2Data, Measurements, and Global Finance

Motivation

Global finance compounds the complexity of traditional finance by taking into account additional economic and financial factors together with political and geopolitical aspects. Financial models are then mostly multivariate, data based, networked, and generally interdependent. Further, data granularity is a constant problem. For example, macroeconomic data may be reported monthly, quarterly, or annually, while financial data are frequently reported daily (or even minute to minute or tic to tic). Therefore, data and measurements used to estimate trends and their properties may require analytic approaches that differ from traditional analysis. The purpose of this chapter is to summarize basic statistical tools, motivate the development of modeling techniques, and explore the empirical tools to better understand global and risk finance. In all subsequent chapters, examples and applications are further developed.

2.1 Data and Models

The choice and the measurement of data in a global and complex space are perhaps the most important aspects of statistical risk pricing and economic analysis. Data may be varied, consisting of qualitative events (such as political outcomes and decisions, time series of national macroeconomic statistics, and social and financial metrics). Data, whether big or small, are used to estimate multiple factors and their relationships. Practically, measurements are based on their availability and on the data ...

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