Alternative Data News and Insight

Published literature finds that a region’s social connections to a COVID-19 hotspot correlates with a higher rate of confirmed cases. We summarise the findings of a research paper that uses social media data for Italy and the US to identify the relationship between social connections and spread of diseases. We also highlight several Neudata-listed data providers for readers interested in applying these findings to practice.

As the financial world recovers from the COVID-19 selloff, we summarise a research note that details the lessons quantitative funds can learn from the crisis. We also highlight several Neudata-listed data providers that may be applicable for investors interested in applying these lessons into practice.

Published research suggests that there is a relationship between mobile app usage and the financial performance of publicly traded companies. We summarise the findings of this research and also highlight several Neudata-listed alternative data providers that may be applicable for such use cases.

We highlight key findings from an academic paper which analyses whether WTI crude oil price movements can be forecast based on daily traffic and sentiment analysis of four different online media platforms. We also highlight why several Neudata-listed alternative data providers may be useful for readers interested in using a similar approach to crude oil price forecasting.

We summarise conclusions drawn from an academic paper comparing Japanese CPI data with a Neudata listed alternative data provider in an attempt to evaluate the accuracy of official statistics vs a ‘true’ inflation measure. The authors conclude that 1) the Japanese CPI is a poor predictor of actual inflation when measured inflation is below c.2%, and 2) the US PCE deflator methodology is superior to the Japanese CPI methodology. We also evaluate several alternative Japanese data providers and recommend further academic reading on this topic.

This study attempts to analyse the effectiveness of using Twitter and Google to predict stock index returns across the US, UK, Canada and China by measuring the appearance of bullish or bearish terms across Twitter and Google Trends and subsequently creating a 'bullishness index'. We identify key findings and the alternative data providers that are relevant to this analysis.

We summarise key findings from an academic paper which attempts to show whether financial performance is positively related to environmental performance by studying alternative data across several hundred Japanese manufacturing firms.

With a popular corporate events data aggregator as the primary source of data for this study, the authors claim companies that advance their earnings announcements by 4 or more days exhibit positive earnings surprises, while firms that delay earnings announcements after previously announcing their release date are more likely to have negative earnings surprises. The authors suggest that companies delay their announcement date due to negative events.

In this study, data from a financial news provider was used to examine whether trading in extended hours is predictive of future returns for US stocks. Specifically, the data provider captured a given stock’s return from the time of the news item through to the end of the session.