Assets 360°
and
Relationship-Driven Investing

A New Paradigm For Data-Driven Investment

Introduction

What are we missing?

We believe that data as it is used today for data-driven investment is incomplete and should be improved. There is an abundance of data out there but these data are fragmented and fail to provide a big picture of what's going on in the financial markets. In other words, given this patchy data, it is hard to connect the dots and reason about the direction that the financial markets are taking.

Furthermore the prevalently used data and techniques are too focused on price-related information and ignore a lot of important factors regarding assets. Factors like the relation between assets (in the form of supply-chain, clients and competitors) are missing. So are relationships between assets and other entities such as their investors, political figures and central banks to name a few. Relationships between assets and events are also partially ignored as most of the solutions out there are solely reactive to events rather than being able to reason about their implications.

What about historical data?

This is not to say that we should completely ignore price-related data (like return, earnings, market capitalization etc). Rather, we should combine these with aforementioned relations in order to see the big picture in the financial market.

A New Analytics Paradigm

In Atlas 4.0, we see market entities as living organisms. This is because these entities exhibit a large number of behaviour which are common to social beings. Not only they leave a quantifiable trace every day, they interact with one another too. A change in one entity affects explicitly related entities and to a lesser degree implicitly related ones. To know the dynamic of these interactions is to understand the entire financial market. This is precisely what Atlas 4.0 offers.
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Assets 360° & Semantic AI

A 360 digital sphere of the market enables us to analyze better, predict better and position better. Of course the relationships between each asset and the rest of the world is a highly complex data which is beyond our collective brain capacity or even currently existing technologies. In other words, so far the technology required to store these relationships have been absent from the markets. That is why equity research firms rely so much on manual research to get the most valuable insights. In addition to this, AI algorithms necessary to mine such data have been absent too. However, this is going to change with our solution. We use a host of in-houes Semantic AI algorithms to create this digital sphere of the financial markets and use a cutting edge database technology to store this data; we call it the Assets 360°. On top of that we use a separate suite of Semantic AI algorithms to extract superior insights at scale from this data which we deliver to our clients via APIs.

Those of our clients who already have running data-driven investment models could just plug our insights as additional features into their model and see the benefits. They wont need to alter any infrastructure to use our data. Customers who conduct equity research can also use our insights directly to expand and boost their brain power by using highly interpretable insights we provide. Furthermore, given the nature of our database, we can visualize it. Clients can use this visualization to directly interact with data to form ideas and strategies. Finally, our clients can use our platform as a simulator to conduct what-if simulation scenarios to stress-test their positions. This enables them to adjust their positions far ahead of any likely or unlikely events which could affect their portfolios.

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