Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model
The current econometric models have the disadvantages of low prediction accuracy and poor model fitting effect. To solve these problems, this study combines Markov chain Monte Carlo algorithm with random coefficient quantile auto-regression model, and optimizes the econometric model based on the fus...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10909092/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850069287803289600 |
|---|---|
| author | Ting Wang |
| author_facet | Ting Wang |
| author_sort | Ting Wang |
| collection | DOAJ |
| description | The current econometric models have the disadvantages of low prediction accuracy and poor model fitting effect. To solve these problems, this study combines Markov chain Monte Carlo algorithm with random coefficient quantile auto-regression model, and optimizes the econometric model based on the fusion algorithm. The results showed that compared with financial time series prediction algorithms, the fusion algorithm improved the prediction accuracy by 4.8% and the computation speed by 6.5 bps. The econometric model based on the fusion algorithm was compared with other models. The results showed that the optimized model improved the prediction accuracy by 10.7% compared to the AdaBoost econometric model. In summary, the fusion algorithm proposed in the study can improve the prediction efficiency of econometric models, accelerate the prediction process, optimize economic benefits, and reduce investment risks for enterprises and individuals. |
| format | Article |
| id | doaj-art-b5cb0f34e29342e99f58eeb799489914 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b5cb0f34e29342e99f58eeb7994899142025-08-20T02:47:49ZengIEEEIEEE Access2169-35362025-01-0113421294214210.1109/ACCESS.2025.354734810909092Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR ModelTing Wang0https://orcid.org/0009-0004-4871-1909Department of Business Administration, Shandong Vocational College of Light Industry, Zibo, ChinaThe current econometric models have the disadvantages of low prediction accuracy and poor model fitting effect. To solve these problems, this study combines Markov chain Monte Carlo algorithm with random coefficient quantile auto-regression model, and optimizes the econometric model based on the fusion algorithm. The results showed that compared with financial time series prediction algorithms, the fusion algorithm improved the prediction accuracy by 4.8% and the computation speed by 6.5 bps. The econometric model based on the fusion algorithm was compared with other models. The results showed that the optimized model improved the prediction accuracy by 10.7% compared to the AdaBoost econometric model. In summary, the fusion algorithm proposed in the study can improve the prediction efficiency of econometric models, accelerate the prediction process, optimize economic benefits, and reduce investment risks for enterprises and individuals.https://ieeexplore.ieee.org/document/10909092/Econometric modelMarkov chain Monte Carlo algorithmrandom coefficient quantile auto-regressive modeleconomic efficiency |
| spellingShingle | Ting Wang Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model IEEE Access Econometric model Markov chain Monte Carlo algorithm random coefficient quantile auto-regressive model economic efficiency |
| title | Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model |
| title_full | Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model |
| title_fullStr | Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model |
| title_full_unstemmed | Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model |
| title_short | Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model |
| title_sort | econometric modeling combining mcmc algorithm and random coefficient quantile ar model |
| topic | Econometric model Markov chain Monte Carlo algorithm random coefficient quantile auto-regressive model economic efficiency |
| url | https://ieeexplore.ieee.org/document/10909092/ |
| work_keys_str_mv | AT tingwang econometricmodelingcombiningmcmcalgorithmandrandomcoefficientquantilearmodel |