Financial Time Series Analysis with Mathematics
Financial time series analysis is the use of mathematical and statistical methods to analyze and model financial data, such as stock prices or exchange rates, over a period of time. This type of analysis is often used to make predictions about future market trends and to identify patterns and relationships in historical data. Techniques used in financial time series analysis include linear and nonlinear regression, time series decomposition, and spectral analysis, among others. The goal of this analysis is to extract useful information from financial data that can be used to support decision-making in the financial industry, such as investment strategy, risk management and portfolio management.