The Central Bank of Russia has released the second issue of the Russian Journal of Money and Finance, presenting research on business-cycle identification, investment forecasting, housing market pricing and valuation tools for yuan-denominated federal government bonds. The issue focuses on how business survey data can signal turning points in economic activity, how patent activity can improve forecasts of fixed capital investment, what drives the price gap between new-build and second-hand homes, and how to construct a yield curve for yuan-denominated OFZs despite limited market data. The research finds that adding patent data to machine-learning models significantly improves forecasts of fixed capital investment. It identifies firms’ assessments of actual demand and the business climate index as the most reliable Bank of Russia survey indicators of business-cycle turning points. On housing, the analysis links the price premium for new-build homes mainly to concentration in regional primary housing markets and the government-subsidised Family Mortgage programme, while stronger competition among banks narrows the gap. For yuan-denominated OFZs, the proposed methodology combines data from sovereign OFZs and yuan-denominated corporate bonds to produce a more reliable yield curve.
Central Bank of Russia2026-06-26
Central Bank of Russia publishes second Russian Journal of Money and Finance issue on business cycle signals housing pricing and yuan OFZ valuation
The Central Bank of Russia has published the second issue of the Russian Journal of Money and Finance, covering research on business-cycle signals, investment forecasting, housing price gaps and yuan-denominated OFZ valuation. Key findings include better investment forecasts when patent data are used, reliable survey indicators for detecting turning points, housing price gaps driven by market concentration and subsidised mortgages, and a yield-curve model that combines OFZ and yuan corporate bond data.