Tag: Options

Computing Option Skews with Dask
ResearchQuant

Computing Option Skews with Dask

Post Outline * Introduction * Links + Datasets * Notebook * Next Steps Introduction This article series provides an opportunity to move towards more interactive analysis. My plan is to integrate more Jupyter notebooks and Github repos into my research/publishing workflow. For datasets that are too big to share through github I will provide a download link both here and in the github readme. I will be posting the notebooks into this blog using iframes. If you experience any issues with f

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How To Get Free Intraday Options Data With Pandas-DataReader
PythonResearch

How To Get Free Intraday Options Data With Pandas-DataReader

Post Outline * Purpose * Intuitive explanation * Code * Next Steps Purpose This is a simple reference article for readers that might wonder where I get/got my options data from. In this regard I would like to shout out the contributors to the pandas-datareader, without their efforts this process would be much more complex. Intuitive Explanation So this code consists of three components. The first is the actual script that wraps the pandas-datareader functions and downloads the options

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Exploring Our Scraped Options Data Bid-Ask Spreads (Part-2)
PythonResearch

Exploring Our Scraped Options Data Bid-Ask Spreads (Part-2)

Post Outline * Notes on Part-2 * The Data * Bid-Ask Spread Analysis * How Do Aggregate Bid-Ask Spreads Vary with Days To Expiration? * How Do Bid-Ask Spreads Vary with Volume? * How Do Bid-Ask Spreads Vary with Volatility? * Summary Conclusions Notes on Part-2 Some astute readers in the comments noted that analysis based on the absolute difference in bid-ask price is not robust when considering the price of the underlying option and can lead to spurious conclusions. They recomme

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Exploring Our Scraped Options Data Bid-Ask Spreads
PythonResearch

Exploring Our Scraped Options Data Bid-Ask Spreads

Post Outline * The Objective * The Data * Basic Data Analysis * Bid-Ask Spread Analysis * How Do Aggregate Bid-Ask Spreads Vary with Days To Expiration? * How Do Bid-Ask Spreads Vary with Volume? * How Do Bid-Ask Spreads Vary with Volatility? * Summary Conclusions The Objective Compared to the equity market, the options market is a level up in complexity. For each symbol there are multiple expiration dates, strike prices for each expiration date, implied volatilities, and that'

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How to Build a Sequential Option Scraper with Python and Requests
PythonResearch

How to Build a Sequential Option Scraper with Python and Requests

Post Outline * Recap * The Problem * The Solution * Barchart Scraper Class * Barchart Parser Class * Utility Functions * Putting it all together * The Simple Trick * Next Steps Recap In the previous post I revealed a web scraping trick that allows us to defeat AJAX/JavaScript based web pages and extract the tables we need. We also covered how to use that trick to scrape a large volume of options prices quickly and asynchronously using the combination of aiohttp and asyncio. The Pr

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How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio
PythonResearch

How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio

Post Outline * Intro * Disclaimers * The Secret to Scraping AJAX Sites * The async_option_scraper script * first_async_scraper class * expirys class * xp_async_scraper class * last_price_scraper class * The option_parser Module * The Implementation Script * References Intro This is Part 1 of a new series I'm doing in semi real-time to build a functional options data dashboard using Python. There are many underlying motivations to attempt this, and several challenges to imp

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Backtesting the Implied Volatility Long/Short Strategy (12/31/16)
QuantResearch

Backtesting the Implied Volatility Long/Short Strategy (12/31/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity returns up to 6 months! ABSTRACT Stocks exhi

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Backtesting the Implied Volatility Long/Short Strategy (12/06/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (12/06/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity returns up to 6 months! ABSTRACT Stocks exhi

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Backtesting the Implied Volatility Long/Short Strategy (11/16/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (11/16/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity returns up to 6 months! ABSTRACT Stocks exhi

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Does Factor Rank Matter for the Implied Volatility Skew Strategy?
PythonQuant

Does Factor Rank Matter for the Implied Volatility Skew Strategy?

Post Outline * Strategy Summary * Results * Conclusions/Analysis Strategy Summary First, if you're unfamiliar with the Implied Volatility Skew Strategy you can find a recent deep dive into the strategy and its performance here. In this short post, I look at the effect of using only the top N ranked ETFs from each Long/Short portfolio. In this case, N is equal to 3. This is an arbitrary selection and this study could be done with the top 1, 2, 4, etc. This differs from the original strate

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Backtesting the Implied Volatility Long/Short Strategy (10/18/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (10/18/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity returns up to 6 months! ABSTRACT Stocks exhi

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Backtesting the Implied Volatility Strategy - A Deeper Dive (10/03/16)
QuantPython

Backtesting the Implied Volatility Strategy - A Deeper Dive (10/03/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) * Deep Dive into the Weekly Strategy using Quantopian's Pyfolio * Strategy Concerns Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their

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Backtesting the Implied Volatility Long/Short Strategy (9/27/16)
ResearchQuant

Backtesting the Implied Volatility Long/Short Strategy (9/27/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity returns up to 6 months! ABSTRACT Stocks exhi

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Backtesting the Implied Volatility Long/Short Strategy (9/20/16)
QuantResearch

Backtesting the Implied Volatility Long/Short Strategy (9/20/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity returns up to 6 months! ABSTRACT Stocks exhi

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Backtesting the Implied Volatility Long/Short Strategy (9/14/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (9/14/16)

Post Outline * Strategy Restart * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Restart After a ~2 month pause, the implied volatility long/short strategy has returned! If you were previously unaware this strategy relied on aggregating free options data via the now defunct Yahoo Finance Options API. After some time I was able to track down another free, reliable, source for options data via Bar

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Aggregating Free Options Data with Python
PythonQuant

Aggregating Free Options Data with Python

Post Outline * Motivation * Code Requirements * Creating our Scraper Class * Aggregating the Data * Github Gist Code * Disclaimers Motivation This year I implemented a simulated trading strategy based on the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor has predictive power for equity returns for up to 6 months. Because historical options data

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Backtesting the Implied Volatility Long/Short Strategy (7/12/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (7/12/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Update (Target Leverage=1) * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts ind

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Backtesting the Implied Volatility Long/Short Strategy (7/6/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (7/6/16)

Post Outline * Strategy Summary * References * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Update (Target Leverage=1) * 1-Week Holding Period Strategy Updated (Target Leverage=2) Strategy Summary This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts ind

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Backtesting the Implied Volatility Long/Short Strategy (6/28/16)
PythonQuant

Backtesting the Implied Volatility Long/Short Strategy (6/28/16)

Post Outline * 4-Week Holding Period Strategy Update * 1-Week Holding Period Strategy Update (Target Leverage=1) * 1-Week Holding Period Strategy Updated (Target Leverage=2) 4-Week Holding Period Strategy Update Download the spreadsheet here. 1-Week Holding Period Strategy Update (Target Leverage=1) Results simulated using quantopian platform 1-Week Holding Period Strategy Update (Target Leverage=2) RESULTS SIMULATED USING QUANTOPIAN PLATFORM I'll post the components of each of the

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Updating the Implied Volatility L/S Strategy (6/21/2016)
PythonQuant

Updating the Implied Volatility L/S Strategy (6/21/2016)

There are two versions of this strategy that I have previously tracked and reported. The original strategy consists of forming weekly portfolios each held for a period of four (4) weeks before being liquidated. The second strategy is a higher frequency version which forms weekly portfolios with a holding period of one (1) week. Thus far, both strategies have exceeded expectations. Their apparent theoretical success is so far beyond expectations it required much deeper investigation and better si

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (6/04/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (6/04/16)

To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. However this study will focus on ETF's as opposed to single name e

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/31/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/31/16)

To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. However this study will focus on ETF's as opposed to single name e

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/21/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/21/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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BACKTESTING THE IMPLIED VOLATILITY STRATEGY WITH QUANTOPIAN (5/20/16)
PythonQuant

BACKTESTING THE IMPLIED VOLATILITY STRATEGY WITH QUANTOPIAN (5/20/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here. To summarize, the strategy calculates a SKEW measure using ATM calls and OTM puts for a collection of ETF symbols. It then sorts the symbols into quintiles based on the SKEW factor. Using daily close/close log return calculations for this strategy has shown exceptional performance as can be seen here. However, translating a successful dail

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/14/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/14/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/08/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (5/08/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/30/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/30/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/24/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/24/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/17/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/17/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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BACKTESTING THE IMPLIED VOLATILITY STRATEGY WITH QUANTOPIAN (4/09/16)
PythonQuant

BACKTESTING THE IMPLIED VOLATILITY STRATEGY WITH QUANTOPIAN (4/09/16)

To see the origin of this series click here. To summarize, the strategy calculates a SKEW measure using ATM calls and OTM puts for a collection of ETF symbols. It then sorts the symbols into quintiles based on the SKEW factor. Using daily close/close log return calculations for this strategy has shown exceptional performance as can be seen here. However, translating a successful daily strategy with no transaction costs and perfect trading fills into a robust strategy that can execute and perfo

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/09/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/09/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/02/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (4/02/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by fol

READ MORE
USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/29/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/29/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by f

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PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/19/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by f

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/14/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/14/16)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by f

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/05/16)
PythonGlobal Markets

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (3/05/16)

#block-yui_3_17_2_2_1457211500463_15952 .social-icons-style-border .sqs-svg-icon--wrapper { box-shadow: 0 0 0 2px inset; border: none; } FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smir

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BACKTESTING THE IMPLIED VOLATILITY STRATEGY WITH QUANTOPIAN (2/27/16)
PythonQuant

BACKTESTING THE IMPLIED VOLATILITY STRATEGY WITH QUANTOPIAN (2/27/16)

#block-yui_3_17_2_5_1456621692348_14798 .social-icons-style-border .sqs-svg-icon--wrapper { box-shadow: 0 0 0 2px inset; border: none; } FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here. To summarize, the strategy calculates a SKEW measure using ATM calls and OTM puts for a collection of ETF symbols. It then sorts the symbols into quintiles based on the SKEW factor. Using daily close/cl

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/20/16)
Global MarketsPython

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/20/16)

#block-yui_3_17_2_3_1456020426677_22579 .social-icons-style-border .sqs-svg-icon--wrapper { box-shadow: 0 0 0 2px inset; border: none; } FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smir

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/13/16)
Global MarketsPython

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/13/16)

#block-yui_3_17_2_4_1455397888451_24737 .social-icons-style-border .sqs-svg-icon--wrapper { box-shadow: 0 0 0 2px inset; border: none; } FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smir

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/06/16)
PythonGlobal Markets

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/06/16)

To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. However this study will focus on ETF's as opposed to single name

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (1/30/16)
PythonGlobal Markets

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (1/30/16)

To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. However this study will focus on ETF's as opposed to single name

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (1/23/16)
PythonGlobal Markets

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (1/23/16)

To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. However this study will focus on ETF's as opposed to single name

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USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (1/17/16)
ResearchQuant

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (1/17/16)

To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors' research shows that their calculation of the Option Volatility Smirk is predictive of equity returns up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. However this study will focus on ETF's as opposed to single name

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USING IMPLIED VOLATILITY TO PREDICT EQUITY/ETF RETURNS (1/11/16)
PythonQuant

USING IMPLIED VOLATILITY TO PREDICT EQUITY/ETF RETURNS (1/11/16)

To see the origin of this series click here In the paper that inspired this series ("What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns") the authors research shows that Option Volatility Smirk they calculate is predictive up to 4 weeks. Therefore, each week, I will calculate the Long/Short legs of a portfolio constructed by following their criteria as closely as possible. I will then track the results of the Long/Short portfolio, in equity returns, cumulatively fo

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Using Implied Volatility to Predict Equity/ETF Returns
Equity AnalysisPython

Using Implied Volatility to Predict Equity/ETF Returns

During a discussion with an knowledgeable options trader, I was told the significance of interpreting the "Implied Volatility Skew" for stocks and given a paper to read for homework. To get a basic understanding of Implied Volatility Skew see this link here. The paper I was told to read was "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. In their paper they show empirically, using their SKEW measure, allowed one to p

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