Integrated Risk Management of Non-Maturing Accounts: Practical Application and Testing of a Dynamic Replication Model

ISBN-13: 9783658049027 / Angielski / Miękka / 2014 / 116 str.

Jeffry Strasser

Opis

​Customer accounts that neither have a fixed maturity nor a fixed interest rate represent a substantial part of a consumer bank's funding. The modelling for their risk management and pricing is a challenging yet crucial task in today's asset/liability management, with increasing computational power allowing for new approaches. Jeffry Straer outlines an implementation of a state-of-the-art dynamic replication model in detail. A case study with recent data supports the expected superiority of the model. Additionally, it provides tangible recommendations for model specifications derived from practical and mathematical consideration, as well as empirical findings. Practitioners will appreciate the comprehensive programming code attached.

Spis treści

Modelling of risk factors.- Setting up a multistage stochastic program.- Model output and performance analysis.- Full program code for all described steps in open-source statistical programming language R.

O autorze

Jeffry Straßer MA obtained his master´s degree at the University of Applied Sciences bfi Vienna in the programme “Quantitative Asset and Risk Management”.

Blurb

Customer accounts that neither have a fixed maturity nor a fixed interest rate represent a substantial part of a consumer bank’s funding. The modelling for their risk management and pricing is a challenging yet crucial task in today’s asset/liability management, with increasing computational power allowing for new approaches. Jeffry Straßer outlines an implementation of a state-of-the-art dynamic replication model in detail. A case study with recent data supports the expected superiority of the model. Additionally, it provides tangible recommendations for model specifications derived from practical and mathematical consideration, as well as empirical findings. Practitioners will appreciate the comprehensive programming code attached.

 

Contents

• Modelling of risk factors
• Setting up a multistage stochastic program
• Model output and performance analysis
• Full program code for all described steps in open-source statistical programming language R

   

 

 Target Groups

• Researchers and students in the field of bank (risk) management, statistics and business informatics
• Practitioners in bank management, bank risk management, and bank regulation

 

The Author

Jeffry Straßer MA obtained his master´s degree at the University of Applied Sciences bfi Vienna in the programme “Quantitative Asset and Risk Management”.