Develop a research question, build the skills behind your next step or shape a learning programme for your team. The aim is work you can explain and defend.
Bring the question, the evidence and the calculation together. Make each step of your reasoning visible.
Wins and losses must both be counted.
Weight the 1R loss as well as the gain.
Costs come out of every trade.
The first sheet states the assumed win probability. It is an input to challenge, not proof of skill.
The model has positive expectancy at 45% wins. Larger wins can offset a lower win rate; the inputs still need evidence.
With a fixed losing outcome of −1R, net expectancy is linear in the decimal probability p. At a gain of 2R, a one-percentage-point rise in p adds 0.03R to expected payoff. This is sensitivity to an assumption; it does not improve the evidence for that assumption. An expected result is not a guaranteed result.
Here one losing trade costs 1R, before fees and slippage. The winning outcome is gR; a cost of cR is paid on every trade. Weight each outcome by its probability, then subtract that cost. Break-even probability is the value of p at which this expectation is zero. In research, estimate inputs from evidence and challenge them with out-of-sample tests.
Illustrative probabilities and fixed outcomes; loss = 1R and cost applies to every trade. Expectation is an average under the assumptions, not a guaranteed result or backtest.
Turn a financial question into a piece of work you can explain. Develop your evidence, analysis and research practice.
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Make sense of your next step. Discuss learning choices, finance careers and the practical skills your direction requires.
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For organisations, universities and learning partners. Discuss a programme shaped around your audience, subjects and practical learning goals.
Format, availability and any fees are confirmed for the specific programme before you enrol.