Take Profit/Stop Loss Profitability Calculator for Trading Crypto

crpto_profit_calc.py

import pandas as pd
import numpy as np

def test_cutoffs(start_amount, start_price, buy_fee, sell_fee, end_price):
    bought_fee = start_amount*buy_fee
    bought_amt = (start_amount-bought_fee) / start_price
    
    sold = bought_amt*end_price
    sold_fee = sold*sell_fee
    sold = sold-sold_fee
    pl = sold-start_amount
    return {'start_price': start_price, 'end_price': end_price, 'bought_fee':bought_fee, 'bought_amt': bought_amt, 'sold': sold, 'sold_fee': sold_fee, 'pl':pl}
    
# under_df would be your stop loss
# over_df would be your take profit
under_df = pd.DataFrame()
over_df = pd.DataFrame()
val_list = list()

# The amount you're willing to risk on the trade
invest = 10000

# don't change this
counter = 1

# the current price or price level you want to buy at
start_price = 310

# diff determines the min,max range to check. I make it a percentage of the starting price to keep it dynamic.
# 0.1 will be a smaller range. 0.5 would be appopriate if you need to look at larger ranges.
diff = start_price*0.1

# this determines the iterator value
iterator = 0.1

for test_val in np.arange( start_price-diff,start_price, iterator):
    temp = pd.DataFrame()
    result = test_cutoffs(invest,start_price, 0.0025, 0.0025, test_val)
    temp['val'] = [test_val-start_price]
    temp['invest'] = invest
    temp['start_price'] = result['start_price']
    temp['end_price'] = result['end_price']
    temp['bought_fee'] = result['bought_fee']
    temp['bought_amt'] = result['bought_amt']
    temp['sold'] = result['sold']
    temp['sold_fee'] = result['sold_fee']
    temp['pl'] = result['pl']
    if counter == 1:
        under_df = temp
        counter +=1
    else:
        under_df = under_df.append(temp)
        
        
counter = 1
for test_val in np.arange(start_price, start_price+diff, iterator):
    temp = pd.DataFrame()
    result = test_cutoffs(invest, start_price, 0.0025, 0.0025, test_val)
    temp['val'] = [test_val-start_price]
    temp['invest'] = invest
    temp['start_price'] = result['start_price']
    temp['end_price'] = result['end_price']
    temp['bought_fee'] = result['bought_fee']
    temp['bought_amt'] = result['bought_amt']
    temp['sold'] = result['sold']
    temp['sold_fee'] = result['sold_fee']
    temp['pl'] = result['pl']
    if counter == 1:
        over_df = temp
        counter +=1
    else:
        over_df = over_df.append(temp)
        

under_df = under_df.reset_index(drop=True)
over_df = over_df.reset_index(drop=True)
print(under_df.shape)
print(over_df.shape)  
  
# displaying stop loss levels
under_df.tail()

# displaying only profitable TP levels
over_df[over_df['pl'] > 5].head()

Image of the results - https://imgur.com/Tl4JF7B