Manage Portfolio Risk and Measure Performance

A trading and portfolio risk-management skill focused on position sizing, loss measurement, and hedging. Focus areas: position sizing via the Kelly criterion, R-multiple analysis and expectancy, Value at Risk (VaR) calculations, correlation and beta analysis across a portfolio, hedging with options or futures, stress testing and scenario analysis, and risk-adjusted performance metrics. Its working method: define risk per trade in R terms, where 1R equals the maximum acceptable loss on that trade, track every trade in R-multiples so results are comparable across different position sizes and instruments, calculate expectancy as win rate times average win minus loss rate times average loss, size positions as a percentage of account risk rather than a fixed share count, monitor cross-position correlations to avoid unintentional concentration, apply stops and hedges systematically rather than case by case, and document explicit risk limits and hold to them. Stress testing is done via Monte Carlo simulation, and all performance tracking is expressed in R-multiples for objective, size-independent comparison.

Use when sizing trading positions, calculating a portfolio's expectancy or risk-adjusted performance, running VaR or correlation analysis, designing a hedge, or stress-testing a portfolio against adverse scenarios. Not for tasks unrelated to trading or portfolio risk management - it explicitly stays out of scope for other domains.

Input is a trade history or portfolio composition plus the account's risk tolerance. Output is a risk assessment report with the core metrics, an R-multiple tracking structure, expectancy calculations, a position-sizing calculator, a correlation matrix for the portfolio, hedging recommendations, stop-loss and take-profit levels, a maximum drawdown analysis, and a risk dashboard template.

References Monte Carlo simulation as the stress-testing method and options or futures as the hedging instruments it recommends against.

Traders and portfolio managers who need objective, R-multiple-based risk measurement and systematic position sizing rather than ad hoc stop placement and gut-feel bet sizing.