adding ranges tracking to markets, and reporting to sim_stats

sharkfin/markets/__init__.py

@@ -168,6 +168,7 @@ class MockMarket(AbstractMarket):
 
     prices = None
     dividends = None
+    ranges = None
 
     dividend_growth_rate = None
     dividend_shock_std = None
@@ -191,6 +192,7 @@ def __init__(
 
         self.prices = [self.default_sim_price]
         self.dividends = [self.default_sim_price / self.price_to_dividend_ratio]
+        self.ranges = []
 
         self.rng = rng if rng is not None else np.random.default_rng()
 
@@ -213,6 +215,7 @@ def run_market(self, seed=0, buy_sell=(0,0), run_args = None):
         print('dividend: ' + str(new_dividend))
 
         self.dividends.append(new_dividend)
+        self.ranges.append(new_price / 10) # entirely arbitrary value for now.
 
         return new_price, new_dividend
 

sharkfin/markets/ammps.py

@@ -25,6 +25,7 @@ class ClientRPCMarket(AbstractMarket):
     rng = None
 
     macro_price_field = None
+    range_field = None
 
     def __init__(self,
         seed=None,
@@ -34,7 +35,8 @@ def __init__(self,
         dividend_std = 0.011988,
         price_to_dividend_ratio = 60 / 0.05,
         rng = None,
-        macro_price_field = None
+        macro_price_field = None,
+        range_field = None
         ):
 
         # discounted future value, divided by days per quarter
@@ -51,6 +53,7 @@ def __init__(self,
         self.latest_price = None
         self.prices = [self.default_sim_price]
         self.dividends = [self.default_sim_price / self.price_to_dividend_ratio]
+        self.ranges = []
 
         self.rpc_queue_name = queue_name
         self.rpc_host_name = host
@@ -59,6 +62,10 @@ def __init__(self,
             if macro_price_field is not None \
             else "ClosingPrice"
 
+        self.range_field = range_field \
+            if range_field is not None \
+            else "DailyRange"
+
         self.init_rpc()
 
     def _get_rpc_market_host(self):
@@ -142,13 +149,15 @@ def run_market(self, buy_sell=(0, 0), run_args = None):
 
             self.latest_price = np.nan
             self.prices.append(np.nan)
+            self.ranges.append(np.nan)
 
             raise MarketFailureError(f"AMMPS Market Failure: {self.response['MarketState']}")
 
         else:
 
             self.latest_price = self.response[ self.macro_price_field ]
             self.prices.append(float(self.response[ self.macro_price_field ]))
+            self.ranges.append(float(self.response[self.range_field]))
 
             return self.latest_price, new_dividend
 

sharkfin/simulation.py

@@ -700,6 +700,16 @@ def class_stat_column_to_dict(clabel):
         }).dropna()
         sim_stats["price_dividend_pearsonr"] = pd_df.corr()['p']['d']
 
+
+        sim_stats["ranges_mean"] = mean(self.market.ranges)
+        sim_stats["ranges_stdev"] = stdev(self.market.ranges)
+        sim_stats["ranges_min"] = min(self.market.ranges)
+        sim_stats["ranges_max"] = max(self.market.ranges)
+
+        ranges_zscore = stats.zscore(np.array(self.market.ranges))
+
+        sim_stats["ranges_zs_max"] = ranges_zscore.max()
+
         return sim_stats