Added ABS and Fees
Fixed Index Alignment that was off moving from scratch to FT Fixed Stoploss, its a negative in FT, had been using positve stop -1 in scratch
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creslinux
parent
07175ebc5a
commit
71c3106f8f
@ -214,22 +214,28 @@ class Backtesting(object):
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trade_count_lock: Dict = {}
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########################### Call out BSlap instead of using FT
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bslap_results: list = []
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last_bslap_resultslist = []
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last_bslap_results: list = []
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for pair, pair_data in processed.items():
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ticker_data = self.populate_sell_trend(
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self.populate_buy_trend(pair_data))[headers].copy()
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ticker_data.loc[:, 'buy'] = ticker_data['buy'].shift(1)
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ticker_data.loc[:, 'sell'] = ticker_data['sell'].shift(1)
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ticker_data.drop(ticker_data.head(1).index, inplace=True)
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# #dump same DFs to disk for offline testing in scratch
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# f_pair:str = pair
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# csv = f_pair.replace("/", "_")
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# csv="/Users/creslin/PycharmProjects/freqtrade_new/frames/" + csv
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# ticker_data.to_csv(csv, sep='\t', encoding='utf-8')
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#call bslap - results are a list of dicts
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bslap_pair_results = self.backslap_pair(ticker_data, pair)
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last_bslap_results = bslap_results
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bslap_results = last_bslap_results + bslap_pair_results
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#bslap_results_df = DataFrame(bslap_results)
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res = DataFrame.from_records(bslap_results, columns=BacktestResult._fields)
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print(res)
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return res
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bslap_results_df = DataFrame(bslap_results, columns=BacktestResult._fields)
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return bslap_results_df
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########################### Original BT loop
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# for pair, pair_data in processed.items():
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# pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run
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@ -302,13 +308,28 @@ class Backtesting(object):
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import utils_find_1st as utf1st
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from datetime import datetime
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stop = self.stop_loss_value
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p_stop = (-stop + 1) # What stop really means, e.g 0.01 is 0.99 of price
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### backslap debug wrap
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debug_2loops = True # only loop twice, for faster debug
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debug_timing = False # print timing for each step
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debug = True # print values, to check accuracy
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# Read Stop Loss Values and Stake
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stop = self.stop_loss_value
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p_stop = (stop + 1) # What stop really means, e.g 0.01 is 0.99 of price
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stake = self.config.get('stake_amount')
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# Set fees
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# TODO grab these from the environment, do not hard set
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# Fees
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open_fee = 0.05
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close_fee = 0.05
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if debug:
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print("Stop is ", stop, "value from stragey file")
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print("p_stop is", p_stop, "value used to multiply to entry price")
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print("Stake is,", stake, "the sum of currency to spend per trade")
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print("The open fee is", open_fee, "The close fee is", close_fee)
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if debug:
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from pandas import set_option
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set_option('display.max_rows', 5000)
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@ -385,9 +406,10 @@ class Backtesting(object):
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while t_exit_ind < np_buy_arr_len:
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loop = loop + 1
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if debug or debug_timing:
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print("----------------------------------------------------------- Loop", loop, pair)
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print("-- T_exit_Ind - Numpy Index is", t_exit_ind, " ----------------------- Loop", loop, pair)
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if debug_2loops:
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if loop == 4:
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if loop == 2:
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print("++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Loop debug max met - breaking")
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break
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'''
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Dev phases
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@ -541,10 +563,10 @@ class Backtesting(object):
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print("=================== STOP ", pair)
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print("Numpy Array STOP Index is:", np_t_stop_ind)
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print("DataFrame STOP Index is:", np_t_stop_ind + 1, "displaying DF \n")
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print("First Stop Index after Trade open in candle", np_t_stop_ind + 1, ": \n",
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print("First Stop after Trade open in candle", t_open_ind + 1, "is ", np_t_stop_ind + 1,": \n",
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str.format('{0:.17f}', bslap.iloc[np_t_stop_ind][sto]),
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"is less than", str.format('{0:.17f}', np_t_stop_pri))
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print("Tokens will be sold at rate:", str.format('{0:.17f}', bslap.iloc[np_t_stop_ind][sco]))
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print("If stop is first exit match sell rate is :", str.format('{0:.17f}', bslap.iloc[np_t_stop_ind][sco]))
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print("HINT, STOPs should close in-candle, i.e", np_t_stop_ind + 1,
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": As live STOPs are not linked to O-C times")
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@ -610,7 +632,7 @@ class Backtesting(object):
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# Loop control - catch no closed trades.
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if debug:
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print("---------------------------------------- end of loop", loop - 1,
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print("---------------------------------------- end of loop", loop,
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" Dataframe Exit Index is: ", t_exit_ind)
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print("Exit Index Last, Exit Index Now Are: ", t_exit_last, t_exit_ind)
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@ -641,23 +663,26 @@ class Backtesting(object):
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close_index: int = t_exit_ind + 2
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else:
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close_index: int = t_exit_ind + 1
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# Munge the date / delta
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start_date = bslap.iloc[t_open_ind + 1]['date']
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end_date = bslap.iloc[close_index]['date']
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# Munge the date / delta (bt already date formats...just subract)
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trade_start = bslap.iloc[t_open_ind + 1]['date']
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trade_end = bslap.iloc[close_index]['date']
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# def __datetime(date_str):
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# return datetime.strptime(date_str, '%Y-%m-%d %H:%M:%S+00:00')
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trade_start = start_date
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trade_end = end_date
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trade_mins = (trade_end - trade_start).total_seconds() / 60
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# Profit ABS.
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# sumrecieved((rate * numTokens) * fee) - sumpaid ((rate * numTokens) * fee)
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sumpaid: float = (np_trade_enter_price * stake) * open_fee
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sumrecieved: float = (np_trade_exit_price * stake) * close_fee
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profit_abs: float = sumrecieved - sumpaid
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# build trade dictionary
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bslap_result["pair"] = pair
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bslap_result["profit_percent"] = (np_trade_exit_price - np_trade_enter_price) / np_trade_enter_price
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bslap_result["profit_abs"] = ""
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bslap_result["open_time"] = start_date
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bslap_result["close_time"] = end_date
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bslap_result["profit_abs"] = str.format('{0:.10f}', profit_abs)
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bslap_result["open_time"] = trade_start
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bslap_result["close_time"] = trade_end
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bslap_result["open_index"] = t_open_ind + 1
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bslap_result["close_index"] = close_index
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bslap_result["trade_duration"] = trade_mins
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