Chapter 57. Basic Data Description for Financial Modeling and Analysis
MARKUS HOECHSTOETTER Dr. rer. pol.
Lecturer, School of Economics and Business Engineering, University of Karlsruhe
SVETLOZAR T. RACHEV, PhD, DrSci
Chair-Professor, Chair of Econometrics, Statistics and Mathematical Finance, School of Economics and Business Engineering, University of Karlsruhe and Department of Statistics Applied Probability, University of California, Santa Barbara
FRANK J. FABOZZI, PhD, CFA, CPA
Professor in the Practice of Finance, Yale School of Management
Abstract: We are confronted with data every day, constantly. Daily newspapers contain information on stock prices, economic figures, quarterly business reports on earnings and revenues and much more. These data offer observed values of given quantities. The basic data types can be qualitative, ordinal, or quantitative.
Keywords: qualitative data, quantitative data, ordinal data, univariate data, nominally scaled data, ordinally scaled data, interval scale, ratio scale, absolute data, cross-sectional data, time series data, frequency distributions, Freedman-Diaconis rule, inner quartile range (IQR), empirical cumulative relative frequency distribution
In this chapter, we will present the first essentials of data description. We describe all data types and levels. We explain and illustrate why one has to be careful about the permissible computations concerning each data level.
We will restrict ourselves to univariate data, that is, data of only one ...
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