How Prometheus models your wealth

The engine takes a setup, the user's investments in equity, fixed income and property, along with rare but devastating custom risks specific to the user (a medical bill, critical home damage, career loss) along with their cash savings, salary, and a user-defined ruin threshold, and produces a distribution of year-end wealth across one million simulated paths.

At the heart of the engine is a dependency structure, known in mathematics as a copula (Latin for "link" or "tie"). The copula binds a set of calibrated market and life risk factors into a single joint distribution, letting their interdependencies flow through the simulation.

This matters because risks rarely move in isolation: a high inflation shock can trigger a rise in interest rates, which in turn hurts equities, which can deepen into a recession and end in a job loss. Conventional simulators do not capture these chains.

Every path is generated under the full set of interdependencies in play across the risk universe. Hidden risks, currency exposure, stochastic inflation shocks, fat-tailed yield-curve moves, are baked into the stress, not bolted on afterwards. The platform then reports the full distribution at key percentiles and gives the user the tools to interrogate it: what-if analysis, tail-risk driver decomposition, conditional probabilities, and threshold sweeps.

Markets behave in characteristic ways. Stocks have calm stretches and panic stretches. Yield curves bend, steepen and flip in a small handful of recognisable patterns. Inflation drifts, then jumps. We don't want a simulator that flattens all of that into a smooth bell curve or a linear projection, because that isn't the world your money lives in. So each market risk gets its own purpose-built calibration.

Equities. For each calibrated index, S&P 500, FTSE 100, FTSE All-Share, NASDAQ, MSCI, we fit an AR-GARCH model on decades of monthly returns. That mouthful does two things that matter: it remembers that quiet months follow quiet months and stormy ones follow stormy ones. Because it draws shocks from a fat-tailed distribution, a once-in-a-decade drawdown is never treated as impossible.

Currencies. Currency pairs (USD/GBP, GBP/EUR, USD/EUR) get the same treatment. If any part of your wealth sits in a foreign currency, the exchange rate is a risk in its own right, and we model it with the same care we apply to equities.

Bonds and yield curves. Rather than guessing one number for "the bond market", we look at the whole curve, every maturity from short bills to long bonds, and ask what its moves actually look like. The answer is that they almost always reduce to three patterns: the whole curve shifting up or down, the curve steepening or flattening, and the middle bowing relative to the ends. We calibrate each of those patterns with a heavy-tailed distribution so the simulator can produce realistically jagged rate scenarios, not just gentle parallel drifts.

Inflation. Same idea. The inflation term structure moves in a small number of recognisable shapes, and we calibrate each one. The simulated inflation rate then flows into your path's expenses, so when a high-inflation world arrives in the simulation, that year's bills actually go up, and you feel the squeeze on the way to year-end.

Property. Residential property returns are calibrated per region (UK, US, EU) from the long-run record. Property is slower-moving than equities, but it isn't immune, and pretending it is would understate the size of a bad year.

The market isn't the only thing that can sink a year. A job loss, a serious medical bill, a critical home repair, these don't show up on Bloomberg, but they show up on your balance sheet. Prometheus treats them as first-class citizens of the simulation, on equal footing with the market factors.

For each life risk you describe, career loss, plus whichever custom risks matter to you, the engine asks two questions on every path: did it happen this year, and if it did, how bad was it? The "how often" piece comes from a frequency assumption (some risks fire at most once, others can recur). The "how bad" piece is calibrated from your own optimistic and pessimistic loss estimates, so the severity range reflects your situation rather than a textbook average.

If you're insured against a risk, the engine applies the cover the way the policy would in real life: a deductible per event, an annual ceiling on what the insurer will pay, and the rest hits your wealth. Risks sharing a policy share its limit. The point is to show you what your insurance actually buys you, and, just as importantly, where it runs out.

If risks were independent, finance would be easy. A bad equity year would be cushioned by a normal property year. An inflation spike would arrive on its own, not riding alongside a rate hike. Job losses would happen in random years rather than clustering with recessions.

That isn't the world we live in. The worst years are bad precisely because shocks arrive together. So we build a correlation matrix that captures, for every pair of risks in the universe, how strongly they've historically moved in sync, calibrated from decades of joint history across equities, rates, inflation, property, currencies and life events.

That matrix isn't decoration. Inside the simulation, it is what binds the individual risk calibrations into a single, internally consistent world on every path. When the engine draws an extreme equity shock, the correlated factors don't roll their own independent dice, they roll conditional on what just happened. A path where equities crash and inflation surges and your career risk fires isn't ruled out; it's exactly the kind of compound bad year the engine is designed to find.

You can override any single cell of the matrix if you hold a strong view on a particular pair. Your override sits on top of the calibrated default for that pair only, without disturbing the rest of the structure.

Press simulate, and the engine plays your year out a million different ways. Each of those million paths is a complete, self-consistent story: an equity return, a bond P&L, an inflation rate that drives your actual expenses, a property return, currency moves on any foreign holdings, and whichever life risks did or didn't fire. At the end of the year, each path has a wealth number, and we ask the question you came here to ask: did you bust your ruin threshold, or didn't you?

The summary you see - median, p10, p5, p1 - is just the distribution of those million year-end wealth values, sorted from worst to best. But the percentiles aren't the interesting bit. The interesting bit is what's behind them.

That's why every percentile is inspectable. Open p5 and you don't just see "you ended the year with X", you see the specific combination of shocks that took you there. Maybe equities were down 28%, inflation ran at 8%, your career risk fired, and the bond ballast didn't save you. That's a story you can do something with: it tells you which exposure was load-bearing in your bad years and which wasn't. It turns a number into a narrative.

And the million paths don't just sit there. They're the raw material for the real work: quantifying your tail and finding out what breaks you. The platform lets you reshape the picture - pull a lever, change an allocation, insure a risk - and watch how the distribution responds, against the exact same simulated world so the comparison is honest. You can carve out the slice of paths that match a scenario you actually worry about and read the probability of ruin under it. You can step into the bust subset and decompose which factors were doing the damage, not in the abstract, but in your specific year. The point isn't a prettier dashboard. It's a sharper answer to the only question that matters: how much loss can your life absorb, and what's most likely to deliver it?

The horizon is one year. This is not a multi-year retirement projection or a financial-planning calculator. It does not forecast markets, recommend products, or tell you what to buy. What it does is something deeper, and, we'd argue, more useful: it shows you how today's position behaves under the joint, fat-tailed shocks of the world as it actually is. One question matters more than the rest, how bad your year can really get, and what would break you. Prometheus was built to reveal both. The methodology behind it powers institutional stress-testing engines at banks, insurers and regulators, turned, for once, on your own balance sheet.