Financial Ratio Analysis

Introduction to Financial Ratio Analysis

Financial ratio analysis is the process of evaluating a company's financial statements to assess its performance, liquidity, and solvency. Ratios transform raw financial data into comparable metrics usable across companies and time periods.

Ratios are only meaningful when compared against industry benchmarks, historical trends, or competitor data. A single ratio in isolation tells you very little.

Liquidity Ratios

Liquidity ratios measure a firm's ability to meet short-term obligations without raising external capital.

Current Ratio

$\text{Current Ratio} = \frac{\text{Current Assets}}{\text{Current Liabilities}}$

Interpretation:

• $> 2$: Excellent short-term liquidity
• $1.5 - 2$: Acceptable
• $< 1$: Potential liquidity crisis (current liabilities exceed current assets)

Quick (Acid-Test) Ratio

Excludes inventory (least liquid current asset):

$\text{Quick Ratio} = \frac{\text{Current Assets} - \text{Inventory}}{\text{Current Liabilities}}$

Cash Ratio

Most conservative liquidity measure:

$\text{Cash Ratio} = \frac{\text{Cash + Cash Equivalents}}{\text{Current Liabilities}}$

Profitability Ratios

These measure how effectively a company generates profit from its resources.

Gross Profit Margin

$\text{Gross Profit Margin} = \frac{\text{Revenue} - \text{COGS}}{\text{Revenue}} \times 100\%$

Net Profit Margin

$\text{Net Profit Margin} = \frac{\text{Net Income}}{\text{Revenue}} \times 100\%$

Return on Equity (ROE)

$\text{ROE} = \frac{\text{Net Income}}{\text{Shareholders' Equity}} \times 100\%$

Return on Assets (ROA)

$\text{ROA} = \frac{\text{Net Income}}{\text{Total Assets}} \times 100\%$

DuPont Analysis

ROE can be decomposed using the DuPont Formula:

$\text{ROE} = \underbrace{\frac{\text{Net Income}}{\text{Revenue}}}_{\text{Profit Margin}} \times \underbrace{\frac{\text{Revenue}}{\text{Total Assets}}}_{\text{Asset Turnover}} \times \underbrace{\frac{\text{Total Assets}}{\text{Equity}}}_{\text{Financial Leverage}}$

Solvency (Leverage) Ratios

These assess long-term financial stability and reliance on debt.

Debt-to-Equity Ratio

$D/E = \frac{\text{Total Debt}}{\text{Shareholders' Equity}}$

Interest Coverage Ratio

$\text{ICR} = \frac{\text{EBIT}}{\text{Interest Expense}}$

An ICR below 1.5 signals potential default risk.

Efficiency (Activity) Ratios

Inventory Turnover

$\text{Inventory Turnover} = \frac{\text{COGS}}{\text{Average Inventory}}$

Accounts Receivable Turnover

$\text{AR Turnover} = \frac{\text{Net Credit Sales}}{\text{Average Accounts Receivable}}$

Days Sales Outstanding (DSO)

$\text{DSO} = \frac{365}{\text{AR Turnover}}$

Solved Example: ABC Manufacturing Ltd.

Given the following data (in NPR '000):

| Item | Value | |------|-------| | Current Assets | 4,500 | | Inventory | 1,200 | | Current Liabilities | 2,000 | | Revenue | 18,000 | | COGS | 12,600 | | Net Income | 2,160 | | Total Assets | 24,000 | | Shareholders' Equity | 9,600 | | Total Debt | 14,400 | | EBIT | 2,880 | | Interest Expense | 720 |

Calculations:

$\text{Current Ratio} = \frac{4,500}{2,000} = 2.25 \quad \checkmark$

$\text{Quick Ratio} = \frac{4,500 - 1,200}{2,000} = \frac{3,300}{2,000} = 1.65 \quad \checkmark$

$\text{Net Profit Margin} = \frac{2,160}{18,000} \times 100 = 12\%$

$\text{ROE} = \frac{2,160}{9,600} \times 100 = 22.5\%$

$\text{D/E Ratio} = \frac{14,400}{9,600} = 1.5$

$\text{ICR} = \frac{2,880}{720} = 4.0 \quad \text{(Healthy)}$

Python Implementation: Ratio Calculator

from dataclasses import dataclass

@dataclass
class FinancialData:
    """Financial statement data for ratio analysis."""
    current_assets: float
    current_liabilities: float
    inventory: float
    cash: float
    revenue: float
    cogs: float
    net_income: float
    total_assets: float
    shareholders_equity: float
    total_debt: float
    ebit: float
    interest_expense: float

def compute_ratios(d: FinancialData) -> dict[str, float]:
    return {
        # Liquidity
        'current_ratio':      d.current_assets / d.current_liabilities,
        'quick_ratio':        (d.current_assets - d.inventory) / d.current_liabilities,
        'cash_ratio':         d.cash / d.current_liabilities,
        # Profitability
        'gross_margin_%':     (d.revenue - d.cogs) / d.revenue * 100,
        'net_margin_%':       d.net_income / d.revenue * 100,
        'roa_%':              d.net_income / d.total_assets * 100,
        'roe_%':              d.net_income / d.shareholders_equity * 100,
        # Leverage
        'd_e_ratio':          d.total_debt / d.shareholders_equity,
        'icr':                d.ebit / d.interest_expense,
    }

# ABC Manufacturing data
abc = FinancialData(
    current_assets=4500, current_liabilities=2000,
    inventory=1200, cash=800, revenue=18000,
    cogs=12600, net_income=2160, total_assets=24000,
    shareholders_equity=9600, total_debt=14400,
    ebit=2880, interest_expense=720
)

for name, value in compute_ratios(abc).items():
    print(f"{name:20s}: {value:.2f}")