In 2022 the US economy realized two consecutive quarters of economic contraction - declining real GDP. The US GDP fell 1.6 percent on an annualized basis in the first quarter 2022 and was followed by a 0.9 percent drop in the second quarter.
However, economists, strategists and financial analysts argue that there was not a significant decline in economic activity so far.
The economic cycle is an important driver of the real activity and of the investment performance. Companies can adjust their business strategy and capital expenditures timely to avoid financial stress. Investors need to have a well-informed view on the business cycle so their portfolio allocations can be adjusted.
Therefore, it is important to analyse the signals of recession risk and to predict a recession with a high probability.
Machine learning, being part of the artificial intelligence science, provides new methods to improve the performance of predictive analysis. Big data and computing power help Machine Learnings algorithms to perform complex tasks in a short time and to increase its popularity in finance.
So, could Machine Learning techniques improve the predictability of a recession, especially in the US?
Join us as we hear Marc Fohr, CFA, explore the effect of Machine Learning techniques.