Corporate Finance

Many organizations rely on formal management control systems that align employee values with organizational values (i.e., culture-fit) to shape organizational culture. Using proprietary data from a highly-decentralized organization, I examine the employee performance consequences of adopting a formal culture-fit measurement system in employee selection. I exploit the staggered feature of the adoption of the system, and find that employees selected with the system perform significantly better than those without the system.

We revisit the firm value and pricing implications of the negative screening of sin stocks. Unlike prior work, we find that institutional ownership and valuations related to sin stocks are not different from those of other stocks after controlling for differences in fundamentals between sin and non-sin stocks. Sin stocks do not differ in the likelihood of exiting the public market, the cost of raising new equity, and in the announcement returns around negative ESG news relative to non-sin stocks, casting further doubt on whether negative screening hurts sin stocks.

The crash of some of the flagbearers of the equity bubble in recent years has been painful for investors. We have seen “pandemic winner” Netflix dive 75 per cent from 2021 peaks, crypto exchange operator Coinbase plunge 86 per cent and the one-time meme stock and cinema chain AMC lose 80 per cent.

Should businesses worry about climate risk because doing so is good for their bottom line, or because their responsibilities ought to go beyond mere financial returns to shareholders? What if expanding one’s lens to include environmental, social, and corporate governance turns out to be good for business? What if not? These fundamental questions lie at the core of numerous ambitious efforts to align tools and resources of finance with global action to address climate change.

In modern asset markets, man and machine compete for profits. How does each fare? I build a learning model in which quantitative investors (reliant on computer models) have more learning capacity but less flexibility to adapt to market conditions than discretionary investors (reliant on human judgment). I use machine learning to categorize US active equity mutual funds as quantitative or discretionary. Consistent with the model's predictions, I find that quantitative funds hold more stocks, specialize in stock picking, and engage in more overcrowded trades.

We examine the ability of existing and new factor models to explain the comovements of G10-currency changes. Extant currency factors include the carry, volatility, value, and momentum factors. Using a new clustering technique, we find a clear two-block structure in currency comovements with the first block containing mostly the dollar currencies, and the other the European currencies.

We use supervisory loan-level data to document that small firms (SMEs) obtain shorter maturity credit lines than large firms, post more collateral, have higher utilization rates, and pay higher spreads. We rationalize these facts as the equilibrium outcome of a trade-off between lender commitment and discretion. Using the COVID recession, we test the prediction that SMEs are subject to greater lender discretion. Consistent with this hypothesis, SMEs did not draw down whereas large firms did, even in response to similar demand shocks.

It will take an evolution of fixed-income managers’ approach to make a difference to corporate behaviour.

Not to be left out of the ESG gold rush, a growing number of bond firms now offer environmental, social and governance funds. ESG integration has become a standard box to be checked (or not) on bond clients’ Requests for Proposals. Investment banks have created tools to help fixed income managers ESG-ify their portfolios.

We develop a model of information and portfolio choice in which ex ante identical investors choose to specialize because of fixed attention costs required in learning about securities. Without this friction, investors would invest in all securities and would be indifferent across a wide range of information choices. When securities' dividends depend on an aggregate (macro) risk factor and an idiosyncratic (micro) shocks, fixed attention costs lead investors to specialize in either macro or micro information.