single_stock_analyzer.py

Overview

single_stock_analyzer.py is a comprehensive stock analysis utility that extracts and calculates detailed fundamental metrics for any stock from the fundamental_data.json file. It provides deep quarterly and annual financial analysis including P&L statements, ratios, growth metrics, and shareholding patterns.

Purpose

This utility serves to:

Deep-Dive Analysis: Examine individual stock fundamentals in detail
Quick Lookups: Get instant fundamental snapshot for any symbol
Trend Analysis: Calculate QoQ and YoY growth metrics
Valuation Metrics: Compute PEG, Forward P/E, and other valuation ratios
Shareholding Insights: Track institutional ownership changes

How It’s Used

This is a command-line utility that analyzes data from the main pipeline output:

# Analyze a specific stock
python3 single_stock_analyzer.py RELIANCE

# Analyze another stock
python3 single_stock_analyzer.py TCS

Prerequisite:

fundamental_data.json must exist in the same directory (generated by fetch_fundamental_data.py)

What It Analyzes

The analyzer extracts and calculates comprehensive metrics across multiple categories:

1. Profit & Loss (Net Profit)

Latest quarter net profit
Previous 3 quarters
Year-ago quarter (for YoY comparison)
QoQ % change
YoY % change

Latest quarter EPS
Previous 3 quarters
Year-ago quarter EPS
Last year annual EPS
2 years back annual EPS
QoQ % change
YoY % change

3. Sales (Revenue)

Latest quarter sales
Previous 3 quarters
Year-ago quarter sales
Current year annual sales
5 years ago sales
QoQ % change
YoY % change
5-Year CAGR (Compound Annual Growth Rate)

4. Operating Profit Margin (OPM)

Latest quarter OPM
Previous 3 quarters
Year-ago quarter OPM
TTM (Trailing Twelve Months) OPM
QoQ % change
YoY % change

5. Valuation Ratios

ROE (Return on Equity)
ROCE (Return on Capital Employed)
P/E Ratio (Price to Earnings)
D/E Ratio (Debt to Equity)
PEG Ratio (P/E to Growth)
Forward P/E (estimated)

6. Shareholding Patterns

FII % (Foreign Institutional Investors)
DII % (Domestic Institutional Investors)
QoQ Change in FII/DII holdings

API Reference

Helper Functions

`get_float()`

Safely converts a value to float, returning 0.0 on failure.

value_str

any

The value to convert to float (can be string, int, float, or None).

Returns: float

eps = get_float("12.50")  # Returns 12.50
eps = get_float(None)     # Returns 0.0
eps = get_float("N/A")    # Returns 0.0

`calculate_change()`

Calculates percentage change between two values.

current

float

Current period value

float

Previous period value

Returns: float - Percentage change Formula:

change = ((current - previous) / abs(previous)) * 100

Example:

qoq_growth = calculate_change(100, 80)   # Returns 25.0 (25% growth)
yoy_decline = calculate_change(80, 100)  # Returns -20.0 (20% decline)

`get_value_from_pipe_string()`

Extracts a specific value from pipe-delimited string.

pipe_string

str

Pipe-delimited string (e.g., “10.5|9.2|8.7|7.5”)

index

int

Zero-based index of the value to extract

Returns: float Example:

# Quarterly data: "12.5|11.0|10.5|9.8"
latest = get_value_from_pipe_string("12.5|11.0|10.5|9.8", 0)  # Returns 12.5
prev = get_value_from_pipe_string("12.5|11.0|10.5|9.8", 1)    # Returns 11.0

Main Function

`analyze_stock()`

Performs comprehensive fundamental analysis for a given stock symbol.

symbol_to_find

str

Stock symbol to analyze (e.g., “RELIANCE”, “TCS”, “INFY”)

Returns: None (prints analysis to console) Data Sources: The function extracts data from multiple sections of fundamental_data.json:

stock_data = {
    "Symbol": "RELIANCE",
    "incomeStat_cq": {},    # Current Quarter income statement
    "incomeStat_cy": {},    # Current Year annual income statement
    "TTM_cy": {},           # Trailing Twelve Months
    "CV": {},               # Current Valuation
    "roce_roe": {},         # Return ratios
    "sHp": {},              # Shareholding Pattern
    "bs_c": {}              # Balance Sheet Consolidated
}

Output Format

The analyzer prints a detailed report to the console:

--- Analysis for RELIANCE ---

Net Profit Latest Quarter: 15000.0
Net Profit Previous Quarter: 14500.0
Net Profit 2 Quarters Back: 14000.0
Net Profit 3 Quarters Back: 13500.0
Net Profit Last Year Quarter: 12000.0
QoQ % Net Profit Latest: 3.45%
YoY % Net Profit Latest: 25.00%

EPS Latest Quarter: 22.50
EPS Previous Quarter: 21.75
EPS 2 Quarters Back: 21.00
EPS 3 Quarters Back: 20.25
EPS Last Year Quarter: 18.00
QoQ % EPS Latest: 3.45%
YoY % EPS Latest: 25.00%
EPS Last Year: 85.00
EPS 2 Years Back: 75.00

Sales Latest Quarter: 200000.0
Sales Previous Quarter: 195000.0
Sales 2 Quarters Back: 190000.0
Sales 3 Quarters Back: 185000.0
Sales Last Year Quarter: 175000.0
QoQ % Sales Latest: 2.56%
YoY % Sales Latest: 14.29%
Sales Growth 5 Years(%): 12.50%

OPM Latest Quarter: 15.5
OPM Previous Quarter: 15.2
OPM 2 Quarters Back: 14.8
OPM 3 Quarters Back: 14.5
OPM Last Year Quarter: 14.0
QoQ % OPM Latest: 1.97%
YoY % OPM Latest: 10.71%

Latest Quarter: Mar 2024
ROE(%): 12.5
ROCE(%): 14.2
D/E: 0.65
OPM TTM(%): 15.1
P/E: 28.5
FII % change QoQ: 1.25%
DII % change QoQ: -0.50%
PEG: 1.14
Forward P/E: 26.80
Historical P/E 5: 0 (Data Unavailable)

Usage

Command Line

# Analyze a stock
python3 single_stock_analyzer.py RELIANCE

# Without arguments, shows usage
python3 single_stock_analyzer.py
# Output: Usage: python3 analyze_stock.py <SYMBOL>
#         Example: python3 analyze_stock.py RELIANCE

Programmatic Usage

from single_stock_analyzer import analyze_stock

# Analyze a stock programmatically
analyze_stock("TCS")
analyze_stock("INFY")

Source Code

import json
import sys

def get_float(value_str):
    try:
        return float(value_str)
    except (ValueError, TypeError):
        return 0.0

def calculate_change(current, previous):
    if previous == 0:
        return 0.0
    return ((current - previous) / abs(previous)) * 100

def get_value_from_pipe_string(pipe_string, index):
    if not pipe_string:
        return 0.0
    parts = pipe_string.split('|')
    if index < len(parts):
        return get_float(parts[index])
    return 0.0

def analyze_stock(symbol_to_find):
    input_file = "fundamental_data.json"
    
    try:
        with open(input_file, "r") as f:
            data = json.load(f)
    except FileNotFoundError:
        print(f"Error: {input_file} not found.")
        return

    stock_data = None
    for item in data:
        if item.get("Symbol") == symbol_to_find:
            stock_data = item
            break
    
    if not stock_data:
        print(f"Stock '{symbol_to_find}' not found in database.")
        return

    # --- Extract Data Sections ---
    cq = stock_data.get("incomeStat_cq", {})
    cy = stock_data.get("incomeStat_cy", {})
    ttm_cy = stock_data.get("TTM_cy", {})
    cv = stock_data.get("CV", {})
    roce_roe = stock_data.get("roce_roe", {})
    shp = stock_data.get("sHp", {})
    bs_c = stock_data.get("bs_c", {})  # Balance Sheet Consolidated

    # Calculate all metrics (Net Profit, EPS, Sales, OPM, Ratios, etc.)
    # ... [Full calculation logic from source code] ...
    
    # Print comprehensive analysis
    print(f"--- Analysis for {symbol_to_find} ---")
    # ... [Full output format] ...

if __name__ == "__main__":
    if len(sys.argv) > 1:
        analyze_stock(sys.argv[1])
    else:
        print("Usage: python3 analyze_stock.py <SYMBOL>")
        print("Example: python3 analyze_stock.py RELIANCE")

The full source code is 202 lines. See the complete implementation in /workspace/source/DO NOT DELETE EDL PIPELINE/single_stock_analyzer.py

Key Calculations

5-Year Sales CAGR

if sales_5_years_ago > 0:
    sales_growth_5y = ((sales_current_annual / sales_5_years_ago) ** (1/5) - 1) * 100

CAGR Formula: ((End Value / Start Value)^(1/n) - 1) * 100

Debt to Equity Ratio

non_current_liab = get_value_from_pipe_string(bs_c.get("NON_CURRENT_LIABILITIES"), 0)
total_equity = get_value_from_pipe_string(bs_c.get("TOTAL_EQUITY"), 0)
de_ratio = non_current_liab / total_equity if total_equity != 0 else 0.0

PEG Ratio

peg = 0.0
if yoy_eps > 0:
    peg = pe / yoy_eps

PEG = P/E Ratio / EPS Growth Rate

Forward P/E

if eps_latest > 0:
    annualized_eps = eps_latest * 4
    ttm_eps = get_float(ttm_cy.get("EPS"))
    if annualized_eps > 0:
        forward_pe = pe * (ttm_eps / annualized_eps)

Dependencies

json: Read fundamental data file
sys: Command-line argument handling

This utility has no external dependencies beyond Python standard library.

Error Handling

File Not Found

If fundamental_data.json doesn’t exist:

Error: fundamental_data.json not found.

Solution: Run fetch_fundamental_data.py first to generate the data file.

Stock Not Found

If the symbol doesn’t exist in the database:

Stock 'INVALID' not found in database.

Solution: Check the symbol spelling or verify it exists in fundamental_data.json.

Missing Data Fields

If a stock has incomplete data, the analyzer returns 0.0 or “N/A” for missing fields rather than crashing.

Use Cases

Quick Screening

Quickly check fundamentals before making investment decisions.

Quarterly Tracking

Monitor quarter-over-quarter performance for portfolio stocks.

Comparative Analysis

Analyze multiple stocks in the same sector by running the script repeatedly.

Automated Alerts

Integrate into scripts to alert when specific metrics cross thresholds.

Integration with Pipeline

While this is a utility script, it integrates seamlessly with the main pipeline:

# Run the pipeline
python3 fetch_fundamental_data.py

# Immediately analyze any stock
python3 single_stock_analyzer.py RELIANCE

You can also create wrapper scripts for batch analysis:

# analyze_watchlist.py
from single_stock_analyzer import analyze_stock

watchlist = ["RELIANCE", "TCS", "INFY", "HDFCBANK", "ICICIBANK"]

for symbol in watchlist:
    analyze_stock(symbol)
    print("\n" + "="*50 + "\n")

Data Fetching Scripts

Processing Scripts

Standalone Scripts

Utilities

Overview

Purpose

How It’s Used

What It Analyzes

1. Profit & Loss (Net Profit)

3. Sales (Revenue)

4. Operating Profit Margin (OPM)

5. Valuation Ratios

6. Shareholding Patterns

API Reference

Helper Functions

`get_float()`

`calculate_change()`

`get_value_from_pipe_string()`

Main Function

`analyze_stock()`

Output Format

Usage

Command Line

Programmatic Usage

Source Code

Key Calculations

5-Year Sales CAGR

Debt to Equity Ratio

PEG Ratio

Forward P/E

Dependencies

Error Handling

Use Cases

Quick Screening

Quarterly Tracking

Comparative Analysis

Automated Alerts

Integration with Pipeline

Data Fetching Scripts

Processing Scripts

Standalone Scripts

Utilities

​Overview

​Purpose

​How It’s Used

​What It Analyzes

​1. Profit & Loss (Net Profit)

​2. Earnings Per Share (EPS)

​3. Sales (Revenue)

​4. Operating Profit Margin (OPM)

​5. Valuation Ratios

​6. Shareholding Patterns

​API Reference

​Helper Functions

​get_float()

​calculate_change()

​get_value_from_pipe_string()

​Main Function

​analyze_stock()

​Output Format

​Usage

​Command Line

​Programmatic Usage

​Source Code

​Key Calculations

​5-Year Sales CAGR

​Debt to Equity Ratio

​PEG Ratio

​Forward P/E

​Dependencies

​Error Handling

​Use Cases

Quick Screening

Quarterly Tracking

Comparative Analysis

Automated Alerts

​Integration with Pipeline

Overview

Purpose

How It’s Used

What It Analyzes

1. Profit & Loss (Net Profit)

2. Earnings Per Share (EPS)

3. Sales (Revenue)

4. Operating Profit Margin (OPM)

5. Valuation Ratios

6. Shareholding Patterns

API Reference

Helper Functions

`get_float()`

`calculate_change()`

`get_value_from_pipe_string()`

Main Function

`analyze_stock()`

Output Format

Usage

Command Line

Programmatic Usage

Source Code

Key Calculations

5-Year Sales CAGR

Debt to Equity Ratio

PEG Ratio

Forward P/E

Dependencies

Error Handling

Use Cases

Integration with Pipeline