کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6895319 | 1445941 | 2018 | 33 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Estimating stochastic discount factor models with hidden regimes: Applications to commodity pricing
ترجمه فارسی عنوان
برآورد مدل های تخفیف تصادفی با رژیم های مخفی: برنامه های کاربردی برای قیمت گذاری کالاها
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کلمات کلیدی
دارایی، مالیه، سرمایه گذاری، کالاها، فاکتور تخفیف تصادفی، مدل مخفی مارکف،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
چکیده انگلیسی
We develop new likelihood-based methods to estimate factor-based Stochastic Discount Factors (SDF) that may accommodate Hidden Markov dynamics in the factor loadings. We use these methods to investigate whether it is possible to find a SDF that jointly prices the cross-section of eight U.S. portfolios of stocks, Treasuries, corporate bonds, and commodities. In particular, we test a range of possible different specification of the SDF, including single-state and Hidden Markov models and compare their statistical and pricing performances. In addition, we assess whether and to which extent a selection of these models replicates the observed moments of the return series, and especially correlations. We report that regime-switching models clearly outperform single-state ones both in term of statistical and pricing accuracy. However, while a four-state model is selected by the information criteria, a two-state three-factor full Vector Autoregression model outperforms the others as far as the pricing accuracy is concerned.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 265, Issue 2, 1 March 2018, Pages 685-702
Journal: European Journal of Operational Research - Volume 265, Issue 2, 1 March 2018, Pages 685-702
نویسندگان
Marta Giampietro, Massimo Guidolin, Manuela Pedio,