Analysis on candles

Currencies pretty much open a new daily bar - where they previously closed, obviously excluding certain Sunday nights when news related events happen over the weekend.

So to say cross candle bottom - that's where they left off :confused:
 
Currencies pretty much open a new daily bar - where they previously closed, obviously excluding certain Sunday nights when news related events happen over the weekend.

So to say cross candle bottom - that's where they left off :confused:

Great point, the analysis roughly excludes the first hourly bar.

Code:
def getFirstCrossFromBelow(x,column,column_to_cross):
  crosses = x[(x.baropen_datetime > x.session) &
  (np.sign(x[column] - x[column_to_cross]) > 0) & \
  (np.sign(x[column].shift() - x[column_to_cross]) < 0)]
  if len(crosses):
  return crosses.iloc[0].baropen_datetime
 
normal distribution (i.e. bell shaped cureve) would allow you stablish mean and SD, from which SD divided by square root of number of observations would give you std error of the mean (SEM) from that co-efficient of variation within a population of candles.
 
normal distribution (i.e. bell shaped cureve) would allow you stablish mean and SD, from which SD divided by square root of number of observations would give you std error of the mean (SEM) from that co-efficient of variation within a population of candles.

Distribution of *what* though?
 
Candle analysis emerged more than 20 years ago, and is still quite popular today. Some people even consider that Japanese candles are the easiest and most comfortable format to represent the prices of the assets
 
Candles are randomly formed by time and by themselves pointless.

But better than line because you can see where spikes down/up have happened, which can indicate reversals.
 
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