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Coursera

Financial Statistics and Quantitative Analysis

EDUCBA via Coursera

Overview

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Master the quantitative techniques that form the foundation of modern finance, risk management, and FRM Part I preparation. This comprehensive course provides a structured learning journey through financial mathematics, statistics, probability, regression analysis, time series modeling, and advanced quantitative methods used by finance professionals worldwide. The course begins with the core principles of time value of money, compounding, discounting, and fixed-income valuation. Learners will develop practical skills in evaluating financial instruments and understanding the mathematical foundations behind investment decisions. Building on this foundation, the course introduces descriptive statistics and probability concepts essential for analyzing financial datasets. Learners will explore measures such as mean, variance, skewness, kurtosis, and probability distributions that play a critical role in risk analysis and portfolio management. The course then progresses into hypothesis testing, statistical inference, and regression analysis, enabling learners to evaluate relationships between variables and make data-driven financial decisions. Advanced modules cover time series analysis, trend identification, seasonality, correlation structures, and volatility modeling techniques including GARCH and EWMA. Learners will also explore simulation methods, copulas, and model diagnostics used to evaluate uncertainty and capture complex financial relationships. Throughout the course, concepts are explained with a strong focus on practical application and FRM exam relevance. By the end of this course, learners will be able to confidently apply quantitative methods to financial problems, interpret statistical outputs, evaluate financial models, and strengthen their readiness for careers in finance, banking, risk management, and quantitative analysis.

Syllabus

  • Foundations of Time Value & Fixed Income
    • Learn core financial mathematics concepts including time value of money, compounding, discounting, and bond valuation techniques essential for financial decision-making.
  • Statistical Measures & Distributions
    • Develop strong statistical foundations by analyzing datasets, understanding distributions, and interpreting key measures like mean, variance, skewness, and kurtosis.
  • Hypothesis Testing & Regression Basics
    • Apply statistical inference techniques and build regression models to analyze relationships and make data-driven financial decisions.
  • Time Series & Correlation Modeling
    • Explore trend analysis, seasonality, correlation, and advanced volatility models like GARCH and EWMA used in financial risk management.
  • Advanced Quant Techniques & Model Diagnostics
    • Understand simulation techniques, copulas, and regression diagnostics to evaluate models and capture complex financial dependencies.

Taught by

EDUCBA

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