Asset Management

Asset Management

At the heart of our transformative approach to asset management and financial strategy is the CPO technology. This advanced feature of our platform is specifically engineered to elevate investment strategies by dynamically optimizing portfolio allocations. By seamlessly integrating with your existing financial workflows, CPO empowers asset managers and financial institutions to harness predictive analytics for making strategic adjustments to market conditions. Our dedicated team of data scientists works in tandem with clients, crafting customized predictors that leverage CPO’s capabilities to meet the sophisticated demands of the finance industry.

How to Get Started

Interested in learning how Corrective AI and CPO can be applied to your strategy or portfolio? See below for our detailed enterprise endeavours.

1. Collaboration and NDA

First, both parties tentatively agree on a proposed collaboration and sign a Mutual NDA

2. Proof of Concept Proposal

Next, a 3-month Proof of Concept project is negotiated and initiated, with objectives outlined in a non-binding Letter of Intent.

3. Proof of Concept Completed

Afterwards, researchers conduct a proof of concept project where they work to prove the effectiveness of the project.

4. Contract

Lastly, and the client sign a contract for a minimum of one year duration.

Asset Management Use Cases


Developed for individual traders, our no-code service allows users to augment their past trading record with big data to compute the probability of profit for their next trade.


Institutional traders or funds that require a more hands-on approach to implement machine learning predictions into their decisions. Premium users can leverage our pre-engineered data features and receive consulting assistance with our engineering team.


For businesses who wish to partner with to negotiate a proof-of-concept machine learning project to demonstrate value to stakeholders

What our Clients Say

Greg Howington

Hedge Fund Investor

I worked with Ernie and Radu as a client on a project using Both researchers are uniformly dedicated to their science. They are fastidious in the development of their software and unrelenting in their diligence towards satisfying their clients.

Jacky Law

Quantitative Analyst, Safe Gold Securities & Futures Limited

This is by far the most efficient way to digest your data and produce interpretable machine learning results I have ever seen.

Stefano Peron

Chief Investment Officer,

We utilised Predictnow to forecast the behaviour of financial time series on the basis of several metrics; we found the system highly effective and its results were indeed proved right by double checking with other systems.

David Skowron

Co-Founder and VP Technology, InvestiQuant

We’re big fans of Dr. Chan and have had success with ensemble forecasting for a number of years, but have struggled with incorporating all of our IP. The Predict Now applications allow us to finally leverage our entire proprietary factor database for intraday forecasting of equities and commodities. Initial out-of-sample results are quite promising.