Using a Robo-advisor to better shape the SAA

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Securing Investment Returns in the Long Run

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University of Geneva

Securing Investment Returns in the Long Run

536 个评分

课程 4（共 5 门，Specialization Investment Management）

In this course, you will learn about the famous dichotomy between active and passive investing, how to appropriately measure and analyze investment performance and what the future trends in the investment management industry are. You will first learn about absolute and relative performance, risk-adjusted returns and how to decompose investment performance. The focus will then shift to the two main categories of investment vehicles, active and passive funds, and what they entail in terms of expected performance. Finally, you will explore the worlds of sustainable finance, neurofinance and fintech, three areas of research that will shape the future of the investment management industry. You will also benefit from the insights of experts from UBS, our corporate partner, on the practical implementation of the various concepts we will develop in this course.

从本节课中

Future Trends

Welcome to the fourth and last module of the course! This module is dedicated to future trends in investment management that are already starting to change how we think about and apply some of the ideas presented in the specialization. We will start with sustainable investing: defining it, examining its value proposition and see how it can be implemented in the context of a widely diversified portfolio. We will then take a quick look at what neurofinance is and how it can help us make better investment decisions. Finally, we will leave you with some insights as to how fintech (i.e. information technology solutions applied to finance) is likely to shape the future of the investment management industry.

Can business analytics (Big Data) improve the value-added of TAA?11:18

Using a Robo-advisor to better shape the SAA6:58

Specialization Outro3:22

与讲师见面

University of Geneva- Tony Berrada
SFI Associate Professor of Finance
Geneva Finance Research Institute
University of Geneva- Ines Chaieb
SFI Associate Professor of Finance
Geneva Finance Research Institute
University of Geneva- Jonas Demaurex
Teaching Assistant
Geneva Finance Research Institute
University of Geneva- Rajna Gibson Brandon
SFI Senior Chaired Professor of Finance and Managing Director of the GFRI
Geneva Finance Research Institute
University of Geneva- Michel Girardin
Lecturer in Macro-Finance - Project Leader for the "Investment Management" specialization
Geneva Finance Research Institute
University of Geneva- Philipp Krueger
SFI Assistant Professor of Finance
Geneva Finance Research Institute
University of Geneva- Kerstin Preuschoff
Associate Professor of Neurofinance and Neuroeconomics
Geneva Finance Research Institute
University of Geneva- Olivier Scaillet
SFI Senior Chaired Professor of Finance and Vice-dean (research) at GSEM
Geneva Finance Research Institute
University of Geneva- Philip Valta
SFI Assistant Professor of Finance
Geneva Finance Research Institute

[MUSIC]

Hello everyone, this is my very last video.

I haven't counted them but probably I've done closed to out 100 for

this whole specialization.

It's been a lot of fun, I must say.

Last video, so I decided to change look [LAUGH] and

be a bit more casual and forget about those striped shirts.

And also, going to talk about the latest game in town, and these are robots.

Robot advisor, we just saw by looking at big data that it can be

helpful in helping you devising a tactical asset allocation.

Robots to do tactical Asset Allocation, I would not feel that confident,

but certainly to do the strategic asset allocation, yes.

Why not?

It's a bit like when you look at these two pictures, the shuttle here,

this is a picture taken from Detroit Airport.

You see the shuttle and it probably drives [LAUGH] the passengers to their

destination without a driver, right so perfectly automated robot, no problem.

Would you feel comfortable knowing that there's no pilot

in this big airplane in the?

Well, it's a bit the same, when you're doing strategic aster location,

the guidelines are pretty strict, straightforward.

It's like the shuttle in the airport, simple.

When you're driving an airplane, you may be subject to some difficult situation,

and I'm not sure the robot would do a perfect job.

So what are the pros of Robo-advisors?

Well certainly, costs, we've talked in this course about cost when active,

considering active or passive funds.

That's certainly something also to consider when you

should allocate your money to a Robo-advisor.

A big pro, a big advantage of the automated Robo-advisors is the fact that

they will take the portfolio rebalancing, they will take care of that for you.

You will not have to do it.

Basically, if you've set that your allocation to risky assets,

equities should be 25%.

And if equity is perform well and that bucket grows to 30%,

the robo will rebalance to 25% automatically, you will not have to do it.

Also, it may be worth considering in some cases, like the US,

you will be subject to taxes on your capital gains, so

the robot here might help in doing some optimal selling.

He will sell the losers to offset the gains you have

made on your winning stocks, so

as to minimize the capital enhance the tax incidents.

Also, it's quite clear that robot, as far as I know,

maybe a wrong and that maybe they also have emotions [LAUGH].

Maybe the guys is devising the robot is also plugging in

some emotional behavior in these robot.

But, we can say, is that a plus?

I don't know.

Probably yes, the answer is yes.

That they are not subject to emotional behavior.

But last but not least, I think we should not forget that robot are perfectly

suited for I would say non-complex pretty standard situation.

And typically, that of devising a strategic asset allocation.

What are the cons?

Well, typically, if the situation is more complex if we have to is like the big

airplane going through a tempest may require here some fine tunings, maybe not.

But perfectly suited for a robot.

Talking about investments, we live now in a more complex world both because

interest rates are low, so there are no more risk free assets.

We have to work with this constraint and

hence its becoming a bit more complex in terms of diversification.

There's also increased regulations; differing from one country to another.

So, here too this makes the situation a bit more

complicated for robot to act perfectly.

Again, here emotions, integration of emotions maybe helpful for

you to better understand the markets.

And we've seen that when we talked about Euro finance this is also a lot

of the latest trends on which we are specializing here at

the University of Geneva.

And sometimes talking about this tax incidents of selling losers,

so as to off set the gains you have made on

your winning stocks may not be optimal.

Why should you sell a stock just for tax purposes?

The robot might not know that, in fact, you are sticking to that position

because you think it's going to bottom out, and out perform soon.

So in conclusion, I would say Robo-advisors are certainly useful

for helping you shape your strategic asset allocation.

This is the sort of highway of your investments but when you have

to deal with tactical asset allocation possibly here big data will help but

it's more complex situation and more difficult.

I would say, robots are different animals, but

no perfect substitutes to perfectly efficient human financial advisers.

[SOUND] Talking about animals, you know I'm quite fond of animals and

the so for this last video, for this concluding video.

I'd like to take you back to where we were during the winter and

this time here it's summer, at last.

And I want to take you back to the same place and

talk about some animals in the world of finance.

So, come with me.

[MUSIC]

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