Overnight market interest rates and banks' demand for reserves in Finland
Pulli, Markku (01.05.1992)
Numero
47Julkaisija
Suomen Pankki
1992
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:bof-201708161557Sisällysluettelo
Acknowledgements 5
1 Introduction 9
2 An Overview of the Theory of Banks' Demand for Reserves 16
2.1 The market for reserves 16
2.1.1 Determination of the short-term interest rate 16
2.1.2 The overnight market interest rate, the call money facility and monetary policy 20
2.2 Studies on the borrowing function 23
2.3 Liquidity management theory 27
2.4 The theoretical framework of the study 30
3 The Market for Overnight Funds and the Call Money Facility in Finland 33
3.1 Evolution and current structure of the call money facility 33
3.1.1 Historical background 33
3.1.2 The structure of the call money facility 37
3.2 The overnight market: some 'stylized facts' 39
4 A Stochastic Asset Allocation Model of the Overnight Market 43
4.1 The basic model 45
4.2 Effects of risk aversion 52
4.3 Quantitative quotas on borrowing 56
4.4 Time-dependent costs of borrowing 59
5 Endogenous Variance: Effects of Liquidity Control 63
5.1 Introduction 63
5.2 The model 64
5.3 Comparative statics 66
5.4 Solution of the model 69
5.5 Concluding remarks 72
6 Empirical Application of the Model with Constant Variance 74
6.1 Data and organization of the empirical study 74
6.2 A model with constant variance 77
6.3 Changes in the standard deviation of borrowing 85
7 Estimation of the Reserve Model with Time-Dependent Conditional Variance 88
7.1 A nonlinear GARCH-in mean model 88
7.2 Empirical results from GARCH(1,1)-in mean 93
7.3 Specification of the variance equation 101
7.4 Alternative distributional assumptions 108
7.5 Estimation results from the modified GARCH-in mean model 110
7.6 Concluding remarks 115
8 Summary and Conclusions 117
Appendix 1: Risk premium 124
Appendix 2: Comparative statics of the liquidity control model 126
Appendix 3: Additional estimation results from applications with constant conditional variance 129
Appendix 4: Maximum likelihood estimation of a nonlinear GARCH-in mean model 132
Appendix 5: Estimating of GARCH-in mean model with Student's t distribution 135
Appendix 6: Modelling the residuals as an AR(1) process 137
Bibliography 140
1 Introduction 9
2 An Overview of the Theory of Banks' Demand for Reserves 16
2.1 The market for reserves 16
2.1.1 Determination of the short-term interest rate 16
2.1.2 The overnight market interest rate, the call money facility and monetary policy 20
2.2 Studies on the borrowing function 23
2.3 Liquidity management theory 27
2.4 The theoretical framework of the study 30
3 The Market for Overnight Funds and the Call Money Facility in Finland 33
3.1 Evolution and current structure of the call money facility 33
3.1.1 Historical background 33
3.1.2 The structure of the call money facility 37
3.2 The overnight market: some 'stylized facts' 39
4 A Stochastic Asset Allocation Model of the Overnight Market 43
4.1 The basic model 45
4.2 Effects of risk aversion 52
4.3 Quantitative quotas on borrowing 56
4.4 Time-dependent costs of borrowing 59
5 Endogenous Variance: Effects of Liquidity Control 63
5.1 Introduction 63
5.2 The model 64
5.3 Comparative statics 66
5.4 Solution of the model 69
5.5 Concluding remarks 72
6 Empirical Application of the Model with Constant Variance 74
6.1 Data and organization of the empirical study 74
6.2 A model with constant variance 77
6.3 Changes in the standard deviation of borrowing 85
7 Estimation of the Reserve Model with Time-Dependent Conditional Variance 88
7.1 A nonlinear GARCH-in mean model 88
7.2 Empirical results from GARCH(1,1)-in mean 93
7.3 Specification of the variance equation 101
7.4 Alternative distributional assumptions 108
7.5 Estimation results from the modified GARCH-in mean model 110
7.6 Concluding remarks 115
8 Summary and Conclusions 117
Appendix 1: Risk premium 124
Appendix 2: Comparative statics of the liquidity control model 126
Appendix 3: Additional estimation results from applications with constant conditional variance 129
Appendix 4: Maximum likelihood estimation of a nonlinear GARCH-in mean model 132
Appendix 5: Estimating of GARCH-in mean model with Student's t distribution 135
Appendix 6: Modelling the residuals as an AR(1) process 137
Bibliography 140