Professional and academic papers using quantitative methods. All of the research in this section is either about the use of quant techniques, or uses quant methodology (mathematical formulae) within the text. The most viewed quant research in this section are papers focused on alpha strategies, particularly for tactical asset allocation. A key issue for quant analysts here is the robustness and validity of the quant model. One paper refers to the risk of "pseudo-mathematics" and "financial charlatanism", when data is...
mined to conceive spurious relationships which don't survive out-of-sample. Therefore, quant papers providing a statistical framework for assessing the robustness of quantitative models (and reducing the risk of overfitting) have generated a lot of interest. Our most downloaded quant research in this section includes papers on risk estimation, performance attribution, big data and risk premia. Other popular reports and white papers cover risk factors and smart beta / scientific beta / alternative beta.
This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers liability liquidity risk (or funding liquidity) modeling, the second dimension focuses on asset liquidity risk (or market liquidity) modeling, and the third…
Some have argued that financial markets are a poor choice for the application of Machine Learning (ML). These articles have focused on the prediction of market or stock returns and cite the Gaussian properties of these returns or the “noisiness” of such data as the reason for their conclusions. Often, these are written by…
This document covers the mathematics of equity index calculations and assumes some acquaintance with mathematical notation and simple operations. The calculations are presented principally as equations, which have largely been excluded from the individual index methodologies, with examples or tables of results to demonstrate…
Even a long history of gains is hard to reconcile with a decade of pain for Value investors. In the second webinar of our CIO Agenda series, Sandy Rattray and Daniel Taylor discuss whether the march towards zero or negative nominal interest rates and their consequences can help provide some clues as to Value’s fate.
Financial markets are now being swayed not only by numbers, but also by words. How can automatic analysis of text by computers, also known as Natural Language Processing, predict financial movements?
David Blitz, Head of Quant Research at Robeco, shares his personal view on whether quantitative investing is still viable, given recent underperformance by many quant strategies. He reflects on the history of quant investing, the current situation, and future expectations.
The authors study what drives the re-use of U.S. Treasury securities in the financial system. Using confidential supervisory data, they estimate the degree of collateral re-use at the dealer level through their collateral multiplier : the ratio between a dealer's secured funding and their outright holdings. They find…
Investors can construct commodity benchmarks better aligned with their investment objectives. This is important because common “plain-vanilla” benchmarks, constructed to mimic relative production activity, may be inconsistent with a CIO’s objectives. CIOs can use the Real Asset Sensitivity Analysis (RASA) framework to…
When analyzing terms-of-trade shocks, it is implicitly assumed that the economy responds symmetrically to changes in export and import prices. Using a sample of developing countries, this paper shows that this is not the case. The authors construct export and import price indices using commodity and manufacturing price data…
This Bank of England paper analyses the impact of Covid-19 on productivity in the United Kingdom using data derived from a large monthly firm panel survey. The authors' estimates suggest that Covid-19 will reduce TFP in the private sector by up to 5% in 2020 Q4, falling back to a 1% reduction in the medium term. Firms…
Factor investing is based on decades of publicly available empirical studies. To stand out from competition, asset managers invest significant resources in carrying out proprietary research, in an effort to enhance factor definitions or to optimize portfolio construction, for example. In this context, new tools such as…
In this article, we model cultural knowledge as a capital in which individuals invest at a cost. To this end, following other models of cultural evolution, we explicitly consider the investments made by individuals in culture as life history decisions. Our aim is to understand what then determines the dynamics of cultural…
The convention in the news media is to announce a recession if a country experiences two consecutive quarters of negative growth. We exploit the arbitrary threshold implied by this practice to identify the economic impact of recession announcements through a Regression Discontinuity Design (RDD). Estimation results show that…
In Part 2, the author tackles notorious technology laggards. This piece transitions to alternative data pioneers (Alt-Venturers) and the 4-1-1 on Alt-Data: Hype or Hope? The author dispels the false dichotomy of the “Unattainable Triangle” for human vs. machine intelligence. The author addresses the “vacuum” concept and…
In Part 1, the author makes the case for high-frequency, short-interval Alt-Data while discussing three primary drawbacks of interpreting official economic statistics amid a global pandemic.
In virtually all studies on asset pricing and asset pricing models, the one-month Treasury bill is the choice as the risk-free rate. In his study “The Risk-Free Asset Implied by the Market: Medium-Term Bonds instead of Short-Term Bills,” published in the September 2020 issue of The Journal of Portfolio Management, David…
This project builds on research conducted by J. Piotroski, who published his paper Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers in 2000, offering a simple yet powerful framework to separate the winners from the losers in a value-investing context (summary here). You…
Among the assumptions in the first formal asset pricing model, the CAPM, is that investors are risk-averse, they maximize the expected utility of absolute wealth, and they care only about the mean and variance of return. However, research has found that these assumptions don’t hold. In the real world, there are investors who…
This article presents an overview of possible approaches to building scenarios and stress tests based on FactSet data, Portfolio Analytics suite, and risk models. FactSet present scenarios on the possible trajectory of an array of markets and asset classes in the context of the COVID-19 pandemic and the policy responses to…
