Stochastic Calculus Applications in Finance

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mathematical-finance black-scholes option-pricing risk-neutral-pricing

Core Idea

Mathematical finance applies stochastic calculus to price and hedge financial derivatives. The fundamental theorem of asset pricing connects arbitrage-freeness to the existence of an equivalent martingale measure, and market completeness to its uniqueness. Under the Black-Scholes model, Girsanov's theorem constructs the risk-neutral measure, the martingale representation theorem provides the hedging strategy, and the Feynman-Kac formula connects risk-neutral expectations to the Black-Scholes PDE.

Explainer

Mathematical finance is the most prominent application of stochastic calculus. The central problem is pricing and hedging derivatives — financial contracts whose value depends on the evolution of an underlying asset. The Black-Scholes framework, built on geometric Brownian motion and Itô calculus, provides the theoretical foundation. The key insight is that in a complete market, every derivative can be replicated by dynamically trading the underlying asset and a risk-free bond, and the replication cost determines the derivative's price.

The fundamental theorems of asset pricing are the theoretical pillars. The first FTAP states that a market is arbitrage-free if and only if there exists an equivalent martingale measure (EMM) Q under which all discounted asset prices are martingales. The second FTAP states that the market is complete (every contingent claim is attainable) if and only if the EMM is unique. In the Black-Scholes model (one stock, one Brownian motion), Girsanov's theorem constructs the unique EMM by setting θ = (μ-r)/σ and defining Q via the Girsanov density. Under Q, the stock satisfies dS = rS dt + σS dW̃ — the physical drift μ is replaced by the risk-free rate r.

The Black-Scholes formula C = S₀Φ(d₁) - Ke^{-rT}Φ(d₂) for a European call with strike K and maturity T follows from computing E_Q[e^{-rT}max(S_T - K, 0)]. Since S_T is lognormally distributed under Q (from GBM with drift r), this is a direct calculation. The same result can be derived via the Black-Scholes PDE ∂V/∂t + rS(∂V/∂S) + (1/2)σ²S²(∂²V/∂S²) = rV, which is obtained by constructing the delta-hedging portfolio and eliminating risk. The Feynman-Kac formula provides the bridge: the PDE solution equals the risk-neutral expectation.

The replicating portfolio is constructed via the martingale representation theorem. The discounted option price V(t)e^{-rt} is a Q-martingale adapted to the Brownian filtration, so by the MRT, V(t)e^{-rt} = V(0) + ∫₀ᵗ H(s) dW̃(s). Converting to the stock numeraire: hold Δ(t) = ∂V/∂S shares of stock and invest the remainder in bonds. This delta-hedging strategy replicates the option payoff exactly — it is self-financing, and at maturity the portfolio value equals max(S_T - K, 0). The strategy's existence (guaranteed by the MRT) is what justifies using the risk-neutral expectation as the price. Without a replication argument, the expectation under Q would be just one possible price among many.

Practice Questions 4 questions

Prerequisite Chain

Counting to 10Counting to 20Understanding ZeroThe Number ZeroCounting to FiveOne-to-One CorrespondenceCombining Small Groups Within 5Addition Within 10Addition Within 20Two-Digit Addition Without RegroupingTwo-Digit Addition with RegroupingAddition Within 100Repeated Addition as MultiplicationMultiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Two-Digit by One-Digit DivisionDivision with RemaindersRemainders and Quotients in DivisionDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueReading and Writing DecimalsComparing and Ordering DecimalsAdding and Subtracting DecimalsMultiplying DecimalsDividing DecimalsDividing FractionsMixed Number ArithmeticOrder of OperationsInteger Order of OperationsVariable ExpressionsCombining Like TermsOne-Step EquationsTwo-Step EquationsSolving Multi-Step EquationsEquations with Variables on Both SidesAngle Pairs: Complementary, Supplementary, and VerticalParallel Lines and TransversalsCorresponding AnglesAlternate Interior AnglesTriangle Angle Sum TheoremExterior Angle TheoremTriangle Inequality TheoremSimilar Triangles: AA SimilaritySimilar Triangles: SSS and SAS SimilarityProportions in Similar TrianglesRight Triangle Trigonometry IntroductionTrigonometric Ratios ReviewRadian MeasureConverting Between Degrees and RadiansThe Unit CircleGraphing Sine and CosineGraphing Tangent and Reciprocal Trigonometric FunctionsDerivatives of Trigonometric FunctionsAntiderivativesIterated Integrals and Fubini's TheoremDouble Integrals in Cartesian CoordinatesDouble Integrals over Rectangular RegionsDouble Integrals in Polar CoordinatesDouble Integrals: Definition and SetupIterated Integrals and Fubini's TheoremDouble Integrals over Rectangular RegionsDouble Integrals over General RegionsApplications of Double Integrals: Area, Mass, and MomentsCenter of MassConservation of Linear MomentumElastic CollisionsInelastic CollisionsCoefficient of RestitutionCollision Analysis and Real-World ApplicationsTwo-Body Collisions in the Center-of-Mass FrameReduced Mass and Two-Body ProblemsKinematics in Two DimensionsProjectile MotionCircular Motion: KinematicsRotational KinematicsTorqueMoment of InertiaRotational Kinetic EnergyThe Work-Energy TheoremConservation of Mechanical EnergyFirst Law of ThermodynamicsThermodynamic Processes and the PV DiagramIsobaric and Isochoric ProcessesHeat EnginesThermal Efficiency of Heat EnginesRefrigerators and Heat PumpsSecond Law of ThermodynamicsEntropyMicrostates and MacrostatesEnsemble Theory FundamentalsCanonical Ensemble (NVT)Partition Function: Definition and PropertiesThe Canonical Partition Function and Thermodynamic DerivationMaxwell-Boltzmann Distribution and Classical LimitBrownian MotionProperties of Brownian MotionThe Itô IntegralItô's Formula (Itô's Lemma)Stochastic Differential EquationsGirsanov TheoremMartingale Representation TheoremStochastic Calculus Applications in Finance

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