Risk — all paths

The whole book, run forward across thousands of simulated paths, read at one horizon. It answers where could this end up — the range of outcomes, how often they are profitable, and whether anything breaks on the way.

The Strategy Analyzer: spot, drift, IV shift and volatility sliders above a row of figures — breakeven, max profit, max loss and probability of profit — with a bar chart splitting the scenario result by greek. — Move spot, drift, implied vol or the clock with the sliders, and everything below follows — what the contract is worth, where it breaks even, and the most and least it can make. Further down the panel the same result is split by greek, so you can see *which* exposure produced it.

Where the paths come from

Not from a bell curve. Each path is built by resampling that name's own historical daily moves, which preserves the two properties that matter and that a normal distribution destroys: the tails are fat, and big moves cluster together. A model that thinks a 5% day is impossible will always tell you a written put is safer than it is.

The horizon is in calendar days Thirty days means thirty days on the wall, not thirty trading days. Option expiries work in calendar time and so does this.

Reading the distribution

The median — the middle outcome. More useful than the mean for a book with written options, where a long tail of small wins and a short tail of large losses pulls the average away from anything typical.
The bands — the range containing a given share of outcomes. A 90% band is genuinely wide; that is not pessimism, it is what a month of market does.
P(profit) — the share of paths finishing above break-even.
P(assign) — for written options, the chance of finishing in the money at expiry. Deliberately conservative: it says "at most this likely". It is also a different question from the probability of being out of the money at the horizon, and for a long-dated put viewed over a short window the two differ a great deal.

The volatility and drift knobs

You can scale volatility and set a drift to ask what-if questions. One thing about the volatility control is worth knowing, because getting it wrong produces a comfortable and false answer:

Raising volatility widens the range symmetrically — reality does not When volatility actually spikes, prices usually fall at the same time. Turning the volatility multiplier up on its own gives you a wider range centred on the same place, which understates the downside of the scenario you are imagining. Pair a volatility increase with a negative drift if you want a stress case that resembles a real one.

The same control is more trustworthy as you push it up than as you push it down: a stressed market is a well-understood shape, whereas asking for less volatility than the history contains tends to produce a range that is too narrow to be useful.

Margin

Written puts and spreads consume buying power, and a path that falls hard consumes more of it exactly when the position is worth least. The page reports whether margin is breached on the simulated paths — the failure that ends a strategy early, because a margin call closes positions at the worst available price regardless of whether the thesis was right.

Then go and fly one

A distribution cannot tell you what holding a position feels like; it has already averaged that away. When the range looks acceptable, take the same book to Flight and live through a single path — particularly a bad one. A position that is fine on the distribution and intolerable in week two is a position you will close at the bottom.