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Institutional Level Long/Short Strategies in Quantopian (OCF/EV)
PythonQuant

Institutional Level Long/Short Strategies in Quantopian (OCF/EV)

Post Outline * Background * Strategy Summary * Implementation Details * Strategy Results and Analysis * References (Notes) Background Recently I was blessed with an introduction to S&P Global-Market Intelligence's Director of Business Development, Matt Morrissy and gifted a trial membership to the S&P Capital IQ platform [1]. Specifically, I was given an opportunity to review and provide feedback for their "Alpha Factor Library." Their team, the Quantamental Group [2], has researched an

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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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Estimated Longevity of a Retirement Portfolio in Years (Python)
EducationPython

Estimated Longevity of a Retirement Portfolio in Years (Python)

Post Outline: * What is Shortfall Risk (Shortfall Probability, Ruin Risk, Risk of Ruin etc.)? * Issues with Traditional Shortfall Risk Estimates * Key Insights (Solutions) * Python Code (Implementation) What is Shortfall Risk (Shortfall Probability, Risk of Ruin, etc.)? portfolio value will fall below some minimum acceptable levelover some time horizonAnalystNotes.com Issues with Traditional Shortfall Risk Estimates In the article "It's Time to Retire Ruin (Probabilities)" the author,

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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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COMPOSITE MACRO ETF WEEKLY ANALYTICS (5/14/2016)
PythonGlobal Markets

COMPOSITE MACRO ETF WEEKLY ANALYTICS (5/14/2016)

FOR A DEEPER DIVE INTO ETF PERFORMANCE AND RELATIVE VALUE SUBSCRIBE TO THE ETF INTERNAL ANALYTICS PACKAGE HERE LAYOUT (Organized by Time Period): Composite ETF Cumulative Returns Momentum Bar plot Composite ETF Cumulative Returns Line plot (best vs worst vs benchmark) Composite ETF Risk-Adjusted Returns Scatter plot (Std vs Mean) Composite ETF Risk-Adjusted Return Correlations Heatmap (Clusterplot) Implied Cost of Capital Estimates Composite ETF Cumulative Return Tables Notable Trends an

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