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Four Types of Money Managers and Their Performance Metrics

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Business Metrics for Data-Driven Companies

Duke University

4.6 (5,268 ratings) | 130K Students Enrolled

Course 1 of 5 in the Excel to MySQL: Analytic Techniques for Business Specialization

In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.

Skills You'll Learn

Data Analysis, Business Analysis, Business Analytics, Business Process

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DG

Aug 20, 2017

This was a great introductory course. I took this up to get a better perspective of business analysis and i can say with surety that it served a lot of purpose. Thanks Coursera and Duke Professor.

YW

Oct 03, 2016

a very interesting course on business metrics, talks about business metrics itself, jobs and companies in this field, also some examples of the application of business metrics like Amazon, Costco.

From the lesson

Going Deeper into Business Metrics

Welcome! This week we’re going to go deeper into the critically-important metrics for web marketing - metrics every type of business needs to understand in order to survive. We’ll dive into the 'vertical' market of financial services - where digital companies are threatening to take away the market from traditional 'brick-and- mortar' companies.By the end of this week, you will be able to: Identify critical business metrics for all companies engaged in web-based marketing; and identify critical business metrics for financial services companies. You’ll find additional website links that expand some of the course materials covered in this week’s video lectures.

Financial Services Metrics - Money Management and Investing13:27

The Equivalence of Different Returns –The Sharpe Ratio8:59

Four Types of Money Managers and Their Performance Metrics14:40

Venture Capital and Private Equity Investors6:27

Taught By

Daniel Egger
Executive in Residence and Director, Center for Quantitative Modeling
Jana Schaich Borg
Assistant Research Professor

Transcript

Different metrics apply to different types of money managers.

Here, we'll classify money managers into four basic groups.

First, index fund managers.

Second, mutual fund managers.

Third, venture capital and private equity investors.

And fourth, hedge fund managers.

Stock indexes are metrics used by investors to track the overall performance

of an entire market rather than the performance of an individual stock.

For example, the S&P 500 index,

lookup symbol ^GSPC, aggregates the stock price performance

of the 500 largest companies in the US ranked by their market capitalization.

We should pause to explain that market capitalization is the current market

price of one share of a companies common stock multiplied by the total

number of shares of stock of that company that potentially could be bought and sold.

For example, a company with a share price of $52 per share.

And 5 million shares that could be traded, would have a market capitalization of

$52 times $5 million or $260 million.

The S&P 500 index is not a simple average of 500 stock prices.

With each stock contributing 1/500th, or .2% to the total.

This would be an equal weighted index.

Instead, the S&P 500 index is a market-capitalization weighted index.

Each company's stock price changes are weighted by how much

their market-capitalization contributes to the total.

For example, because Apple has a current market capitalization

of $666 billion and all 500 companies together

have a market capitalization of $15 trillion,

then Apple stock price changes contribution to the index

is weighted a 666 divided by 15,000 or 4.44% of the total.

Now one very popular type of investment strategy called

passive investing is to buy and hold for the long term

an investment attracts the performance of an index as closely as possible.

To do this for the S&P 500 index, one would buy units in

State Street's SPDR S&P 500 ETF investment trust, lookup symbol SPY.

SPY is a $135 billion exchange traded fund that holds

shares in all 500 index stocks in exactly the proportions they have in the index.

SPY was created in 1993 and is one of the most heavily traded assets in the world.

Index fund managers do not need to pick stocks.

They are managing a passive investment.

Nevertheless, they do have a challenging job.

They are constantly working to rebalance and

maintain the correct ratios of each stock to match a paper index

exactly while at the same time minimizing transaction costs.

Index fund managers are judged on two factors.

How closely their fund performance matches that of their index.

And how low their expense ratio is.

Most index funds track their index extremely closely.

Differences of even one tenth of 1% in a year are unusual.

So the primary focus in evaluating passive managers is on their expense ratio.

The expense ratio is the money spent on operating the fund

divided by the total market value of the fund assets.

Operating costs include marketing, general and administrative expense, but

mostly they're what the fund managers pay themselves.

The expense ratio does not include brokerage fees the fund pays to buy and

sell its assets.

SPY has a current expense ratio of only 0.0945%,

which sounds good until you consider that that is

over $127 million paid out every year.

Two more recently created competitors to the SPY, the iShares S&P 500

Exchange Trade and Fund, symbol IVV, and the Vanguard S&P 500 Exchange Trade and

Fund, symbol VOO, have significantly lowered expense ratios.

0.07% and 0.05% respectively.

In so called efficient markets, such as US publicly traded securities,

a strategy of identifying a subset of stocks in one's universe

that one's research suggests will out perform the market as a whole.

Then buying and holding those stocks, almost never works over the long term.

In fact, according to State Street, which markets SBY,

over the past years, 80% of professional active money managers

who selected their stocks from among the universe of S&P 500 stocks.

And by the way, who are paid much higher fees typically than

the 0.09% paid despised managers, performed worse than SPY.

That's worse than random chance.

If the managers pick their portfolios at random, simply weighing them by relative

market capitalization, and held them, 50% of managers would outperform the index.

Nevertheless, many people still choose to invest their money

with so-called long only mutual fund managers.

People who pick equities from a Universe.

Mutual fund mangers are expected to specialize.

Some of the ways that they specialize are by only buying stocks of a particular

company size, by market cap, large, small, micro, are the main categories.

Or in a particular market sector, such as mining, retail, or information technology.

Or in a particular country or group of countries such as the BRIC,

Brazil, Russian, India, China markets.

The larger pool of 500 or 1,000 or more potential investments

from which a manager selects the 30 or so stocks he or she chooses to hold.

Is known as his or her universe.

The mean return of all the stocks in his or her universe is the relevant index

that becomes the benchmark for evaluating the performance of that manager.

Mutual fund managers are judged primarily on

three measures of how they perform relative to their benchmark.

The first is excess return.

So if the S&P 500 is their benchmark and it's up 8% and

a manager selecting 30 S&P 500 stocks is up 12%,

the manager's excess return over the benchmark is 4%.

One problem with the excess return methodology is that if the S&P 500

is down 20%, a manager with an excess return of 4%

over his benchmark could still be down 16%.

In addition to excess return over their benchmark managers

are expected not to deviate too much from their benchmark.

The standard deviation of their excess returns is known as their tracking error.

And it is considered undesirable to have a large tracking error.

Tracking error is a kind of risk matrix.

It is the standard deviation of the difference between

returns of the manager's portfolio and returns of their benchmark index.

The standard deviation of excess returns.

The third metric which combines excess return with the tracking error is the so

called information ratio.

The information ratio is the excess return divided by the tracking error.

>> We use the example of a market that over four years was up 25% one year,

up to 10% one year, down 4% one year, and down 18% one year.

>> In addition to excess return over the benchmark, managers are expected

not to deviate too much from their benchmark, and we can measure the degree

of deviation by measuring the standard deviation of the excess return.

So let's suppose that this is the market and this is a manager.

Say the manager returns 27% when the market returned 25%.

12%, minus 2% when the market returned minus 4%.

And minus 23% when the market returned minus 18%.

So, our excess returns would be 2%,

2%, 2% and minus 5%.

Okay.

In this case we would take the standard deviation

of the excess returns and this would give us a value

of 3.03% which is known as the tracking error.

Okay, a third metric combines excess returns with the tracking error.

It's the so-called information ratio.

So, if we look at the geometric mean return

of the manager over these four years,

it's an annual return that exceeds the market return by 1.79%.

So we have 1.79% excess return over the four years annualized.

Divided by the tracking error of 3.03%.

And this will give us an information

ratio, or IR of .59.

An alternative approach to evaluating active equity managers.

One that, in my opinion,

makes a great deal of sense, is to look at their Sharpe ratio and in particular,

their Sharpe ratio compared to the Sharpe ratio of their benchmark.

For example.

Suppose that the S&P 500 index returns 12% over

a 5 year period with a volatility of returns of 14%.

We can plot this on our standard chart at x axis equals 14%, y axis equals 12%.

Okay.

Now we want to compare that to a money manager who returned 17% per year.

So, initially it sounds like that manager returned 5% per year more

than the S&P 500, so that sounds good.

However, when we look at that manager's volatility of return,

it turns out that they had a volatility of returns of 25%.

So to plot on our standard chart we would have a position of 25% and 17%.

Now let's suppose that over the time interval that we were

talking about, there was a risk free rate of 2%.

What we would quickly see.

Is that, simply using the passive index investment,

but increasing leverage by borrowing money to buy the index would

have outperformed money managing.

The slope of the line is clearly less.

S&P return 10% more than the risk free rate

of the annual volatility of 14% so

the slope of that line is 10% over 14%

equals .714 and the integers return and

her slope was significantly less.

Their sharp ratio would be 15%.

Divide it by 25%, or .6.

We could have achieved the same 15% excess return,

with a volatility of only 21% by simply buying the passive index fund and

paying for one third of it with borrowed money.

And that would put us somewhere right about here.

In order for an active manager to outperform a passive index fund,

they must maintain a higher Sharpe ratio than the index Sharpe ratio.

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