최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기응용통계연구 = The Korean journal of applied statistics, v.36 no.1, 2023년, pp.85 - 100
강태현 (중앙대학교 응용통계학과) , 황범석 (중앙대학교 응용통계학과)
The stochastic volatility (SV) model is one of the main methods of modeling time-varying volatility. In particular, SV model is actively used in estimation and prediction of financial market volatility and option pricing. This paper attempts to model the time-varying volatility of the bitcoin market...
Bosire MB and Maina SC (2021). Modelling stochastic volatility in the kenyan securities market using hidden?markov models, Journal of Financial Risk Management, 10, 367-395.
Derek S (2011). Monte Carlo approaches to hidden Markov model state estimation, Master of Science in Applied?Mathematics (pp. 1-40), eScholarship, University of California, California.
Harvey AC and Shephard N (1996). Estimation of an asymmetric stochastic volatility model for asset returns,?Journal of Business & Economic Statistics, 14, 429-434.
Hassan MR and Nath B (2005) Stock market forecasting using hidden Markov model: A new approach. In?Proceedings of the 5th International Conference on Intelligent Systems Design and Applications, Warsaw,?Poland, 192-196.
Heston SL (1993). A closed-form solution for options with stochastic volatility with applications to bond and?currency options, The Review of Financial Studies, 6, 327-343.
Hoffman MD and Gelman A (2014). The No-U-Turn Sampler: Adaptively setting path lengths in hamiltonian?Monte Carlo, Journal of Machine Learning Research, 15, 1593-1623.
Kang HJ and Hwang BS (2021). A hidden Markov model for predicting global stock market index, The Korean?Journal of Applied Statistics, 34, 447-461.
Kim JE (2005). Parameter estimation in stochastic volatility model with missing data using particle methods and?the EM algorithm (Doctoral dissertation), University of Pittsburgh, Pittsburgh, PA.
Krichene N (2003). Modeling Stochastic Volatility with Application to Stock Returns, International Monetary?Fund 2003.
Lamoureux CG (1990). Persistence in variance, structural change, and the GARCH model, Journal of Business?& Economic Statistics, 8, 225-234.
Lihn HT (2017). Hidden Markov model for financial time series and its application to S&P 500 index, Quantitative Finance, Forthcoming.
Nguyen N (2018). Hidden Markov model for stock trading, International Journal of Financial Studies, 6, 1-17.
Nguyen N and Nguyen D (2015). Hidden Markov model for stock selection, Risks, 3, 455-473.
Nkemnole EB and Abass O (2017). Forecasting volatility of stock indices with HMM-SV models, unpublished?paper, 1-20.
Rabiner LR (1989). A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, 77, 257-286.
Raggi D and Bordignon S (2006). Sequential Monte Carlo methods for stochastic volatility models with jumps,?unpublished paper, 1-19.
Sandmann G and Koopman SJ (1998). Estimation of stochastic volatility models via Monte Carlo maximum?likelihood, Journal of Econometrics, 87, 271-301.
Scott R (2021). Predicting stock and portfolio returns with bayesian methods, Available from: https://srome.github.io/Eigenvesting-IV-Predicting-Stock-And-Portfolio-Returns-With-Bayesian-Statistics/
Taylor SJ (1994). Modeling stochastic volatility: A review and comparative study, Mathematical Finance, 4,?183-204.
Viterbi A (1967). Error bounds for convolutional codes and an asymptotically optimum decoding algorithm,?IEEE Transactions on Information Theory, 13, 260-269.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.