I have obtained daily close price stock data ( and transformed them to logarithmic returns series data) from a Stock Exchange between 2 financial years, and I wish to generate a power spectral density to study its behaviour.
I work on Python , I went to the documentation of Scipy.Signal.Welch : https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.welch.html#r34b375daf612-1
Under parameter documentation it is written : fs: float, optional Sampling frequency of the x time series. Defaults to 1.0
I can not figure a way out to find a sampling frequency for the daily frequency financial time series data which I have. (my time series data is daily date indexed i.e. 12/1/2023 is the date and corresponding close price value is attached.)
Also if possible could the experts on this forum explain the parameters mentioned in documentation mean : window , nperseg, noverlap and what should be their recommended settings values for daily frequency financial time series data and returns series data.