1 files changed, 81 insertions, 0 deletions
diff --git a/ema_algo.py b/ema_algo.py
new file mode 100644
index 0000000..db25c08
--- /dev/null
+++ b/ema_algo.py
@@ -0,0 +1,81 @@
+from algo import Algo
+import plotly.graph_objects as go
+import datetime
+
+class Ema_Algo(Algo):
+    def __init__(self, shortPeriod=5, longPeriod=13):
+        self.shortPeriod = shortPeriod
+        self.longPeriod = longPeriod
+        self.g_data = {
+            "timestamps" : [],
+            "ema_short" : [],
+            "ema_long" : []
+        }
+
+    @property
+    def name(self):
+        return "EMA Algo"
+    
+    @property
+    def graph_data(self):
+         return self.g_data
+    
+    def export_graph(self, g_data):
+        timestamps = [datetime.datetime.fromtimestamp(t) for t in g_data['timestamps']]
+        ema_5 = g_data['ema_short']
+        ema_13 = g_data['ema_long']
+        exp = [
+            go.Scatter(name='5 day EMA', x=timestamps, y=ema_5, line=dict(color='rgb(0, 255, 0)'),  mode='lines'),
+            go.Scatter(name='13 day EMA', x=timestamps, y=ema_13, line=dict(color='rgb(0, 0, 255)'),  mode='lines')
+        ]
+        return exp
+    
+    def detemine_signal(self, timestamps, prices):
+
+        ema_5 = self.calc_emas(self.shortPeriod, prices)
+        ema_13 = self.calc_emas(self.longPeriod, prices)
+
+        # add to graph data
+        self.graph_data["timestamps"].append(timestamps[-1])
+        self.graph_data["ema_short"].append(ema_5[-1])
+        self.graph_data["ema_long"].append(ema_13[-1])
+
+        # determine the sign from the most recent price
+        sign_signal = ema_5[-1] - ema_13[-1]
+        # current position, (liquid, shares)
+        if sign_signal > 0:
+                return 1.0 # buy max shares
+        if sign_signal < 0:
+                return 0.0 # sell all shares
+        
+        return 0.5
+
+    """
+    Calculates the simple moving average of the first period of the data
+    """
+    def calc_first_sma(self, period, prices):
+        prices_sum = 0
+        for i in range(0, period):
+            prices_sum += prices[i] # 0, 1, 2, 3 ("popping" order)
+        # print('prices_sum:\t', prices_sum)
+
+        return prices_sum / period
+    
+    """
+    Returns an array off all EMAs, computed according to period
+    """
+    def calc_emas(self, period, prices):
+        weighted_multiplier = 2.0 / (period + 1.0)
+
+        # calculate the first ema
+        first_ema = self.calc_first_sma(period, prices)
+
+        # calculate the rest ema's using that first
+        emas = [first_ema] * period # 0, 1, 2 (for period 3)
+        for i in range(period, len(prices)): # 3, 4, 5, 6, ... , last
+            last_ema = emas[-1]
+            if prices[i] == None or prices[i] == 0:
+                print(i)
+            next_ema = prices[i] * weighted_multiplier + last_ema * (1 - weighted_multiplier)
+            emas.append(next_ema)
+        return emas
+\ No newline at end of file