Partner Events – All Regions

December 11, 2018
When: 6:00 PM
Where: Stout 133 West 33rd Street, NY, NY 10001

Summary: Existing research has found seasonality in cross-sectional stock returns – the periodic outperformance of certain stocks during the same calendar months or weekdays. Professor Jiang and her co-authors propose a theory based upon investor mood shifts to explain these effects, and document new forms of seasonality.

In their model, assets differ in their sensitivities to investor mood, i.e., they have mood betas. During periods with positive mood shifts, stocks which have higher betas to ascending mood earn higher average returns; the converse is true during periods of negative mood shifts. They also find “congruent mood recurrence” and “non-congruent mood reversal” effects, which explain cross-sectional return seasonality. E.g., stocks which out-perform in January (a high investor mood month) tend to do better again during the same month in the future because there is a congruent mood at the time. However, these same stocks tend to under-perform in during the month of October (a low mood month) for the next several years.

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December 11, 2018

Fama-French 1992 Redux with Robust Statistics

When: 6:00 PM

Where: Fordham School of Law, MootCourt RM 1-01, 150 West 62nd Street New York, NY 10023

We begin with a brief overview of the theoretical foundations of robust statistics, including a standard outlier generating model and an optimal bias robust regression estimator. The latter is very useful for cross-section regression in empirical asset pricing research, as well as for fundamental factor model fitting. We focus on the application of the optimal robust regression estimator to the main models studied by Fama and French in their 1992 empirical asset pricing paper “The Cross-Section of Expected Stock Returns” (FF92), as well as application to two important models not considered by FF92. In doing so, we consider the time intervals 1963-2015 and 1980-2015, as well as the FF92 1963-1990 interval. The results show quite dramatically that the FF92 least squares fits are highly influenced by quite small fractions of outliers in the cross-sections, resulting in misleading conclusions concerning the behavior of the cross-section of returns for the vast majority of the equities. The robust regressions are not much influenced by outliers, and lead to opposite conclusions than some of those in FF92. In particular, robust regression shows that the size factor effect is positive rather than negative and highly significant, the beta factor effect is negative and significant rather than insignificant. Furthermore, a simple E/P factor not considered by FF92 is positive and highly significant, and all three factors in a size and beta model with interaction are highly significant. We note that a robust location estimator special case of the robust regression estimator has an important application to the time series of robust regression slopes, as well as to decile analysis of returns versus factors. We close with a strong recommendation to use the optimal bias robust regression estimator in empirical asset pricing research, and for fundamental factor model fitting.

Non-Members – $25

Members – Free

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December 12, 2018

When: 5:00 – 8:00 PM

Where: THE TRUNK CLUB
501 Boylston Street, Suite 3102
Boston, Massachusetts 02116
United States

COMBINED NETWORKING EVENT
Network meets celebrating the holidays meets shopping…
Please join CFA Society Boston, Boston Women in Finance, Women in ETFs Boston, Women in Investing; Network & Supporting, and Women Investing for a Sustainable Economy for a holiday joint-networking event! We look forward to a delightful evening of cocktails, networking and wardrobe styling at the Trunk Club Boston.

Light appetizers and drinks included.

EVENT FEE: $35 per person…

Register Here

 

December 18, 2018

When: 6:00 PM

Where: Not Your Average Joe’s
49 St James Place
Suburban Square
Ardmore, Pennsylvania 19003
United States

Please join us as we celebrate a successful year for the Philadelphia Chapter. As this time of year, we also look to help those less fortunate then ourselves. We are partnering with Women Against Abuse this year and will be collecting donations at the event. If you feel you can donate please review this link and bring your donation to the event. http://www.womenagainstabuse.org/donate/donate-goods Even if you cannot make a donation at this time, we welcome you to come and enjoy the evening.

Register Here

 

January 24, 2019

When: 8:30 AM – 5:30 PM

Where: CFA Society New York, 1540 Broadway, New York, NY

2nd Annual SQA/CFA Society NY Joint Conference “Data Science in Finance: looking beyond the hype”

Data Science is blossoming in the financial industry and literature. More and more financial firms are introducing machine learning systems to forecast markets and trade. Academics are astounded by “unprecedented out-of-sample return prediction” ability of ML and are setting а “new standard for accuracy in measuring risk premia.”[1]  They find that “in designing and pricing securities, constructing portfolios, and risk management… deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.”[2]  At the same time, “rapid empirical success in this field currently outstrips mathematical understanding.”[3]

Join us to learn from leading academics and practitioners about Data Science applications in finance and to understand what’s behind these techniques and why they work so well.

 

*First 100 people to register get $170 discount*

Early Bird Pricing 

SQA Member – $425

Non-Member – $525
Student/Transitional Member – $250

Non-Member (Affiliated) – $475

 

Regular Pricing

SQA Member – $595

Non-Member – $695

Student/Transitional Member – $250

Non-Member (Affiliated) – $645

 

January 24, 2018

2nd Annual SQA/CFA Society NY Joint Conference

“Data Science in Finance: looking beyond the hype”

When: 8:30 am – 5:30 pm

Where: CFA Society New York, 1540 Broadway, New York, NY

Data Science is blossoming in the financial industry and literature. More and more financial firms are introducing machine learning systems to forecast markets and trade. Academics are astounded by “unprecedented out-of-sample return prediction” ability of ML and are setting а “new standard for accuracy in measuring risk premia.”[1]  They find that “in designing and pricing securities, constructing portfolios, and risk management… deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.”[2]  At the same time, “rapid empirical success in this field currently outstrips mathematical understanding.”[3]

Join us to learn from leading academics and practitioners about Data Science applications in finance and to understand what’s behind these techniques and why they work so well.

*First 100 people to register get $170 discount*

Register Here

 

February 28, 2019

Quandl Data Conference 2019

Where: New York, United States

The third annual Quandl Data Conference is the industry-leading event for data-driven investing.
The shift towards systematic investing is pushing the industry to rethink everything through the lens of data – alternative and otherwise. You’ll learn about new alternative data products and strategies that drive superior performance, and how to structure your organization for success in a data-driven world.
We are pleased to welcome 450 attendees from the world’s top hedge funds, asset managers, and investment banks. This year’s event will be by invitation only.

Request for Registration