Tag: SKEW

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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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

READ MORE
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

READ MORE
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

READ MORE
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

READ MORE
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

READ MORE
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

READ MORE
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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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

READ MORE
USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/27/16)
PythonGlobal Markets

USING IMPLIED VOLATILITY TO PREDICT ETF RETURNS (2/27/16)

#block-yui_3_17_2_1_1456604859059_182762 .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 Smi

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