Stochastic Process

Definition: A stochastic process is an ordered collection of random variables. Discrete ones are indexed, often by the subscript t for time, e.g., y_t, y_t+1, although such a process could be spatial instead of temporal. Continuous ones can be described as continuous functions of time, e.g. y(t).

A stochastic process is specified by properties of the joint distribution for those random variables. Examples:

• the random variables are independently and identically distributed (iid).
• the process is a Markov process
• the process is a martingale
• the process is white noise
• the process is autoregressive (e.g. AR(1))
• the process has a moving average (e.g. see MA(1))

Terms related to Stochastic Process:

• Stochastic Difference Equation
• Stochastic Dominance
• Stochastic

About.Com Resources on Stochastic Process:

• Alternative Hypothesis
• Box-Cox Transformation
• 2SLS

Writing a Term Paper? Here are a few starting points for research on Stochastic Process:

Journal Articles on Stochastic Process:

• A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices
• A Model for Human Resource Valuation: A Stochastic Process with Service Rewards
• What is a Stochastic Process?