Alternative data project

Alternative data has become a key topic for investors over the years. Alexander Denev and Saeed Amen are currently working on an alternative data project to create a comprehensive introduction to the area for investors. Over the past few years we have worked on many different alternative datasets. The project will be published on Wiley in early 2020 as The Book of Alternative Data.

How you can get involved in the project

As well as using our own experience working within this space, we are also keen to get feedback about the topic from others working in the field. If you are interested in supporting the book let us know by contacting and – we are currently seeking to hear from those working within alternative data. In particular we are looking for:


  • alternative data case studies in finance
  • alternative datasets
  • thoughts on the evolution of alternative data
  • thoughts on how alternative data is currently being used


Our focus is in particular on traditional asset classes (eg. equities, FX etc). However, we might also be adding a small amount on cryptocurrencies too.

The Book of Alternative Data (Wiley) by Alexander Denev & Saeed Amen

The book will provide a concise introduction to the area of alternative data for investors. In particular, it will discuss how data is produced and consumed. There will be an introduction giving readers an idea about the various types of alternative data which are available such as:


  • satellite imagery
  • consumer transaction data
  • text based data (such as news and social media),
  • expert networks,
  • crowdsourced datasets etc.


In addition we shall discuss how alternative data can be sourced. The book will also talk about how signals from different alternative datasets can be combined. Use cases will be given to cover many different examples of how investors can use alternative data to help them understand the market. These will be drawn from both existing literature and also new work. These use cases for investors include:


  • using Twitter to forecast nonfarm payrolls
  • using text from newswire articles to trade FX
  • identifying retail activity from satellite photography