Financial Statement Analysis

Python
# Core analysis template
import pandas as pd
import numpy as np

# Load financial data
df = pd.read_excel('financials.xlsx', sheet_name=['BS', 'IS', 'CF'])

# Calculate YoY growth
for col in df['IS'].select_dtypes(include=[np.number]).columns[1:]:
    df['IS'][f'{col}_growth'] = df['IS'][col].pct_change() * 100

# Key liquidity ratios
current_ratio = df['BS']['Current Assets'] / df['BS']['Current Liabilities']
quick_ratio = (df['BS']['Current Assets'] - df['BS']['Inventory']) / df['BS']['Current Liabilities']

Progress:

• Data extraction and validation
• YoY growth calculation for all line items
• Key ratio computation (liquidity, leverage, profitability, efficiency)
• Trend analysis over 3-5 years
• Red flag identification
• Quality of earnings assessment
• Executive summary creation
• Dashboard visualization

Step 1: Data Validation

• Verify mathematical consistency (BS balances, cash flow ties)
• Check for restatements or accounting changes
• Identify one-time items and extraordinary charges

Step 2: Growth Analysis

Calculate YoY growth for:

• Revenue and segments
• Operating expenses by category
• Net income and EPS
• Balance sheet items (assets, debt, equity)

Step 3: Ratio Calculation

Liquidity:

• Current Ratio = Current Assets / Current Liabilities
• Quick Ratio = (Current Assets - Inventory) / Current Liabilities
• Cash Ratio = Cash / Current Liabilities

Leverage:

• Debt-to-Equity = Total Debt / Total Equity
• Interest Coverage = EBIT / Interest Expense
• Debt Service Coverage = Operating Cash Flow / Total Debt Service

Profitability:

• Gross Margin = Gross Profit / Revenue
• Operating Margin = Operating Income / Revenue
• ROE = Net Income / Average Shareholders' Equity
• ROA = Net Income / Average Total Assets

Efficiency:

• Asset Turnover = Revenue / Average Total Assets
• Inventory Turnover = COGS / Average Inventory
• Receivables Turnover = Revenue / Average AR

Step 4: Red Flag Detection

• Revenue recognition irregularities (DSO spikes, revenue without cash)
• Expense capitalization (unusual increases in capitalized costs)
• Working capital manipulation (unusual payable extensions)
• Related party transactions
• Goodwill impairments or asset write-downs

Example 1: Input: XYZ Corp income statements 2021-2023, balance sheets, cash flow statements Output:

• Revenue CAGR: 12.5%
• Operating margin deterioration: 15.2% → 11.8%
• Current ratio declining: 2.1 → 1.4 (industry avg: 1.8)
• RED FLAG: DSO increased 45 days, suggesting revenue quality issues

Example 2: Input: Manufacturing company with 5-year history Output:

• Asset turnover declining: 1.2x → 0.8x (efficiency concern)
• Debt-to-equity rising: 0.4 → 0.8 (leverage risk)
• Interest coverage strong: 8.5x (adequate buffer)
• Quality score: 7/10 (inventory buildup concern)

• Always analyze 3-5 year trends, not just year-over-year
• Compare ratios to industry benchmarks using sources like Bloomberg, S&P Capital IQ
• Focus on operating metrics before non-recurring items
• Reconcile cash flow to net income (quality of earnings)
• Weight recent periods more heavily in trend analysis
• Use median values for volatile metrics
• Create ratio charts with industry percentile bands

• Don't ignore footnotes - Critical information on accounting policies, contingencies
• Don't rely on single metrics - Use multiple ratios for comprehensive view
• Don't compare across industries without adjusting for sector differences
• Don't miss seasonality - Use appropriate time periods for cyclical businesses
• Don't overlook cash conversion - Profitable companies can still fail from cash issues
• Don't trust adjusted metrics blindly - Verify management's non-GAAP adjustments
• Don't ignore segment performance - Aggregate numbers can mask underlying issues

Create Excel templates with automated ratio calculations and conditional formatting for red flags. Use pivot tables for multi-period trend analysis and Power Query for data refresh capabilities.