کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5053062 | 1476503 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discrete-time optimal asset allocation under Higher-Order Hidden Markov Model
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
اقتصاد، اقتصادسنجی و امور مالی
اقتصاد و اقتصادسنجی
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چکیده انگلیسی
This paper studies an optimal portfolio selection problem under a discrete-time Higher-Order Hidden Markov-Modulated Autoregressive (HO-HMMAR) model for price dynamics. By interpreting the hidden states of the modulating higher-order Markov chain as different states of an economic condition, the model discussed here may incorporate the long-term memory of economic states in modeling price dynamics and optimal asset allocation. The estimation of an estimation method based on Expectation-Maximization (EM) algorithm is used to estimate the model parameters with a view to reducing numerical redundancy. The asset allocation problem is then discussed in a market with complete information using the standard Bellman's principle and recursive formulas are derived. Numerical results reveal that the HO-HMMAR model may have a slightly better out-of-sample forecasting accuracy than the HMMAR model over a short horizon. The optimal portfolio strategies from the HO-HMMAR model outperform those from the HMMAR model without long-term memory in both real data and simulated data experiments.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Economic Modelling - Volume 66, November 2017, Pages 223-232
Journal: Economic Modelling - Volume 66, November 2017, Pages 223-232
نویسندگان
Dong-Mei Zhu, Jiejun Lu, Wai-Ki Ching, Tak-Kuen Siu,