We summarise a recent paper from the BIS, which outlines the usage of big data and machine learning within the central bank community, based on a recent survey of Irving Fischer Committee members.

We discuss an industry report that polled hedge fund managers on their alternative data usage. We highlight the major challenges that respondents reported and provide a brief discussion of our own findings.

We summarise the findings of a recently published paper that applies an algorithm developed by MIT researchers to infer which products a consumer has purchased when given information on only the total transaction amount. The paper also explores further applications of their algorithm such as the detection of new product launches from credit and debit card transactions.

When expectations for headline economic indicators are off-beat, economists sometimes point to the Keynesian notion of ‘animal spirits’ as the cause of error. Animal spirits can be loosely defined as the emotional and psychological drivers of economic decision making, that commonly diverge from models of rational, self-optimizing behaviors. But what if we could quantify and measure the animal spirits in headline indicators? Would it make forecasts for growth and inflation more accurate?

We summarise findings of a recently published academic paper that evaluates different classification techniques for identifying market manipulation activity on online forums.

We summarise findings from a recent academic work that investigated whether ESG investing offered funds any resilience during the COVID-19 crisis.

Below we summarize key findings from a 2020 working paper, which proposes that investors do not promptly incorporate information on government contracts into stock prices.

We highlight the findings of a research paper that takes a unique approach to the topic of re-identification risk and highlights the privacy risks associated with current de-identification methods.

Poor data quality can have far-reaching effects, reiterating the importance for data users – buyers and sellers alike – to closely follow a quality assurance framework. In this Literature Review, we summarise the findings of a 2019 research that surveyed and assessed 12 data quality frameworks on behalf of data users.

This review summarizes the key empirical findings from an academic work that explores how the market reacts to the stocks recommended via official WeChat accounts. We summarise the findings of this research and highlight several Neudata-listed alternative data providers applicable for such use cases.