diff --git a/.Jules/palette.md b/.Jules/palette.md
new file mode 100644
index 0000000..320601a
--- /dev/null
+++ b/.Jules/palette.md
@@ -0,0 +1,3 @@
+## 2024-05-23 - CLI Visual Hierarchy
+**Learning:** CLI tools often neglect visual hierarchy. Adding simple colors (Green for good, Red for bad, Purple for headers) and emojis drastically improves scannability and "delight" without adding heavy dependencies.
+**Action:** For future CLI tools, always implement a basic `Colors` class or use `rich`/`click` to ensure the user isn't staring at a wall of white text.
diff --git a/bitcoin_trading_simulation.py b/bitcoin_trading_simulation.py
index e619723..cbbf2f8 100644
--- a/bitcoin_trading_simulation.py
+++ b/bitcoin_trading_simulation.py
@@ -1,6 +1,17 @@
 import numpy as np
 import pandas as pd
 
+class Colors:
+    HEADER = '\033[95m'
+    BLUE = '\033[94m'
+    CYAN = '\033[96m'
+    GREEN = '\033[92m'
+    WARNING = '\033[93m'
+    FAIL = '\033[91m'
+    ENDC = '\033[0m'
+    BOLD = '\033[1m'
+    UNDERLINE = '\033[4m'
+
 def simulate_bitcoin_prices(days=60, initial_price=50000, volatility=0.02):
     """
     Simulates Bitcoin prices for a given number of days using Geometric Brownian Motion.
@@ -47,11 +58,11 @@ def simulate_trading(signals, initial_cash=10000):
     """
     portfolio = pd.DataFrame(index=signals.index).fillna(0.0)
     portfolio['price'] = signals['price']
-    portfolio['cash'] = initial_cash
+    portfolio['cash'] = float(initial_cash)
     portfolio['btc'] = 0.0
     portfolio['total_value'] = portfolio['cash']
 
-    print("------ Daily Trading Ledger ------")
+    print(f"\n{Colors.HEADER}{Colors.BOLD}------ 📊 Daily Trading Ledger ------{Colors.ENDC}")
     for i, row in signals.iterrows():
         if i > 0:
             portfolio.loc[i, 'cash'] = portfolio.loc[i-1, 'cash']
@@ -62,14 +73,14 @@ def simulate_trading(signals, initial_cash=10000):
             btc_to_buy = portfolio.loc[i, 'cash'] / row['price']
             portfolio.loc[i, 'btc'] += btc_to_buy
             portfolio.loc[i, 'cash'] -= btc_to_buy * row['price']
-            print(f"Day {i}: Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}")
+            print(f"{Colors.GREEN}🟢 Day {i}: Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
 
         # Sell signal
         elif row['positions'] == -2.0:
             if portfolio.loc[i, 'btc'] > 0:
                 cash_received = portfolio.loc[i, 'btc'] * row['price']
                 portfolio.loc[i, 'cash'] += cash_received
-                print(f"Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}")
+                print(f"{Colors.FAIL}🔴 Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
                 portfolio.loc[i, 'btc'] = 0
 
         portfolio.loc[i, 'total_value'] = portfolio.loc[i, 'cash'] + portfolio.loc[i, 'btc'] * row['price']
@@ -99,9 +110,14 @@ def simulate_trading(signals, initial_cash=10000):
     buy_and_hold_btc = initial_cash / prices.iloc[0]
     buy_and_hold_value = buy_and_hold_btc * prices.iloc[-1]
     
-    print("\n------ Final Portfolio Performance ------")
+    print(f"\n{Colors.HEADER}{Colors.BOLD}------ 📈 Final Portfolio Performance ------{Colors.ENDC}")
     print(f"Initial Cash: ${initial_cash:.2f}")
     print(f"Final Portfolio Value: ${final_value:.2f}")
-    print(f"Profit/Loss: ${profit:.2f}")
+
+    if profit >= 0:
+        print(f"{Colors.GREEN}💰 Profit: ${profit:.2f}{Colors.ENDC}")
+    else:
+        print(f"{Colors.FAIL}📉 Loss: ${profit:.2f}{Colors.ENDC}")
+
     print(f"Buy and Hold Strategy Value: ${buy_and_hold_value:.2f}")
-    print("-----------------------------------------")
+    print(f"{Colors.HEADER}-----------------------------------------{Colors.ENDC}")