Why I joined CircleUp

Throughout my career, I have been fortunate to work with a top tier investment bank and leading quant hedge fund. I had the chance to build mathematical models for multi-million dollar private investments at Goldman Sachs, and manage a billion dollar systematic macro fund at AQR Capital. Two absolutely amazing firms, with world class people and systems, where if you are a top performing data scientist, there is a clear path to ascend through ranks of responsibility.

So why did I leave those glorious firms to join CircleUp? First, the team. I had never seen such a collection of diverse skill sets working in such harmony. It was so different from my previous experiences and struck a chord. At CircleUp, investors, data scientists and engineers are operating as a single organism to build something new. Second, I love the CircleUp mission, to help entrepreneurs thrive, and on top of that, I love how the team is seeking to accomplish it – by using data and technology to fundamentally change private investing forever. CircleUp has already demonstrated they are onto something, with both a discretionary equity fund and credit business that are backed by leading institutional LPs. What can I say? I had to be part of it – I want to help build this future.

CircleUp is creating something that has never existed before – systematic investing in the private consumer market. This will have immense value. A systematic approach is the next generation of financial investment in private equity, driven by the innovation of technology and big data. The public markets have already been transformed by automated algorithmic trading and systematic investing, both of which greatly increased the efficiency and scalability of investing at much lower cost. Having spent my career in both private investing and quant public markets, I am excited to see the synergy between the two.

Systematic investing in public markets

Systematic fund managers design mathematical methods to make investment decisions based on fundamental economic and quantitative signals (factors). With rigorous research and quantitative analysis, systematic investing can generate good performance with several advantages:

  •      Efficiency
  •      Repeatability
  •      Scalability
  •      Diversification
  •      Disciplined risk management
  •      Reduced human bias or error

Such advantages are predicated on a few fundamental features of public markets: (1) standardized data that is robust enough to build algorithms on top of, (2) platforms that allow for real-time access to such data and, (3) infrastructure to complete a transaction at the push of a button.

It goes without saying that the private markets pose some additional business and execution challenges.

Systematic investing in private market

Despite the growing popularity of systematic investing in public markets, things haven’t significantly changed for private investors. The biggest names in private equity still employ the same techniques to source and evaluate companies that they used 20 years ago. Plus there are thousands of new firms with billions of dollars of dry powder using those same tactics. Read as: more competition, little differentiation. This old way has been justifiable given the lack of transparency and lack of data in the private market.

In order to build systematic strategies for private investments we are solving both technical challenges and business challenges.

For the technical challenges we need:

  •      Clean datasets that are rich in both time and cross-section dimensions to help us        understand the growth drivers
  •      Robust risk metrics for both systematic and specific risk quantification
  •      Rules based portfolio construction

For the business challenges, we need the ability to:

  •     Identify breakout brands
  •     Efficiently evaluate the investment opportunity
  •     Win the deal
  •     Quickly deploy capital
  •     Effectively manage a large portfolio

Thanks to the data-rich consumer sector and explosion in computational power,  we are confident we can solve the technical side of the problem. At CircleUp, we have built comprehensive data pipelines to pull in billions of consumer product data points from both online and offline sources. Highly skilled data scientists and engineers have created innovative and sophisticated logic to process such massive, unstructured data to generate business insights for each brand. Such a powerful data engine opens the door for the automated private investing framework we are creating. By studying the features that will forecast future growth and defining the metrics, we can build an algorithm to select the potential companies based on these metrics, analyze the correlations across segments, and create an optimized holding portfolio.

We are tackling the business side of the problem with a system that automates the deal workflow. By streamlining deal sourcing, due diligence and execution, we plan to reduce the deal cycle from months to weeks, maybe even days.

As we solve these problems, the private investment world will enter a new era, where a much larger universe of small businesses will be evaluated simultaneously, capital will be allocated more efficiently, and investment selections will be more consistent and diversified.

Unlocking growth

The core of CircleUp is Helio, our machine learning platform that analyzes billions of pieces of data in CPG, and provides insights into products, companies and industry trends. Such a powerful engine provides the foundation upon which to build a systematic investing framework. In demonstrating the value of systematic investing in private markets, we can transform private investing and unlock huge growth potential.

As the pioneers attempting such an approach, we will face both opportunities and challenges. Together with the entire CircleUp team, I am confident we can build this framework from the ground up and overcome the inevitable hurdles along the way. It is the next chapter in our vision to bring transparency and efficiency to an opaque market.

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