Calculating the difference between Parkinson's volatility and normal volatility is useful for trading low-liquidity financial assets.
A high Parkinson's volatility with a low normal volatility tells us about a profitable trading opportunity with low risk.
In this case, we create a function that returns a bar chart with the top-20 spreads given 2 limits: an upper limit for the volatility and a lower limit for the difference value.
Market data is from the last 3 months provided by yfinance
Formulas for each type of volatility.
Normal volatility has as input the Close price serie.
Parkinson´s volatility has as input Low and High price series.
We then define our v_df dataset that we will work with, which contains both volatilities with their difference for each Ticker.
The last function find_ticker with inputs:
♦ dif which is the minimum difference between both volatilities that we want
♦ v which is the maximum normal volatility (Risk) that we want to assume
Search in v_df for all the stocks that meet those requirements and return a bar chart with the first 20 ordered by the difference between volatilities
