title: ÐÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ½Ð¾Ð·Ð½Ð°ÑÐ½ÑÐµ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ Ð² Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Complex-valued autoregressions in forecasting economic data
Creators: name: Ð¡Ð°Ð¼Ð°ÑÐ¸Ð½Ð°, ÐÐ»Ð¸Ð·Ð°Ð²ÐµÑÐ°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ðµ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐµÐ½ Ð½Ð° Ð¼ÐµÑÐ°Ð»Ð»Ñ
ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¾Ðµ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
Ð²ÐµÐºÑÐ¾ÑÐ½ÑÐµ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸
ÐºÐ¾Ð¼Ð»ÐµÐºÑÐ½Ð¾Ð·Ð½Ð°ÑÐ½ÑÐµ Ð²ÐµÐºÑÐ¾ÑÐ½ÑÐµ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸
short-term forecasting
metal price forecasting
economic forecasting
vector autoregressions
complex-valued vector autoregressions

description: Ð¦ÐµÐ»ÑÑ Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐµÑÐµÐ½Ð¸Ðµ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ ÑÐ°Ð·Ð¼ÐµÑÐ½Ð¾ÑÑÐ¸ Ð¼Ð°ÑÑÐ¸ÑÑ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ð² Ð¼Ð¾Ð´ÐµÐ»ÑÑ Ð²ÐµÐºÑÐ¾ÑÐ½Ð¾Ð¹ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ ÐºÐ°Ðº ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾Ð¼ ÑÐ¿Ð¾ÑÐ¾Ð±Ðµ ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ. ÐÐµÑÐ¾Ð´Ñ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÐ¼ÑÐµ Ð¿ÑÐ¸ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐµ Ðº Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÐµÐ³Ð¾ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸: Ð´ÐµÐ´ÑÐºÑÐ¸Ñ, Ð¸Ð½Ð´ÑÐºÑÐ¸Ñ, Ð¸ÑÑÐ¾ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð¼ÐµÑÐ¾Ð´, Ð¼ÐµÑÐ¾Ð´ Ð°Ð½Ð°Ð»Ð¾Ð³Ð¸Ð¹, Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸ ÑÐ¸Ð½ÑÐµÐ·Ð°. ÐÑÐ½Ð¾Ð²Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1) Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¾ Ð°ÐºÑÑÐ°Ð»ÑÐ½Ð¾Ðµ ÑÐ¾ÑÑÐ¾ÑÐ½Ð¸Ðµ Ð¿ÑÐ¾Ð³Ð½Ð¾ÑÑÐ¸ÑÐµÑÐºÐ¾Ð¹ Ð½Ð°ÑÐºÐ¸ Ð½Ð° Ð¿ÑÐµÐ´Ð¼ÐµÑ Ð¼Ð½Ð¾Ð³Ð¾Ð¾Ð±ÑÐ°Ð·Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ, Ð¸Ñ Ð¿ÑÐµÐ¸Ð¼ÑÑÐµÑÑÐ² Ð¸ Ð½ÐµÐ´Ð¾ÑÑÐ°ÑÐºÐ¾Ð²; 2) Ð´Ð¾ÐºÐ°Ð·Ð°Ð½Ð¾, ÑÑÐ¾ Ð²ÐµÐºÑÐ¾ÑÐ½ÑÐµ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ñ Ð´Ð°Ð²Ð°ÑÑ Ð±Ð¾Ð»ÐµÐµ ÑÐ¾ÑÐ½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð² ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ð¸ Ñ Ð´ÑÑÐ³Ð¸Ð¼Ð¸ Ð¼Ð¾Ð´ÐµÐ»ÑÐ¼Ð¸; 3) Ð´Ð¾ÐºÐ°Ð·Ð°Ð½Ð¾, ÑÑÐ¾ ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ½ÑÐµ Ð²ÐµÐºÑÐ¾ÑÐ½ÑÐµ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ â Ð¿ÐµÑÑÐ¿ÐµÐºÑÐ¸Ð²Ð½Ð¾Ðµ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ, ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸ÑÑ Ð²ÑÑÐ¾ÐºÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿ÑÐ¸ Ð¼ÐµÐ½ÑÑÐµÐ¼ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ðµ Ð¾ÑÐµÐ½Ð¸Ð²Ð°ÐµÐ¼ÑÑ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ¾Ð²; 4) ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° Ð¼ÐµÑÐ¾Ð´Ð¸ÐºÐ° Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ Ð½ÐµÐ»Ð¸Ð½ÐµÐ¹Ð½ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð²ÐµÐºÑÐ¾ÑÐ½Ð¾Ð¹ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸ Ñ Ð´Ð¾ÐºÐ°Ð·Ð°Ð½Ð½Ð¾Ð¹ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑÑ; 5) Ð¾Ð±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð° Ð¸ Ð´Ð¾ÐºÐ°Ð·Ð°Ð½Ð° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð·Ð°Ð¼ÐµÐ½Ñ Ð¼ÐµÑÐ¾Ð´Ð° Ð¾ÑÐµÐ½Ð¸Ð²Ð°Ð½Ð¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð²ÐµÐºÑÐ¾ÑÐ½ÑÑ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¹ Ð¼Ð¸Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸ÐµÐ¹ ÐºÐ¾Ð²Ð°ÑÐ¸Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾-Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð¼Ð°ÑÑÐ¸ÑÑ Ð½Ð° Ð¼ÐµÑÐ¾Ð´ Ð¿Ð¾ÑÐ»ÐµÐ¼ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ Ð¾ÑÐµÐ½Ð¸Ð²Ð°Ð½Ð¸Ñ Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ð¹. ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÐÐÐ  â ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð¾Ðµ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½Ð¾-ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¸Ñ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð². ÐÐ°ÑÑÐ½Ð°Ñ Ð½Ð¾Ð²Ð¸Ð·Ð½Ð° Ð´Ð¸ÑÑÐµÑÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð·Ð°ÐºÐ»ÑÑÐ°ÐµÑÑÑ Ð² ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¼ÐµÑÐ¾Ð´Ð° ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð½ÐµÐ»Ð¸Ð½ÐµÐ¹Ð½ÑÑ Ð²ÐµÐºÑÐ¾ÑÐ½ÑÑ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¹ Ð¸ Ð¾Ð±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ð¸ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð·Ð°Ð¼ÐµÐ½Ñ Ð¼ÐµÑÐ¾Ð´Ð° Ð¾ÑÐµÐ½Ð¸Ð²Ð°Ð½Ð¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð²ÐµÐºÑÐ¾ÑÐ½ÑÑ Ð°Ð²ÑÐ¾ÑÐµÐ³ÑÐµÑÑÐ¸Ð¹ Ð¼Ð¸Ð½Ð¸Ð¼Ð¸Ð·Ð°ÑÐ¸ÐµÐ¹ ÐºÐ¾Ð²Ð°ÑÐ¸Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾-Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð¼Ð°ÑÑÐ¸ÑÑ Ð½Ð° Ð¼ÐµÑÐ¾Ð´ Ð¿Ð¾ÑÐ»ÐµÐ¼ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ Ð¾ÑÐµÐ½Ð¸Ð²Ð°Ð½Ð¸Ñ Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ð¹.
description: The purpose of the graduate qualification work is to solve the problem of dimensionality of the coefficient matrix in vector autoregression models as an effective method of short-term forecasting. Methods used in preparation for the research and its implementation: deduction, induction, historical method, method of analogies, analysis and synthesis. The main results of the study: 1) the current state of prognostic science was analyzed for the variety of forecasting models, their advantages and disadvantages; 2) it is proved that vector autoregressions can give more accurate results of short-term forecasting in comparison with other models; 3) it is proved that complex vector autoregressions are a promising direction that can provide high accuracy with a smaller number of estimated coefficients; 4) a methodology for constructing nonlinear vector autoregression models with proven efficiency has been developed; 5) the efficiency of replacing the method of estimating vector autoregression parameters by minimizing the covariance-dispersion matrix with the method of element-by-element estimation of dispersions is justified and proved. The field of application of the results of the research is short-term forecasting of socio-economic processes. Scientific novelty of the dissertation research consists in the development of the method of formation of nonlinear vector autoregressions and justification of the effectiveness of replacing the method of estimating the parameters of vector autoregressions by minimizing the covariance-dispersion matrix by the method of element-by-element estimation of dispersions.