Financial Analysis

The indicative module outline is as follows:

Objectives and Framework of Financial Analysis: The purpose of financial analysis in capital markets, users and uses of financial analysis, the informational role of financial reporting, the analyst's toolkit, the impact of accounting standards on comparability, and the structure of the analytical process from data collection to investment recommendation.

Accounting Quality and Earnings Management: The concept of earnings quality, accruals and their role in financial reporting, discretionary versus non-discretionary accruals, earnings management techniques and incentives, red flags in financial statements, the Beneish M-Score model, and the implications of accounting choice for financial analysis.

Profitability Analysis: Gross profit margin, operating profit margin, net profit margin, return on assets, return on equity, return on invested capital, DuPont decomposition and its three- and five-factor extensions, economic value added, and the interpretation of profitability trends across industries and business cycles.

Liquidity, Efficiency, and Working Capital Analysis: Current ratio, quick ratio, cash ratio, operating cash flow ratio, working capital management and the cash conversion cycle, inventory turnover, receivables turnover, payables turnover, and the assessment of short-term financial health and operational efficiency.

Leverage and Solvency Analysis: Debt-to-equity ratio, debt-to-assets ratio, interest coverage ratio, fixed charge coverage, financial and operating leverage, the implications of off-balance-sheet financing, lease obligations and their analytical treatment under IFRS 16, and the assessment of long-term solvency and capital structure risk.

Cash Flow Analysis: Structure and interpretation of the statement of cash flows, the distinction between operating, investing, and financing cash flows, free cash flow to the firm and free cash flow to equity, cash flow-based performance metrics, and the reconciliation of earnings and cash flows as a quality-of-earnings diagnostic.

Financial Forecasting and Pro Forma Analysis: Forecasting revenue growth and profit margins, percentage-of-sales method, constructing pro forma income statements, balance sheets, and cash flow statements, scenario and sensitivity analysis, and the integration of forecasted financials into valuation models.

Equity Valuation I — Discounted Cash Flow Models: Discounted cash flow valuation framework, free cash flow to the firm and free cash flow to equity models, terminal value estimation using the Gordon Growth Model and exit multiples, the weighted average cost of capital as the discount rate, and sensitivity analysis in DCF valuation.

Equity Valuation II — Relative Valuation and Residual Income: Price-to-earnings, price-to-book, enterprise value-to-EBITDA, and price-to-sales multiples, selection and application of comparable companies, the residual income model and its link to accounting return on equity, and the reconciliation of intrinsic and relative valuation approaches.

Credit Analysis and Financial Distress: The objectives of credit analysis, quantitative and qualitative dimensions of creditworthiness, the Altman Z-score and its extensions for private and non-manufacturing firms, credit ratings and their analytical basis, early warning signals of financial distress embedded in financial statements, and the implications for lenders and equity investors.

Segment Analysis and Off-Balance-Sheet Items: Segment reporting under IFRS 8 and its analytical value, geographic and product segment analysis, the identification and analytical treatment of off-balance-sheet exposures including operating leases, pension obligations, contingent liabilities, and special purpose entities.

Integrated Financial Analysis and Equity Research: The structure and content of a professional equity research report, integrating quantitative and qualitative analysis, communicating analytical findings to investment audiences, ESG integration in financial analysis, and current developments in the practice of financial analysis including the use of alternative data and machine learning.