Newbie here, it happens that I have 8 months of OHLC price data set at 1 hour timeframe from a particular cryptocurrency (ticket) called ALICE
, here's a little sample of those:
The first column above represent the timestamp of the open price, the next 4 columns represent the OHLC price values (set in USD), and the next to the next column represents the timestamp of the close price.
In this case, the last row in the dataframe above has the following OHLC values:
O = 7.56459843
H = 7.70936971
L = 7.45377539
C = 7.68385709
Now, if we look for the corresponding candle to that row in this chart we get the following candle in the picture down below:
And that candle has the following OHLC values:
O = 7.557
H = 7.709
L = 7.444
C = 7.681
So, as can be seen, the OHLC values I have do not exactly match with the OHLC values displayed in the chart.
So, I want to know if I just should round (up or down) every single OHLC value in my dataframe up to having 3 decimal points, before starting the definition and backtest of any trading strategy on this?
Or, should I actually work with the data as were delivered to me?
Keep in mind that, obviously, when trying whatever strategy on live trading, the bot could only set prices up to 3 decimal points, so it would have to round the values anyway