- Abstract Algebra (3)
- Representation Theory (1)
- Ring Theory
- Algebra (51)
- Algebraic Geometry (2)
- Analytic Geometry (1)
- Applied Mathematics (202)
- Arithmetic (6)
- Calculus (112)
- Differential Calculus (69)
- Differential Equations (41)
- Integral Calculus (64)
- Limits (19)
- Multivariable Calculus (131)
- Precalculus (3)
- Tensor Calculus (1)
- Vector Calculus (1)
- Chaos Theory (1)
- Combinatorics (1)
- Polynomial Method (1)
- Complex Analysis (4)
- Complex Numbers
- Differential Geometry (3)
- Functional Analysis (2)
- Geometry (5)
- Fractals
- Non-Euclidean Geometry (2)
- Group Theory
- Lie Groups (2)
- History of Math (59)
- Linear Algebra (6)
- Mathematical Logic
- Set Theory (1)
- Mathematical Modeling
- Mathematics Education (11)
- Number Theory (1)
- Elliptic Curves (1)
- Quaternions
- Numerical Analysis (2)
- Partial Differential Equations (5)
- Probability (41)
- Queueing Theory
- Stochastic Process (2)
- Real Analysis (5)
- Recreational Mathematics
- Math Games
- Math Puzzles
- SAT Math (52)
- Statistics (49)
- Linear Models
- Stochastic Calculus
- Topology (5)
- K-theory (1)
- Point-Set Topology
- Trigonometry (18)
Topics: Stochastic Calculus
Stochastic Calculus
Stochastic calculus is a branch of mathematics that operates on stochastic processes. It allows a consistent theory of integration to be defined for integrals of stochastic processes with respect to stochastic processes. It is used to model systems that behave randomly.The best-known stochastic process to which stochastic calculus is applied is the Wiener process (named in honor of Norbert Wiener), which is used for modeling Brownian motion as described by Louis Bachelier in 1900 and by Albert Einstein in 1905 and other physical diffusion processes in space of particles subject to random forces. Since the 1970s, the Wiener process has been widely applied in financial mathematics and economics to model the evolution in time of stock prices and bond interest rates.
