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# lecture13 - Lecture 13: Financial Time Series Data Steven...

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Lecture 13: Financial Time Series Data Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794–4400 http://www.cs.sunysb.edu/ skiena

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Time Series Analysis A time series consists of the values of a function sampled at different points in time. Time series data arises throughout the natural and physical sciences, as growth curves, statistical measurements of activity, . . .
Financial Time Series Data With respect to financial data, the price of any asset as a function of time naturally gives a time series. Many relevant statistics (such as the unemployment rate or index of leading economic indicators) can also be thought of as time series data.

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Approaches to Time Series Analysis A wide variety of mathematical and statistical tools have been developed for working with time series data. Adherents to technical analysis argue that insight into future price movements follow from the analysis of a given asset’s price time series. Regardless, the analysis of financial time series is important in developing/evaluating any investment strategy, risk model- ing, and arbitrage.
Issues of Time Series Data Is it sampled at equally-spaced intervals? Is there noise or error in the data? How long/rapidly growing is the available series? Are there any missing values? Different answers will result when working with stock prices, tick data, sales data, polling data, and government statistics like the unemployment rate. Has anyone here ever worked with time series data in some context?

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The Discrete Nature of Stock Prices When the price of a share of stock gets so expensive it is unwieldy, each share splits into equal-sized pieces which sum to the the original value. Reverse splits combine several shares into a single more expensive share. Such games are played for psychological reasons, but also to set an meaningful lower bound on the minimum amount prices can change. Since decimalization , the minimum change is typically \$0.01, but used to be \$0.125 (one eighth). Reducing this minimum change in principle enables buyers and sellers to get fairer prices.
Computing an adjusted price time series corrects for splits and dividends, but requires recomputing all past history on each new event. Dividends are best adjusted for by adding them back to the

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## This note was uploaded on 01/02/2012 for the course FINANCE 347 taught by Professor Bayou during the Fall '11 term at NYU.

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lecture13 - Lecture 13: Financial Time Series Data Steven...

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