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Trend-Following Filters – Part 6
This article analyzes six trend-following indicators from a digital signal processing (DSP) frequency domain perspective in which the indicators are considered as digital filters and their frequency response characteristics are determined.
Measuring Geopolitical Risk
Although geopolitical risk has traditionally been approached from a qualitative aspect, what makes it a novel risk is the application of innovative techniques to measure it.
Financial Markets Responding to Climate Risks
This paper provides new evidence showing that carbon transition risk is becoming increasingly material and is priced both in equity and debt markets. We find that there is a widespread price-earnings discount linked to corporate carbon emissions. This discount varies, however, by sector and trends differently in Europe than in the US. We also find that a small discount emerges for corporate bonds, although it is statistically significant only for small caps. Finally, we find evidence that the pricing discount also emerges, albeit to a smaller extent, for other greenhouse gas emissions.
Is There a Gender Gap in Kickstarter Campaigns?
This study focuses on the launch phase of the leading reward-based crowdfunding market—Kickstarter. It documents the behavior of male and female entrepreneurs in raising early stage capital. We find that women share as entrepreneurs in the platform (34.7%) does not equal to their share in the overall population, and they are concentrated in stereotyped sectors, both as entrepreneurs and as backers. We also find that women do not set lower funding goals than men, they enjoy higher rates of success than men, even after controlling for project categories and funding goals, and that backers of both genders have a tendency to fund entrepreneurs of their own gender. Our survey of Kickstarter backers finds evidence of taste-based discrimination by male backers.
The Future of Factor Investing
In this article, the author discusses current structural research and investment trends that are shaping the future of factor investing. Specifically, the author focuses on three emerging trends: the ongoing evolution of traditional factor models and strategies, recent innovation in data sources and modeling techniques, and the potential disruption from integrating factor strategies into the asset allocation process.
Can Market Maker Capital Constraints Result in Mispricing of ETFs?
Capital constraints of financial intermediaries can affect liquidity provision. We investigate whether these constraints spillover and consequently cause contagion in the degree of market efficiency across assets managed by a common intermediary. Specifically, we provide evidence of strong comovement in pricing gaps between ETFs and their constituents for ETFs served by the same lead market maker (LMM). The effects are stronger for ETFs that are more illiquid and volatile, when the underlying constituents of the ETFs are more costly to arbitrage, and for LMMs with more constrained capital. Using extreme disruptions in debt markets during COVID-19 as an experiment, we show that non-fixed income ETFs serviced by LMMs managing a larger fraction of fixed income ETFs experience greater pricing gaps. Overall, our results indicate that intermediaries’ constraints indeed influence comovements in pricing efficiencies.
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Who Bears the Cost of Machine Learning in Credit Markets?
The primary idea behind this research is that a more sophisticated statistical technology (in the sense of reducing predictive mean squared error) produces predictions with greater variance than a more primitive technology. These technologies range from a simple logistic regression of default outcomes based on borrowers and default variables to random forest machine learning models. Said differently, improvements in predictive technology act as mean-preserving spreads for predicted outcomes—in this case, predicted default propensities on loans, which also means that there will always be some borrowers considered less risky by the new technology, or “winners”, while other borrowers will be deemed riskier “losers”, relative to their position under the pre-existing technology.