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.

We summarise key findings from a backtest using an alternative data provider’s cognitive data scores and shareholder returns. Scores were sourced from statements made by company executives on quarterly earnings calls. In short, the backtest supports the view that higher than trend value scores are likely to precede shareholder gains.

We summarise key findings of a research paper co-authored by a pharmaceutical data provider. Using Takeda Pharmaceutical’s FY 2017 Q4 pipeline as an example, we also evaluate how phase transition data can be used by investors to gain a better understanding of which drugs are most likely to be approved by the FDA and to analyse the health of a pharmaceutical company’s pipeline.

Sports Direct and Ryanair have both demonstrated share price volatility in the last few years that many attribute to poor labour management practices. Finding a way to measure social intangibles, and in particular monitoring significant changes to such, could therefore be a useful leading indicator in predicting share price movements. We outline 1) ways in which one can measure the ‘S’ factor, 2) studies that support incorporating social intangibles into the investment process and 3) examples of alternative data providers that can help an investor do so.

Using data sourced from a Neudata-listed alternative data provider, we highlight key findings from the group's analysis on Carillion, and establish the early warning signals that could have helped investors anticipate the group’s failure, including: 1) High revenue concentration 2) Lumpy construction projects 3) A shift towards the construction sector, and 4) A decrease in award value

At Neudata we have seen increased interest in alternative datasets that offer insights into a given company’s Intellectual Property. We explain 1) why we think this is, 2) why we believe trademark data is particularly interesting, 3) empirical studies that support this view, and 4) recommended providers to use in order to access trademark data.

Companies are more likely to share information to the public which demonstrates a high commitment to ESG standards. The same companies tend to avoid the disclosure of information that could reflect poorly on corporate practices. As an investor, one can overcome this issue by adopting an ‘outside-in’ approach through the use of alternative data sources.

Using data sourced from a transportation alternative data provider, we provide an overview of key correlations between railroad commodity volumes data and a number of economic indicators.

We offer our advice on the following three issues for: 1) challenges and pitfalls to be aware of when using e-receipt datasets 2) how different e-receipt data providers compare, and 3) what to look for ahead of selecting an alternative data provider

We summarise backtesting results directly sourced from one of our data providers, explaining how South Korean export data can be used as a leading indicator of company revenue. Specifically, this alternative dataset identifies correlations for companies that export products with a South Korean dominance.