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Working Paper

In Search of the True Greenium

The greenium (the expected return of green securities relative to brown) is a central impact measure for ESG investors. We propose a robust green score combined with forward-looking expected returns, yielding a more precisely estimated annual equity greenium.

Working Paper

How Global is Predictability?

We show that asset pricing has a strong global component in the sense that a common global model has stronger predictability of stock returns than local models estimated in each country – even when the global model is estimated without the use of local data. Nevertheless, asset pricing has a small local component – in order to detect it, we develop a refined transfer learning model that gains power and precision by building off the global component.

Working Paper

Corporate Bond Factors: Replication Failures and a New Framework

We demonstrate that the literature on corporate bond factors suffers from replication failures, inconsistent methodological choices, and the lack of a common error-free dataset. Going beyond identifying this replication crisis, we create a clean database of corporate bond returns where outliers are analyzed individually and propose a robust factor construction.

Working Paper

Carbon Pricing versus Green Finance

We show that green finance should not be used if the carbon price equals its social cost. However, with too low carbon prices, green finance can implement the social optimum if the cost of capital can be controlled and there are no stranded assets. We show explicitly how to "translate" a carbon tax into green finance terms, highlight how green finance should depend on scope 1, 2, and 3 emissions, present its limitations, and illustrate the predictions empirically.

Working Paper

Is Capital Structure Irrelevant with ESG Investors?

We examine whether capital structure is irrelevant for enterprise value and investment when investors care about ESG issues, which we denote “ESG-Modigliani-Miller” (ESG-MM). Theoretically, we show that ESG-MM holds if ESG is additive and markets are perfect. Empirically, we provide evidence of failure of ESG-MM, implying that firms and governments can exploit non-additive ESG or segmented markets.

Working Paper

Machine Learning and the Implementable Efficient Frontier

We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading costs leads to excessive reliance on fleeting small-scale characteristics, resulting in poor net returns. We develop a framework that produces a superior frontier by integrating trading-cost-aware portfolio optimization with machine learning

Journal Article

Is There a Replication Crisis in Finance?

Several papers argue that financial economics faces a replication crisis because many studies cannot be replicated or are the result of multiple testing of too many factors. We develop and estimate a Bayesian model of factor replication that leads to different conclusions, including finding the majority of asset pricing factors can be replicated.

Working Paper

Game On: Social Networks and Markets

This paper studies how echo-chamber effects and fake news can lead to disagreement and misinformation with effects on investors’ portfolios and market prices. It presents a model how an investment idea can propagate through a social network, generating a trading frenzy with high turnover, a bubble in the price, and high price volatility. The paper also presents empirical evidence on the dramatic events related to the GameStop stock in January 2021 and discusses broader economic implications.

Working Paper

Does ESG Help or Hurt Returns?

Combining several large data sets, we compute the empirical ESG-efficient frontier and show the costs and benefits of responsible investing.

Data Set

Responsible Investing: The ESG-Efficient Frontier – Original Paper Data

This the original data set used in “Responsible Investing: The ESG-Efficient Frontier” (Pedersen, Fitzgibbons and Pomorski). It contains the total returns of the value-weighted and equal-weighted portfolios used in the paper.