Lots of changes. Modified the Position object to handle more of the actual position calculations instead of the Portfolio. Added more unit tests for both Position and Portfolio. Allowed Positions to trade in currencies other than GBPUSD and in base/quotes which aren't the home currency. Modified the backtester to be single-threaded and added a basic Moving Average Crossover strategy. Also added a basic equity curve output script.

strategy/strategy.py

@@ -2,8 +2,17 @@ from qsforex.event.event import SignalEvent
 
 
 class TestStrategy(object):
-    def __init__(self, instrument, events):
-        self.instrument = instrument
+    """
+    A testing strategy that alternates between buying and selling
+    a currency pair on every 5th tick. This has the effect of
+    continuously "crossing the spread" and so will be loss-making
+    strategy. 
+
+    It is used to test that the backtester/live trading system is
+    behaving as expected.
+    """
+    def __init__(self, pairs, events):
+        self.pairs = pairs
         self.events = events
         self.ticks = 0
         self.invested = False
@@ -12,11 +21,70 @@ class TestStrategy(object):
         if event.type == 'TICK':
             if self.ticks % 5 == 0:
                 if self.invested == False:
-                    signal = SignalEvent(self.instrument, "market", "buy")
+                    signal = SignalEvent(self.pairs[0], "market", "buy", event.time)
                     self.events.put(signal)
                     self.invested = True
                 else:
-                    signal = SignalEvent(self.instrument, "market", "sell")
+                    signal = SignalEvent(self.pairs[0], "market", "sell", event.time)
                     self.events.put(signal)
                     self.invested = False
             self.ticks += 1
+
+
+class MovingAverageCrossStrategy(object):
+    """
+    A basic Moving Average Crossover strategy that generates
+    two simple moving averages (SMA), with default windows
+    of 500 ticks for the short SMA and 2,000 ticks for the
+    long SMA.
+
+    The strategy is "long only" in the sense it will only
+    open a long position once the short SMA exceeds the long
+    SMA. It will close the position (by taking a corresponding
+    sell order) when the long SMA recrosses the short SMA.
+
+    The strategy uses a rolling SMA calculation in order to
+    increase efficiency by eliminating the need to call two
+    full moving average calculations on each tick.
+    """
+    def __init__(
+        self, pairs, events, 
+        short_window=500, long_window=2000
+    ):
+        self.pairs = pairs
+        self.events = events
+        self.ticks = 0
+        self.invested = False
+        
+        self.short_window = short_window
+        self.long_window = long_window
+        self.short_sma = None
+        self.long_sma = None
+
+    def calc_rolling_sma(self, sma_m_1, window, price):
+        return ((sma_m_1 * (window - 1)) + price) / window
+
+    def calculate_signals(self, event):
+        if event.type == 'TICK':
+            price = event.bid
+            if self.ticks == 0:
+                self.short_sma = price
+                self.long_sma = price
+            else:
+                self.short_sma = self.calc_rolling_sma(
+                    self.short_sma, self.short_window, price
+                )
+                self.long_sma = self.calc_rolling_sma(
+                    self.long_sma, self.long_window, price
+                )
+            # Only start the strategy when we have created an accurate short window
+            if self.ticks > self.short_window:
+                if self.short_sma > self.long_sma and not self.invested:
+                    signal = SignalEvent(self.pairs[0], "market", "buy", event.time)
+                    self.events.put(signal)
+                    self.invested = True
+                if self.short_sma < self.long_sma and self.invested:
+                    signal = SignalEvent(self.pairs[0], "market", "sell", event.time)
+                    self.events.put(signal)
+                    self.invested = False
+            self.ticks += 1