Added get_fee function, states and trading now accounts for fees

The Kraken wrapper can now get the trading fee for a crypto pair

The bot uses this when making decisions to buy or sell

The bot on startup will now not initially do anything, it will instead
wait until the state changes between buy and sell to do anything in
order to prevent regrettable trades.

api/kraken.py

@@ -26,7 +26,9 @@ class Kraken:
 
         self.prices = pandas.concat([self.prices, pandas.DataFrame(new_row)], ignore_index=False)
 
-
+    def get_fee(self, pair):
+        self.fee = k.kraken_wrapper.get_tradable_asset_pairs(pair=currency_pair)["fees"][0][0][1]
+    
     # Calculates the exponential moving average by grabbing data from Kraken on the conversion rate every interval minutes.
     def calculate_ema(self, short_time=5, long_time=30):
         self.long_ema = self.prices.ewm(span=long_time).mean()

main.py

@@ -3,10 +3,11 @@ import time, threading, pandas, numpy
 from api.kraken import Kraken
 from api.fake import Fake
 
-def percent_difference(first, second):
-    return abs(first-second)/((first+second)/2)
 
 if __name__ == "__main__":
+    current_state = "Unknown"
+    previous_state = "Unknown"
+
     currency_buy = "XXBT"
     currency_sell = "ZUSD"
     currency_pair = "XXBTZUSD"
@@ -22,24 +23,37 @@ if __name__ == "__main__":
     time.sleep(1)
 
     while True:
-        #print("Main loop")
-        
         k.get_current_price(currency_pair)
         k.calculate_ema()
 
+        k.get_fee()
+
         # If we have crypto, check for sell behaviour, if we have fiat, check for buy behavior, otherwise, get really confused
         if k.balances["vol"][currency_buy] > 10**-5:
+            if current_state == "Buying":
+                previous_state = "Buying"
+            
+            current_state = "Selling"
+
             # Sell shit
-            # If short term change dips below long term change, sell
+            # If the previous state is known, and the short term EMA (accounting for the fee) is less than the long term EMA,
-            if k.short_ema.tail(1)[0][0] < k.long_ema.tail(1)[0][0] and percent_difference(k.short_ema.tail(1)[0][0], k.long_ema.tail(1)[0][0]) > 0.001:
+            # and there is more than a 0.1% difference between short and long term EMA (accounting for the fee), sell
+            if previous_state != "Unknown" and k.short_ema.tail(1)[0][0] * (1-self.fee/100) < k.long_ema.tail(1)[0][0] and k.long_ema.tail(1)[0][0]/(k.short_ema.tail(1)[0][0] * (1-self.fee/100)) - 1  > 0.001:
+                if k.short_ema.tail(1)[0][0]
                 print("Selling shit")
                 k.sell_order(currency_pair, currency_buy, currency_sell, k.balances["vol"][currency_buy])
                 print(k.balances)
 
         elif k.balances["vol"][currency_sell] > 10**-2:
+            if current_state == "Selling":
+                previous_state = "Selling"
+            
+            current_state = "Buying"
+            
             # Buy shit
-            # If short term goes above long term, buy
+            # If the previous state is known, and the short term EMA (accounting for the fee) is greater than the long term EMA,
-            if k.short_ema.tail(1)[0][0] > k.long_ema.tail(1)[0][0] and percent_difference(k.short_ema.tail(1)[0][0], k.long_ema.tail(1)[0][0]) > 0.001:
+            # and there is more than a 0.1% difference between short and long term EMA (accounting for the fee), buy
+            if previous_state != "Unknown" and k.short_ema.tail(1)[0][0] * (self.fee/100+1) > k.long_ema.tail(1)[0][0] and (k.short_ema.tail(1)[0][0] * (self.fee/100+1))/k.long_ema.tail(1)[0][0] - 1 > 0.001:
                 print("Buying shit")
                 k.buy_order(currency_pair, currency_buy, currency_sell, k.balances["vol"][currency_sell] * 0.95 * (1/k.prices.tail(1)[0][0]))
                 print(k.balances)