of the reservoir inflow leading to an increase in uncertainty associated with the inflow prediction. The Autoregressive (AR) model is commonly used to provide the simulation and forecast of hydrometeorological data. However, because its estimation is based solely on the time-series data, it has the disadvantage of being unable to account for external variables such as climate information. This study proposes the use of the Autoregressive Exogenous Stochastic Volatility (ARXSV) model within a Bayesian modeling framework for increased predictability of the monthly dam inflow by addressing the exogenous and stochastic factors. This study analyzes 45 years of hydrological input data of the Soyang Dam from the year 1974 to 2019. The result of this study will be beneficial to strengthen the potential use of data-driven models for accurate inflow predictions and better reservoir management.

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OPTION PRICING UNDER STOCHASTIC VOLATILITY MODEL WITH JUMPS IN BOTH THE STOCK PRICE AND THE VARIANCE PROCESSES

  • Kim, Ju Hong
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제21권4호
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    • pp.295-305
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    • 2014
  • Yan & Hanson [8] and Makate & Sattayatham [6] extended Bates' model to the stochastic volatility model with jumps in both the stock price and the variance processes. As the solution processes of finding the characteristic function, they sought such a function f satisfying $$f({\ell},{\nu},t;k,T)=exp\;(g({\tau})+{\nu}h({\tau})+ix{\ell})$$. We add the term of order ${\nu}^{1/2}$ to the exponent in the above equation and seek the explicit solution of f.

풍력단지의 발전량 추계적 모형 제안에 관한 연구 (Development of a Stochastic Model for Wind Power Production)

  • 류종현;최동구
    • 경영과학
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    • 제33권1호
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    • pp.35-47
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    • 2016
  • Generation of electricity using wind power has received considerable attention worldwide in recent years mainly due to its minimal environmental impact. However, volatility of wind power production causes additional problems to provide reliable electricity to an electrical grid regarding power system operations, power system planning, and wind farm operations. Those problems require appropriate stochastic models for the electricity generation output of wind power. In this study, we review previous literatures for developing the stochastic model for the wind power generation, and propose a systematic procedure for developing a stochastic model. This procedure shows a way to build an ARIMA model of volatile wind power generation using historical data, and we suggest some important considerations. In addition, we apply this procedure into a case study for a wind farm in the Republic of Korea, Shinan wind farm, and shows that our proposed model is helpful for capturing the volatility of wind power generation.

THE VALUATION OF TIMER POWER OPTIONS WITH STOCHASTIC VOLATILITY

  • MIJIN, HA;DONGHYUN, KIM;SERYOONG, AHN;JI-HUN, YOON
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제26권4호
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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.

금융시장 불확실성의 효과: 금융시장 위기 기간 중 국면전환이 발생하였는가? (The Effects of Financial Market Uncertainty: Does Regime Change Occur During Financial Market Crises?)

  • 김시원
    • 경제분석
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    • 제25권3호
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    • pp.70-99
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    • 2019
  • 본 연구는 주가지수, 원달러 환율, 국채수익률 및 신용스프레드로 구성된 Stochastic volatility-in-mean VAR 모형을 이용하여 금융시장 불확실성이 금융시장에 미치는 효과를 분석하였다. 첫째, 불확실성 증가충격의 효과는 경기후퇴적(recessionary)이며, 특히 주가 하락효과와 원달러 환율 상승효과가 강력한 것으로 나타났다. 둘째, 금융시장 스트레스에 따른 국면전환(regime shift) 효과에 대한 분석에서는 금융시장 위기 기간 중 불확실성의 효과가 평상시에 비해 더욱 강력해진다는 결과를 얻었다. 마지막으로 금융시장 불확실성 증가는 금융부문을 넘어 실물부문까지 영향을 미치는 실질효과 가능성에 대한 증거가 제시되었다.

Sentiment Shock and Housing Prices: Evidence from Korea

  • DONG-JIN, PYO
    • KDI Journal of Economic Policy
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    • 제44권4호
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    • pp.79-108
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    • 2022
  • This study examines the impact of sentiment shock, which is defined as a stochastic innovation to the Housing Market Confidence Index (HMCI) that is orthogonal to past housing price changes, on aggregate housing price changes and housing price volatility. This paper documents empirical evidence that sentiment shock has a statistically significant relationship with Korea's aggregate housing price changes. Specifically, the key findings show that an increase in sentiment shock predicts a rise in the aggregate housing price and a drop in its volatility at the national level. For the Seoul Metropolitan Region (SMR), this study also suggests that sentiment shock is positively associated with one-month-ahead aggregate housing price changes, whereas an increase in sentiment volatility tends to increase housing price volatility as well. In addition, the out-of-sample forecasting exercises conducted here reveal that the prediction model endowed with sentiment shock and sentiment volatility outperforms other competing prediction models.

Evolution of China's Economy and Monetary Policy: An Empirical Evaluation Using a TVP-VAR Model

  • Kim, Seewon
    • East Asian Economic Review
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    • 제25권1호
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    • pp.73-97
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    • 2021
  • China has experienced many structural changes in the process of economic development over the past three decades. Using a time-varying parameter VAR model with stochastic volatility and mixture innovations, this study investigates whether such structural changes in, especially tools and operational aims of monetary policy, affect the monetary transmission mechanism. We find that impulse responses of output growth and inflation to monetary shocks have substantially increased and then reversed to decrease around 2005-2006. This time variation is mainly caused by changes in the monetary transmission mechanism, i.e., the manner in which main macroeconomic variables respond to policy shocks, rather than by changes in volatilities of exogenous shocks. The result implies that aggressive monetary policy to facilitate economic growth in the developing economies may be legitimized, unless it causes inflation seriously.

ROBUST PORTFOLIO OPTIMIZATION UNDER HYBRID CEV AND STOCHASTIC VOLATILITY

  • Cao, Jiling;Peng, Beidi;Zhang, Wenjun
    • 대한수학회지
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    • 제59권6호
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    • pp.1153-1170
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    • 2022
  • In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

전력계통한계가격 변동성 결정요인 분석: 베이지안 변수선택 방법 (What determines the Electricity Price Volatility in Korea?)

  • 이서진;김영민
    • 자원ㆍ환경경제연구
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    • 제31권3호
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    • pp.393-417
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    • 2022
  • 전력시장 도매가격인 전력계통한계가격(System Marginal Price, SMP)의 급등락은 발전 사업자들의 재생에너지 및 기존 신규 발전설비에 대한 투자 결정을 변경하거나 지연시켜 에너지 정책 실현에 부정적인 영향을 미칠 수 있다. 이 연구는 2016~2020년 시간별 데이터를 활용하여 우리나라 SMP 주간 실현 변동성을 측정하고 결정요인을 파악함으로써 SMP 급등락 현상에 대한 정보 제공을 목적으로 한다. 국면전환(regime-switching)을 베이지안 변수선택(Bayesian stochastic selection) 모형에 적용하여 추정한 결과, SMP 고변동·저변동 국면 모두에서 기저 발전인 석탄 및 원자력 발전과 재생에너지인 태양광 발전의 증가는 SMP 변동성을 심화시키고, 가스발전량과 LNG 가격 변화는 고변동 국면에서만 SMP 변동성을 감소시키는 것으로 나타났다. 이러한 결과는 탄소 중립이나 에너지 전환 정책에 따른 재생에너지의 점진적인 확대가 SMP 변동성을 확대할 수 있지만, 재생에너지의 간헐성을 보완하기 위한 가스발전의 증가나 탄소 중립을 위한 석탄발전 감축은 SMP 변동성 증가를 상쇄시키는 역할을 할 수 있음을 시사한다.