We summarise a recent paper based on a high-frequency trading firm that adopts deep neural network (DNN) machine learning systems for trading functions. The paper considers how we can begin to explain the decisions of DNNs, despite their opacity.

With current concerns over rising inflation across major economies, we summarise two studies that anticipate official CPI figures ahead of their release. These studies use high-frequency alternative data sources, which are found to improve the forecast accuracy of inflation models and provide timely insights into global pricing dynamics.

Recent research from 2022 suggests that incorporating transactional and POS data can replicate or outperform the Bank of Japan’s current Consumption Activity Index released since 2016. We summarise the findings of this research and highlight several Neudata-listed data providers that may be leveraged for such use cases.

We summarise the key findings from a recent research paper that examines the features of the Chinese stock market through various machine learning models and analyses the predictability of different machine learning models for Chinese stock returns.

We summarise a paper that questions if various sources of ‘consumer big data’ can predict company revenue and stock returns. We highlight several Neudata-listed clickstream, geolocation and brand sentiment providers that may be applicable for this use case.

We summarise a research paper which showcases how equity investors can use machine-readable news data to create systematic trading strategies. The researcher was able to do so by deriving sentiment indicators from a large point-in-time dataset of news articles.

A 2021 paper analysed how Moody’s, S&P, and Fitch, integrate ESG into their sovereign credit ratings. We add to the research’s demarcation between the three methodologies and highlight alternative ESG credit rating providers

A trio of academics recently surveyed the dataset catalogues of nearly 40 commercial data marketplaces to empirically answer the question: what is the price of data? We summarise key findings from this study, such as median price of a dataset, as well as compare the literature’s conclusions with Neudata’s own metadata.

Recent research from 2022 suggests that incorporating POS and Google Trends data can improve the precision and accuracy of Japanese GDP nowcasts. We summarise these findings and highlight several Neudata-listed data providers that may be leveraged for such use cases.

We summarise a study that employs machine learning techniques to analyse corporate commitments to climate actions in annual reports to identify greenwashing.