Method to Identify Stocks with Positive VDCA After Liabilities

I want to use a method called VERY DISCOUNTED CURRENT ASSET to analyze stocks. Defining VERY DISCOUNTED CURRENT ASSET(VDCA) as 0.7account receivable+0.5Inventory+cash, can you help me find stocks which have positive value after we minus the VDCA with its total liability?

To find stocks that have a positive value after subtracting the Very Discounted Current Asset (VDCA) from their total liabilities, you will need to follow these steps:

1. Collect Financial Data: Gather the necessary financial data for the stocks you are interested in. This includes:

   • Accounts Receivable
   • Inventory
   • Cash
   • Total Liabilities

2. Calculate VDCA: Use the formula you provided to calculate the VDCA for each stock: [ \text{VDCA} = 0.7 \times \text{Accounts Receivable} + 0.5 \times \text{Inventory} + \text{Cash} ]

3. Subtract Total Liabilities: Subtract the total liabilities from the VDCA to determine if the result is positive: [ \text{VDCA - Total Liabilities} ]

4. Filter Stocks: Identify stocks where the result of the above calculation is positive.

Example Calculation

Let's assume you have the following data for a stock:

• Accounts Receivable: $1,000,000
• Inventory: $500,000
• Cash: $200,000
• Total Liabilities: $1,000,000

First, calculate the VDCA: [ \text{VDCA} = 0.7 \times 1,000,000 + 0.5 \times 500,000 + 200,000 = 700,000 + 250,000 + 200,000 = 1,150,000 ]

Next, subtract the total liabilities: [ \text{VDCA - Total Liabilities} = 1,150,000 - 1,000,000 = 150,000 ]

Since the result is positive ($150,000), this stock meets your criteria.

Tools and Resources

To perform this analysis on a large number of stocks, you can use financial data platforms such as:

• Yahoo Finance
• Google Finance
• Bloomberg
• Morningstar
• Financial Statements from Company Websites

Automating the Process

If you want to automate this process, you can use programming languages like Python with libraries such as pandas for data manipulation and yfinance for fetching financial data. Here is a basic example of how you might do this in Python:

import yfinance as yf
import pandas as pd

# List of stock tickers you are interested in
tickers = ['AAPL', 'MSFT', 'GOOGL', 'AMZN']

# Function to calculate VDCA
def calculate_vdca(ticker):
    stock = yf.Ticker(ticker)
    balance_sheet = stock.balance_sheet
    accounts_receivable = balance_sheet.loc['Net Receivables'][0]
    inventory = balance_sheet.loc['Inventory'][0]
    cash = balance_sheet.loc['Cash'][0]
    total_liabilities = balance_sheet.loc['Total Liab'][0]
    
    vdca = 0.7 * accounts_receivable + 0.5 * inventory + cash
    return vdca - total_liabilities

# DataFrame to store results
results = pd.DataFrame(columns=['Ticker', 'VDCA - Total Liabilities'])

# Calculate for each ticker
for ticker in tickers:
    try:
        result = calculate_vdca(ticker)
        results = results.append({'Ticker': ticker, 'VDCA - Total Liabilities': result}, ignore_index=True)
    except Exception as e:
        print(f"Error processing {ticker}: {e}")

# Filter stocks with positive VDCA - Total Liabilities
positive_stocks = results[results['VDCA - Total Liabilities'] > 0]
print(positive_stocks)

This script fetches the necessary financial data for each stock, calculates the VDCA, and then filters out the stocks with a positive VDCA after subtracting total liabilities. Note that you may need to handle exceptions and data availability issues depending on the specific stocks and data sources.