Added the ability for the backtester to use unrealised PnL from the Position objects to calculate a tick-by-tick equity curve. Added a performance directory that calculates drawdown statistics. Modified the output.py script to use Seaborn and output the equity curve, returns and drawdown curve.

backtest/backtest.py

@@ -39,6 +39,7 @@ def backtest(
             if event is not None:
                 if event.type == 'TICK':
                     strategy.calculate_signals(event)
+                    portfolio.update_portfolio(event)
                 elif event.type == 'SIGNAL':
                     portfolio.execute_signal(event)
                 elif event.type == 'ORDER':
@@ -70,7 +71,9 @@ if __name__ == "__main__":
     )
 
     # Create the portfolio object to track trades
-    portfolio = Portfolio(ticker, events, equity=equity)
+    portfolio = Portfolio(
+        ticker, events, equity=equity, backtest=True
+    )
 
     # Create the simulated execution handler
     execution = SimulatedExecution()

backtest/output.py

@@ -1,7 +1,13 @@
 import os, os.path
 
 import pandas as pd
+import matplotlib
+try:
+    matplotlib.use('TkAgg')
+except:
+    pass
 import matplotlib.pyplot as plt
+import seaborn as sns
 
 from qsforex.settings import OUTPUT_RESULTS_DIR
 
@@ -14,11 +20,29 @@ if __name__ == "__main__":
     It requires OUTPUT_RESULTS_DIR to be set in the project
     settings.
     """
+    sns.set_palette("deep", desat=.6)
+    sns.set_context(rc={"figure.figsize": (8, 4)})
+
     equity_file = os.path.join(OUTPUT_RESULTS_DIR, "equity.csv")
     equity = pd.io.parsers.read_csv(
-        equity_file, header=True, 
-        names=["time", "balance"], 
-        parse_dates=True, index_col=0
+        equity_file, parse_dates=True, header=0, index_col=0
     )
-    equity["balance"].plot()
-    plt.show()
+
+    # Plot three charts: Equity curve, period returns, drawdowns
+    fig = plt.figure()
+    fig.patch.set_facecolor('white')     # Set the outer colour to white
+    
+    # Plot the equity curve
+    ax1 = fig.add_subplot(311, ylabel='Portfolio value')
+    equity["Equity"].plot(ax=ax1, color=sns.color_palette()[0])
+
+    # Plot the returns
+    ax2 = fig.add_subplot(312, ylabel='Period returns')
+    equity['Returns'].plot(ax=ax2, color=sns.color_palette()[1])
+
+    # Plot the returns
+    ax3 = fig.add_subplot(313, ylabel='Drawdowns')
+    equity['Drawdown'].plot(ax=ax3, color=sns.color_palette()[2])
+
+    # Plot the figure
+    plt.show()