$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

[해외논문] Generalized exponential moving average (EMA) model with particle filtering and anomaly detection

Expert systems with applications, v.73, 2017년, pp.187 - 200  

Nakano, M. ,  Takahashi, A. ,  Takahashi, S.

Abstract AI-Helper 아이콘AI-Helper

This paper proposes a generalized exponential moving average (EMA) model, a new stochastic volatility model with time-varying expected return in financial markets. In particular, we effectively apply a particle filter (PF) to sequential estimation of states and parameters in a state space framework....

Keyword

참고문헌 (51)

  1. Bayesian Statistics Aguilar 6 1 1 1998 Bayesian inference on latent structure in time series 

  2. Journal of Business and Economic Statistics Aguilar 18 338 2000 10.1080/07350015.2000.10524875 Bayesian dynamic factor models and variance matrix discounting for portfolio allocation 

  3. Expert Systems with Applications Araújo 42 8 4081 2015 10.1016/j.eswa.2015.01.004 A hybrid model for high-frequency stock market forecasting 

  4. Expert Systems with Applications Ballings 42 20 7046 2015 10.1016/j.eswa.2015.05.013 Evaluating multiple classifiers for stock price direction prediction 

  5. Box 1970 Time Series Analysis: Forecasting and Control 

  6. Braga 2016 Risk-Based Approaches to Asset Allocation 

  7. Journal of Computational Information Systems Cai 18 7273 2013 Particle filtering with observation anomaly detection in wireless sensor networks 

  8. Review of Financial Studies Campbell 21 4 1509 2008 10.1093/rfs/hhm055 Predicting excess stock returns out of sample: Can anything beat the historical average? 

  9. Journal of Geodesy Chang 88 4 391 2014 10.1007/s00190-013-0690-8 Robust kalman filtering based on mahalanobis distance as outlier judging criterion 

  10. Journal of Portfolio Management, Winter 1993 Chopra 19 2 1993 The effect of errors in means, variances, and covariances on optimal portfolio choice 

  11. The Journal of Business Fama 38 1 34 1965 10.1086/294743 The behavior of stock-market prices 

  12. Journal of Financial Economics Fama 33 1 3 1993 10.1016/0304-405X(93)90023-5 Common risk factors in the returns on stocks and bonds 

  13. Journal of Financial Economics Fama 105 3 457 2012 10.1016/j.jfineco.2012.05.011 Size, value, and momentum in international stock returns 

  14. Fukui 2016 Preprint, CARF-f-383, university of tokyo Estimating style weights of mutual funds by monte carlo filter with generalized simulated annealing 

  15. Radar and Signal Processing, IEE Proceedings F Gordon 140 2 107 1993 10.1049/ip-f-2.1993.0015 Novel approach to nonlinear/non-gaussian bayesian state estimation 

  16. Expert Systems with Applications Hsu 61 215 2016 10.1016/j.eswa.2016.05.033 Bridging the divide in financial market forecasting: machine learners vs. financial economists 

  17. Expert Systems with Applications Huang 34 4 2870 2008 10.1016/j.eswa.2007.05.035 Application of wrapper approach and composite classifier to the stock trend prediction 

  18. Computers & Operations Research Huang 32 10 2513 2005 10.1016/j.cor.2004.03.016 Forecasting stock market movement direction with support vector machine 

  19. European Journal of Operational Research Huck 207 3 1702 2010 10.1016/j.ejor.2010.06.043 Pairs trading and outranking: The multi-step-ahead forecasting case 

  20. Journal of Business & Economic Statistics Jacquier 12 69 1994 Bayesian analysis of stochastic volatility models 

  21. The Journal of Finance Johannes 69 2 611 2014 10.1111/jofi.12121 Sequential learning, predictability, and optimal portfolio returns 

  22. Expert Systems with applications Khashei 37 1 479 2010 10.1016/j.eswa.2009.05.044 An artificial neural network (p, d, q) model for timeseries forecasting 

  23. Expert Systems with Applications Khashei 39 4 4344 2012 10.1016/j.eswa.2011.09.157 A new class of hybrid models for time series forecasting 

  24. Applied Soft Computing Kim 7 2 569 2007 10.1016/j.asoc.2006.03.004 A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets 

  25. Journal of Computational and Graphical statistics Kitagawa 5 1 1 1996 10.1080/10618600.1996.10474692 Monte carlo filter and smoother for non-gaussian nonlinear state space models 

  26. Journal of the American Statistical Association Kitagawa 1203 1998 A self-organizing state-space model 

  27. Knorn 1 2008 INFOCOM workshops 2008, IEEE Adaptive kalman filtering for anomaly detection in software appliances 

  28. IEEE Transactions on Neural Networks Kwon 18 3 851 2007 10.1109/TNN.2007.891629 A hybrid neurogenetic approach for stock forecasting 

  29. Expert Systems with Applications Lee 36 8 10896 2009 10.1016/j.eswa.2009.02.038 Using support vector machine with a hybrid feature selection method to the stock trend prediction 

  30. The Journal of Finance Lettau 56 3 815 2001 10.1111/0022-1082.00347 Consumption, aggregate wealth, and expected stock returns 

  31. Liu 197 2001 Sequential monte carlo methods in practice Combined parameter and state estimation in simulation-based filtering 

  32. Lopes 515 2010 Rethinking risk measurement and reporting: Uncertainty, bayesian analysis and expert judgement’, riskbooks Bayesian inference for stochastic volatility modeling 

  33. Expert Systems with Applications Mundnich 54 228 2016 10.1016/j.eswa.2016.01.052 Early online detection of high volatility clusters using particle filters 

  34. Forthcoming in The Journal of Economics Nakano 2016 Optimal portfolio with particle filtering (in japanese) 

  35. Expert Systems with Applications de Oliveira 40 18 7596 2013 10.1016/j.eswa.2013.06.071 Applying artificial neural networks to prediction of stock price and improvement of the directional prediction index-case study of PETR4, petrobras, brazil 

  36. Omega Pai 33 6 497 2005 10.1016/j.omega.2004.07.024 A hybrid ARIMA and support vector machines model in stock price forecasting 

  37. Expert Systems with Applications Patel 42 1 259 2015 10.1016/j.eswa.2014.07.040 Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques 

  38. Expert Systems with Applications Patel 42 4 2162 2015 10.1016/j.eswa.2014.10.031 Predicting stock market index using fusion of machine learning techniques 

  39. Microelectronics Reliability Patil 52 3 482 2012 10.1016/j.microrel.2011.10.017 A prognostic approach for non-punch through and field stop IGBTs 

  40. Journal of the American Statistical Association Pitt 94 446 590 1999 10.1080/01621459.1999.10474153 Filtering via simulation: Auxiliary particle filters 

  41. Expert Systems with Applications Rather 42 6 3234 2015 10.1016/j.eswa.2014.12.003 Recurrent neural network and a hybrid model for prediction of stock returns 

  42. Rios 23 2013 State-space models The extended liu and west filter: Parameter learning in markov switching stochastic volatility models 

  43. Annals of the Institute of Statistical Mathematics Takahashi 53 1 50 2001 10.1023/A:1017964304055 A monte carlo filtering approach for estimating the term structure of interest rates 

  44. Omega Tay 29 4 309 2001 10.1016/S0305-0483(01)00026-3 Application of support vector machines in financial time series forecasting 

  45. Taylor 1986 Modelling Financial Time Series 

  46. IEEE Transactions on Neural Networks Van Gestel 12 4 809 2001 10.1109/72.935093 Financial time series prediction using least squares support vector machines within the evidence framework 

  47. Omega Wang 40 6 758 2012 10.1016/j.omega.2011.07.008 Stock index forecasting based on a hybrid model 

  48. Review of Financial Studies Welch 21 4 1455 2008 10.1093/rfs/hhm014 A comprehensive look at the empirical performance of equity premium prediction 

  49. West 409 1993 Journal of the royal statistical society. series b (methodological) Approximating posterior distributions by mixture 

  50. West 1993 Computing science and statistics Mixture models, monte carlo, bayesian updating, and dynamic models 

  51. International Journal of Forecasting Zhou 30.4 963 2014 10.1016/j.ijforecast.2014.03.017 Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models 

관련 콘텐츠

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로