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Backslap bug on “stop loss triggered” indexes resolved

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This commit is contained in:
misagh 2018-09-20 16:15:53 +02:00
parent 88854cba2d
commit decaf6c42e
2 changed files with 34 additions and 11 deletions
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22
freqtrade/optimize/backslapping.py
View File

@ -280,10 +280,19 @@ class Backslapping:
# debug = False # print values, to check accuracy
debug_2loops = self.debug_2loops # only loop twice, for faster debug
debug_timing = self.debug_timing # print timing for each step
debug = self.debug # print values, to check accuracy
#debug = self.debug # print values, to check accuracy
debug = False
ticker_data = ticker_data.sort_values(by=['date'])
ticker_data = ticker_data.reset_index(drop=True)
#pandas_df = df.toPandas()
#pandas_df.to_json
# Read Stop Loss Values and Stake
# pdb.set_trace()
stop = self.stop_loss_value
#stop = stoploss
p_stop = (stop + 1) # What stop really means, e.g 0.01 is 0.99 of price
if debug:
@ -583,7 +592,7 @@ class Backslapping:
elif np_t_sell_ind < 99999999 and np_t_sell_ind < np_t_stop_ind:
# move sell onto next candle, we only look back on sell
# will use the open price later.
t_exit_ind = t_open_ind + np_t_sell_ind + 1 # Set Exit row index
t_exit_ind = t_open_ind + np_t_sell_ind # Set Exit row index
t_exit_type = SellType.SELL_SIGNAL # Set Exit type (sell)
np_t_exit_pri = np_open # The price field our SELL exit will use
if debug:
@ -693,6 +702,7 @@ class Backslapping:
if t_exit_type == SellType.STOP_LOSS:
if np_t_exit_pri == 6:
np_trade_exit_price = np_t_stop_pri
t_exit_ind = t_exit_ind + 1
else:
np_trade_exit_price = np_bslap[t_exit_ind, np_t_exit_pri]
if t_exit_type == SellType.SELL_SIGNAL:
@ -737,6 +747,7 @@ class Backslapping:
"""
# TODO :add handing here to record none closed open trades
if debug:
print(bslap_pair_results)
break
@ -745,6 +756,12 @@ class Backslapping:
Add trade to backtest looking results list of dicts
Loop back to look for more trades.
"""
# We added +1 to t_exit_ind if the exit was a stop-loss, to not exit early in the IF of this ELSE
# removing the +1 here so prices match.
if t_exit_type == SellType.STOP_LOSS:
t_exit_ind = t_exit_ind - 1
# Build trade dictionary
## In general if a field can be calculated later from other fields leave blank here
## Its X(number of trades faster) to calc all in a single vector than 1 trade at a time
@ -753,6 +770,7 @@ class Backslapping:
close_index: int = t_exit_ind
bslap_result = {} # Must have at start or we end up with a list of multiple same last result
bslap_result["pair"] = pair
bslap_result["stoploss"] = stop
bslap_result["profit_percent"] = "" # To be 1 vector calc across trades when loop complete
bslap_result["profit_abs"] = "" # To be 1 vector calc across trades when loop complete
bslap_result["open_time"] = np_bslap_dates[t_open_ind + 1] # use numpy array, pandas 20x slower

17
freqtrade/optimize/edge.py
View File

@ -133,6 +133,10 @@ class Edge:
if self.debug_timing: # Start timer
fl = self.s()
# Sorting dataframe by date and reset index
pair_data = pair_data.sort_values(by=['date'])
pair_data = pair_data.reset_index(drop=True)
ticker_data = self.populate_sell_trend(
self.populate_buy_trend(pair_data))[headers].copy()
@ -151,11 +155,6 @@ class Edge:
for stoploss in stoploss_range:
bslap_results += self.backslap_pair(ticker_data, pair, round(stoploss, 3))
#bslap_results += self.backslap_pair(ticker_data, pair, -0.05)
# bslap_pair_results = self.backslap_pair(ticker_data, pair, -0.05)
# last_bslap_results = bslap_results
# bslap_results = last_bslap_results + bslap_pair_results
if self.debug_timing: # print time taken
tt = self.f(st)
@ -737,6 +736,7 @@ class Edge:
if t_exit_type == SellType.STOP_LOSS:
if np_t_exit_pri == 6:
np_trade_exit_price = np_t_stop_pri
t_exit_ind = t_exit_ind + 1
else:
np_trade_exit_price = np_bslap[t_exit_ind, np_t_exit_pri]
if t_exit_type == SellType.SELL_SIGNAL:
@ -789,6 +789,12 @@ class Edge:
Add trade to backtest looking results list of dicts
Loop back to look for more trades.
"""
# We added +1 to t_exit_ind if the exit was a stop-loss, to not exit early in the IF of this ELSE
# removing the +1 here so prices match.
if t_exit_type == SellType.STOP_LOSS:
t_exit_ind = t_exit_ind - 1
# Build trade dictionary
## In general if a field can be calculated later from other fields leave blank here
## Its X(number of trades faster) to calc all in a single vector than 1 trade at a time
@ -1014,6 +1020,5 @@ args = arguments.get_parsed_arg()
config = setup_configuration(args)
config["strategy"] = "MultiRSI"
edge = Edge(config)
edge.start()