A long short-term memory machine learning algorithm has been applied to the two-hour data of agricultural and energy futures. The delicately implemented algorithm is able to predict the future movement of the contracts approximately two or three days ahead. A special method of standardization has been employed so that the data fed into the model […]

An auto-regressive time series model has been applied to the treasury auction process every month to closely monitor what is happening on site. We’ve managed to output a nice prediction on the auction spreads (WI – old until auction date and current – old until settlement date) on a rolling window basis (approximately a two-hour […]