The time traveller’s CAPM

@article{French2017TheTT,
  title={The time traveller’s CAPM},
  author={Jordan French},
  journal={Investment Analysts Journal},
  year={2017},
  volume={46},
  pages={81 - 96}
}
  • J. French
  • Published 3 April 2017
  • Economics
  • Investment Analysts Journal
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References

SHOWING 1-10 OF 59 REFERENCES
A COMPARISON BETWEEN CAPM, FAMA AND FRENCH‘S MODELS AND ARTIFICIAL NEURAL NETWORKS IN PREDICTING THE IRANIAN STOCK MARKET
Comparison between the Capital Asset Pricing Model, Fama & Ferench three factors model and Arti#cial Neural Network models in predicting Tehran Stock Exchange returns is discussed in this research.Expand
Forecasting time-varying daily betas: a new nonlinear approach
Purpose - – The purpose of this paper is to examine the predictive ability of different well-known models for capturing time variation in betas against a novel approach where the beta coefficient isExpand
The three-factor model and artificial neural networks: predicting stock price movement in China
TLDR
Examining the predictive ability of several well-established forecasting models, including dynamic versions of a single-factor CAPM-based model and Fama and French’s three-factor model, finds that each ANN model outperforms the corresponding linear model, indicating that neural networks may be a useful tool for stock price prediction in emerging markets. Expand
Nonlinear Time-Series Analysis of Stock Volatilities
SUMMARY The absolute value of the mean-corrected excess return is used in this paper to measure the volatility of stock returns. We apply various nonlinearity tests available in the literature toExpand
Neural network forecasts of Canadian stock returns using accounting ratios
Abstract This study compares neural network forecasts of one-year-ahead Canadian stock returns with the forecasts obtained using ordinary least squares (OLS) and logistic regression (logit)Expand
Estimating Time-Varying Beta Coefficients: An Empirical Study of US and ASEAN Portfolios
Abstract As the Association of Southeast Asian Nations (ASEAN) becomes an emerging market, US investors will want to know how their favorite method of calculating asset pricing fits into this newExpand
Another Look at the Cross-section of Expected Stock Returns
Our examination of the cross-section of expected returns reveals economically and statistically significant compensation (about 6 to 9 percent per annum) for beta risk when betas are estimated fromExpand
Estimating Time-Varying Beta-Coefficients: An Empirical Study of US & ASEAN Portfolios
As the Association of Southeast Asian Nations (ASEAN) becomes an emerging market, US investors will want to know how their favorite method of calculating asset pricing fits into this new undevelopedExpand
Asset Pricing
TLDR
This report focuses specifically on quantitative structural asset pricing models, and some of these models provided an important base for understanding financial institutions, frictions in financial markets, liquidity, investor heterogeneity, and the potential presence of investor irrationality in some markets. Expand
Stock price prediction using neural networks: A project report
TLDR
Analyzing the possibility of predicting stock prices on a short-term, day-to-day basis with help of neural networks by studying three important German stocks chosen at random found that neural network could considerably improve the prognosis of stock prices in the future. Expand
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