I'm co-hosting a new podcast series with Chat with Traders. Chat with Traders is a podcast in which career traders come on and chat about their work and philosophy with the host, Aaron Fifield. We thought it would be a lot of fun to bring a series covering quantitative investing to the podcast, so we sat down with Aaron and produced a series of 6 episodes covering various parts of a quantitative workflow. The final episode will be a Q&A episode. Send your questions in here.
In the podcast we make references to lectures, tutorials, and examples from Quantopian and elsewhere. I'll post the links to the references here.
Episode 1 - You Don't Know How Wrong You Are
Guests: Delaney Granizo-Mackenzie
The worst case in finance is when you think you’re right, but you’re actually wrong. This can be especially dangerous when you’ve used some methodology or statistics to justify a decision, but are unaware of all the subtle biases that can cause false results. In this episode we’ll cover many of the ways that you can be wrong without knowing it in trading and finance.
- Jupyter Notebooks/Research Tutorial
- The Quantopian Lecture Series
- Our Open Sourced Code on GitHub
- Quantopian API Tutorials
- Weird Meaningless Correlations
- Michael Halls-Moore on Chat with Traders
- An Example of a Satellite Imagery Data Provider
Episode 2 - Seeking Alpha? Try Alpha Factors
Guests: Dr. Jessica Stauth and Delaney Granizo-Mackenzie
Factors are at the core of a modern quant equity workflow. We’ll introduce the notion of alpha and risk factors at a high level, and delve into some of the use cases which include: understanding how the market is moving, understanding how a portfolio is exposed to sources of risk, and turning ideas for price forecasting into encapsulated alpha factors.
- Can Investing in Female CEOs Beat the Market?
- Position Concentration Risk
- Universe Selection
- Alpha Factors
- Risk Factors
- The Signal and the Noise, Nate Silver
- Fooled by Randomness, Nassim Taleb
Episode 3 - Seeking Alpha? Try More Alpha Factors
Guests: Jonathan Larkin and Delaney Granizo-Mackenzie
In practice, no one trading model will ever be that good on its own. Luckily statistics has come up with a lot of theory about how you can combine weaker models to create better overall predictions. We’ll discuss how to combine many different trading signals into overall models and some of the practical considerations in doing so.
Episode 4 - Portfolio Optimization: Risk Preferences go in, Trades Come Out
Guests: Scott Sanderson and Delaney Granizo-Mackenzie
When one has a price model that they think will work well for forecasting returns, the next step is to actually trade it. This isn’t that simple for a variety of reasons. For one thing, you need to define how much risk you’re okay with taking on in a portfolio, and then try to maximize your returns while staying within those boundaries. This is the foundation of modern portfolio theory, and we’ll discuss some real life issues with this.
- Intro to Optimization
- Optimization API
- Portfolio Optimization notebook
- Real returns vs. Normal distributions
- How mass shootings and politics boost gun shares
Episode 5: Good and Bad Uses of Machine Learning in Finance
Guests: Max Margenot and Delaney Granizo-Mackenzie
Machine learning is a very hot topic these days, with a lot of people wondering how it could be used in finance. Used naively, machine learning poses a great deal of risk. We’ll discuss why that’s the case and also some good ways to use it carefully.
- Dr. Andrei Kirilenko
- Machine learning on Quantopian
- Machine learning alpha factor
- Andrew Ng
Episode 6: Q&A
Guest: Delaney Granizo-Mackenzie
Thanks for all the great questions, we answered as many as we could here.
- Frank Fabozzi
- Dessislava A. Pachamanova
- Driven to Distraction Example by Rob Reider
- Quantitative Investment Analysis
- Big data: The next frontier for innovation…
- Pyfolio – Portfolio and risk analytics in Python
- Pyfolio Example
- Machine Learning on Quantopian
- How Accurate is Our Slippage Model
- Position Concentration Risk
- How to Get an Allocation