Expected Value & Betting Games
Warm up with expected-value computations and optimal stopping rules on dice and card-draw games that mirror the decision logic used later in quoting.
Build expected-value games and a quoting engine that manages inventory, adverse selection, and P&L.
Every source step is its own lesson with intuition, concepts, correctly rendered MathJax mathematics, implementation, tests, mistakes, and a checkpoint.
Warm up with expected-value computations and optimal stopping rules on dice and card-draw games that mirror the decision logic used later in quoting.
Implement the basic quoting loop: turn a fair value into a bid/ask, execute counterparty trades, and mark cash and inventory to market for P&L.
Extend the quoter to account for adverse selection, uncertainty, and inventory skew, and update fair-value estimates from observed trades and revealed cards.
Tie everything together by running full market-making episodes and aggregating P&L statistics across many simulated runs.