Equity Research Analyst Course with NSE Certification

Our Excel workshop empowers participants with the knowledge needed for finance analyst roles in consulting, equity research or investment banking. The training starts from basic to advanced levels of excel skills so that every possible area is covered.

Key Learning Areas:

• Efficient navigation of excel using keyboard shortcuts

• Advanced techniques for sorting and filtering data

• Better management of data by freezing panes

• Making your presentation more impactful through conditional formatting

• Financial modeling linkages and formula creation

• SUM, PRODUCT, DIVISION, CONCATENATE are essential functions

• VLOOKUP, HLOOKUP and MATCH are functions used to lookup data

• You can combine functions to solve complex problems: VLOOKUP + MATCH; INDEX + MATCH; VLOOKUP + IF.

CAGR IRR EMI are examples of financial calculations.

Table usage and pivot table utilization will also be taught during this session.

Logical/reference functions such as IF SUMIF COUNTIF SUMIFS SUMPRODUCT should not miss out too!

So if you want a strong foundation in Excel or become an expert at it which is crucial for building efficient financial/business models then join us!

Curriculum of Advanced Excel Workshop

Our workshop takes you to the next level after mastering basic skills, focusing on complex formulas and advanced data analysis techniques in Excel. The emphasis is placed on using Excel for fast data analysis and presentation.

Advanced Formulas and Analysis:

Combining multiple functions (VLOOKUP + MATCH, INDEX + MATCH, VLOOKUP + IF)

Applying the OFFSET function

Techniques for Sensitivity Analysis

Application of Scenario Manager

Management of iterative calculations

Statistical Analysis (Correlation, Regression, Variance)

Summarizing data with INDIRECT function

Charting and Visualization:

Making appropriate charts (bar, pie etc.)

Using dynamic charts and Name Manager

Advanced chart types (Waterfall, Thermometer)

Charts with Sensitivity analysis

Charts with Form Controls that are interactive

Practical Application:

Building dashboards using advanced formulas, conditional formatting and charting techniques

PowerPoint Training: Creating impactful slides through data representation including effective charting as well as visual appeal.

Key Learning Outcomes:

Efficiently analyzing data with advanced excel functions

Professional charting & Data Visualization

Creation of comprehensive dashboards

Effective PowerPoint presentations fit for corporate standards.

This workshop equips you with practical skills needed for a finance analyst role where complex data analysis becomes simple yet impactful when presented.

No one can become a financial analyst without knowing accounting and financial statement analysis required for investment finance field for analysing the financial performance.  The investment banking course offered by Mentor Me will teach you financial accounting , analysis, various line items from the basics.

• Introduction to Fundamental Analysis Framework– Annual report reading, Con Call reports, Quarterly reports, statement of change in equity, Supplementary information

• Financial statement linkages and creating financial statement in excel

• Income statement– Revenue recognition principles, Expense recognition principles, Diluted EPS, EPS, LIFO, FIFIO,AVCO

• Balance Sheet– Format of balance sheet, current assets, current liabilities, Fixed assets, Non current liabilities

• Cash flow statement– Format of cash flow statement, Direct method , Indirect method, FCFF, FCFEE

• Ratio analysis– Solvency Ratios, Profitability ratios, Activity Ratios.

Ratio Analysis Case Study- Analyse persistent systems annual report

• How to Read an annual Report step by step

• Franchisee Business Model Valuation- NPV , IRR, Sensitivity analysis

• Minority Interest, Impairment, Good will analysis

Trading Comps Valuation Technique

Investment bankers and finance professionals widely use the trading comps valuation method, which compares a company with other similar companies to find its market value. In this course you will learn:

Building Trading Comps: From choosing peers to analyzing final output.

Understanding Multiples: How they are compared and used, the reasons for their differences, and how to deal with them.

Detailed Analysis:

Constructing analyses (enterprise value, latest twelve months, cleaning financials, calculating multiples)

Convertible securities impact, leases, R&D expenses

Different multiples in same sector and why they vary

IPO valuation multiples

Regression analysis on multiples

Industry relevant multiple

High growth vs low multiple scenarios

Differences among industry multiples and their drivers

Peer selection when there are no similar listed companies available

By taking this comprehensive approach you will be able to use trading comps effectively for accurate company valuation.

Investment bankers use the precedent transaction method or deal comps as a vital valuation technique to supplement trading comps and DCF valuation. To find out what a deal is worth, this method looks at past deals that have been done under similar circumstances.

Key Points:

Building Transaction Comps: Involves calculating transaction multiples, cleaning up financials, benchmarking multiples among others.

Comparative Study: The distinction between transaction and trading comps.

Controlling Premium: Its effect on multiples and how to measure it.

Right Situations: When to apply transaction comp multiples for accurate valuation.

Market behavior is better understood through this approach which also assists in valuing firms based on historical transactions data.

Check out our demo class of financial modeling valuation .

This is the final section before the specialization kicks in. In this section we will take a publicly listed company from NSE stock exchange and create a DCF Valuation Model and Relative /Comparable analysis financial model. This is one of the other applications of financial modeling in decision making. This model is specifically useful for people who want to pursue to join equity research and Investment banking

1. Valuation Basics- DCF, Gordon growth, WACC, Cost of equity , Levered, Un levered Beta, Terminal Value

2. Creating a model template

3. Data collection and data feeding in financial model

4. Revenue Driver- breaking the business into Price and quantity metrics, so that you can forecast those metrics

5. Cost Driver

6. Debt Schedule , Asset schedule Forecast

7. Free Cash flow calculation

8. Valuation Calculation

9. Sensitivity Analysis

10. Report Writing

Check out our demo class of financial modeling valuation .

This is the final section before the specialization kicks in. In this section we will take a publicly listed company from NSE stock exchange and create a DCF Valuation Model and Relative /Comparable analysis financial model. This is one of the other applications of financial modeling in decision making. This model is specifically useful for people who want to pursue to join equity research and Investment banking

1. Valuation Basics- DCF, Gordon growth, WACC, Cost of equity , Levered, Un levered Beta, Terminal Value

2. Creating a model template

3. Data collection and data feeding in financial model

4. Revenue Driver- breaking the business into Price and quantity metrics, so that you can forecast those metrics

5. Cost Driver

6. Debt Schedule , Asset schedule Forecast

7. Free Cash flow calculation

8. Valuation Calculation

9. Sensitivity Analysis

10. Report Writing

This is our major success metric at Mentor Me, your placement. With over a decade of experience in this field, we have developed resources and process which will make you polished for the interview and job in investment banking and research. This module will include

• Employability quizzes for each skill tested in the interview

• Case studies practice for interview

• Written test question bank

• Mock Interviews- Face to face

• Stress Interviews

• CV Edits and recommendation

• Soft Questions practice for HR Rounds

More and more finance Jobs require candidates to know the basics of python. In the Financial modeling course with placement in the weekday program we cover

• Python basics
• Data Sets
• Data visualisation using matplotlib and seaborn
• Linear and logistic Regression machine learning models using python.

Case study for finance on python.

  Module 1: Power BI Set up

    Learn the basic set up requirements of Microsoft Power BI & Overview of the major functionalities.

  Module 2: EDA Using Power BI

   Learn how to use the easy to use power BI Functionalities, to explore the data. Before beginning any analysis further

 Module 3: Data Visualization with Reports        Learn how to create beautiful charts and data presentation using Power BI

      Module 4: Dashboards using Power BI

    Learn how to create powerful interactive dashboards to summarize the data analysis in Power B

• Sql introduction
• SqL Operators
• Data tables in SQL
• Major Sql functions
• SQL Data base

• 4 Technical Mocks
• Interview cases role wise
• Face to face advice questions  in finance 
• General Market Questions
• Practice Questions

• Vocabulary Training
• Role Play
• Non Verbal Communication
• Difficult HR Questions