fix bugs

TradeMaster-NTU · Mar 4, 2023 · 98e270d · 98e270d
1 parent 463567d
commit 98e270d
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Showing 15 changed files with 378 additions and 265 deletions.
diff --git a/configs/portfolio_management/portfolio_management_dj30_eiie_eiie_adam_mse.py b/configs/portfolio_management/portfolio_management_dj30_eiie_eiie_adam_mse.py
@@ -44,7 +44,7 @@
 
 trainer = dict(
     type='PortfolioManagementEIIETrainer',
-    epochs=10,
+    epochs=2,
     work_dir=work_dir,
     if_remove=False )
 

diff --git a/configs/portfolio_management/portfolio_management_dj30_sarl_sarl_adam_mse.py b/configs/portfolio_management/portfolio_management_dj30_sarl_sarl_adam_mse.py
@@ -54,4 +54,5 @@
     if_remove=False ,
     configs = {},
     work_dir=work_dir,
+    epochs=2,
 )
diff --git a/trademaster/environments/algorithmic_trading/environment.py b/trademaster/environments/algorithmic_trading/environment.py
@@ -296,7 +296,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = tr*(252)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(252)** 0.5 / (np.std(return_rate_list)+ 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/trademaster/environments/high_frequency_trading/environment.py b/trademaster/environments/high_frequency_trading/environment.py
@@ -296,7 +296,7 @@ def step(self, action):
             stats = OrderedDict(
                 {
                     "Total Return": ["{:04f}%".format(tr * 100)],
-                    "Sharp Ratio": ["{:04f}".format(sharpe_ratio)],
+                    # "Sharp Ratio": ["{:04f}".format(sharpe_ratio)],
                     "Volatility": ["{:04f}%".format(vol* 100)],
                     "Max Drawdown": ["{:04f}%".format(mdd* 100)],
                     # "Calmar Ratio": ["{:04f}".format(cr)],
@@ -387,7 +387,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = np.mean(return_rate_list)*(31536000)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(31536000)** 0.5 / (np.std(return_rate_list)+ 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/trademaster/environments/portfolio_management/deeptrader_environment.py b/trademaster/environments/portfolio_management/deeptrader_environment.py
@@ -213,7 +213,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = tr*(252)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(252)** 0.5 / (np.std(return_rate_list) + 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/trademaster/environments/portfolio_management/eiie_environment.py b/trademaster/environments/portfolio_management/eiie_environment.py
@@ -245,7 +245,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = tr*(252)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(252)** 0.5 / (np.std(return_rate_list) + 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/trademaster/environments/portfolio_management/environment.py b/trademaster/environments/portfolio_management/environment.py
@@ -233,7 +233,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = tr*(252)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(252)** 0.5 / (np.std(return_rate_list) + 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/trademaster/environments/portfolio_management/inverstor_imitator_environment.py b/trademaster/environments/portfolio_management/inverstor_imitator_environment.py
@@ -436,7 +436,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = tr*(252)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(252)** 0.5 / (np.std(return_rate_list) + 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/trademaster/environments/portfolio_management/sarl_environment.py b/trademaster/environments/portfolio_management/sarl_environment.py
@@ -302,7 +302,7 @@ def evaualte(self, df):
         tr = df["total assets"].values[-1] / (df["total assets"].values[0] + 1e-10) - 1
         return_rate_list=self.get_daily_return_rate(df["total assets"].values)
 
-        sharpe_ratio = tr*(252)** 0.5 / (np.std(return_rate_list) * (len(df) ** 0.5) + 1e-10)
+        sharpe_ratio = np.mean(return_rate_list)*(252)** 0.5 / (np.std(return_rate_list) + 1e-10)
         vol = np.std(return_rate_list)
         mdd = 0
         peak=df["total assets"][0]

diff --git a/tutorial/Tutorial1_EIIE.ipynb b/tutorial/Tutorial1_EIIE.ipynb
diff --git a/tutorial/Tutorial2_DeepScalper.ipynb b/tutorial/Tutorial2_DeepScalper.ipynb
@@ -26,8 +26,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2023-03-03 02:05:01,150\tINFO services.py:1476 -- View the Ray dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8265\u001b[39m\u001b[22m\n",
-      "2023-03-03 02:05:03,178\tINFO worker.py:973 -- Calling ray.init() again after it has already been called.\n"
+      "2023-03-04 18:50:27,916\tINFO services.py:1476 -- View the Ray dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8266\u001b[39m\u001b[22m\n",
+      "2023-03-04 18:50:30,042\tINFO worker.py:973 -- Calling ray.init() again after it has already been called.\n"
      ]
     }
    ],
@@ -453,25 +453,25 @@
       "+--------------+-------------+------------+--------------+\n",
       "| Total Return | Sharp Ratio | Volatility | Max Drawdown |\n",
       "+--------------+-------------+------------+--------------+\n",
-      "| 663.053338%  |  103.820287 | 3.726925%  |  63.966805%  |\n",
+      "| 663.053338%  |   1.465309  | 3.726925%  |  63.966805%  |\n",
       "+--------------+-------------+------------+--------------+\n",
       "Valid Episode: [1/2]\n",
       "+--------------+-------------+------------+--------------+\n",
       "| Total Return | Sharp Ratio | Volatility | Max Drawdown |\n",
       "+--------------+-------------+------------+--------------+\n",
-      "| -35.444878%  |  -0.597242  | 42.560375% | 118.689588%  |\n",
+      "| -35.444878%  |   0.430537  | 42.560375% | 118.689588%  |\n",
       "+--------------+-------------+------------+--------------+\n",
       "Train Episode: [2/2]\n",
       "+--------------+-------------+------------+--------------+\n",
       "| Total Return | Sharp Ratio | Volatility | Max Drawdown |\n",
       "+--------------+-------------+------------+--------------+\n",
-      "| 967.324329%  |  145.920481 | 3.868479%  |  64.052556%  |\n",
+      "| 967.324329%  |   1.621369  | 3.868479%  |  64.052556%  |\n",
       "+--------------+-------------+------------+--------------+\n",
       "Valid Episode: [2/2]\n",
       "+--------------+-------------+------------+--------------+\n",
       "| Total Return | Sharp Ratio | Volatility | Max Drawdown |\n",
       "+--------------+-------------+------------+--------------+\n",
-      "| -199.576611% |  -9.537242  | 15.006834% | 289.010033%  |\n",
+      "| -199.576611% |   0.292613  | 15.006834% | 289.010033%  |\n",
       "+--------------+-------------+------------+--------------+\n"
      ]
     }
@@ -501,7 +501,7 @@
       "+--------------+-------------+------------+--------------+\n",
       "| Total Return | Sharp Ratio | Volatility | Max Drawdown |\n",
       "+--------------+-------------+------------+--------------+\n",
-      "| 218.177594%  |  74.097753  | 2.131242%  |  29.503340%  |\n",
+      "| 218.177594%  |   1.966325  | 2.131242%  |  29.503340%  |\n",
       "+--------------+-------------+------------+--------------+\n"
      ]
     }