trading

According to @rspadim, functions in entropy.py could use numpy array instead of strings, as it's better to numba.

Guide on how to implement this is available in the comments in PR #311 .

hi,
if possible, please add these indicators as well:
TDI (Traders Dynamic Index)
chandelier exit
pivot points
BOP (balance of power)
CTM (Chande trend meter)
Coppock Curve
Correlation Coefficient
PMO (DecisionPoint Price Momentum Oscillator)
Ulcer Index
most of them except TDI are available on stockcharts.com
thanks

Some suggestions to make it easier to run the backend without the front end. Some of these suggestions might be *ix only:

• a command line parameter to indicate that the back end should start with everything that is pending without waiting for a front end to be available in the browser.
• some instruction to make it work as a daemon (Linux) or service (Windows) to gain independence from the te

this is how Buy & Hold Return is calculated:

        c = data.Close.values
        s.loc['Buy & Hold Return [%]'] = (c[-1] - c[0]) / c[0] * 100  # long-only return

so it's calced use day one and the day last.

Expected Behavior

Buy & Hold Return is used for compare with strategy gain. Therefore, I guess they should started at same time, since the strategy get enough data to w

import yfinance as yf
from pandas_ta.overlap import kama
import mplfinance as mpf

ticker = yf.Ticker("SPY")
minute_data = ticker.history(period="7d", interval="1m")

kama_results = kama(minute_data["Close"])
addplot = [
    mpf.make_addplot(kama_results, color='blue')
]
mpf.plot(minute_data, volume=True, type='candle', addplot=addplot)

![Figure_1](https://user-images