The book begins with a brief introduction to the current challenges of the private banking industry before identifying the foundations of behavioural finance – decision theory. The book addresses the many psychological traps (behavioural biases) that are commonly observed along a typical decision–making process and in particular, how these biases differ across different cultures, something which is of vital importance for any bank offering private banking services worldwide. The authors then show how to integrate these insights into a tool of highly practical relevance – a risk profiler. The book also covers structured products – and how to evaluate them both from an expected utility theory perspective and from a prospect theory point of view. Moreover, the authors explain how to design structured, tailor–made products for private clients. The dynamics of investing are then explored by demonstrating which investor will rebalance their portfolio during the course of investments and which one will take their profits or increase risks providing a foundation for common investment advice like the age rule. The book concludes with wealth management showing how a typical advisory process should be structured to make the best use of the services the bank can offer, integrating personal asset–liability management, life cycle aspects, a risk profiler, a strategy implementation, and a well–suited documentation.
In particular, readers will learn:
- How to assess the client s risk profile;
- How to find an optimal asset allocation according to client′s risk profile;
- Which investment products are optimal from client′s perspective;
- When it is wise to rebalance the portfolio during the course of investments, and when it is better to take the profits or to increase the risks;
- The foundation of some commonly used rules of thumb and when are they wrong;
- How to adjust the asset allocation over the life cycle
A balance is made throughout the book between written explanations, examples, and case studies, with the use of some mathematics to deepen understanding. With a unique focus on client advisory as opposed to asset pricing, Behavioural Finance for Private Banking provides valuable insights and will enable practitioners to improve service quality at every step along the wealth management process.
1.1 The Private Banking Business.
1.2 Current Challenges in Private Banking.
1.3 Improving Service Quality with Behavioural Finance.
2. DECISION THEORY.
2.2 Mean–Variance Analysis.
2.3 Expected Utility Theory.
2.4 Prospect Theory.
2.5 Prospect Theory and the Optimal Asset Allocation.
2.6 A Critical View on Mean–Variance Theory.
2.7 A Critical View on Expected Utility Axioms.
2.8 Comparison of Expected Utility, Prospect Theory, and Mean Variance Analysis.
3. BEHAVIOURAL BIASES.
3.1 Information Selection Biases.
3.2 Information–Processing Biases.
3.3 Decision Biases.
3.4 Decision Evaluation Biases.
3.5 Biases in Inter–Temporal Decisions.
3.6 Behavioural Biases and Speculative Bubbles.
3.7 Cultural Differences in the Behavioural Biases.
4. RISK PROFILING.
4.1 Dealing with Behavioural Biases.
4.2 The Risk Profiler and its Benefits.
4.3 Designing a Risk Profiler: Some General Considerations.
4.4 Implemented Risk Profilers: Case Study former Bank Leu.
4.5 A Risk Profiler Based on the Mean–Variance Analysis.
4.6 Integrating Behavioural Finance in the Risk Profiler.
4.7 Case Study: Comparing Risk Profiles.
5. PRODUCT DESIGN.
5.1 Case Study Ladder Pop .
5.2 Case Study DAX Sparbuch .
5.3 Optimal Product Design.
6. DYNAMIC ASSET ALLOCATION.
6.1 The Optimal Tactical Asset Allocation.
6.2 The Optimal Strategic Asset Allocation.
7. LIFE CYCLE PLANNING.
7.1 Case Study: Widow Kassel.
7.2 Main Decisions over Time.
7.3 Consumption Smoothing.
7.4 The Life Cycle Hypothesis.
7.5 The Behavioural Life Cycle Hypothesis.
7.6 The Life Cycle Asset Allocation Problem.
7.7 The Life Cycle Asset Allocation of an Expected Utility Maximizer.
7.8 The Life Cycle Asset Allocation of a Behavioural Investor.
7.9 Life Cycle Funds.
7.10 Summary 207.
8. STRUCTURED WEALTH MANAGEMENT PROCESS.
8.1 The Benefits of a Structured Wealth Management Process.
8.2 Problems Implementing a Structured Wealth Management Process.
8.3 Impact of the New Process on Conflicts of Interests.
8.4 Learning by Cycling Through the Process.
8.5 Case Study: Credit Suisse.
8.6 Mental Accounting in the Wealth Management Process.
9. CONCLUSION AND OUTLOOK.
9.1 Recapitulation of the main achievements.
9.2 Outlook of further developments.
List of Notation.
List of Figures.
List of Tables.
Kremena Bachmann, born in Bulgaria in 1976, currently holds a postdoctoral position at the University of Zurich′s Swiss Banking Institute. She received an MS in Finance from the University of St. Gallen (HSG) and a PhD in Finance from the University of Zurich, where she held a research position at the Institute for Empirical Research in Economics. Her research interests are behavioural finance and investment management. Mrs. Bachmann worked on different projects for Credit Suisse Asset Management and Bank Wegelin. Her teaching experience includes lectures on behavioural finance and wealth management at the University of Zurich and the Swiss Training Centre for Investment Professionals (AZEK).