The article introduces a new way to predict how different things are related over time, like stock market indices. Traditional methods struggle to capture these changes accurately. The new method doesn't make assumptions about the shape of the relationships and can be used for various types of data. It's especially useful for studying how networks change over time. The researchers applied this method to forecast the connection between the S&P500 and NASDAQ indices.