AI-Powered Financial Trading Algorithms
Hedge funds manage more than $3.2 trillion in assets. But historically, only a small handful of them have had access to the type of sophisticated financial models that could help them generate strong returns.
Alpha Vertex aims to provide the professionals running these funds — essentially, research analysts, portfolio managers, and financial advisors — with Artificial Intelligence-based trading algorithms.
Specifically, its technology provides tools to translate complex financial and unstructured data into accurate, impactful predictions. As a result, clients can perform predictive analysis of financial markets to create higher investment returns.
Alpha Vertex is led by a team with backgrounds in finance, engineering, and data science from companies including Bloomberg, Citi, J.P. Morgan, Intel, Merrill Lynch, and NASA.
It’s backed by investors including Anthemis Group and ffVC, and its financial forecasts have an accuracy rate of 60%.
Now it’s ready to start selling its products to hedge funds, asset managers, corporations, and banks.
Financial markets live on data. But the data is spread out across numerous disconnected sources. This makes it difficult to use.
Many of the investment professionals who need to make sense of this data lack the proper processing and analytical tools. Alpha Vertex provides these tools.
Its products use machine learning to analyze thousands of data sets. These include market and volatility information, macro economic data, and news sentiment.
The company’s products include:
• Predictive Models: These are stock selection models designed to uncover equities that are likely to outperform or underperform the market. These models can forecast the prices of commodities such as crude oil, iron ore, and steel.
• Alpha Signals: These signals provide quantifiable data on hard-to-find information, such as an estimated number of data scientists at companies like Google, or companies with high employee turnover or low morale.
• Alternative Data: Using natural language models, this technology can track what is being said by a company executive. This could include his or her comments about business prospects, views on the global economy, or pending litigation issues.
In short, each of these products uses AI to solve tough problems associated with large scale information processing, financial modeling, and investment management.
And because its data-driven process becomes more accurate as it collects more data, Alpha Vertex’s products improve over time.
To better understand this company’s product, consider a case study completed by Alpha Vertex with an auto manufacturer. The auto company was attempting to forecast the price of commodities used in vehicle manufacturing to improve its operating margins. But prices of these commodities are influenced by numerous factors, and the manufacturer lacked sophisticated tools to model future prices.
Alpha Vertex’s algorithms incorporated factors such as weather and pollution data into its forecasting, helping deliver 3-month price forecasting on commodities with an accuracy rate of 60%. As a result, the auto manufacturer saved an estimated $10 million to $15 million.
Alpha Vertex’s products and services are delivered as enterprise cloud solutions. Clients license the models, signals, and data sets on a subscription basis, and fees can range between $30,000 and $100,000 annually. Customers requiring custom-made models pay an additional build fee and annual license charge of $100,000.
The company has also begun conversations with asset managers to design and license specific investment strategies. This commercial model would be charged as a percentage of the strategy’s gross profits, ranging from 10% to 15%.
Alpha Vertex’s customers include a Fortune 500 Japanese auto manufacturer, and two multi-billion-dollar hedge funds. In addition, the company has been selected as part of the inaugural AI Nexus Lab in collaboration with NYU, and graduated from FinTech Innovation Lab in 2018.
In the future, Alpha Vertex aims to be acquired by a large data analytics or financial services company. In March 2018, Kensho, a financial intelligence tool, was acquired by S&P Global for $550 million. And in January 2019, Quovo, a provider of data analytics for financial companies, was acquired by Plaid for $200 million.
Mutisya has more than 10 years of domain experience in machine learning, natural language processing, and big data analytics.
He was the Head of Strategy and Business Development for Bloomberg Enterprise Solutions, where he oversaw product strategy and incubation of new financial products and services.
He was the Head of North America Business Development for Susquehanna International Group, a privately held trading company. While there, he was also Lead Manager of the company’s quantitative research and trading divisions.
Mutisya earned a Bachelor’s degree in Electrical Engineering and a Master’s degree in Financial Engineering from Cornell University.
Michael has 20 years of experience in financial services, startups, and technology.
His background includes knowledge of systems design, engineering, programming, networking, graph theory, high performance computing, and machine learning.
Before starting Alpha Vertex, he worked at JP Morgan, building secure access systems and overseeing a team of 250 technologists.
Michael previously ran a small private equity firm and advised startups located in South Africa, New Zealand, the UK, and Hungary. In addition, he was Chief Technology Officer of Emozia, a company focused on implementing machine learning into mobile devices.
A four-month program run by NYU’s Future Labs and ff Venture Capital.
A London-based venture investment firm focused on financial services companies.
A venture capital firm providing seed-stage and early-stage funding to technology companies. Portfolio includes Lithium Technologies (acquired by Vista Equity Partners) and Qualia (acquired by IDify).
Supporting early-stage fintech startups based in New York City.