Redefining Economic Forecasts: How insytz’s Algorithm Could Have Predicted the Great Recession

Few events demonstrate a clear, back-to-back domino effect quite like the Great Recession of 2008. It was a time marked by a housing market collapse, widespread economic downturn, and seismic disruptions across the global financial system. The devastating aftermath left economists and analysts all wondering one crucial thing: could this have been predicted?

It’s widely accepted that, at the time, no formal model in existence could have foreseen the magnitude of this economic downturn.

But technology advancements sky-rocketed during the pandemic and beyond, and now, new invest-tech company, insytz, says they can solve this lack of foresight and ensure history doesn’t repeat itself.

Harnessing the Power of Historical Insights

Co-founder and Chief Strategist Jay Samuels says insytz has that in 2007, during the tumultuous period leading up to the Great Recession, their algorithm would have detected the subtle yet critical market shifts that eluded so many experts. Armed with this data, investors could have anticipated the impending crisis, potentially safeguarding their portfolios from the severe losses many ultimately faced.

The foundation of their product is an algorithm that looks back at global market conditions over the last 80 years and applies the findings—trends, patterns, and opportunities—to inform our current day-to-day market conditions. This Python-coded tech tests the philosophy that the past can illuminate the future.

The algorithm employs weighted dimensions and criteria from over 360 global markets, synthesized into color-coded (just three colors, so it’s not an overwhelming data rainbow) dashboards that update daily, providing real-time market intelligence that is clear and actionable.

Had this technology been available during the Great Recession, it could have significantly improved how investors and wealth advisors navigated the crisis. According to Samuels, one look at all the red on the insytz calendar would have alerted investors to the warning signs of a serious impending downturn. With real-time insights into market mispricing, overreactions, and even emerging opportunities, this foresight could have been instrumental in adjusting clients' portfolios.

Most Registered Investment Advisors (RIAs) and professional investors already use a significant amount of data to drive their decision-making. Many even employ historical data, so how is this different?

While other data sources—think Bloomberg, CNBC, and other invest-techs—curate data, guiding investors toward decisions while obscuring the big picture, insytz is focused on offering the unbiased big picture. Their dashboards provide high-level market overviews down to micro-movements within macro regimes—all in visual models that help illuminate opportunities.

New Standards for Market Clarity and Confidence

In a survey published this year, 75% of advisory clients reported leaving their advisors or at least considering it. Of that number, over half actually left, and 12% moved to a “robo-advisor.”

In an industry where trust is the cornerstone of client relationships, the ability to provide clients with financial clarity and actionable advice based on robust, data-driven insights significantly enhances an advisor’s credibility and value. Today’s investors don’t trust their advisors, and unexpected downturns like the Great Recession are part of the—arguably reasonable—doubt.

Today’s investors aren’t just looking for someone to manage their wealth; they’re seeking assurance that their financial future is secure. RIAs that can’t provide that clarity and reassurance will see their portfolio dwindle. That’s why Samuels believes their color-coded visual models will change the industry.

“Today’s financial advisors have to become teachers,” he explains, “And some learners are visual. I know I am.”

According to the insytz team, the results speak for themselves. Tracking their algorithm’s guidance from the time of the Great Depression to today, their algorithm successfully identified oncoming bear markets (which they call downturn regimes), sideways markets, and bull markets (or upturn regimes) before they occurred. With this knowledge, investment advisors can make decisions that offer higher risk-adjusted returns. Following the algorithm, Samuels explains, can easily result in an impressive 21.5% average annual return compared to an S&P 500 Buy and Hold strategy.

From Insight to Foresight

The question, "Does the past predict the future?" is complex, but when it comes to financial markets, insytz suggests that there is a lot we can learn from history. And, as we look toward that future, it’s clear that new investment-tech and visualization models will play an increasingly crucial role.

The insytz team claims that had their company been around in the early aughts, the Great Recession could have been anticipated. The question that remains is: If we were able to predict The Great Recession, what moves would we have made to mitigate the risk?