diff --git a/projects/forex_algo_trading.md b/projects/forex_algo_trading.md
index 86e5054..013a814 100644
--- a/projects/forex_algo_trading.md
+++ b/projects/forex_algo_trading.md
@@ -55,55 +55,64 @@ swing_trading_project/
 ```python
 import os
 import pandas as pd
-from oandapyV20 import API
+from oandapyV20 import API  # Import the Oanda API client
 import oandapyV20.endpoints.instruments as instruments
 
-# Configuration
+# Set your Oanda API credentials and configuration for data fetching
 ACCOUNT_ID = 'your_account_id_here'
 ACCESS_TOKEN = 'your_access_token_here'
-INSTRUMENTS = ['EUR_USD', 'USD_JPY', 'GBP_USD', 'AUD_USD', 'USD_CAD']  # Extendable to more pairs
-GRANULARITY = 'H4'  # Can be parameterized as needed
-DATA_DIR = 'data'
+# List of currency pairs to fetch. Add or remove pairs as needed.
+CURRENCY_PAIRS = ['EUR_USD', 'USD_JPY', 'GBP_USD', 'AUD_USD', 'USD_CAD']
+TIME_FRAME = 'H4'  # 4-hour candles, change as per your analysis needs
+DATA_DIRECTORY = 'data'  # Directory where fetched data will be saved
 
-def fetch_and_save_data(account_id, access_token, instruments, granularity, data_dir):
-    """Fetch historical forex data for specified instruments and save to CSV."""
-    client = API(access_token=access_token)
+# Ensure the data directory exists, create it if it doesn't
+if not os.path.exists(DATA_DIRECTORY):
+    os.makedirs(DATA_DIRECTORY)
+
+def fetch_and_save_forex_data(account_id, access_token, currency_pairs, time_frame, data_dir):
+    """Fetch historical forex data for specified currency pairs and save it to CSV files."""
+    # Initialize the Oanda API client with your access token
+    api_client = API(access_token=access_token)
     
-    if not os.path.exists(data_dir):
-        os.makedirs(data_dir)
-    
-    for instrument in instruments:
-        params = {
-            "granularity": granularity,
-            "count": 5000  # Adjust based on needs
-        }
+    for pair in currency_pairs:
+        # Define the parameters for the data request: time frame and number of data points
+        request_params = {"granularity": time_frame, "count": 5000}
         
-        data_request = instruments.InstrumentsCandles(instrument=instrument, params=params)
-        data = client.request(data_request)
-        candles = data.get('candles', [])
+        # Prepare the data request for fetching candle data for the current currency pair
+        data_request = instruments.InstrumentsCandles(instrument=pair, params=request_params)
+        # Fetch the data
+        response = api_client.request(data_request)
+        # Extract the candle data from the response
+        candle_data = response.get('candles', [])
         
-        if candles:
-            df = pd.DataFrame([{
+        # If data was fetched, proceed to save it
+        if candle_data:
+            # Convert the candle data into a pandas DataFrame
+            forex_data_df = pd.DataFrame([{
                 'Time': candle['time'],
                 'Open': float(candle['mid']['o']),
                 'High': float(candle['mid']['h']),
                 'Low': float(candle['mid']['l']),
                 'Close': float(candle['mid']['c']),
                 'Volume': candle['volume']
-            } for candle in candles])
+            } for candle in candle_data])
             
-            # Save to CSV
-            output_filename = f"{instrument.lower()}_data.csv"
-            df.to_csv(os.path.join(data_dir, output_filename), index=False)
-            print(f"Data saved for {instrument} to {output_filename}")
+            # Construct the filename for the CSV file
+            csv_filename = f"{pair.lower()}_data.csv"
+            # Save the DataFrame to a CSV file in the specified data directory
+            forex_data_df.to_csv(os.path.join(data_dir, csv_filename), index=False)
+            print(f"Data for {pair} saved to {csv_filename}")
 
 def main():
-    """Main function to orchestrate data fetching and saving."""
-    print("Fetching data for instruments...")
-    fetch_and_save_data(ACCOUNT_ID, ACCESS_TOKEN, INSTRUMENTS, GRANULARITY, DATA_DIR)
-    print("Data fetching and saving complete.")
+    """Orchestrates the data fetching and saving process."""
+    print("Starting data fetching process...")
+    # Call the function to fetch and save data for the configured currency pairs
+    fetch_and_save_forex_data(ACCOUNT_ID, ACCESS_TOKEN, CURRENCY_PAIRS, TIME_FRAME, DATA_DIRECTORY)
+    print("Data fetching process completed.")
 
 if __name__ == '__main__':
+    # Execute the script
     main()
 ```