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STATS 215: Statistical Models in Biology

Poisson and renewal processes, Markov chains in discrete and continuous time, branching processes, diffusion. Applications to models of nucleotide evolution, recombination, the Wright-Fisher process, coalescence, genetic mapping, sequence analysis. Theoretical material approximately the same as in STATS 217, but emphasis is on examples drawn from applications in biology, especially genetics. Prerequisite: 116 or equivalent.
Terms: Win | Units: 3
Instructors: Zhang, N. (PI)

STATS 217: Introduction to Stochastic Processes

Discrete and continuous time Markov chains, point processes, random walks, branching processes, first passage times, recurrence and transience, stationary distributions. Prerequisite: STATS 116 or consent of instructor.
Terms: Win, Sum | Units: 3

STATS 219: Stochastic Processes (MATH 136)

Introduction to measure theory, Lp spaces and Hilbert spaces. Random variables, expectation, conditional expectation, conditional distribution. Uniform integrability, almost sure and Lp convergence. Stochastic processes: definition, stationarity, sample path continuity. Examples: random walk, Markov chains, Gaussian processes, Poisson processes, Martingales. Construction and basic properties of Brownian motion. Prerequisite: STATS 116 or MATH 151 or equivalent. Recommended: MATH 115 or equivalent.
Instructors: Zuniga, J. (PI)

STATS 237: Time Series Modeling and Forecasting

Box-Jenkins and Bayesian approaches. State-space and change-point models. Application to revenue prediction, forecasting product demand, and other real world problems. Development and assessment of models and forecasts in practical applications. Hands-on experience with real data.

STATS 240: Statistical Methods in Finance

(SCPD students register for 240P.) Regression analysis and applications to investment models. Principal components and multivariate analysis. Parametric inference. Financial time series. Estimation and modeling of volatilities. Statistical methods for portfolio management. Bayesian and empirical Bayes methods.
Terms: Aut | Units: 3-4
Instructors: Lai, T. (PI)

STATS 240P: Statistical Methods in Finance

For SCPD students; see 240.
Terms: Aut | Units: 3
Instructors: Lai, T. (PI)

STATS 241: Financial Modeling and Risk Management

(SCPD students register for 241P.) Substantive and empirical modeling approaches in financial markets. Statistical trading strategies and their evaluation. High-frequency data and microstructure. Advanced time series modeling and forecasting. Nonparametric regression. Statistical models for market and credit risks. Backtesting, stress testing and Monte Carlo methods. Prerequisite: 240 or equivalent.
Terms: Spr | Units: 3-4
Instructors: Lai, T. (PI)

STATS 241P: Financial Modeling and Risk Management

For SCPD students; see 241.
Terms: Spr | Units: 3
Instructors: Lai, T. (PI)

STATS 243: Introduction to Mathematical Finance

Interest rate and discounted value. Financial derivatives, hedging, and risk management. Stochastic models of financial markets, introduction to Ito calculus and stochastic differential equations. Black-Scholes pricing of European options. Optimal stopping and American options. Prerequisites: MATH 53, STATS 116, or equivalents.
Terms: Sum | Units: 3-4

STATS 244: Algorithmic Trading

An introduction to financial trading strategies based on methods of statistical arbitrage that can be automated. Methodologies related to high frequency data and stylized facts on asset returns; models of order book dynamics and order placement, dynamic trade planning with feedback; momentum strategies, pairs trading. Emphasis on developing and implementing models that reflect the market and behavioral patterns. Prerequisite: STATS 240 or equivalent.
Terms: Sum | Units: 3
Instructors: Velu, R. (PI)
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