By the act of lending banks do not actually intermediate preaccumulated real resources but rather create new financial resources in the form of deposits. Therefore, bank credit needs to be modelled as a monetary phenomenon, which directly fuels domestic demand and inflationary pressures. So far, there have been just a few attempts to model banks as monetary institutions in the DSGE model. In this paper we propose a simple DSGE model, which nevertheless accommodates banks as genuinely monetary institutions and captures banks' institutional ability to create money. Our model features a small open economy with nominal prices, savers and borrowers and a banking sector. Following an exogenously induced shock to banker's willingness to lend, the bank does not have to raise deposit rates or significantly increase borrowing from abroad as deposit dynamics closely resembles that of credit, which allows us to analyse real and nominal consequences of bank credit (and money) creation.
ARTICLE HISTORY
Abstract. In this paper we propose an artifi cial stock market model based on interaction of heterogeneous agents whose forward-looking behaviour is driven by the reinforcement-learning algorithm combined with some evolutionary selection mechanism. We use the model for the analysis of market self-regulation abilities, market effi ciency and determinants of emergent properties of the fi nancial market. Distinctive and novel features of the model include strong emphasis on the economic content of individual decision-making, application of the Q-learning algorithm for driving individual behaviour, and rich market setup. Along with that a parallel version of the model is presented, which is mainly based on research of current changes in the market, as well as on search of newly emerged consistent patterns, and which has been repeatedly used for optimal decisions' search experiments in various capital markets.
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