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Modigliani risk-adjusted performance

Modigliani risk-adjusted performance is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Modigliani risk-adjusted performance rather than just read about it. In short: Modigliani risk-adjusted performance (also known as M2, M2, Modigliani–Modigliani measure or RAP) is a measure of the risk-adjusted returns of some investment portfolio. It measures the returns of the portfolio, adjusted for the risk of the portfolio relative to that of some benchmark (e.g., the market).

Key takeaways

  • Modigliani risk-adjusted performance belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Modigliani risk-adjusted performance to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Modigliani risk-adjusted performance from memory before moving on to harder problems.

Reference excerpt

Modigliani risk-adjusted performance (also known as M2, M2, Modigliani–Modigliani measure or RAP) is a measure of the risk-adjusted returns of some investment portfolio. It measures the returns of the portfolio, adjusted for the risk of the portfolio relative to that of some benchmark (e.g., the market). It can be interpreted as the difference between the scaled excess return of the portfolio and that of the market, where the scaled portfolio has the same volatility as the market. It is derived from the widely used Sharpe ratio, but it has the significant advantage of being in units of percent return (as opposed to the Sharpe ratio – an abstract, dimensionless ratio of limited utility to most investors), which makes it dramatically more intuitive to interpret.

History In 1966, William F. Sharpe developed what is now known as the Sharpe ratio. Sharpe originally called it the "reward-to-variability" ratio before it began being called the Sharpe ratio by later academics and financial operators. Sharpe slightly refined the idea in 1994. In 1997, Nobel-prize winner Franco Modigliani and his granddaughter, Leah Modigliani, developed what is now called the Modigliani risk-adjusted performance measure. They originally called it "RAP" (risk-adjusted performance). They also defined a related statistic, "RAPA" (presumably, an abbreviation of "risk-adjusted performance alpha"), which was defined as RAP minus the risk-free rate (i.e., it only involved the risk-adjusted return above the risk-free rate). Thus, RAPA was effectively the risk-adjusted excess return. The RAP measure has since become more commonly known as "M2" (because it was developed by the two Modiglianis), but also as the "Modigliani–Modigliani measure" and "M2", for the same reason.

Definition Modigliani risk-adjusted return is defined as follows: Let D t {\displaystyle D_{t}} be the excess return of the portfolio (i.e., above the risk-free rate) for some time period t {\displaystyle t} :

D t ≡ R P t − R F t {\displaystyle D_{t}\equiv R_{P_{t}}-R_{F_{t}}}

where R P t {\displaystyle R_{P_{t}}} is the portfolio return for time period t {\displaystyle t} and R F t {\displaystyle R_{F_{t}}} is the risk-free rate for time period t {\displaystyle t} . Then the Sharpe ratio S {\displaystyle S} is

S ≡ D ¯ σ D {\displaystyle S\equiv {\frac {\overline {D}}{\sigma _{D}}}}

where D ¯ {\displaystyle {\overline {D}}} is the average of all excess returns over some period and σ D {\displaystyle \sigma _{D}} is the standard deviation of those excess returns. And finally:

M 2 ≡ S × σ B + R F ¯ {\displaystyle M^{2}\equiv S\times \sigma _{B}+{\overline {R_{F}}}}

where S {\displaystyle S} is the Sharpe ratio, σ B {\displaystyle \sigma _{B}} is the standard deviation of the excess returns for some benchmark portfolio (often, the market) against which the portfolio in question is being compared, and R F ¯ {\displaystyle {\overline {R_{F}}}} is the average risk-free rate for the period in question. For clarity, one can substitute in for S {\displaystyle S} and rearrange:

M 2 ≡ D ¯ × σ B σ D + R F ¯ . {\displaystyle M^{2}\equiv {\overline {D}}\times {\frac {\sigma _{B}}{\sigma _{D}}}+{\overline {R_{F}}}.}

The original paper also defined a statistic called "RAPA" (presumably, an abbreviation of "risk-adjusted performance alpha"). Consistent with the more common terminology of M 2 {\displaystyle M^{2}} , this would be

M 2 α ≡ S × σ B {\displaystyle M^{2}\alpha \equiv S\times \sigma _{B}}

or equivalently,

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Modigliani risk-adjusted performance

Start with the simplest possible case. Write down what Modigliani risk-adjusted performance claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Modigliani risk-adjusted performance before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Modigliani risk-adjusted performance ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Modigliani risk-adjusted performance

In research
Modigliani risk-adjusted performance appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Modigliani risk-adjusted performance in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Modigliani risk-adjusted performance is common in secondary-school and first-year university syllabi. It links to neighbouring topics Financial markets, Investment indicators, Mathematical finance, so understanding it makes those chapters shorter.
In everyday life
Look for Modigliani risk-adjusted performance outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Modigliani risk-adjusted performance in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Modigliani risk-adjusted performance means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Modigliani risk-adjusted performance out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Modigliani risk-adjusted performance in simple terms?

Modigliani risk-adjusted performance (also known as M2, M2, Modigliani–Modigliani measure or RAP) is a measure of the risk-adjusted returns of some investment portfolio. It measures the returns of the portfolio, adjusted for the risk of the portfolio relative to that of some benchmark (e.g., the ma…

Why does Modigliani risk-adjusted performance matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Modigliani risk-adjusted performance?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Modigliani risk-adjusted performance.

Tags

  • Financial markets
  • Investment indicators
  • Mathematical finance

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