Risk as volatility?

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From the course by University of Geneva

Portfolio and Risk Management

724 ratings

University of Geneva

Portfolio and Risk Management

724 ratings

Course 3 of 5 in the Specialization Investment Management

In this course, you will gain an understanding of the theory underlying optimal portfolio construction, the different ways portfolios are actually built in practice and how to measure and manage the risk of such portfolios. You will start by studying how imperfect correlation between assets leads to diversified and optimal portfolios as well as the consequences in terms of asset pricing. Then, you will learn how to shape an investor's profile and build an adequate portfolio by combining strategic and tactical asset allocations. Finally, you will have a more in-depth look at risk: its different facets and the appropriate tools and techniques to measure it, manage it and hedge it. Key speakers from UBS, our corporate partner, will regularly add a practical perspective on these different topics as you progress through the course.

From the lesson

Risk Management

This fourth and final week is dedicated to risk. We will start by looking in more depth at different sources of risk such as illiquidity and currency risk but also at the different tools available to investors to perform risk management. But how should we measure risk? We will see that it may be valuable to go a step beyond standard deviation, the risk measure we used so far, and look at the Value-at-Risk and Expected Shortfall which focus on potential large losses. Finally, we will use the financial instruments at our disposal to hedge market and currency risk.

Defining forwards and options - Forwards10:08

Defining forwards and options - Options11:44

Risk as volatility?4:21

What about illiquidity? - UBS guest speaker2:56

Currency risk - Return7:35

Currency risk - Risk6:11

Meet the Instructors

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

[MUSIC]

Hi, I'm Olivier, so I will talk today about risk as volatility.

So we will mainly concentrate on two questions.

So the first question is are you sure that the vacuums or

the volatility is always a good measure of risk?

And the second question that we will address is are you sure that profit and

low distribution, so PNL distribution are always symmetric?

Remember more input for

your theory put forward by the Nobel Prize winner Harry Markowitz.

When you want to invest in financial assets,

you should do a tradeoff between risk and award.

And how do you measure risk?

You measure risk using the volatility or the variance,

which is the square of the volatility.

So this is perfectly correct to use the variance as a measure of risk.

But when you do that you assume implicitly that the return

distribution or the profit distribution or the loss distribution are symmetric.

So the possibility of getting a positive return or

the possibility to get a negative return are roughly the same.

So this assumption is indeed correct if you look at investment in standard assets.

Like for example, when you invest in the portfolio like the standard in pools.

Indeed propriety to have a positive return on the Standard pools.

And the propriety to have a negative return on the standard and

pools is roughly the same.

But now if you look at more complex asset like option and you want to invest

this option, the assumption of symmetry is not really collect.

So if I remember what I talked about in basic concept in finance,

when you look at the histogram, the histogram, so

the distribution of the return, can be symmetric or asymmetric.

And when we have an asymmetry we speak about stillness.

When you look at investment in option,

typically what you will have is asymmetric distribution.

So, for example, when you invest in a course or

you buy in a course what do you do?

You pay the premium today, and in the future you expect to have an upward

movement in the stock so that you can benefit from a limited potential gain.

So here, clearly, you have an asymmetry in the distribution because the loss

are kept to the premium that you pay, and the gain, in fact, can be unlimited.

If you look at the reverse position, so if I sell a call, so

in that case what I will do is I will cash the premium.

And so my upside potential is limited to the premium that I receive.

But I might have an unlimited downside and an unlimited loss.

So in that case clearly the assumption of a symmetry distribution is not correct.

Because the priority to get an up movement and

the priority to get a down movement are not the same.

So what are the learning outcomes of the session?

So we have two, in fact, three learning outcomes.

The first learning outcome is that variance is indeed a good risk measure,

but only if you look at symmetric distribution.

The second learning outcome that we have,

is that be careful in which asset you invest.

Because the P&L distribution or the profit and loss distribution can be asymmetric.

This is a case for example, in if you invest in options,

that it will also be the case for example.

If you invest in corporate bonds where you can have a default of the company and

if you have a default of the company, obviously the profit and

loss distribution will be asymmetric.

So the third learning outcome is that when you look at asymmetric profit and

losses distributions, you should pay particularly attention to

negative outcomes, or very large extreme negative returns.

So in the next session about the value at risk and the expected shortfall,

we'll see that due time of this measure are particularly suited to

that type of asymmetry distribution when you want to have a good measure of risk.

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