We study qualitative information disclosure by mutual funds when investors learn from these disclosures in addition to past performance. We show theoretically that fund managers with specialized strategies optimally choose to disclose detailed strategy descriptions, while managers with standardized strategies provide generic descriptions. Generic descriptions lead to errors in benchmarking by investors and thus higher volatility in capital flows.
A two-factor model explains returns for a variety of test portfolios, including those based of CAPM beta and those underlying factors in extant pricing models. The two-factor model involves the market factor and a factor based on firms’ fundamentals that has the feature of providing a hedge in down markets and a reverse-hedge in up markets. For a wide range of test portfolios, returns are described by sensitivity to the market factor with a beta of one and positions in the hedging factor.
We extract aggregate supply and aggregate demand shocks for the US economy from macroeconomic data on inflation, real GDP growth, core inflation and the unemployment gap. We first use unconditional non-Gaussian features in the data to achieve identification of these structural shocks while imposing minimal economic assumptions. We find that recessions in the 1970s and 1980s are better characterized as driven by supply shocks while later recessions were driven primarily by demand shocks. The Great Recession exhibited large negative shocks to both demand and supply.
Turning around distressed operations is an alternative response to underperformance — as contrasted with using transactions such as divestitures or resource redeployment to deal with troublesome assets during corporate renewal. Taking the perspective of private-equity owners whose interests are primarily financial, we explain how their approach to turnarounds of troubled companies may differ from that of managers within publicly traded firms who may envision the realization of longer-term sources of operating synergy among their firms' lines of business.
We propose a parsimonious model of leverage and investment dynamics featuring a diffusion-jump cash-flow process, retained earnings, short-term debt, and external equity. Crucially equity issuance is costly. We show that firms' efforts to avoid incurring equity issuance costs generate empirically plausible target leverage and nonlinear leverage dynamics. Paradoxically, it is the high cost of equity issuance that causes the firm to keep leverage low, in contrast to the predictions of Modigliani-Miller and Leland tradeoff and Myers' pecking-order theories.
Day trading coverage perpetuates myths about the ‘real job’ of investment management.
If you were to ask a discretionary investment fund manager to draw a Venn diagram of the set notation where digitalization meets discretionary investing, many would not show the sets as overlapping. Moreover, they believe that the investment world is bifurcated and the discretionary managers are independent of the quantitative. I would argue that not only are the two sets converging but that the quantitative managers pose an existential threat to the discretionary managers, or perhaps will ‘Pac-Man’-style consume the discretionary managers.
This study uses advanced natural language processing methods to identify companies that are aligned with the UN SDGs based on the text in their sustainability disclosures. Using CSR reports of Russel 1000 companies between 2010-2019 we apply a logistic classifier, support vector machines (SVM) and a fully-connected neural network to predict alignment with the SDGs. Specifically, we use word embeddings to augment dictionary-based input features as well as use the embeddings as features themselves based on Word2Vec and Doc2Vec models to classify companies’ alignment with the SDGs over time.
Current market pricing of risk is evidence of late-cycle behaviour.