Our Blog

July 28th, 2021

Something we at Boosted.ai have learned from our clients is that for institutional investors, explainable AI is not a nice-to-have, it is a must. In order to pass muster for asset managers, any reason our machine learning algorithms make decisions must be transparent to their stakeholders. We like to think of our machine learning algorithms

June 18th, 2021

AI for asset management is a new and exciting field. It’s also pretty complex to understand. At Boosted.ai, we endeavour to make artificial intelligence for investment management as simple and point-and-click as possible, while still offering the powerful machine learning that institutional investors require to succeed. However, we have found that “show, don’t tell” tends

May 31st, 2021

Institutional asset management is under pressure – fee compression, shifting investor sentiment and technological advances are placing demands on portfolio managers to find new ways to deliver value to investors. A massive explosion of alternative data has started to appear over the last several years and is likely to continue to accelerate over the next

May 13th, 2021

Executive Summary: Artificial intelligence portfolio optimizations can help institutional investors with volatility and turnover portfolio needs Significant reductions in volatility and turnover can come at only minor reductions to return (and sometimes improvements in other metrics like Sharpe and alpha) Our optimizers led to a 576 bps drop in volatility, a 92.26 percentage point drop

April 12th, 2021

Implementation brings performant, explainable AI to one of China’s largest asset managers Boosted.ai, the leading distributed machine learning platform for global investment professionals, today announced it will provide its machine learning platform, Boosted Insights, to China Asset Management Co., Ltd. (ChinaAMC), one of the largest fund management firms in China ($245.5B AUM as of December 31,

March 22nd, 2021

Executive Summary Factor timing is a very predictive use of machine learning for investment managers Utilizing factor timing can help flag signals on momentum, value, volatility and other factors Our machine learning surfaced the switch to Value over Momentum in early 2021 Capital markets expertise is still needed to glean the most value from the

February 12th, 2021

Executive Summary Machine learning in investment management works very well on bottom-up fundamental analysis Using artificial intelligence to practice factor timing is also predictive Factor timing aggregates the star rankings and factor scores the machine learning assigns to each equity in a user’s stock universe Our AI factor timing led to average returns of +1.42%

January 29th, 2021

It’s no secret trends come in waves. Right now, the 90’s are back in a big way. Fresh Prince of Bel-Air, Saved by the Bell and Sex and the City have all gotten reboots, kids are dressing like they’re en route to a Counting Crows concert, and GameStop (GME) – that place actual 90’s kids

December 1st, 2020

Machine learning can be useful for a lot of things – picking out movies to suggest, performing live translation, even (one day) fully self-driving cars. In investment and finance, the application of machine learning is still relatively new, but it offers exciting results, especially in the age of uncertainty we find ourselves in, here in

August 26th, 2020

How can you measure and predict the effects of something that hasn’t happened in a century?

August 26th, 2020

We are thrilled to announce that we recently closed an $8 million USD Series A financing round, led by Portag3 Ventures.

August 26th, 2020

Nobody can tell the future. Six months ago, I would have never guessed (even for April Fool’s Day) that we would find ourselves here, in a real-life version of the film Contagion. Modelling a black swan event like COVID-19 with traditional quantitative techniques is extremely difficult, due precisely to any black swan event’s inherent unpredictability.