diff --git a/frontend/visualization/indicators.py b/frontend/visualization/indicators.py
index 086fd90..7f857c7 100644
--- a/frontend/visualization/indicators.py
+++ b/frontend/visualization/indicators.py
@@ -1,21 +1,43 @@
+import pandas as pd
 import pandas_ta as ta  # noqa: F401
 import plotly.graph_objects as go
 
 from frontend.visualization import theme
 
 
-def get_bbands_traces(candles, bb_length, bb_std):
+def get_bbands_traces(df, bb_length, bb_std):
     tech_colors = theme.get_color_scheme()
-    candles.ta.bbands(length=bb_length, std=bb_std, append=True)
+    df.ta.bbands(length=bb_length, std=bb_std, append=True)
     bb_lower = f'BBL_{bb_length}_{bb_std}'
     bb_middle = f'BBM_{bb_length}_{bb_std}'
     bb_upper = f'BBU_{bb_length}_{bb_std}'
     traces = [
-        go.Scatter(x=candles.index, y=candles[bb_upper], line=dict(color=tech_colors['upper_band']),
+        go.Scatter(x=df.index, y=df[bb_upper], line=dict(color=tech_colors['upper_band']),
                    name='Upper Band'),
-        go.Scatter(x=candles.index, y=candles[bb_middle], line=dict(color=tech_colors['middle_band']),
+        go.Scatter(x=df.index, y=df[bb_middle], line=dict(color=tech_colors['middle_band']),
                    name='Middle Band'),
-        go.Scatter(x=candles.index, y=candles[bb_lower], line=dict(color=tech_colors['lower_band']),
+        go.Scatter(x=df.index, y=df[bb_lower], line=dict(color=tech_colors['lower_band']),
                    name='Lower Band'),
     ]
     return traces
+
+
+def get_volume_trace(df):
+    df.index = pd.to_datetime(df.timestamp, unit='ms')
+    return go.Bar(x=df.index, y=df['volume'], name="Volume", marker_color=theme.get_color_scheme()["volume"], opacity=0.7)
+
+def get_macd_traces(df, macd_fast, macd_slow, macd_signal):
+    tech_colors = theme.get_color_scheme()
+    df.ta.macd(fast=macd_fast, slow=macd_slow, signal=macd_signal, append=True)
+    macd = f'MACD_{macd_fast}_{macd_slow}_{macd_signal}'
+    macd_s = f'MACDs_{macd_fast}_{macd_slow}_{macd_signal}'
+    macd_hist = f'MACDh_{macd_fast}_{macd_slow}_{macd_signal}'
+    traces = [
+        go.Scatter(x=df.index, y=df[macd], line=dict(color=tech_colors['macd_line']),
+                   name='MACD Line'),
+        go.Scatter(x=df.index, y=df[macd_s], line=dict(color=tech_colors['macd_signal']),
+                   name='MACD Signal'),
+        go.Bar(x=df.index, y=df[macd_hist], name='MACD Histogram',
+               marker_color=df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"].apply(lambda x: '#FF6347' if x < 0 else '#32CD32'))
+    ]
+    return traces
\ No newline at end of file
diff --git a/frontend/visualization/signals.py b/frontend/visualization/signals.py
index 81055a8..6762c7c 100644
--- a/frontend/visualization/signals.py
+++ b/frontend/visualization/signals.py
@@ -3,9 +3,10 @@ import plotly.graph_objects as go
 import pandas_ta as ta  # noqa: F401
 
 
-def add_bbands_with_threshold(fig, candles, bb_length, bb_std, bb_long_threshold, bb_short_threshold, row=1, col=1):
+def get_bollinger_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold):
     tech_colors = theme.get_color_scheme()
     # Add Bollinger Bands
+    candles = df.copy()
     candles.ta.bbands(length=bb_length, std=bb_std, append=True)
 
     # Generate conditions
@@ -13,10 +14,39 @@ def add_bbands_with_threshold(fig, candles, bb_length, bb_std, bb_long_threshold
     sell_signals = candles[candles[f"BBP_{bb_length}_{bb_std}"] > bb_short_threshold]
 
     # Signals plot
-    fig.add_trace(go.Scatter(x=buy_signals.index, y=buy_signals['close'], mode='markers',
-                             marker=dict(color=tech_colors['buy_signal'], size=10, symbol='triangle-up'),
-                             name='Buy Signal'), row=row, col=col)
-    fig.add_trace(go.Scatter(x=sell_signals.index, y=sell_signals['close'], mode='markers',
-                             marker=dict(color=tech_colors['sell_signal'], size=10, symbol='triangle-down'),
-                             name='Sell Signal'), row=row, col=col)
-    return fig
+    traces = [
+        go.Scatter(x=buy_signals.index, y=buy_signals['close'], mode='markers',
+                   marker=dict(color=tech_colors['buy_signal'], size=10, symbol='triangle-up'),
+                   name='Buy Signal'),
+        go.Scatter(x=sell_signals.index, y=sell_signals['close'], mode='markers',
+                   marker=dict(color=tech_colors['sell_signal'], size=10, symbol='triangle-down'),
+                   name='Sell Signal')
+    ]
+    return traces
+
+
+def get_macdbb_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold, macd_fast, macd_slow,
+                                macd_signal):
+    tech_colors = theme.get_color_scheme()
+    # Add Bollinger Bands
+    df.ta.bbands(length=bb_length, std=bb_std, append=True)
+    # Add MACD
+    df.ta.macd(fast=macd_fast, slow=macd_slow, signal=macd_signal, append=True)
+    # Decision Logic
+    bbp = df[f"BBP_{bb_length}_{bb_std}"]
+    macdh = df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"]
+    macd = df[f"MACD_{macd_fast}_{macd_slow}_{macd_signal}"]
+
+    buy_signals = df[(bbp < bb_long_threshold) & (macdh > 0) & (macd < 0)]
+    sell_signals = df[(bbp > bb_short_threshold) & (macdh < 0) & (macd > 0)]
+
+    # Signals plot
+    traces = [
+        go.Scatter(x=buy_signals.index, y=buy_signals['close'], mode='markers',
+                   marker=dict(color=tech_colors['buy_signal'], size=10, symbol='triangle-up'),
+                   name='Buy Signal'),
+        go.Scatter(x=sell_signals.index, y=sell_signals['close'], mode='markers',
+                   marker=dict(color=tech_colors['sell_signal'], size=10, symbol='triangle-down'),
+                   name='Sell Signal')
+    ]
+    return traces