@hfrog713 said in Correct way to use nested If statements on a SignalStrategy:
delta_under_flag = bt.If(delta_below_zero, 1, 0) hl2_under_flag = bt.If(delta_and_hl2_down, 1, 0)
Seems to be working fine, i accidentally had 1 on both the buy and the sell signal.
Now everything seems to be working well.
Please let me know if there are any comments.
Hello Guys,
Fairly new, trying to figure out the correct way to do nested if statements.
I do the following but it seems like the function itself is showing up as opposed to the evaluated If return.
Can someone please help?
Thanks,
Hernando
class SMACloseSignalStrategy(bt.SignalStrategy):
params = (('fastMA',22),('slowMA', 23),('macd1',7),('macd2',8),('macdsig',3),('period',30),)
def log(self, txt, dt=None):
'''Logging function for the strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def __init__(self):
self.high = self.datas[0].high
self.low = self.datas[0].low
self.close = self.datas[0].close
self.ema_slow = self.datas[0].ema_slow
self.ema_fast = self.datas[0].ema_fast
self.macd_delta = self.datas[0].macd_delta
self.high_low2 = self.datas[0].high_low2
close_over_emaS = self.close > self.ema_slow
delta_over_zero = self.macd_delta > 0
hl2_over_emaF = self.high_low2 > self.ema_fast
close_below_emaS = self.close < self.ema_slow
delta_below_zero = self.macd_delta < 0
hl2_below_emaF = self.high_low2 < self.ema_slow
delta_and_hl2_up = bt.And(delta_over_zero, hl2_over_emaF)
delta_and_hl2_down = bt.And(delta_below_zero, hl2_below_emaF)
delta_over_flag = bt.If(delta_over_zero, 1, 0)
hl2_over_flag = bt.If(delta_and_hl2_up, 1, 0)
delta_under_flag = bt.If(delta_below_zero, 1, 0)
hl2_under_flag = bt.If(delta_and_hl2_down, 1, 0)
#long_signal = bt.If(close_over_emaS, bt.If(delta_over_zero, 1, 0), bt.If(delta_and_hl2_up, 1, 0))
#short_signal = bt.If(close_below_emaS, bt.If(delta_below_zero, 1, 0), bt.If(delta_and_hl2_down, 1, 0))
long_signal = bt.If(close_over_emaS, delta_over_flag, hl2_over_flag)
short_signal = bt.If(close_below_emaS, delta_under_flag, hl2_under_flag)
#Another working example with 2 mil profit lol ....
#long_signal = bt.If(close_over_emaS, 1, 0)
#short_signal = bt.If(close_below_emaS, -1, 0)
breakpoint()
#Selling on SMA strategy......seems pretty profitable
sma1, sma2 = bt.ind.SMA(period=self.p.fastMA), bt.ind.SMA(period=self.p.slowMA)
#self.signal_add(bt.SIGNAL_LONG, bt.ind.CrossOver(sma1,sma2))
#self.signal_add(bt.SIGNAL_SHORT, bt.ind.CrossOver(sma2,sma1))
self.signal_add(bt.SIGNAL_LONG, long_signal)
self.signal_add(bt.SIGNAL_SHORT, short_signal)
I guess the crux of the question is.......
I have some logic in tradingview....
//@version=3
strategy(title = "test", overlay=true, initial_capital = 10000, pyramiding = 0, commission_type = strategy.commission.percent, commission_value = 0.0, calc_on_order_fills = false, calc_on_every_tick = false, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, currency = currency.USD)
fastMA = ema(close, 22)
slowMA = ema(close, 23)
buyCondition = crossover(fastMA, slowMA)
closeCondition = crossunder(fastMA, slowMA)
if buyCondition
strategy.entry("MA Cross - Long", strategy.long)
strategy.close("MA Cross - Long", closeCondition)
How do i convert that to logic in backtrader.......
I thought the following, but i end up with different results.
class LongCloseLarpStrat(bt.Strategy):
params = (('fastMA',22),('slowMA', 23))
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.datetime(0)
print('%s, %s' % (dt.isoformat(), txt))
def __init__(self):
self.livetrades = {}
self.counter = 0
self.fastMA = bt.indicators.ExponentialMovingAverage(period=self.p.fastMA)
self.slowMA = bt.indicators.ExponentialMovingAverage(period=self.p.slowMA)
self.crossover = bt.indicators.CrossOver(self.fastMA, self.slowMA)
def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted, order.Partial]:# Buy/Sell order submitted/accepted to/by broker/partially filled - Nothing to do
return
# Check if an order has been completed
if order.status in [order.Completed]:
if order.isbuy():
self.log('BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, tradeID: %d' %(order.executed.price, order.executed.value, order.executed.comm, order.tradeid))
elif order.issell():
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, tradeID: %d' %(order.executed.price, order.executed.value, order.executed.comm, order.tradeid))
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')
def notify_trade(self, trade):
if trade.justopened:
self.log('New trade just opened with id %d'%(trade.tradeid))
self.livetrades[trade.tradeid] = trade
elif trade.isclosed:
self.log('A trade just closed with id %d'%(trade.tradeid))
self.livetrades.pop(trade.tradeid)
else:
self.log('Trade id %d updated'%(trade.tradeid))
def next(self):
if self.position.size:
if self.crossover == -1:
self.sell()
elif not self.position.size:
if self.crossover == 1:
self.buy()
Can someone help me out here?
Thanks in advance,
Hernando
@run-out Hi Sorry, i am not getting an error......the problem is the number of trades, trade prices, and times of trades don't match at all with what i am seeing in the tradingview strategy. I have confirmed that the data looks the same in the dataframe as the data i am using in tradingview.
I can upload samples of the data if required.
The results i get from backtrader is the following.
Trade Analysis Results:
Total Open Total Closed Total Won Total Lost
0 62 8 54
Strike Rate Win Streak Losing Streak PnL Net
12.9 2 11 -96628.15
Final Portfolio Value: $3371.849999999994
The results i get from TradingView are attached as a picture.
Please let me know if you need anything else.
I believe I am just trying to get a simple EMA crossover to buy and sell on positive and negative crossover. You can see what i am trying to do directly in the PineScript.
Thanks in advance for your help.
Hi Guys,
I need help with converting a tradingview strategy over into backtrader. I have been working on this for a couple of months and can't seem to get the numbers to matchup. We are getting the data from the Bybit API and loading into a pandas dataframe. We then use backtrader to load the dataframe into Cerebro.
Please see below for the BackTrader Strategy and Pandas Data.
class LongCloseLarpStrat(bt.Strategy):
params = (('fastMA',22),('slowMA', 23))
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.datetime(0)
print('%s, %s' % (dt.isoformat(), txt))
def __init__(self):
self.livetrades = {}
self.counter = 0
self.fastMA = bt.indicators.ExponentialMovingAverage(period=self.p.fastMA)
self.slowMA = bt.indicators.ExponentialMovingAverage(period=self.p.slowMA)
self.crossover = bt.indicators.CrossOver(self.fastMA, self.slowMA)
def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted, order.Partial]:# Buy/Sell order submitted/accepted to/by broker/partially filled - Nothing to do
return
# Check if an order has been completed
if order.status in [order.Completed]:
if order.isbuy():
self.log('BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, tradeID: %d' %(order.executed.price, order.executed.value, order.executed.comm, order.tradeid))
elif order.issell():
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, tradeID: %d' %(order.executed.price, order.executed.value, order.executed.comm, order.tradeid))
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')
def notify_trade(self, trade):
if trade.justopened:
self.log('New trade just opened with id %d'%(trade.tradeid))
self.livetrades[trade.tradeid] = trade
elif trade.isclosed:
self.log('A trade just closed with id %d'%(trade.tradeid))
self.livetrades.pop(trade.tradeid)
else:
self.log('Trade id %d updated'%(trade.tradeid))
def next(self):
if self.position.size:
if self.crossover < 0:
self.sell()
elif self.crossover > 0:
self.buy()
Pandas Data
class PandasData(bt.feeds.PandasData):
lines = ('turnover','high_low2', 'ema_slow', 'ema_fast', 'macd_delta')
params = (
('datetime', None),
('open','Open'),
('high','High'),
('low','Low'),
('close','Close'),
('volume','Volume'),
('openinterest', None),
('turnover','Turnover'),
('high_low2','high_low2'),
('ema_slow', 'ema_slow'),
('ema_fast', 'ema_fast'),
('macd_delta', 'macd_delta')
)
Please see below for the Pinescript Code.
//@version=3
strategy(title = "test", overlay=true, initial_capital = 10000, pyramiding = 0, commission_type = strategy.commission.percent, commission_value = 0.0, calc_on_order_fills = false, calc_on_every_tick = false, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, currency = currency.USD)
fastMA = ema(close, 22)
slowMA = ema(close, 23)
plot(fastMA, color = red, linewidth = 1, title = "Fast MA")
plot(slowMA, color = blue, linewidth = 1, title = "Slow MA")
buyCondition = crossover(fastMA, slowMA)
closeCondition = crossunder(fastMA, slowMA)
strategy.entry("MA Cross - Long", strategy.long)
strategy.close("MA Cross - Long", closeCondition)
I apologize if I did not ask this question in the correct manner.
Please let me know if there is any additional questions or anything I can add.
Here is a link to the tradingview ticker.
https://www.tradingview.com/symbols/BTCUSD/?exchange=BYBIT
We are working on the 3 hour timeframe.
Also, here is the code for getting the data from bybit.
def get_historical_klines_pd(client, symbol, interval, start_str, end_str=None):
"""Get Historical Klines from Bybit
See dateparse docs for valid start and end string formats
http://dateparser.readthedocs.io/en/latest/
If using offset strings for dates add "UTC" to date string
e.g. "now UTC", "11 hours ago UTC"
:param symbol: Name of symbol pair -- BTCUSD, ETCUSD, EOSUSD, XRPUSD
:type symbol: str
:param interval: Bybit Kline interval -- 1 3 5 15 30 60 120 240 360 720 "D" "M" "W" "Y"
:type interval: str
:param start_str: Start date string in UTC format
:type start_str: str
:param end_str: optional - end date string in UTC format
:type end_str: str
:return: list of OHLCV values
"""
# set parameters for kline()
interval = int(interval)
timeframe = str(interval)
limit = 200
start_ts = int(date_to_milliseconds(start_str)/1000)
end_ts = None
if end_str:
end_ts = int(date_to_milliseconds(end_str)/1000)
else:
end_ts = int(date_to_milliseconds('now')/1000)
# init our list
output_data = []
# loop counter
idx = 0
# it can be difficult to know when a symbol was listed on Binance so allow start time to be before list date
symbol_existed = False
while True:
# fetch the klines from start_ts up to max 200 entries
temp_tuple = client.Kline.Kline_get(symbol=symbol, interval=timeframe, **{'from':start_ts}, limit=limit).result()
temp_dict = temp_tuple[0]
# handle the case where our start date is before the symbol pair listed on Binance
if not symbol_existed and len(temp_dict):
symbol_existed = True
if symbol_existed:
# extract data and convert to list
temp_data = [list(i.values()) for i in temp_dict['result']]
# append this loops data to our output data
output_data += temp_data
# update our start timestamp using the last value in the array and add the interval timeframe
# NOTE: current implementation does not support inteval of D/W/M/Y
start_ts = temp_data[len(temp_data) - 1][2] + interval*60
else:
# it wasn't listed yet, increment our start date
start_ts += timeframe
idx += 1
# check if we received less than the required limit and exit the loop
if len(temp_data) < limit:
# exit the while loop
break
# sleep after every 3rd call to be kind to the API
if idx % 3 == 0:
time.sleep(0.2)
# convert to data frame
df = pd.DataFrame(output_data, columns=['Symbol', 'Interval', 'TimeStamp', 'Open', 'High', 'Low', 'Close', 'Volume', 'Turnover'])
df['Date'] = [datetime.fromtimestamp(i).strftime('%Y-%m-%d %H:%M:%S.%d')[:-3] for i in df['TimeStamp']]
return df
Thanks,
Hernando