diff --git a/rl_portfolio_management/callbacks/notebook_plot.py b/rl_portfolio_management/callbacks/notebook_plot.py
index 295fa43..94db233 100644
--- a/rl_portfolio_management/callbacks/notebook_plot.py
+++ b/rl_portfolio_management/callbacks/notebook_plot.py
@@ -48,8 +48,10 @@ class LivePlotNotebook(object):
         # update limits
         y = np.concatenate(ys)
         y_extra = y.std() * 0.1
-        self.ax.set_xlim(x.min(), x.max())
-        self.ax.set_ylim(y.min() - y_extra, y.max() + y_extra)
+        if x.min() != x.max():
+            self.ax.set_xlim(x.min(), x.max())
+        if (y.min() - y_extra) != (y.max() + y_extra):
+            self.ax.set_ylim(y.min() - y_extra, y.max() + y_extra)
 
         if self.log_dir:
             self.fig.savefig(os.path.join(
diff --git a/rl_portfolio_management/environments/portfolio.py b/rl_portfolio_management/environments/portfolio.py
index 0207df5..284b0c2 100644
--- a/rl_portfolio_management/environments/portfolio.py
+++ b/rl_portfolio_management/environments/portfolio.py
@@ -318,18 +318,19 @@ class PortfolioEnv(gym.Env):
 
         if close:
             self._plot = self._plot2 = self._plot3 = None
-        if not self._plot:
-            self._plot = LivePlotNotebook(
-                '/tmp', title='performance', labels=["buy & hold", "portfolio_value"])
 
-        # show a plot of portfolio vs mean market performance
         df_info = pd.DataFrame(self.infos)
         df_info.index = pd.to_datetime(df_info["date"], unit='s')
 
+        # plot prices and performance
+        if not self._plot:
+            self._plot = LivePlotNotebook(
+                '/tmp', title='prices & performance', labels=self.sim.asset_names + ["Portfolio"])
         x = df_info.index
-        y1 = df_info["market_value"]
-        y2 = df_info["portfolio_value"]
-        self._plot.update(x, [y1, y2])
+        y_portfolio = df_info["portfolio_value"]
+        y_assets = [df_info['price_' + name].cumprod()
+                    for name in self.sim.asset_names]
+        self._plot.update(x, y_assets + [y_portfolio])
 
         # plot portfolio weights
         if not self._plot2:
@@ -338,12 +339,5 @@ class PortfolioEnv(gym.Env):
         ys = [df_info['weight_' + name] for name in self.sim.asset_names]
         self._plot2.update(x, ys)
 
-        # plot portfolio prices
-        if not self._plot3:
-            self._plot3 = LivePlotNotebook(
-                '/tmp', labels=self.sim.asset_names, title='price changes')
-        ys = [df_info['price_' + name] for name in self.sim.asset_names]
-        self._plot3.update(x, ys)
-
         if close:
             self._plot = self._plot2 = self._plot3 = None