I build the models behind finance decisions: Monte Carlo hedging tools, structured-product pricing, valuation and portfolio construction. Every project below opens in its original, working form.
A client had to buy €8bn in six months against a $9.28bn budget. Our team had to recommend a hedge. I built this Monte Carlo tool to back the recommendation with numbers: it compares going unhedged, a forward, a call and a zero-cost collar across bull, neutral, bear and extreme-downside regimes.
Should a $165m public pet-food company stay public, sell to a strategic buyer, take an LBO or sign a private-label deal? We valued each path with DCF, trading comps, precedents and an LBO, recommended a strategic sale, and presented to a panel of investment bankers.
We structured a 10-year, $10m note that gives a client NVIDIA upside with full principal protection. We split each $100 into a zero-coupon bond, a fee and an option budget, priced the upside with Black-Scholes, then checked it with Monte Carlo paths and tested capped and Asian-averaging alternatives.
We answered a university's request for proposals for outsourced investment management. Tuition is 85% of its revenue, so we built a liquidity-first plan: an efficient-frontier analysis, a two-tranche allocation, stress tests and a draft investment policy statement.
For fun, I applied a portfolio approach to fantasy football. I collected 16 expert squads, weighted the experts by credibility, and solved for the best 15-player squad under a $100m budget. Then I compared expert and public ownership to find picks the market had mispriced.