Executive Master in Strategic Finance and Business Leadership

Financial Data Analysis using Mathematical and Statistical Methods

Course ID: 2506230101053EGI

Course Dates :      23/06/25       Course Duration :   5   Studying Day/s   Course Location:  London,   UK

Course Category:    Professional and CPD Training Programs


Course Subcategories:

Compliance and Governance Finance and Accounting Leadership and Management Sustainability and Environmental Practices Technology and Innovation

Data visualization Econometrics Financial modeling Machine learning Portfolio optimization Regulatory compliance Risk management

Course Certified By:

 * Projacs Academy

* Professional Training and CPD Programs
Leading to:
Executive Diploma Certificate
Leading to:
Executive Mini Masters Certificate
Leading to
Executive Masters Certificate

Certification Will Be Issued From :  KSA


Course Fees:    £4,884.83

Vat Not Included in the price. VAT may vary depending on the country where the course or workshop is held.

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Executive Master in Strategic Finance and Business Leadership

Course Information

Introduction

Financial data analysis has become a cornerstone for effective decision-making in today’s rapidly evolving global economy. Organizations rely on precise mathematical and statistical methods to analyze complex datasets, identify trends, and predict future performance. This course is designed to equip professionals with the tools and techniques required to interpret financial data effectively and make data-driven decisions that foster business growth.

Mathematical and statistical methods play a pivotal role in transforming raw financial data into actionable insights. From understanding regression analysis and time series forecasting to mastering probability distributions, this course emphasizes practical techniques that help participants gain a comprehensive understanding of data dynamics. These skills are critical for managing financial risk, optimizing resource allocation, and driving operational efficiency.

The course integrates theoretical knowledge with hands-on application, ensuring participants are well-versed in analyzing financial metrics such as revenue, profitability, liquidity, and market performance. Participants will gain practical experience through real-world case studies, exercises, and interactive sessions designed to challenge their analytical skills.

A core focus of the program is understanding and applying advanced statistical tools, including hypothesis testing, variance analysis, and correlation techniques, to financial datasets. These skills will enable participants to decipher patterns and relationships within data, which are crucial for crafting effective strategies in corporate finance, investment management, and business operations.

Additionally, the course delves into modern technologies and software tools that automate financial data analysis, such as Python, R, and Excel. By learning to integrate these tools with mathematical models, participants will enhance their efficiency and accuracy in conducting financial analyses.

Whether you aim to sharpen your analytical skills or broaden your expertise in financial data interpretation, this course provides a solid foundation for professionals seeking to stay competitive in the era of data-driven decision-making.

Objectives

By attending this course, participants will be able to:

Analyze financial data using advanced mathematical and statistical techniques.
Interpret and apply key statistical concepts, including regression, correlation, and probability distributions, to financial datasets.
Conduct time series analysis and forecasting for predicting financial trends.
Perform hypothesis testing and variance analysis to support evidence-based decision-making.
Utilize modern tools such as Python, R, and Excel for automating financial data analysis.
Translate financial data insights into actionable strategies for improved organizational performance.
Manage financial risks by identifying patterns and anomalies within complex datasets.
Enhance reporting and visualization skills to effectively communicate analytical findings.

Who Should Attend?

This course is ideal for:

Financial analysts, accountants, and auditors seeking to enhance their analytical capabilities.
Data analysts and business intelligence professionals working with financial datasets.
Investment professionals and portfolio managers focused on data-driven strategies.
Managers and executives responsible for financial decision-making and reporting.
Professionals aspiring to transition into financial data analysis roles.
CPD candidates looking to broaden their expertise in mathematical and statistical applications in finance.

Training Method

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a 7” Tablet containing a copy of the presentation, slides and handouts
• Post-assessment

Program Support

This program is supported by:
* Interactive discussions
* Role-play
* Case studies and highlight the techniques available to the participants.

Daily Agenda

The course agenda will be as follows:
• Technical Session 08.30-10.00 am
• Coffee Break 10.00-10.15 am
• Technical Session 10.15-12.15 noon
• Coffee Break 12.15-12.45 pm
• Technical Session 12.45-02.30 pm
• Course Ends 02.30 pm

Course Outlines

Week 1
Day 1:
Foundations of Financial Data Analysis

Overview of financial datasets and key metrics for analysis.
Introduction to mathematical and statistical principles in finance.
Exploring data visualization techniques for financial reporting.
Hands-on session: Cleaning and preparing financial data for analysis.

Day 2:
Statistical Analysis in Finance

Understanding descriptive and inferential statistics.
Hypothesis testing and its applications in financial decision-making.
Variance analysis and its role in financial performance evaluation.
Case study: Analyzing company profitability using statistical tools.

Day 3:
Regression and Correlation Techniques

Fundamentals of regression analysis and correlation in finance.
Application of simple and multiple regression models.
Identifying relationships between financial variables using correlation.
Practical exercise: Predicting revenue growth through regression modeling.

Day 4:
Time Series Analysis and Forecasting

Introduction to time series data and key forecasting models.
Decomposition of time series into trend, seasonal, and irregular components.
Applying ARIMA and exponential smoothing techniques.
Workshop: Forecasting stock market trends using time series models.

Day 5:
Advanced Financial Data Tools and Applications

Overview of financial analysis tools: Python, R, and Excel.
Automating data analysis using scripts and templates.
Real-world application: Integrating statistical models with financial software.
Final project: End-to-end financial data analysis and presentation of findings.