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Summary digital household

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  • Contemporary Issues in Finance
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  • Katholieke Universiteit Leuven (KU Leuven)

Master the "Digital Household" Course with Ease! This summary is your ultimate study tool, covering all key lecture content and linked with extra insights from the professor’s materials. Difficult English terms are translated into Dutch or simplified with synonyms, ensuring clarity and underst...

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Información del documento

  • 31 de diciembre de 2024
  • 119
  • 2024/2025
  • Resumen

Temas

  • positioning of the course
  • cases
  • conclusion
  • people profiling investors
  • products positioning investment products
  • portfolio contructing investment portfolios

Escuela, estudio y materia

  • Katholieke Universiteit Leuven (KU Leuven)
  • Handelswetenschappen
  • Contemporary Issues in Finance
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Digital Household

Inhoud
Positioning of the course ............................................................................................................ 4
Household finance: Campbell (2006) ..................................................................................... 4
Policy relevance of “underusage of annuities” .................................................................. 4
Household finance, Cambell (2006) ....................................................................................... 5
Digital conversion ................................................................................................................... 6
3 recent analyses ................................................................................................................ 9
Use case → behavioural design ........................................................................................... 19
Behavioural design for digital financial services .............................................................. 20
In summary ....................................................................................................................... 22
Relevance, related to regulatory and supervisory initiatives ............................................... 22
More recent → choice architecture ................................................................................. 22
More in general ................................................................................................................ 23
Europe’s retail investment strategy .................................................................................. 23
Regulatory and supervisory initiatives ............................................................................. 24
Positioning of Standard Finance and Behavioural Finance .................................................. 26
Standard finance .............................................................................................................. 26
Behavioural Finance ......................................................................................................... 26
Behavioural finance 2.0 .................................................................................................... 26
People: profiling investors ........................................................................................................ 27
Expected Value (Sint-Petersburg paradox) ....................................................................... 27
Expected utility (rules of rationality) ................................................................................ 28
Prospect utility (reference point, loss aversion, probability weighting) .......................... 36
Use Case: investor risk profiling (exam!) ......................................................................... 40
Key take-aways ................................................................................................................. 50
Products: positioning investment products ............................................................................. 51
Return distributions.............................................................................................................. 51
Return distributions: Simulations ..................................................................................... 52
Return distributions: time-series view ............................................................................. 53
Return distributions: cross-sectional view ....................................................................... 53

1

, Mean and variance (random walks) ................................................................................. 54
Upside potential and downside risk (skewness has a price) ............................................ 61
Understanding the various aspects of a product offer ......................................................... 69
Product classification........................................................................................................ 69
Product classifications: special cases ............................................................................... 70
Product classification: example of how to complete the offer ........................................ 71
Applied to performance reporting ....................................................................................... 73
Performance reporting ..................................................................................................... 73
Use case: structured products .............................................................................................. 75
Overview of the (retail) investment landscape ................................................................ 75
Base case: term deposit ................................................................................................... 76
Variation: structured fund ................................................................................................ 77
Defaultable bond .............................................................................................................. 77
Structured bond ............................................................................................................... 78
The fundamental law of structured products .................................................................. 78
Structured funds versus structured bonds ....................................................................... 79
Fund versus bond: ............................................................................................................ 80
Fees in structured products .............................................................................................. 80
Make your own structured product ................................................................................. 82
How the price of a call and put are linked........................................................................ 84
Make your own structured product: input ....................................................................... 85
Key understanding ................................................................................................................ 96
Ket take-aways ...................................................................................................................... 96
Portfolio: constructing investment portfolios .......................................................................... 97
The power of diversification ................................................................................................. 97
How diversification looks like ............................................................................................... 98
The power of diversification: two assets .......................................................................... 99
The power of diversification: three assets ....................................................................... 99
Efficient combinations ........................................................................................................ 100
Classic approach: finding the optimal efficient allocation ................................................. 101
Classic approach: alternative optimization objective ......................................................... 102
Equivalence..................................................................................................................... 103

2

, Goal based wealth management ....................................................................................... 104
Behavioural portfolio theory (adaptivity, probability matching)........................................ 104
A crucial implicit assumption ......................................................................................... 104
Probability matching explained ...................................................................................... 109
In summary ..................................................................................................................... 113
Adaptivity 3 ? .................................................................................................................. 113
Behavioural portfolio theory (finance for normal people) ................................................. 114
Behavioural finance, Statman (2019)............................................................................. 114
Use case: Comfort zone investing (exam) .......................................................................... 114
“Comfort zone investing” ............................................................................................... 115
Explore – experiment – experience ................................................................................ 116
Diversification revisited: next, let’s play ......................................................................... 116
Key understanding .......................................................................................................... 118
Key take-aways ............................................................................................................... 118
Conclusion .............................................................................................................................. 119




3

,Positioning of the course
Household finance: Campbell (2006)
• By analogy to corporate finance, household finance asks how households use financial
instruments to attain their objectives.
• Research, as always, can be positive (« understand what people do ») or normative
• (« describe what people should do »). In many cases however, both do not coïncide:
people don’t behave as they « should », or alternatively models can not explain why
people behave the way they do.
• Known examples in household finance of such « mistakes » are:
o Under participation in financial markets – households do not invest enough
o Under diversification in portfolios – when they invest, households hold too
few assets
o Underusage of annuities – households prefer lump sum pensions over
monthly « for life »

Policy relevance of “underusage of annuities”
• A collaboration of Belgian universities performed in 2022 a « pension test »
addressing the general public, e.g. via popular news sites, amongst others in
collaboration with the Ministry of Pensions.
• One of the key features of the test is to ask for the preference
• between lump sum pensions or annuities, or a combination.
• The simplified scenario goes as follows:
o The user is asked to share general info on financial wealth
o From this info the test motivates a level of legal pension and assumes an
amount of corporate pension (« groepsverzekering »)
o The user is asked how the corporate pension should be paid out: as a lump
sum or as monthly payment on top of the legal pension (for example to
maintain a desired living standard)
• [ignore the numbers]
• On this screen the user has to specify how the
corporate pension has to be split into a lump
sum and an annuity.
• Note how the test informs on the difference in
« risk score » between lump sum and
annuities. Annuities receive a higher risk score
because they are paid « for life » and hence
avoid the risk of outliving your financial wealth.




4

,Household finance, Cambell (2006)
• What should we do to get rid of such « mistakes »? What is the welfare cost of such
mistakes? One way is to build models that improve our understanding of actual
behavior. This, however, « explains » the initial differences but does this mean they
disappeared? There might still be a welfare cost attached to the actual behavior.
• John Campbell concludes with an interesting reflection, which touches the core of
this course. He mentions:
o Financial education – « teach people how to do better »
o Financial engineering – « change context, improve products so people do
better » → best way
• If household finance can achieve a good understanding of the sources of investment
mistakes, it may be possible for the field to contribute ideas to limit the costs of these
mistakes.
o Regulation and supervision – we give ample examples on this at the end of
part 1
o Product and context design – we dive deeper into this in parts 2, 3 and 4
o - …
• Keynes (1932) wrote that he looked forward to a distant future when economists
would be “thought of as humble, competent people, on a level with dentists.” Today,
dentists spend much of their time delivering advice and easy-to-use products that
promote oral hygiene; economists for their part can deliver, or at least design, advice
and innovations that promote financial hygiene.
• The possibility that household finance may be able to improve welfare is an inspiring
one.
→ This is what we do in this course: first improve our understanding of human
behaviour, next use this knowledge to build applications that improve financial
wellbeing in a digital world.
• “Financial well-being underlies well-being in all other domains of well-being (family &
friends, work & activities, mental & physical health), and well-being in each domain
is impossible without financial well-being.” (Meir Statman, 2019, founding father of
behavioural finance in Journal of Financial Planning).




5

,Digital conversion
• “Conversion” means that an interested client effectively executes a transaction.
• Take the situation where a client visits a branch, talks to the advisor while drinking a
coffee. In such setting there is a very high chance the client will execute a transaction.
Indeed, the client started off by making the effort and taking the time to come to the
branch.
• In a digital context the average conversion is much, much lower. And surely if you
simply automate the process; if you leave out the human encouragement of the
advisor but put nothing in place to compensate.
• How come? And how can we do better?




• Take the situation where a client visits a branch, talks to the advisor while drinking a
coffee. In such setting there is a very high chance the client will execute a
transaction. Indeed, the client started off by making the effort and taking the time to
come to the branch.




• In a digital context the average conversion is much, much lower. And surely if you
simply automate the process; if you leave out the human encouragement of the
advisor but put nothing in place to compensate




6

, see more on slides

• Investing is an emotional process. Managing these emotions is probably the greatest
open challenge of financial technology
• by constructing algorithms that accurately capture human behaviour, we can build
countermeasures to protect us from ourselves




7

, • Since the 50s of the previous century the wealth management business is organized
around human advisors servicing their clients. The underlying framework of such
model is very much risk-focussed and hinges on the assumption of rationality.
Investors are considered cold hearted machines.
• Today, investing is still the least digitized financial service. We do see technological
innovation leading to a proliferation of trading platforms, or gamified investment
propositions.




• Yet, the ambition is rather to create a long term investor relationship through
automated, digitized advisory services that address the investor as a human being.
• This is not an easy task.
• This course will take a deep dive into “applied behavioural finance” in the context of
investing, particularly in a digitized setting.

→ European average of people investing = 10%




8

,3 recent analyses
1. How technology has the potential to increase financial welfare.

« human-robot interactions in investment decisions»

2. How technology has to potential to boost financial inclusion.

« invest your spare change »

3. How technology may also challenge financial welfare.

« smart(phone) investing»

→ Niet in detail kennen!

How technology has the potential to increase financial welfare.
Bianchi & Brière (2024)




• The setup is original
o They investigate the introduction of a robo-advising service by a major French
asset manager in a large set of Employee Saving Plans.
o The robo starts by eliciting information on the client’s characteristics, builds
the client’s profile, and proposes a portfolio allocation.
o If the client accepts the proposal, the robo implements the allocation. Over
time, the robo sends email alerts if the current portfolio allocation ends up
being too far from the target allocation. These alerts suggest to connect to
the platform and to rebalance the portfolio towards the target, while the
ultimate decision has to be taken directly by the investor.
o The key distinctive feature of this service is that it is truly a robo-advisor which
gives advice to the investors, both at the time of the subscription and over
time, while leaving investors free to follow or to ignore the advice.




9

, • Questions addressed
o How much would investors be willing to rely on automated
recommendations? [there exists such a thing as “algorithm aversion”, and
focussing too much on the cost reduction of automation might even trigger
this]
o Can the robo-service be used to complement, rather than to replace,
investors’ reasoning and actions? [again, looking at technology as improving
welfare rather than simply reducing costs]
• Findings in brief
o A recurrent theme is that the human-robo interactions are key to understand
the ultimate effects of the robo on financial outcomes. A significant part of
the effects are driven by how investors change their behaviours over time,
suggesting that the robo can be used to improve investors’ decisions, while
letting them being the ultimate decision maker.
o Another interesting feature of the setting is that a large proportion of the
investors have small portfolios and little experience in the stock market. This
sample is particularly useful to explore whether robo-advisors can promote
financial inclusion
• Key results
o The robo attracts investors who are rather heterogeneous in terms of age,
education and wealth
o Investors who take up the robo increase their attention to the portfolio
o Investors increase the amount they invest in the saving plans, as well as their
risk exposure
o The robo-alerts are effective in increasing investor’s attention and rebalancing
o Investors with the robo experience a substantial increase in risk-adjusted
returns, mainly due to rebalancing
o The increased equity exposure and returns are larger for investors with lower
financial capabilities




10

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