House Price Indices are one of the most closely observed economic indicators in the world, especially since the global recession in 2008. However, various government and private organisations rely on proprietary and/or public datasets to produce their own interpretation of an HPI. We evaluate some of the leading HPIs in the UK (construction methods, outcomes, advantages, and disadvantages) and highlight relevant alternative data sources for readers interested in constructing a more appropriate HPI for their needs.

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.

A recent survey of 80 hedge funds by AIMA found that almost 40% of respondents are already engaging in responsible investing practices. However, data quality issues appear to be the biggest barrier to increasing such initiatives. For quants, these data limitations have made building systematic strategies particularly challenging. At Neudata, we see evidence of this changing as a result of alternative data addressing the many quality-related shortfalls plaguing the industry.

We highlight key findings from a commodity alternative data provider's recent backtest on their US corn production forecasts. The results establish that the group’s forecasts lead USDA estimates, market consensus, and corn futures closing prices. Neudata are the first third party to be made aware of these results.

Neudata has combined insights from multiple empirical studies to provide 1) an overview of potential use cases for AIS-derived vessel tracking data, 2) a case study investigating the alignment of AIS-based trade estimates and official customs statistics, 3) an introduction to AIS data challenges, and 4) advice for data buyers.

From counting cars at mall and shopping centre parking lots to gauge consumer traffic, to calculating the shadows cast on floating-roof tanks to estimate global crude oil supply, satellite data has become one of the more well-known types of alternative data in the market. With significant numbers of institutional investors realizing the value of this data, we address the current state of the industry, as well as some words of caution when approaching satellite data.

We summarise a case study illustrating how corporate jet activity can yield signals that help investors to identify the most likely acquirer for a takeover target. We also outline an alternative approach to tracking corporate jets using free alternative data sources.

With 90% of today’s data created in the last two years, opportunities to leverage vast amounts of unstructured data sources are growing at an exponential rate. The proliferation of AI and big data is transforming the ESG industry – providing investors with a greater supply of more timely information and the ability to develop more sophisticated investing strategies. Alternative data is the driving force behind ESG 2.0.

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.