Implied Volatility From Theory to Practice

Something I always preach vs just something like VIX

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*TRADING ALERTS*Implied Volatility From Theory to Practice

Something I always preach vs just something like VIX

Someone in my Facebook group notified me of this QuantInsti webinar. All I can say is that implied volatility is more moving forward looking as opposed to the lazy view of VIX. It is an aggregate of historical pricing of the S&P 500 which is an average of the largest stock. It can only be used as a continuous gauge so why would you trade like that? You need to forecast the future, not the present.

Watch this video to understand

Just as note, I am finishing off the third version of the new Quant Analytics service. Why so many versions? I will do a review of the sub-par software we rely on to implement this.

Anyhow, I will be posting various videos to highlight the changes once complete which will be hopefully later today. I really don’t doing these different versions but it is part of any software development process we all go through.

This comes from someone on my Facebook group. This is also from QuantInsti

How to calculate beta ATR implied volatility with IQFeed in Python

Because of this literal showstopper, I have decided to find a few workarounds on a non Windows environment

Here are some links and Python code to help you out

#https://pypi.python.org/pypi/stockstats import stockstats import pandas as pd #better to use IQFEED to create CSV #create csv from http://stackoverflow.com/questions/22991567/pandas-yahoo-finance-datareader #use Gaspare Bonventre answer stock = stockstats.StockDataFrame.retype(pd.read_csv('stocks.csv')) print stock.get('atr') #calculate beta (R Squared) from http://gouthamanbalaraman.com/blog/calculating-stock-beta.html #implied volatility with option pricing #http://stackoverflow.com/questions/35391850/implied-volatility-calculation-in-python

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Simple demo of implied volatility and beta in Python

1/10th the amount of code vs C++ but ok for simplified arbitrage trading

Beta defined:

http://www.investopedia.com/articles/financial-theory/09/calculating-beta.asp

Code:

http://docs.scipy.org/doc/scipy-0.16.1/reference/generated/scipy.stats.linregress.html

http://quant.stackexchange.com/questions/11397/estimate-implied-volatility-using-newton-raphson-in-python

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Working demo of implied volatility in Cpp

Here is the simplest way to calculate implied volatility found from

https://www.quantstart.com/articles/implied-volatility-in-c-using-template-functions-and-interval-bisection

Get my XCode project found in my* Quant Elite Membership*

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Implied volatility and my apparent fame

From a very long time follower (one of the originals from 5.5 years ago!)

Small world Doing some implied vol. projects at work and guess whose video I come across!

On the issue of implied vol. isn’t there an online stream that has it pre-calculated for given underlying tickers?

I can say that this no longer works via Yahoo Finance. You can no longer download option chain data programatically but there may be fixes but Yahoo keeps changing it.

How to use Implied Volatility for Risk Management in Options Trading

An important risk metric if you are using options trading or option chain for liquidity or forecasting

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New video: Hooray I can finally get implied volatility from Yahoo Finance through Matlab

Finally I can calculate it via pure option chain data

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As said yesterday, I have highlight my last important view on Implied Volatility (but don’t tell anyone to keep this as part of your trading edge ;->)

*Is implied volatility the TRUE SECRET indicator to use for forward looking when to portfolio manage vs day trade for short term profit?* – See more

Details are in the exact link above!

Highlights include:

*This could be the key to long term profitable trading that the general retail traders might not know. From what I am learning, no matter how you trade over 80% of your time should be spent managing your portfolio (hello proper risk management?) vs 20% in day trading for short term profit potential. Why should we be focusing all this energy on model and strategy development when this appears to be a very short sighted way of trading. This is just a hunch at this point.*

*For my Elite members, I am focusing on this:*

**“Forward looking implied volatility enables shorter term trade vs portfolio management stance to look at long term time horizons”**

– See more

*If you are day trading all the time, you are at best handing back your profits to the market over the long run or losing most of the time. Hey no matter what you think of this theory, you are most likely going to be in the wrong but this is most likely the fundamental reason why most retail trader lose . It seems what you read is dead wrong as they are put out by amateurs who are either selling junk to you or really don’t know what really is going on* – See more

Onwards and upwards as they say!