Financial Statistics and Quantitative Analysis
Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.
Financial Statistics and Quantitative Analysis
This course is part of Financial Risk and Quantitative Finance Specialization
Instructor: EDUCBA
Included with
Learn more
Ask Coursera
What you'll learn
Apply time value of money, bond valuation, and quantitative methods in finance.
Analyze financial data using probability, hypothesis testing, and regression techniques.
Evaluate volatility, time series, and simulation models for financial risk analysis.
Skills you'll gain
- Finance
- Probability
- Probability Distribution
- Trend Analysis
- Analysis
- Portfolio Management
- Statistical Inference
- Risk Modeling
- Financial Modeling
- Risk Management
- Time Series Analysis and Forecasting
- Probability & Statistics
- Regression Analysis
- Financial Data
- Statistical Methods
- Risk Analysis
- Statistics
- Correlation Analysis
- Statistical Hypothesis Testing
- Descriptive Statistics
Details to know
June 2026
20 assignments
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 5 modules in this course
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.
Learn core financial mathematics concepts including time value of money, compounding, discounting, and bond valuation techniques essential for financial decision-making.
What's included
8 videos4 assignments
8 videosβ’Total 75 minutes
- Introduction to Time Value of Moneyβ’11 minutes
- Questions and Answerβ’9 minutes
- Bondsβ’12 minutes
- IRRβ’7 minutes
- PV Calculation of a Bondβ’7 minutes
- Introduction to Basic Statisticsβ’10 minutes
- Dataset for Stockβ’10 minutes
- Arithmetic and Geometric Meanβ’8 minutes
4 assignmentsβ’Total 60 minutes
- Foundations of Time Value & Fixed Incomeβ’30 minutes
- Understanding the Time Value of Moneyβ’10 minutes
- Bond Valuation & Return Conceptsβ’10 minutes
- Data Foundations for Analysisβ’10 minutes
Develop strong statistical foundations by analyzing datasets, understanding distributions, and interpreting key measures like mean, variance, skewness, and kurtosis.
What's included
8 videos4 assignments
8 videosβ’Total 74 minutes
- Arithmetic and Geometric Mean Continueβ’6 minutes
- Covariance and Correlationβ’10 minutes
- Moments and Central Momentsβ’9 minutes
- Population and Sample Meanβ’12 minutes
- Kurtosisβ’5 minutes
- Distributionβ’9 minutes
- Distribution Exampleβ’12 minutes
- Distribution Example Continueβ’11 minutes
4 assignmentsβ’Total 60 minutes
- Statistical Measures & Distributionsβ’30 minutes
- Measuring Returns & Relationshipsβ’10 minutes
- Understanding Data Behaviorβ’10 minutes
- Applying Distributionsβ’10 minutes
Apply statistical inference techniques and build regression models to analyze relationships and make data-driven financial decisions.
What's included
8 videos4 assignments
8 videosβ’Total 75 minutes
- Hypothesisβ’11 minutes
- Hypothesis Testing Procedureβ’12 minutes
- Hypothesis Exampleβ’8 minutes
- Hypothesis Example Continueβ’7 minutes
- P-Valueβ’8 minutes
- Linear Regression with one Regressorβ’12 minutes
- Linear Regression with Multiple Regressorβ’8 minutes
- Modeling and Forecasting Tendβ’7 minutes
4 assignmentsβ’Total 60 minutes
- Hypothesis Testing & Regression Basicsβ’30 minutes
- Hypothesis Testing Fundamentalsβ’10 minutes
- Statistical Inference in Practiceβ’10 minutes
- Expanding Regression Modelsβ’10 minutes
Explore trend analysis, seasonality, correlation, and advanced volatility models like GARCH and EWMA used in financial risk management.
What's included
8 videos4 assignments
8 videosβ’Total 62 minutes
- Selected the Correct Trend Modelβ’10 minutes
- Akaike and Schwarz Criterionβ’8 minutes
- Forecasting Tend and Seasonalityβ’6 minutes
- Characterizing Cycleβ’8 minutes
- Characterizing Cycle Continueβ’6 minutes
- Correlation and Covarianceβ’7 minutes
- Garth and EWMA Modelβ’10 minutes
- Copulasβ’7 minutes
4 assignmentsβ’Total 60 minutes
- Time Series & Correlation Modelingβ’30 minutes
- Trend Analysis & Model Selectionβ’10 minutes
- Cycles & Relationships in Dataβ’10 minutes
- Volatility & Risk Modelsβ’10 minutes
Understand simulation techniques, copulas, and regression diagnostics to evaluate models and capture complex financial dependencies.
What's included
8 videos4 assignments
8 videosβ’Total 68 minutes
- Types of Copulasβ’7 minutes
- Simulation Methodsβ’10 minutes
- Simulation Methods Continueβ’8 minutes
- Quants Important Topics Summaryβ’9 minutes
- Summary Correlationβ’8 minutes
- Adjusted R Squareβ’7 minutes
- Multicollinearityβ’9 minutes
- T-Statisticsβ’10 minutes
4 assignmentsβ’Total 60 minutes
- Advanced Quant Techniques & Model Diagnosticsβ’30 minutes
- Advanced Dependence & Simulationβ’10 minutes
- Key Quant Concepts Recapβ’10 minutes
- Regression Diagnostics & Inferenceβ’10 minutes
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
Offered by
Explore more from Finance
Why people choose Coursera for their career
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you canβt afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, youβll find a link to apply on the description page.
More questions
Financial aid available,
