Schmaltz A Quantitative Liquidity Model for Banks

2010
ISBN: 978-3-8349-8554-5
Verlag: Betriebswirtschaftlicher Verlag Gabler
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 223 Seiten, eBook

Christian Schmaltz identifies product cash flows, funding spread, funding capacity, haircuts, and short-term interest rates as key liquidity variables. Then, he assumes specific stochastic processes for the key variables leading to a particular liquidity model. The model is used to derive liquidity funds transfer prices and to optimally manage liquidity.



Dr. Christian Schmaltz completed his doctoral thesis under the supervision of Prof. Dr. Thomas Heidorn at the Frankfurt School of Finance and Management. He works as a consultant for risk management.

Zielgruppe

Research

Autoren/Hrsg.

Schmaltz, Christian

Inhaltsverzeichnis

1;Foreword;7
2;Acknowledgements;9
3;Contents;10
4;List of Figures;13
5;List of Tables;16
6;Symbols;17
7;Chapter 1 Introduction;20
7.1;1.1 Motivation;20
7.2;1.2 Problem Description;25
7.2.1;1.2.1 Bank Liquidity Models;25
7.2.2;1.2.2 Quantitative Liquidity Models;26
7.2.2.1;1.2.2.1 Cash Management Models;26
7.2.2.2;1.2.2.2 Debt Management Models;30
7.2.3;1.2.3 Complete Liquidity Models;31
7.3;1.3 Objective and Proceeding;32
8;Chapter 2 Liquidity Concepts;34
8.1;2.1 Asset Liquidity;34
8.2;2.2 Institutional Liquidity;38
8.3;2.3 National Liquidity;39
8.4;2.4 Interdependencies between Liquidity Concepts;41
8.5;2.5 Summary;42
9;Chapter 3 Liquidity Framework;44
9.1;3.1 Modelling Fundamentals;44
9.1.1;3.1.1 Stock versus Flow Perspective;44
9.1.2;3.1.2 Cash Flow Maturity Ladder;45
9.1.3;3.1.3 Interest Rates and Liquidity Management;46
9.1.4;3.1.4 Liquidity Options;47
9.1.5;3.1.5 Repo;51
9.2;3.2 Liquidity Strategies of Banks;53
9.2.1;3.2.1 Maturity Mismatch Strategy;54
9.2.2;3.2.2 Liquidity Option Strategy;56
9.2.3;3.2.3 Summary;60
9.3;3.3 Framework;61
9.4;3.4 Comparison with Literature;62
9.5;3.5 Summary;63
10;Chapter 4 Liquidity Model;64
10.1;4.1 Time Scale;64
10.2;4.2 Cash Flow Model;65
10.2.1;4.2.1 Requirements;65
10.2.2;4.2.2 Product Cash Flows;66
10.2.2.1;4.2.2.1 Cash Flow Assumption;66
10.2.2.2;4.2.2.2 Generic Product;72
10.2.2.3;4.2.2.3 Model Horizon;73
10.2.3;4.2.3 Aggregation;74
10.3;4.3 Funding Model;79
10.3.1;4.3.1 Requirements;79
10.3.2;4.3.2 Funding Model;80
10.3.3;4.3.3 Calibration;83
10.4;4.4 Liquidation Model;83
10.4.1;4.4.1 Requirements;83
10.4.2;4.4.2 Liquidation Model;84
10.5;4.5 Interest Rate Model;90
10.6;4.6 Bank Liquidity Model;91
10.7;4.7 Summary;92
11;Chapter 5 Liquidity Management;94
11.1;5.1 Cash Flow Transfer;94
11.1.1;5.1.1 Basic Transfer Model;94
11.1.2;5.1.2 Extended Transfer Model;97
11.1.3;5.1.3 Model Horizon;108
11.2;5.2 Transfer Pricing;110
11.2.1;5.2.1 Transfer Price for Deterministic Cash Flows;113
11.2.2;5.2.2 Transfer Price for the Brownian Component;114
11.2.3;5.2.3 Transfer Price for the Jump Component;127
11.2.3.1;5.2.3.1 Reconciliation with the Literature;142
11.2.3.2;5.2.3.2 Pricing Examples;145
11.3;5.3 Summary;147
12;Chapter 6 Liquidity Optimization;152
12.1;6.1 Setup;152
12.2;6.2 Origination Department;156
12.2.1;6.2.1 The Model;156
12.2.1.1;6.2.1.1 Setup;156
12.2.1.2;6.2.2 Optimization without Funding Risk;159
12.2.2;6.2.3 Optimization with Funding Capacity Risk;160
12.2.2.1;6.2.3.1 Impact of Funding Stochastic;163
12.2.2.2;6.2.3.2 Impact of Spread Definition;165
12.2.3;6.2.4 Comparison with the Literature;170
12.2.4;6.2.5 Conclusion;172
12.3;6.3 Money Market Department;172
12.3.1;6.3.1 The Model;172
12.3.1.1;6.3.1.1 Setup;172
12.3.1.2;6.3.1.2 Choice of Model Horizon;176
12.3.2;6.3.2 Optimality Candidates;181
12.3.3;6.3.3 Reserve Decisions in t1;183
12.3.4;6.3.4 Reserve Decisions in t0;189
12.3.5;6.3.5 Numerical Example;196
12.3.6;6.3.6 Comparison with the Literature;200
12.3.7;6.3.7 Conclusion;201
12.4;6.4 Risk Controlling;202
12.5;6.5 Summary;202
13;Chapter 7 Conclusion;206
14;Appendix A Liquidity Model;212
14.1;A.1 Cash Flow Expectations;212
14.1.1;Conditional versus Unconditional Expectations;212
14.1.2;Unrestricted Products;213
14.1.3;Restricted Products;214
14.1.4;Suboptimality and Attenuation;215
15;Appendix B Liquidity Management;218
15.1;B.1 Brownian Transfer Prices for Large and Homogeneous Portfolios;218
16;Appendix C Liquidity Optimization;220
16.1;C.1 Optimization in Origination Department;220
16.2;C.2 Optimization in Money Market Department;224
16.2.1;C.2.1 Approximation of Cash Flow SDE by Binomial Cash Flow Model;224
16.2.2;C.2.2 Determination of Optimality Candidates;227
16.2.2.1;C.2.2.1 Candidates for t0;232
17;References;236

Liquidity Concepts.- Liquidity Framework.- Liquidity Model.- Liquidity Management.- Liquidity Optimization.- Conclusion.

Leseproben

Chapter 1 Introduction (p. 1-2)

1.1 Motivation

Banks are intermediaries between liquidity supplying depositors and liquidity demanding borrowers.1 Furthermore, they provide contingent liquidity in the form of loan commitments and liquidity backup lines. Importantly, liquidity is a core resource for banks that needs to be actively managed. For that purpose, we will develop a quantitative model of bank liquidity.

Consequently, our model must be stochastic, complete, and will incorporate bank particularities. Here, completeness refers to the fact that the model encompasses product and aggregate as well as short and long-term liquidity. Signi?cantly, an important particularity of banks’ business that our model addresses is con?dence. Incidentally, liquidity modelling is only the starting point for liquidity management, and we therefore discuss modelling, managing and optimizing liquidity. Liquidity does not matter in perfect capital markets2: symmetric information ensures that agents have a perfect knowledge of banks’ asset quality and asset value.

The ability to raise external funds is only limited by the true asset value and not by the value that agents estimate. Moreover, assets are perfectly liquid and can always be sold at their true value. As a consequence, banks are not needed in perfect capital markets. By contrast, the true asset value of banks is unknown to investors in real markets. These investors have to replace the true value with an estimate that could be heavily biased by rumours. Thus, any bank could face funding problems if the bank is exposed to adverse rumours.3 Furthermore, other banks could hoard their liquidity as they face funding dif?culties themselves.

Additionally, liquidity is important for banks since they are the exclusive liquidity channel for central banks. The channel must function effectively to ensure that economy works smoothly. Besides, banks have mutually high liquidity exposures. The failure of one bank can easily encroach on other banks. Finally, liquidity is for banks what commodities are for corporations: an input factor for their (loan) production function. Hence, liquidity is important for banks in general. Institutional changes during the last decade require a readjustment of banks’ liquidity management. Important changes are.

Über Autor(innen)

Dr. Christian Schmaltz completed his doctoral thesis under the supervision of Prof. Dr. Thomas Heidorn at the Frankfurt School of Finance and Management. He works as a consultant for risk management.