I’m using Camarilla pivot in my algo and calculating it from 1-minute candles.
I’m already checking HLC properly, but still the pivot levels are not matching chart values.
Am I missing something here?
Yes, this will happen in the one minute candle data is used from the historical data.
Because, Camarilla (and most pivots) should not be calculated from one minute candles.
Correct approach:
You have to calculate pivot in the previous full day candle not the previous day one-minute candles.
Because the last candle close in the minute candle is different from the previous full day candle – just slightly different of some points but still the values in pivot will be inaccurate.
Below is the code that you can refer:
def camarilla_pivot(prev_high, prev_low, prev_close):
diff = prev_high - prev_low
levels = {
"H1": prev_close + (diff * 1.1 / 12),
"H2": prev_close + (diff * 1.1 / 6),
"H3": prev_close + (diff * 1.1 / 4),
"H4": prev_close + (diff * 1.1 / 2),
"PP": (prev_high + prev_low + prev_close) / 3.0,
"L1": prev_close - (diff * 1.1 / 12),
"L2": prev_close - (diff * 1.1 / 6),
"L3": prev_close - (diff * 1.1 / 4),
"L4": prev_close - (diff * 1.1 / 2),
}
return levels
# Example (use previous day data of 1 day timeframe candle)
prev_high = 200
prev_low = 180
prev_close = 190
levels = camarilla_pivot(prev_high, prev_low, prev_close)
print(levels)