A whole portfolio — what are the odds?
Build a mix of covered names, set a target return, and see what the simulations already published for each name say about the mix: the chance of reaching your target, the chance of losing money instead and roughly how much, and which names carry the gain and which carry the risk.
Same discipline as everywhere else on this site: these are odds read off published studies, not a recommendation of any stock or mix. You choose the names and the weights — the page only does the arithmetic on what we've already published.
build return-first-v16-goodbad
On each row, good case is that name's best-1-in-20 simulated outcome and bad case its worst-1-in-20 — the 95th and 5th percentiles of its own published simulation. The centre of every covered name's range is anchored to the same policy-rate carry by design (see the methodology), so what tells names apart is how wide and how lopsided that range is, not its middle.
"Load a starting mix" picks the five EGX names with the best typical return for the downside risk they carry (median outcome divided by the worst-1-in-20 case) at the chosen horizon, equally weighted — not just the highest headline number. Each name below shows its own good and bad case, so a weak trade-off is visible before you swap anything. Nothing on this page is stored or sent anywhere.
The chance of reaching +25% in 3 months Simulation
—
And the loss side Simulation
The four outcomes, side by side Simulation
Same four buckets as the single-stock odds page — a move of 10% or more is "big" — applied to the whole mix under the one co-movement assumption above. Adds to 100%.
Where the gain would come from — and where the risk sits Simulation
Each name's weight times its own published outcome, in percentage points of the whole portfolio. The gain side adds up exactly to the mix's middle-of-the-road outcome — that's always true, it's just arithmetic on an average. The risk side isn't: summing each name's own bad case assumes every name has its worst day at once, which overstates the mix's real bad case. The true, correlated figure is smaller — see the note under the risk list.
Contribution to the middle outcome
Contribution to the plausible bad case
Build me the safest EGX mix for my target return Simulation
Type the typical (median) outcome you'd like this slice of your portfolio to aim for — the same "Typical outcome" figure the card below reports back — and this finds the least-risky available combination of covered EGX names that gets there, weights included, using the same correlated simulation as everything above. Reaching further up the return scale always costs more risk, never less, and often means holding fewer names — concentrating in just one or two carries more risk than the probabilities below fully capture. EGX names only for now.
This is the same kind of number as "Target return" above, just used differently here: instead of asking your chance of reaching it with a mix you built, this searches for the least-risky mix that reaches it for you. Type 10 to mean "I'd like this slice to typically land around +10%."
This is an optimisation over published simulations — arithmetic, not a recommendation. It searches for the least risky available mix that still reaches your stated target; if no covered combination gets there, it falls back to the single highest-return mix available and says so plainly in the note above. Reaching for more return only ever costs more risk, and often means holding fewer names — the note above will flag it when the mix shown is concentrated.
What this can't tell you
How much these names actually move together day to day is the biggest unknown on this page. Each study publishes its own stock's distribution, but not how the stocks move jointly, so some assumption is unavoidable. Rather than asking you to guess, this page uses one stated assumption: pairs on the same exchange are modelled at about 0.55 correlation, pairs on different exchanges at about 0.25 — both on the high side of typically measured equity correlations, because EGX and Gulf names share FX, rate-cycle and foreign-flow exposure. That is a modelling choice, not a live measurement and not a view on any stock — it only shapes how the odds of whatever mix you build combine, the same role a covariance matrix plays in any risk model.
Mixing currencies adds a risk these numbers don't carry at all: each name's odds are in its own currency, so a mix of EGX and Gulf names also bets on the exchange rates between them. Dates are the other thing a mix quietly blurs: each name's odds are struck from that name's own last close, on its own day, and run to its own end date — all of which are printed on its row above and summarised under the headline chance. The arithmetic combines them as if they shared one window, because published data supports nothing else; where the anchors are far apart, the page says so rather than averaging the gap away. These are last closes, never live prices. And a target is just a number you typed — setting 25% doesn't make 25% likely, and no mix of covered names has a typical outcome anywhere near it over these horizons; the page will tell you when your target lives in the tail.
Educational tooling and personal analytical opinion — not investment advice, not a recommendation, and not an invitation to build any particular portfolio. Full disclaimer.