--- title: CC junk Rookley tags: research --- # Rookley's method summarized by Ning :::info This document summarizes feedback from Ning and my questions after running his codes. ::: ## Python scripts by Franziska Wehrmann 1. The file with the name "risk_neutral_density.py" defines a function that returns the calculated result of a State-Price Density (SPD). 2. The file with the name "smoothing.py", using the data set to be inputted, defines in the end a function that returns the estimated values of inputs that are needed in the function defined in "risk_neutral_density.py". 3. The file with the name "plotting.py" returns to 1. scatterplots of data for all possibilities of tau_day (dates to maturity) given the fixed date; 2. calculated SPDs for all possibilities of tau_day given the fixed date; 3. volatility smile + 1st derivative of implied volatiloty + 2nd derivative of implied volatility for all possibilities of tau_day (dates to maturity) given the fixed date; (:question: green for implied volatility $\sigma$, blue, and green? ) 4. For each possibility of tau_day, the scatterplot +implied volatility together with its 1st and 2nd derivatives plots+ the calculated SPD. 4. The file with the name "CrypOpt_RiskNeutralDensity.py" is the main body of the codes. One uses this part to input the data set of a fixed date and gets a output called "res" that contains the following values: - 'df': the data columns of ['M', 'iv', 'S', 'K'] (moneyness, implied volatility, underlying price, strike price) for all possibilities of tau_day given the fixed date - 'M': moneyness (underlying prices divided by strike prices) - 'smile': implied volatility - 'first': first derivative of implied volatility - 'second': second derivative of implied volatility - 'K': strike prices - 'q': (local polynomial kernel) SPD - 'S': underlying prices (corrected for future dividends) ## Input The file "trades_clean.csv" provided by Ms. Franziska Wehrmann has the following varaibles and descriptions: | Index | Column | Description | |---|----|---| |1 | date|trading date in the format of "2020/3/4"| |2 | P| :question: | |3 |S| underling price| |4 |K|strike price | |5 | tau| days to maturity divided by 365| |6 |tau_day| days to maturity in days| |7 |iv| implied volatility | |8 |M| Moneyness (underlying prices divdided by strike prices)| |9 |r| risk-free rate | |10 |option| 'P': put, 'C': call |11 | direction| 'sell', 'buy'| ## Output of Franziska's data ### Fig A. Smoothing the implied volatility at different times to maturity ![](https://i.imgur.com/scDLszz.png) ### Fig B. Risk-neutral probability ![](https://i.imgur.com/eB3x4p8.png) ### Fig C. Why there are three different colors of implied volatility?(:question:) ![](https://i.imgur.com/OMCShGY.png) ### Fig D. Whats are the differences between the implied volatility and that in Figs A, B, C? Why the implied volatility in orange color is negative? ![](https://i.imgur.com/GeNia1n.png) ![](https://i.imgur.com/MdJT5pg.png) ![](https://i.imgur.com/v9saYdj.png) ## Output of the data from BRC