Question 1

What is the mean absolute deviation?

Accepted Answer

The mean absolute deviation is the average distance between each day's portfolio return and the portfolio's average return over the window. $$ 	ext{MAD} = \frac{1}{{T}} \sum_{t=1}^{T} \left| {r_{p,t}} - {\bar{r}_p} ight| $$ where: the number of days in the calculation window the portfolio's return on day t the portfolio's average daily return In words: how far, on a typical day, the portfolio lands from where it usually lands — counting a day twice as far away as twice as bad, not four times as bad.

Question 2

How does Fincanva handle it?

Accepted Answer

The method picker labels it "Min MAD" and describes it as "Reduces the average deviation of returns: one unusual day weighs little". Min MAD is offered at both levels: across the instruments of a strategy, and across the strategies of a Combined. It has no settings of its own. It reads the calculation window (In-sample, 12 months by default) and works on the daily returns themselves, so it does not read the Covariance matrix choice. The picker marks it "slow to compute": each rebalance solves an optimisation over every day of the window.

Question 3

When does Min MAD differ from minimising variance?

Accepted Answer

When returns have outliers. If returns were normally distributed, minimising MAD and minimising variance would lead to the same weights; the two part ways when some days are far more extreme than the rest. So a large gap between Min MAD's weights and the Min volatility weights of MPT on the same instruments is itself a sign that their history has fat tails.

What Min MAD does not offer is an efficient-frontier picture or a target to choose: it has one objective and no settings.

Question 4

Which plan includes Min MAD?

Accepted Answer

It depends on your plan, at each level where the method is offered.

Inside a strategy

Included from Ultimate upwards. See what each plan includes.

Inside a Combined

Included from Ultimate upwards. See what each plan includes.

Question 5

What does it look like in practice?

Accepted Answer

A window holds 250 days on which an instrument moves 1% away from its average, and one day on which a data glitch or a one-off event puts it 20% away.

In variance, each ordinary day adds 0.01² = 0.0001 and the one extreme day adds 0.20² = 0.04 — as much as 400 ordinary days. That single day outweighs the rest of the window put together.
In MAD, each ordinary day adds 0.01 and the extreme day adds 0.20 — as much as 20 ordinary days. It counts, but it does not decide.

An optimiser minimising variance would reorganise the whole portfolio around that one day; Min MAD treats it as one bad day among many.