About Us

September 2024

September Newsletter

Keep up to date on the latest CQA news.

CQA Updates:

Last week we had a very successful meeting at the InterContinental Hotel on the magnificent mile in downtown Chicago. Thanks to all of the speakers for the excellent presentations. See details below on the Academic Competition results and links to the papers. The academic presentations were exceptional and the final vote was very close. The Tuesday reception was held at the Gleacher Center and we had the pleasure of watching the presidential debate while having a few drinks. The Wednesday night dinner was held at Chicago landmark Geno’s East. The weather was fantastic, with temperatures reaching the 80’s. We will be gathering feedback (see survey below) and make a decision on whether to come back to the InterContinental, return to the Gleacher Center, or explore other options for next year.

Once again we have a great list of articles in our Recommended Reads section this month. You can also check out the Recommended Reads from past newsletters on our website by clicking here.

Please see the information below on the CQA Challenge. We are still looking for schools to compete in the Challenge and the deadline is October 1.

The ASSA meetings will be in San Francisco this year and CQA will be sponsoring a reception on Friday evening. See below for more details and links to conference registration.

-Dan Cardell

CQA Fall Conference

Conference Speakers

Itzhak Ben-David
Ohio State
“Competition for Attention in the ETF Space”

Tarek Eldin
PEO Partners
“The Residual Drag – Why the Residual in Return Attributions Tends to be Negative and What to Do About It”

Estelle Inack
yiyaniQ
“Exploration of Quantum+AI Advantage in Portfolio Optimization”

Larry Siegel
Vintage Quants, LLC
“Fewer, Richer, Greener: Prospects for Humanity in an Age of Abundance”

Jeff Meli
Barclays Investment Bank
“Portfolio Trading in Corporate Bond Markets”

Andrew Weisman
Windham Capital Management
“Market Experts vs Expert Markets”

Rodney Sullivan
University of Virginia
“Global Macro and Managed Futures Hedge Fund Strategies: Portfolio Differentiators?”

Benjamin Hood
Parametric Portfolio Associates
“Volatility Targeting is Trendy: How Trend Following Explains Alpha in Volatility-Managed Strategies”

Petter Kolm
New York University
“Deep Learning of Alpha Term Structures from the Order Book”

Larry Kotlikoff
Boston University
“Why Wall Street Should Fear Economics-Based Financial Planning”

Download Agenda

Academic Competition Results

First Place

Leland Bybee

University of Chicago

"The Ghost in the Machine: Generating Beliefs withLarge Language Models"

Second Place

Norman Guo

St. Louis University

"Can Machines Understand Human Skills? Insights from Analyst Selection"

Third Place

Dat Mai

University of Missouri

"StockGPT: A GenAI Model for Stock Prediction and Trading"

Conference Location Feedback

Help us choose the best location for next year’s fall conference! Let us know if you preferred this year's InterContinental Hotel, last year’s Gleacher Center, or if you'd like to see us try somewhere new. Your input will guide us in creating an even better experience next time.

Take Survey

EFA Recap

Lubos Pastor delivered an over the top experience this year having the venue within the Bratislava Symphony building. The topics this year were high quality and hopefully we’ll have some of those presenters participate in next year’s CQA conferences. Click here for a full list of awards and the complete program.

CQA Investment Challenge

Do you know of some current students (undergrad or grad students) who are interested in the 2024-2025 CQA Investment Challenge competition?

The competition runs from October 28th to March 28th. Each school can register up to 3 teams with 5 students per team. There are 3 rounds. The first round is based completely on compliance. The second round (top 20 portfolios) is based on compliance and returns. The final round (top 10 portfolios) is based on compliance, returns, and a video that the team needs to create. A mentor/teacher is not required for each team, but it’s useful to have a mentor/teacher so that we can reach the school next year and inform them of the competition.

First place gets $3,000, second place gets $2,000, and third place gets $1,000.

For a listing of the rules Click Here
For a quick PowerPoint of the key rules Click Here

If you have participated in this competition before, then please note that there is one modification to the rules: a bit of ‘grace’.

“A Bit of Grace: During the course of the competition, teams get demerit points if they are not compliant. Teams will be able to remove up to 3 demerit points (total) during the competition (as a reminder, a team can get at most 5 demerit points / week). When a team is not compliant, then I’ll notify them that they need to fix their issues by the end of that week. If the issues are fixed, then they can claim back 3 demerit points. Once a team claims back a total of 3 demerit points in the competition, then I will not provide any further ‘grace’ and I will not provide any other warnings if they are not compliant.”

If you know of some students (or a professor at a school) that would be interested in the competition, then please have them email this registration form to Kai Petainen, at challenge@cqa.org

Once Kai gets the registration form, then he will send the group a link to the competition and students can practice their trading right away (this will not count in the rankings). Then, all the portfolios will be reset on the October 26th weekend, and the competition will start on Oct. 28th.

Larry Kotlikoff Newsletter

Fall Conference speaker Larry Kotlikoff is offering CQA members a lifetime subscription to Economics Matters, his insightful newsletter covering finance, economics, and global affairs. Click below to join for free, and Larry will personally upgrade your membership to lifetime access, giving you expert content and exclusive podcasts for the long term.

Subscribe Now

Recommended Reads

Alex Muniz - Editor
Please contact Alex at amuniz@varetire.org

“Large (and Deep) Factor Models”

This paper shows that a deep neural network trained to maximize the Sharpe ratio of the Stochastic Discount Factor is equivalent to a large factor model. It also demonstrates that deeper networks improve out-of-sample performance, with optimal results at around 100 hidden layers.

Read

“CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solving”

These researchers propose the Collaborative Multi-Agent, Multi-Reasoning-Path (CoMM) framework to enhance the problem-solving abilities of Large Language Models. CoMM uses multiple agents that collaborate by playing different expert roles, enabling better performance in complex tasks like college-level physics and moral reasoning. The framework is tested in both zero-shot and few-shot scenarios, showing improvements over traditional single-agent and chain-of-thought methods.

Read

“Intangibles Investment and Asset Quality”

This paper introduces a new "quality" factor based on an earnings measure that treats intangible and physical investments equally. Compared to the RMW factor from Fama and French, this new factor exhibits less downside risk and performs better in bear markets. It also generates a significant alpha (2.9%) relative to many existing multi-factor models, including Fama-French, largely due to effective stock selection on the long side and market timing on the short side.

Read

“The Three Types of Backtests”

This team highlights common pitfalls and biases in backtesting systematic investment strategies, which can lead to false conclusions and poor out-of-sample performance. It reviews three main types of backtesting methods—walk-forward testing, the resampling method, and Monte Carlo simulations—each with its own challenges and benefits. They also suggest techniques to improve simulation quality and offer approaches for Sharpe ratio calculations that reduce the impact of multiple trials.

Read

“Filled and Killed: Forecast and Realized Trading Costs across Horizons from Global Equity and Fixed Income Portfolio Trades”

This study examines trading costs across different regions and asset classes using data from over 2,000 portfolio transitions between 2016 and 2023, representing $3.1 trillion in trade value. The authors find that actual trading costs align with pretrade estimates, even for large and complex trades, which can be executed at relatively low cost. Using count-data models, they determine that the optimal trade horizon increases with trade risk, value, and complexity, and is similar across equities and fixed income.

Read