Various updates

.gitignore

@@ -3,4 +3,5 @@ build/*
 dist/*
 src/naiback.egg-info/*
 .*
-__pycache__
+__pycache__
+\#*.*\#

src/naiback/analyzers/statsanalyzer.py

@@ -3,6 +3,9 @@ from .analyzer import Analyzer
 
 from prettytable import PrettyTable
 
+import numpy as np
+import math
+
 def render_float(a):
     return "{:.3f}".format(a)
 
@@ -98,4 +101,26 @@ class StatsAnalyzer(Analyzer):
         result['long']['profit_factor'] = render_ratio(result['long']['total_won'], -result['long']['total_lost'])
         result['short']['profit_factor'] = render_ratio(result['short']['total_won'], -result['short']['total_lost'])
 
+        mean = np.mean(list(map(lambda x: x.pnl(), positions)))
+        stddev = np.std(list(map(lambda x: x.pnl(), positions)))
+        sharpe = mean / stddev
+        tstat = sharpe * math.sqrt(len(positions))
+        result['all']['sharpe_ratio'] = sharpe
+        result['all']['t_stat'] = tstat
+
+        mean = np.mean(list(map(lambda x: x.pnl(), longs)))
+        stddev = np.std(list(map(lambda x: x.pnl(), longs)))
+        sharpe = mean / stddev
+        tstat = sharpe * math.sqrt(len(longs))
+        result['long']['sharpe_ratio'] = sharpe
+        result['long']['t_stat'] = tstat
+
+        mean = np.mean(list(map(lambda x: x.pnl(), shorts)))
+        stddev = np.std(list(map(lambda x: x.pnl(), shorts)))
+        sharpe = mean / stddev
+        tstat = sharpe * math.sqrt(len(shorts))
+        result['short']['sharpe_ratio'] = sharpe
+        result['short']['t_stat'] = tstat
+
+
         return result

src/naiback/analyzers/tradeslistanalyzer.py

@@ -16,6 +16,7 @@ class TradesListAnalyzer(Analyzer):
                  'entry_time' : pos.entry_time(),
                  'exit_time' : pos.exit_time(),
                  'pnl' : pos.pnl(),
+                 'profit_percentage' : pos.profit_percentage(),
                  'is_long' : pos.is_long(),
                  'security' : pos.ticker,
                  'size' : pos.original_size() }

src/naiback/indicators/highest.py

@@ -7,7 +7,7 @@ def Highest(data, period):
         return result
     result[0] = data[0]
     for i in range(1, len(data)):
-        result[i] = max(data[max(0, i - period):(i+1)])
+        result[i] = max(data[max(0, i - period + 1):(i+1)])
 
     return result
     
@@ -16,4 +16,4 @@ def HighestValue(data, index, period):
         return None
     if index == 0:
         return data[0]
-    return max(data[max(0, index - period):(index+1)])
+    return max(data[max(0, index - period + 1):(index+1)])

src/naiback/indicators/lowest.py

@@ -7,7 +7,7 @@ def Lowest(data, period):
         return result
     result[0] = data[0]
     for i in range(1, len(data)):
-        result[i] = min(data[max(0, i - period):(i+1)])
+        result[i] = min(data[max(0, i - period + 1):(i+1)])
 
     return result
     
@@ -16,4 +16,4 @@ def LowestValue(data, index, period):
         return None
     if index == 0:
         return data[0]
-    return min(data[max(0, index - period):(index+1)])
+    return min(data[max(0, index - period + 1):(index+1)])

src/naiback/strategy/strategy.py

@@ -100,7 +100,7 @@ class Strategy:
         for dt in all_dates:
             if len(bars.timestamp) > bar_pos:
                 print("new close: {} ({})".format(close, dt))
-                    
+
                 if bars.timestamp[bar_pos] > dt:
                     print("Inserting at {}: {}".format(dt, close))
                     bars.insert_bar(bar_pos, open_, high, low, close, volume, dt)