Behavioral Finance for Private Banking

From the Art of Advice to the Science of Advice

Kremena K. Bachmann, Enrico G. De Giorgi, Thorsten Hens

• Publisher: Wiley
• Year: 2018
• ISBN:
  9781119453710
• Edition: 2
• Topic: Economia
• Subtopic: Settore bancario

An essential framework for wealth management using behavioral finance

Behavioral Finance for Private Banking provides a complete framework for wealth management tailored to the unique needs of each client. Merging behavioral finance with private banking, this framework helps you gain a greater understanding of your client's wants, needs, and perspectives to streamline the decision making process. Beginning with the theoretical foundations of investment decision making and behavioral biases, the discussion delves into cultural differences in global business and asset allocation over the life cycle of the investment to help you construct a wealth management strategy catered to each individual's needs. This new second edition has been updated to include coverage of fintech and neurofinance, an extension of behavioral finance that is beginning to gain traction in the private banking space.

Working closely with clients entails deep interpersonal give and take. To be successful, private banking professionals must be as well-versed in behavioral psychology as they are in finance; this intersection is the heart of behavioral finance, and this book provides essential knowledge that can help you better serve your clients' needs.

• Understand the internal dialogue at work when investment decisions are made
• Overcome the most common behavioral biases—and watch for your own
• Learn how fintech and neurofinance impact all aspects of private banking
• Set up a structured wealth management process that places the client's needs front and center

Private banking clients demand more than just financial expertise. They want an advisor who truly understands their needs, and can develop and execute the kind of strategy that will help them achieve their goals. Behavioral Finance for Private Banking provides a complete framework alongside insightful discussion to help you become the solution your clients seek.

CHAPTER 1
Introduction

Behavioral finance is an interdisciplinary research area that combines insights from psychology with finance to better understand investors' behavior and asset prices. It has managed to bridge the gap between theory and practice. Moreover, the psychological research that behavioral finance is based on recently got a foundation in biological differences found in the brain.

Traditional finance has focused on the ideal scenario of thoroughly rational investors in efficient markets. According to this standard paradigm in finance, individuals rationally search for information and know all available actions that serve their preferences. The latter are stable over time and robust to the occurrence of unanticipated events. As a result, rational investors searching for superior returns detect and eliminate any predictability in the asset prices—the market is efficient. According to traditional finance, the market remains efficient even if some investors behave irrationally. Indeed, rational investors will detect any mispricing generated by irrational investors and exploit it with the use of arbitrage strategies, which are assumed to be unlimited.¹ Consequently, any mispricing will very quickly be corrected, irrational investors will be driven out of the market, and the market will again quickly become efficient. A statistical consequence of prices being unpredictable is that returns are (log)‐normally distributed—which is the content of the central limit theorem—a cornerstone of statistics. Consequently, optimal decisions can be taken based on the two parameters of a normal distribution: the mean and the variance. Thus, the mean‐variance optimization and the efficient markets hypothesis are logical consequences of the rationality assumption.

In practice, however, we observe that even professional investors behave irrationally. Moreover, there is empirical evidence that the use of arbitrage strategies to exploit observed mispricing is limited (e.g., implementing an arbitrage strategy could be expensive and typically not at zero risk). The consequence of irrational investors and limited arbitrage is inefficient markets. As we will discuss in detail, investors are not always able to make rational decisions so that market prices show anomalies. For example, investors tend to adopt the behavior of other investors, and this herding behavior causes short‐term predictability that leads ultimately to market crashes. Consequently, asset returns are no longer normally distributed. For example, they have fat tails (i.e., too many very bad returns)—which Taleb (2007) called black swans. Moreover, in inefficient markets, the mean‐variance optimization is no longer rational. Thus, ignoring the insights from behavioral finance can be costly for investors adhering to traditional finance.

Behavioral finance emerged when Nobel laureate Daniel Kahneman and his colleague Amos Tversky conducted psychological research to question the assumptions of rationality—a cornerstone of the classical decision theory. Kahneman & Tversky (1979) developed a new theory, which they called prospect theory. Prospect theory has two phases: an editing phase and an evaluation phase. In the first phase, Kahneman and Tversky show how choice alternatives are mentally coded and transformed to be evaluated in the second phase. The editing phase has developed into a rich knowledge of behavioral biases—the topic of the next section. In the evaluation phase, Kahneman and Tversky develop a new decision model, which is the main content of our section on decision theory. The knowledge of behavioral biases is very valuable for a better understanding of clients in wealth management. Prospect theory also offers a risk measure that is consistent with the client's experience. With this measure one can construct asset allocations that better suit the clients than the asset allocations based on the volatility used in traditional finance. Prospect theory states that investors dislike losses more than volatility. In fact, investors react more to losses than they react to gains. Unlike volatility, the psychological risk measure is not the same for all investors, but is a characteristic of the individual. For this reason and others, the advantages of having a quality risk profiling procedure are numerous.

In this book, we apply these insights from behavioral finance to truly identify the client's situation from a holistic standpoint. With discoveries in the way people deal with information and respond to it in investment risk taking, it is reasonable to say that behavioral finance gives more attention to the investor's behavior. A more realistic investor, as described in behavioral finance, has a different perception and a different understanding of risk than the theoretical investor in the traditional decision theory. Consequently, this investor will need to invest differently than the theoretical investor in the traditional decision theory.

The book combines new research results with practical applications. It draws on the rich research body of behavioral finance and on profound experience in the practice of wealth management. The book starts with the behavioral biases—the mistakes that people make when dealing with information and making financial decisions. The chapter describes the biases, discusses their implications for financial decisions, and suggests strategies with a proven success in moderating the biases. The following four chapters discuss the cultural dimensions of the biases and their biological foundation as well as their moderation and suggest how advisors could proceed in assessing the biases of their clients.

Thereafter, we explain decision theory (rational and behavioral) as a foundation of finance and show how it can be used in the construction of clients' portfolios and for the design of structured products. The question of how optimal portfolios should be adjusted over time is discussed in the following two chapters. The last chapters show how the new insights that behavioral finance has generated can be applied to client advisory, to designing behaviorally founded risk profiles, and to structuring the wealth management process. Thus, our books give a scientific foundation to financial advice given in private banking, which in practice is seen more as an art than a science. We believe that practitioners find some useful foundation for their work and that the transition from the art of advice to the science of advice is not disruptive but smooth.

This book is the second edition of the book Behavioral Finance for Private Banking that was published in the middle of the financial crisis. Many banks and financial advisors used the existing body of knowledge to improve their products and advisory services. A tool that we have developed demonstrates how this can be done.² In addition, this book benefits from insights of new areas of research such as cultural finance, neurofinance, and fintech. Finally, it compares the insights behavioral finance has gained with the new regulatory requirements in Europe (MiFID II) and in Switzerland (FIDLEG).

We are grateful to Mei Wang and Marc Oliver Rieger for their collaboration in the assessment of the cultural dimensions of investors' behavior. Moreover, this work greatly benefited from BhFS Behavioral Finance Solutions, a spinoff firm of the University of Zurich and the University of St. Gallen, which allowed us to present their tools. Last but not least we are grateful to the Wiley team and to Marie Hardelauf for their patience and help in editing our book.

NOTES

1 An arbitrage strategy is a strategy that generates positive returns at no risk. The assumption that arbitrage is unlimited means that arbitrage strategies can be implemented in the real‐world and their costs is low. 2 Access to a demo version of the tool can be requested from [email protected].

CHAPTER 2
Behavioral Biases

Behavioral finance research is driven by observations suggesting that individuals' decisions can be irrational and different from what previous theories assume. In this chapter, we will see that individuals' decisions can be systematically wrong because people's decisions are driven by emotions or misunderstandings or because people use inappropriate rules of thumb, also called heuristics, to handle information and make decisions. Certainly, financial markets are very complex so that optimization can lead to fragile results and good heuristics are preferable.¹ But what is typically observed is that people apply successful heuristics from other domains without properly assessing their effect in the investment domain. One example for the latter is adaptive learning, which is very successful in many day‐to‐day situations like choosing food: One tries out a new wine. If one likes it, one buys it again. However, in finance it leads to buying assets when they are expensive and selling them when they are cheap, as the roller coaster in Figure 2.01 illustrates.

FIGURE 2.01 Market dynamics and decision behavior of a typical investor

To more deeply understand why we may observe such behavior, we consider a typical decision‐making process and discuss how each stage of the process can be biased. First, decision makers select the information that appears to be relevant for their decisions. Then, they process the selected information to form beliefs and to compare alternatives. After deciding, individuals receive new information as a feedback. This feedback influences, in return, the way the decision makers search for more data, that is, the loop is closed.

The chapter provides evidence that certain mistakes can occur in each of these steps. It discusses the relevance of these mistakes for investors and suggests strategies to avoid the mistakes.

2.1 INFORMATION SELECTION BIASES

When confronted with information, individuals need to judge how relevant it is for the task they need to handle. Thereby individuals seem to consider only particular information while disregarding other that might be relevant as well. For investment decisions, such information filtering can be dang...

Table of contents

• Cover
• Table of Contents
• CHAPTER 1: Introduction
• CHAPTER 2: Behavioral Biases
• CHAPTER 3: Cultural Differences in Investors' Behavior
• CHAPTER 4: Neurological Foundations and Biases' Moderation
• CHAPTER 5: Diagnostic Tests for Investment Personality
• CHAPTER 6: Decision Theory
• CHAPTER 7: Product Design
• CHAPTER 8: Dynamic Asset Allocation
• CHAPTER 9: Life‐Cycle Planning
• CHAPTER 10: Risk Profiling
• CHAPTER 11: Structured Wealth Management Process
• CHAPTER 12: Fintech
• CHAPTER 13: Case Studies
• CHAPTER 14: Conclusions
• CHAPTER 15: Appendix: Mathematical Arguments
• References
• Index
• End User License Agreement