### Abstract

Language | English |
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Date | 2017 |

Number of pages | 57 |

State | Published - 2017 |

Event | 2017 Annual Meeting of the Society for Economic Dynamics - Edinburgh, United Kingdom Duration: 22 Jun 2017 → 24 Jun 2017 https://www.economicdynamics.org/sedam_2017/ |

### Conference

Conference | 2017 Annual Meeting of the Society for Economic Dynamics |
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Country | United Kingdom |

City | Edinburgh |

Period | 22/06/2017 → 24/06/2017 |

Internet address |

### Cite this

*What Is the Expected Return on a Stock?*. Paper presented at 2017 Annual Meeting of the Society for Economic Dynamics , Edinburgh, United Kingdom.

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**What Is the Expected Return on a Stock?** / Martin, Ian; Wagner, Christian.

Research output: Contribution to conference › Paper › Research › peer-review

TY - CONF

T1 - What Is the Expected Return on a Stock?

AU - Martin,Ian

AU - Wagner,Christian

PY - 2017

Y1 - 2017

N2 - We derive a formula that expresses the expected return on a stock in terms of the risk-neutral variance of the market and the stock's excess risk-neutral variance relative to the average stock. These components can be computed from index and stock option prices; the formula has no free parameters. We test the theory in-sample by running panel regressions of stock returns onto risk-neutral variances. The formula performs well at 6-month and 1-year forecasting horizons, and our predictors drive out beta, size, book-to-market, and momentum. Out-of-sample, we find that the formula outperforms a range of competitors in forecasting individual stock returns. Our results suggest that there is considerably more variation in expected returns, both over time and across stocks, than has previously been acknowledged.

AB - We derive a formula that expresses the expected return on a stock in terms of the risk-neutral variance of the market and the stock's excess risk-neutral variance relative to the average stock. These components can be computed from index and stock option prices; the formula has no free parameters. We test the theory in-sample by running panel regressions of stock returns onto risk-neutral variances. The formula performs well at 6-month and 1-year forecasting horizons, and our predictors drive out beta, size, book-to-market, and momentum. Out-of-sample, we find that the formula outperforms a range of competitors in forecasting individual stock returns. Our results suggest that there is considerably more variation in expected returns, both over time and across stocks, than has previously been acknowledged.

M3 - Paper

ER -