title: Use of Machine Learning Methods to Forecast Investment in Russia
abstract: This work forecasts the growth rate of quarterly gross fixed capital formation in Russia using machine learning methods (regularisation methods, ensemble methods) over a horizon of up to eight quarters. The methods tested show higher quality in terms of RMSFE than that of simple alternative models (autoregressive model, random walk model), with ensemble methods (boosting and random forest) leading in quality. The last statement is consistent with the results of other research on the application 
journal: Russian Journal of Money and Finance