BTC/USDT Probability Plot

I have been working on developing a technical indicator based upon the binomial model. Essentially estimating the 95% CI of the probability of the next close being higher than the current close.
In the above, I have linked directly to the CoinGecko API and so it should be live - up to the minute data for the last 31 days

  For x observed nonconforming units in a sample of size n,
      a two-sided conservative 100(1 − α)% confidence interval for π is
      [π, π􏰆] = [qbeta(α/2;x,n−x+1), qbeta(1−α/2;x+1,n−x)]
      Without making any assumptions about the form of the distribution of the closes,
      it is possible to estimate Pr(close+1>close): the probability of exceeding the current close price.
      We assume naively that both the past and the future close prices are independently and randomly chosen
      from the same stationary process.  An estimate of this probability is the count of previous close prices
      that are greater than the current close price divided by the number of closes up until now.
      The binomial distribution can then be used to compute a one-sided lower confidence bound on this probability.
      The conservative method below gives a one-sided lower 95% confidence bound on the probability of exceeding
      the current close  on a randomly selected close.

NB it would be better to test for stationarity first (eg with an ADF test) and be sure we arent in a trend (i.e. kendall)