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We estimate a narrative factor pricing model from news text of The Wall Street Journal. Our empirical method integrates topic modeling (LDA), latent factor analysis (IPCA), and variable selection (group lasso). Narrative factors achieve higher out-of-sample Sharpe ratios and smaller pricing errors than standard characteristic-based factor models and predict future investment opportunities in a manner consistent with the ICAPM. We derive an interpretation of the estimated risk factors from narratives in the underlying article text. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online

We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk exposures. We show that this approach yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample. We discuss multiple directions for future research on financial approaches to managing climate risk.

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based strategies from the literature. We identify the best-performing methods (trees and neural networks) and trace their predictive gains to allowing nonlinear predictor interactions missed by other methods. All methods agree on the same set of dominant predictive signals, a set that includes variations on momentum, liquidity, and volatility. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

The purpose of this paper is to review the requirements of the law that are relevant to nuclear risk assessment at UK nuclear licensed sites. The relevant Acts of Parliament, Statutory Instruments and Approved Codes of Practice are reviewed for nuclear risk assessment requirements. Relevant requirements are drawn together and grouped in appropriate categories. The issue of nuclear risk assessment depth is considered. Definitions and interpretations of key legal words and phrases are discussed.

On July 20, 2004, the Securities and Exchange Commission (SEC) published for comment proposed rules under the Investment Advisers Act of 1940 (the Act), which would require many non‐U.S. hedge fund advisers to be registered with the SEC. The proposed rules would require non‐U.S. investment advisers to look through their hedge funds (U.S. and non‐U.S. funds) to count all U.S. investors therein as clients for purposes of the Section 203(b)(3) “private adviser” exemption. The SEC stated in the proposing release that it did not intend the proposed rules to change current policy of substantially limiting the extraterritorial application of the Act to dealings between a registered non‐U.S. investment adviser and its non‐U.S. clients. However, there remains some ambiguity as to the application of this policy, which has been developed over the past 12 years through a series of no‐action letters. In addition, notwithstanding the SEC’s statement in the proposing release, the proposed rules could be read as changing current SEC policy in a couple of respects. This article explains those issues.