augmenting a large class of volatility models with implied volatility and Google Trends data improves the quality of the … during periods of high volatility, when parameters estimates became very unstable. Moreover, several models augmented with … markets, T-GARCH models with implied volatility and student's t errors are better choices if robust market risk measures are …

I apply the model with unobserved components and stochastic volatility (UC-SV) to forecast the Russian consumer price …

-crises level is expected by the end of 2022. Forecast for the Russian economy has been improving too, decrease of GDP will not … debt without the risk to Russia's debt sustainability. In 2021, the high budget deficit will remain (no less than 5,0% of …

We analyze the effects of the outbreak of the Russian-Ukrainian war on the volatility in commodity and financial … markets. The Russian invasion sharply raised the volatility of most assets, however, the scale of reactions was market … accuracy of volatility models and find the superiority of the modified Range GARCH model. Our findings reveal also a specific …

leading business cycle indicators in Russia and Germany …

leading business cycle indicators in Russia and Germany. -- adaptive lasso ; elastic net ; forecasting ; genetic algorithms …

activity in the context of Russia. In an era characterized by global economic volatility and geopolitical shifts, understanding … utilizes a comprehensive dataset based on the results of business tendency surveys in Russia, spanning the period from 2009 to … this study is: can uncertainty indicators predict business activity in Russia or not? To address this question, we compared …