I trained as a rocket engineer and ended up trading markets, and when people hear that they usually assume there was a dramatic change of direction somewhere. There wasn’t. The move from one to the other was smaller than it sounds, and I want to describe it plainly, partly because it is the honest version and partly because the honest version is more useful to anyone thinking about a similar path.
The engineering
I did a master’s in mechanical engineering at UCL, specialising in propulsion systems. The part of the course that stayed with me was not the rockets themselves but the mathematics underneath them: partial differential equations, fluid dynamics, the modelling of systems that are too complex to solve by hand and have to be approximated, simulated and checked against what actually happens. An engineer learns early that a model is only as good as its assumptions, that every system has a regime where the assumptions break, and that the interesting problems are the ones near that boundary.
The markets
Markets are such a system. A price is the output of a very large number of decisions, most of them small and none of them fully known, and the only way to say anything useful about it is to build a model, state its assumptions, and watch for the moment the assumptions stop holding. That is the same job as modelling flow through a nozzle. The equations are different, the discipline is identical, and I was surprised when I first moved into trading by how directly the habit transferred.
I have now spent well over fifteen years in and around markets, in investment banking, in trading and in market analytics, working for some of the better-known investment banks and hedge funds and, over that time, managing more than $300 million in assets. The piece of work I am proudest of from that time was at Oil Analytics, where I was a partner in building a quantitative framework for the energy market. It modelled refineries, petrochemical plants and the supply chain between them, and it was used for derivatives trading, equity analysis, project evaluation and advisory work. The framework was eventually taken on as a Bloomberg data provider, which meant it had to stand up to scrutiny from people who had no reason to be kind to it. I recommend that experience to anyone who builds models for a living. It changes how carefully you state your assumptions.
What came out of those years was a particular way of working, which is quantitative and macro at the same time. Quantitative because the view is expressed as a model with numbers in it, not as a feeling. Macro because the inputs to the model are the large forces, supply, demand, policy, liquidity, rather than the pattern on a chart. I have applied it to energy, to currencies and rates, and in more recent years to digital assets, which are the most volatile market I have traded and the one where the discipline of writing the model down before forming a view matters most. Over the last crypto cycle that approach returned more than 2,200 per cent, which is the number people tend to ask about, and which I would rather explain than quote. The explanation is the rest of this site.
What connects them
If I had to say what the engineering gave me that a finance degree would not, it is three things. A respect for the boundary where the model breaks, because in engineering that boundary is where things explode. An instinct to measure rather than to assert, because an engineer’s opinion about whether a structure will hold is worth nothing next to a test. And a certain humility about complex systems, because fluid dynamics teaches you very early that the system does not care what you think it should do.
Those are not glamorous qualities and they do not make for a dramatic story. But they are the reason the move from rockets to markets was not really a move at all, and they are what I would tell a young engineer who is wondering whether their training is wasted in finance. It is not. It is the most useful thing you will bring.