Unlike their public markets counterparts, venture capital investors can be hindered by a lack of data to help inform investment processes. Several venture-oriented platforms have materialised to fill this void, providing numerous metrics with varying relevancy. We summarise a study that uses machine learning to identify the most relevant factors for early-stage venture capital investors.

Text is an underexploited data source for understanding asset markets. So far, academic research has studied only a tiny fraction of market-relevant text data and often focuses on a single specialised data source. As a result, text information is often represented in rudimentary ways. This report summarises a study that aims to improve stock-return prediction models by extracting contextualised representations of news text derived from large language models (LLMs).

The return of high inflation has revived the economic trauma of the 1970s concerning wage-price spirals. To compare the current conditions of inflationary pressure, we summarise a working paper by the IMF that studies the impacts of wage-price spirals on inflation. We also highlight alternative sources of relevant economic data, including salary information, that offer timely insights into wage growth and the current macroeconomic climate.

This literature review summarises a recent paper on comparative performance persistence across PE investment strategies (buyout versus venture capital) in the US since 1984. We examine the underlying data in the study and assess the applicability of other datasets in understanding managers’ interim and final performance, based on internal rate of return, multiple on invested capital and public market equivalent benchmarks.

Almost 3bn of the world’s population still lacked access to and use of digital technologies in 2021. We review a recent study that explores whether investing in shared telecom infrastructure – particularly where independent companies own towers and lease them to network operators – could improve digital connectivity in some developing nations.

The potential uses for ChatGPT have grown as rapidly as its popularity. We summarise a 2023 paper that explores how the technology can assist with financial research, particularly for generating ideas and identifying data.

Current expected credit loss (CECL) is an accounting standard introduced to mitigate banks’ potential losses. But some financial industry professionals believe that implementing this model could raise interest rates and reduce credit access to consumer loans. In light of these claims, we look at a study that assesses the CECL's effects on credit access and pricing.

We review a study that investigates the NYSE and NASDAQ composite indices' return and volatility spillover on Chinese A-share sector indices and broad market indices from 2010-2022. It shows the composition of an A-share index can influence its sensitivity to the spillover effect of a particular US index. And the spillover becomes more prominent during a weak market.

With ChatGPT’s rising popularity, a range of studies have considered how applicable it can be to different industries. In this report, we look at a 2023 paper assessing how effective the technology could be in aiding asset allocation and portfolio management.

Investors are increasingly turning to commodity derivatives as a means to hedge risk and ensure high returns. For agricultural commodities, however, academics have not historically examined the persistent nature of the returns that can be generated. In this report, we summarise a study that examines the performance persistence of agricultural commodity trading strategies using market data from the CME.