diff --git a/stockpredictor/analysis/Analyzer.py b/stockpredictor/analysis/Analyzer.py
index b851a89..d540ef2 100644
--- a/stockpredictor/analysis/Analyzer.py
+++ b/stockpredictor/analysis/Analyzer.py
@@ -89,8 +89,9 @@ class Analyzer:
     def draw(self, stock):
 
         last_index = self.get_last_index(stock)
-        if last_index > 300:
-            index = 300  # 최대 300일치 그래프 확인
+
+        if last_index > 540:
+            index = 540  # 최대 540일치 그래프 확인
             df_stock = pd.DataFrame(stock["PRICE"][len(stock["PRICE"]) - index:])
             df_stochastic = pd.DataFrame(stock["STOCHASTIC"][len(stock["STOCHASTIC"]) - index:last_index+1])
         else:
@@ -99,6 +100,13 @@ class Analyzer:
             df_stochastic = pd.DataFrame(stock["STOCHASTIC"][:index+1])
 
         # general
+        candle_stick = go.Candlestick(x=df_stock.DATE, open=df_stock.open, high=df_stock.high, low=df_stock.low, close=df_stock.close, increasing_line_color='red', decreasing_line_color='blue')
+        avg5 = go.Scatter(x=df_stock.DATE, y=df_stock.avg5, name="avg5", line_color='#000000')
+        avg20 = go.Scatter(x=df_stock.DATE, y=df_stock.avg20, name="avg20", line_color='#f84c43')
+        avg60 = go.Scatter(x=df_stock.DATE, y=df_stock.avg60, name="avg60", line_color='#f89543')
+        avg120 = go.Scatter(x=df_stock.DATE, y=df_stock.avg120, name="avg120", line_color='#0ed604')
+        candle_data = [candle_stick, avg5, avg20, avg60, avg120]
+
         volume = go.Bar(x=df_stock.DATE, y=df_stock['volume'], name="volume")
         volume_data = [volume]
 
@@ -107,14 +115,16 @@ class Analyzer:
         slow_d = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_d'], name="Slow%D", line_color='#4169E1')
         stochastic_data = [slow_k, slow_d]
 
-        fig = subplots.make_subplots(rows=2, cols=1, subplot_titles=('거래량', 'Stochastic'))
+        fig = subplots.make_subplots(rows=3, cols=1, subplot_titles=('차트', '거래량', 'Stochastic'))
 
-        for trace in volume_data:
+        for trace in candle_data:
             fig.append_trace(trace, 1, 1)
-        for trace in stochastic_data:
+        for trace in volume_data:
             fig.append_trace(trace, 2, 1)
+        for trace in stochastic_data:
+            fig.append_trace(trace, 3, 1)
 
-        fig.update_layout(height=800)
+        fig.update_layout(height=1200, xaxis_rangeslider_visible=False)
 
         return fig
 
@@ -368,26 +378,19 @@ class Analyzer:
         return status, buy_price
 
     def getPositionalEnergy(self, stock, i):
-        # 350일 중 가장 찾은 금액과 가장 높았던 금액 중 현재가의 위치 계산
+        # 260 (= 52 * 5)일 중 가장 찾은 금액과 가장 높았던 금액 중 현재가의 위치 계산
 
         top = stock[i]['close']
         bottom = stock[i]['close']
-        price = stock[i]['close']
 
-        for i in range(8, 540):
+        for i in range(8, 260):
             if i > len(stock) or not stock[-i]:
                 break
 
             if top < stock[-i]["close"]:
                 top = stock[-i]["close"]
 
-            if stock[-i]["close"] < bottom:
-                bottom = stock[-i]["close"]
-
-        if top - bottom == 0:
-            energy = 100
-        else:
-            energy = round(((price - bottom) / (top - bottom)), 2)
+        energy = round(bottom / top, 2)
 
         return energy
 
@@ -515,7 +518,7 @@ class Analyzer:
                 isbuy = 0
 
                 # 스토케스틱이 20이하이어야 하며, 볼린저밴드 0.3 보다 작으며, 위치에너지도 0.2보다 낮다면,
-                if stochastic_score < 30 and bolingerband_score < 0.3 and positionalEnergy < 0.3:
+                if stochastic_score < 30 and bolingerband_score < 0.3 and positionalEnergy < 0.6:
                     isbuy = 1
 
                     # 위치에너지가 낮거나 240일선 아래에 있는 상태에서 상태값을 갖는 경우 매수한다.
@@ -553,7 +556,7 @@ class Analyzer:
                             if (STOCK[last_index]['close'] < STOCK[last_index]['open']) and (STOCK[last_index-1]['close'] < STOCK[last_index]['open'] and STOCK[last_index-1]['open'] < STOCK[last_index]['close']):
                                 isbuy = 5
 
-                        if isbuy==4 and stochastic_score < 30 and bolingerband_score < 0.3 and positionalEnergy < 0.3:
+                        if isbuy==4 and stochastic_score < 30 and bolingerband_score < 0.3 and positionalEnergy < 0.5:
                             isbuy = 9
 
                 fig = self.draw(stock)