Quantitative Methods - Articles & White Papers

In recent years, machine learning (ML) has been a popular technique in various domains, ranging from streaming video and online shopping recommendations to image detection and generation to autonomous driving. The attraction and desire to apply machine learning in finance are no different.

The Q1 2023 edition of Risk & Reward is dedicated exclusively to one of Invesco’s key strengths – factor investing. Here, we ask the important question: does factor investing work for fixed income? To answer this and other questions, we review motivations for factor investing, describe the implementation of a multi-…

Factor portfolios based on quantitative characteristics such as value, momentum, quality, size and low volatility have historically generated attractive excess returns, outperforming market cap weight (MCW) benchmarks on a risk-adjusted basis. While single factors have outperformed over the long-term, they have also…

This article proposes a parsimonious paradigm to evaluate factor existence for practitioners. It focuses on economic theory, along with robust empirical evidence and incorporates implementation considerations without compromising the statistical rigor of multiple testing.

How can investors construct highly accurate transfer ranking models? Daniel Poh, Dphil Student at the Oxford-Man Institute of Quantitative Finance shares his research findings.

While responsible investors consider that the environmental and social pillars are highly interconnected when implementing ESG and climate strategies, our research shows that the green and social bond markets are not integrated.

In Silico is a multi-part series discussing artificial intelligence, its economic and financial impact, and its role as a driver of change. This article is the first in a series in which we explore AI’s explosion of interest in 2023, contextualising this moment in a brief historical overview and outlining opportunities.…

It feels like everyone is talking about trend following – and so they should. Against one of the most challenging economic backdrops in several decades, trend following managers largely managed to deliver substantial profits to their investors in 2022. Unsurprisingly, this has generated a rising tide of interest in the…

Last year saw a recruitment boom and professionals were able to find great roles with exceptional salaries. It is difficult to predict what the job market will offer in 2023 with further economic and social turbulence in the UK, the ongoing war in Europe, and other global headwinds. However, while there are clouds on the…

The 2023 QuantNet ranking of Financial Engineering, Quantitative Finance masters programs in the US provides detailed information on placement and admission statistics as well as salary.

Land of the rising equity market.

Artificial intelligence has been evolving since the 1950s. A generation of scientists, mathematicians and philosophers pondered that if humans use available information as well as reason to solve problems and make decisions, why can’t machines do the same thing?

Size mattered in April, with the more economically sensitive small and mid caps posting losses, as fears of recession grew.

Generative AI tools such as ChatGPT are expected to disrupt numerous industries and could fundamentally alter the way economic agents process information. We probe the economic usefulness of these tools in extracting information from complex corporate disclosures using the stock market as a laboratory. We use the GPT…

Economist Professor Robert J. Shiller formally devised with John Y. Campbell in 1988 the Cyclically Adjusted Price Earnings (CAPE) ratio (Shiller and Campbell (1988)), a powerful valuation metric that allows investors to assess the expensiveness of equity markets (initially the US and, later, major developed markets), taking…

The emerging literature suggests that machine learning (ML) is beneficial in many asset pricing applications because of its ability to detect and exploit nonlinearities and interaction effects that tend to go unnoticed with simpler modelling approaches. In this paper, we discuss the promises and pitfalls of applying machine…

We examine the potential of ChatGPT, a large language model, in predicting stock market returns using sentiment analysis of news headlines. We use ChatGPT to indicate whether a given headline is good, bad, or irrelevant news for firms' stock prices. We then compute a numerical score and document a positive correlation…

It’s always fun to push the boundaries of technology and see what it can do. The AI chatbots are the hot topic of current discussion in the quant blogosphere. So we have decided to test OpenAI’s ChatGPT abilities. Will we persuade it to become a data analyst for us? While we may not be there yet, it’s clear that AI language…

Conditional Portfolio Optimization is a portfolio optimization technique that adapts to market regimes via machine learning. Traditional portfolio optimization methods take summary statistics of historical constituent returns as input and produce a portfolio that was optimal in the past, but may not be optimal going forward…