Valuation Measure of the Stock Market using Stochastic Volatility and Stock Earnings
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918263685906432 |
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| author | Sarantsev, Andrey Piotrowski, Angel Anderson, Ian |
| author_facet | Sarantsev, Andrey Piotrowski, Angel Anderson, Ian |
| contents | We create a time series model for annual returns of three asset classes: the USA Standard & Poor (S&P) stock index, the international stock index, and the USA Bank of America investment-grade corporate bond index. Using this, we made an online financial app simulating wealth process. This includes options for regular withdrawals and contributions. Four factors are: S&P volatility and earnings, corporate BAA rate, and long-short Treasury bond spread. Our valuation measure is an improvement of Shiller's cyclically adjusted price-earnings ratio. We use classic linear regression models, and make residuals white noise by dividing by annual volatility. We use multivariate kernel density estimation for residuals. We state and prove long-term stability results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_06010 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Valuation Measure of the Stock Market using Stochastic Volatility and Stock Earnings Sarantsev, Andrey Piotrowski, Angel Anderson, Ian Risk Management Probability Applications 62P05, 91G15, 91G70 We create a time series model for annual returns of three asset classes: the USA Standard & Poor (S&P) stock index, the international stock index, and the USA Bank of America investment-grade corporate bond index. Using this, we made an online financial app simulating wealth process. This includes options for regular withdrawals and contributions. Four factors are: S&P volatility and earnings, corporate BAA rate, and long-short Treasury bond spread. Our valuation measure is an improvement of Shiller's cyclically adjusted price-earnings ratio. We use classic linear regression models, and make residuals white noise by dividing by annual volatility. We use multivariate kernel density estimation for residuals. We state and prove long-term stability results. |
| title | Valuation Measure of the Stock Market using Stochastic Volatility and Stock Earnings |
| topic | Risk Management Probability Applications 62P05, 91G15, 91G70 |
| url | https://arxiv.org/abs/2508.06010 |