I’m running a Supertrend based algo, but at market open (9:15), the signals are completely wrong for the first few minutes.
After that, everything becomes normal.
I’m generating my own 1-minute candles from ticks.
Is this a data issue or something wrong with Supertrend calculation?
And I am using Zerodha’s kite.trade
Supertrend depends on ATR, and ATR needs historical candles.
So, you have to pass both the historical and live data.
Aggregate the data first and then pass in Supertrend function you will get the accurate value.
Eg code below:
def get_supertrend_input(symbol, live_candles):
# Fetch historical
query = "GET HISTORICAL DATA"
values = [symbol, "minute"]
historical_candles = fetch_historical_data(query, values)
# Merge
all_candles = historical_candles + live_candles
# Safety check
if len(all_candles) < 15: # minimum for ATR(10)
return []
return all_candles
def run_supertrend(symbol, live_candles):
candles = get_supertrend_input(symbol, live_candles)
if not candles:
return None
result = compute_supertrend(candles, period=10, multiplier=3)
if not result:
return None
return result[-1] # latest signalYes, this happens because of candle instability at market open.
At 9:15 the volatility is very high, candles move very fast, ATR is not stable initially that’s why this happens.
So, the main fix is using only closed candles, wait for enough candles like 20 candles minimum and use proper ATR smoothing/alignment.
After first few candles your super trend will be working great.
Can refer the below code:
def compute_supertrend(candles, period=10, multiplier=3):
if len(candles) < period + 2:
return []
trs = []
for i in range(1, len(candles)):
h = candles[i]["high"]
l = candles[i]["low"]
pc = candles[i - 1]["close"]
tr = max(
h - l,
abs(h - pc),
abs(l - pc)
)
trs.append(tr)
if len(trs) < period:
return []
atr_vals = [sum(trs[:period]) / period]
for i in range(period, len(trs)):
atr = (
(atr_vals[-1] * (period - 1)) + trs[i]
) / period
atr_vals.append(atr)
atr = [None] * period + atr_vals
final_upper = [None] * len(candles)
final_lower = [None] * len(candles)
supertrend = [None] * len(candles)
direction = [None] * len(candles)
result = []
for i in range(len(candles)):
if atr[i] is None:
result.append(None)
continue
h = candles[i]["high"]
l = candles[i]["low"]
c = candles[i]["close"]
hl2 = (h + l) / 2
upper_band = hl2 + (multiplier * atr[i])
lower_band = hl2 - (multiplier * atr[i])
if final_upper[i - 1] is None:
final_upper[i] = upper_band
final_lower[i] = lower_band
else:
prev_upper = final_upper[i - 1]
prev_lower = final_lower[i - 1]
prev_close = candles[i - 1]["close"]
final_upper[i] = (
upper_band
if upper_band < prev_upper or prev_close > prev_upper
else prev_upper
)
final_lower[i] = (
lower_band
if lower_band > prev_lower or prev_close < prev_lower
else prev_lower
)
if supertrend[i - 1] is None:
if c <= final_upper[i]:
supertrend[i] = final_upper[i]
direction[i] = "SELL"
else:
supertrend[i] = final_lower[i]
direction[i] = "BUY"
elif supertrend[i - 1] == final_upper[i - 1]:
if c <= final_upper[i]:
supertrend[i] = final_upper[i]
direction[i] = "SELL"
else:
supertrend[i] = final_lower[i]
direction[i] = "BUY"
else:
if c >= final_lower[i]:
supertrend[i] = final_lower[i]
direction[i] = "BUY"
else:
supertrend[i] = final_upper[i]
direction[i] = "SELL"
result.append({
"supertrend": round(supertrend[i], 2),
"signal": direction[i]
})
return result
# Sample candles - reolace thsi with actual live candle data
candles = [
{"high": 101, "low": 99, "close": 100},
{"high": 102, "low": 100, "close": 101},
{"high": 103, "low": 101, "close": 102},
{"high": 104, "low": 102, "close": 103},
{"high": 105, "low": 103, "close": 104},
{"high": 106, "low": 104, "close": 105},
{"high": 107, "low": 105, "close": 106},
{"high": 108, "low": 106, "close": 107},
{"high": 109, "low": 107, "close": 108},
{"high": 110, "low": 108, "close": 109},
{"high": 111, "low": 109, "close": 110},
{"high": 112, "low": 110, "close": 111},
{"high": 113, "low": 111, "close": 112},
]
result = compute_supertrend(candles)
for row in result:
print(row)