Simple (portfolio)
heuristics that make us
smart(er)
03/20/2025
Giuseppe (Gappy) Paleologo
Balyasny Asset Management
Plan & Message
●
Goal : help bridge the gap between book-level Mean-Variance
Optimization and application-level MVO…
●
… by proposing modifications that give a Minimum Viable Product
in closed form
●
Messages : Simple is beautiful. Simple is not easy.
●
Requirements : basics of factor models; basics of Mean-Variance
Optimization (MVO). See book recommendations at the end.
●
Disclaimers : the opinions expressed in this talk are not
necessarily those of my cat. Or my employer. Also, not investment
advice.
A Practical Problem
1.
2.
3.
4.
5.
6.
You have "alphas": expected returns of a large set of assets
They change fast enough, and you are rich enough, that you have to
worry about transaction costs
You have a primitive factor model, e.g., a simple 1-factor model, or
a more complex non-commercial one (e.g.,
https://github.com/0xfdf/toraniko)
Optimization is either too complex or it gives unintuitive
results
You want to generate a tradeable portfolio that is essentially
correct
N.B.: I wrote a book and discarded a lot of material. This talk is
discarded material from the red book
What People Do
●
Real weird stuff, like this:
exp. return
avg. daily volume
or this:
est. daily volatility
but with ceiling and floors on the parameters because otherwise
the formula gives strange recommendations
A Different Procedure
First, orthogonalize your alphas to factors. Very standard procedure
(e.g., see my coming book on quant investing). For example, for a simple
market model with betas
Because of orthogonalization, in the absence of transaction costs, the
MVO only sees the diagonal idiosyncratic covariance matrix.
Second, solve the MVO problem. Now it's separable.
=>
(separable because cov.mat. is diagonal)
We need a market impact model. Almgren-Chriss:
estimate k, calibrate it or
get from a reputable source
Reasonable Asymptotics
Exercise: what is the asymptotic size for lambda -> Inf?
Extension #1: Initial Trading Positions
We can extend to non-zero
initial positions, at zero-cost
[pun!].
Intuition:
1.
2.
change of alpha
change of starting point
Extension #2: Alpha Uncertainty
This is much more important an non-trivial. Assume
We estimate tau from the Information Coefficient. It is usually high!
(~1/IC):
=>
=>
Summing Up
1.
Orthogonalize. Always
2.
Regularize. Always
3.
Account for transaction costs. Also Alw…
4.
A lot of good science & engineering is knowing what terms to keep
and what terms to drop
Coordinates, books
X (finance): @__paleologo
LinkedIn:
www.linkedin.com/in/gappy/
Web: linktr.ee/paleologo
Advanced Portfolio Management
The Elements of Quantitative
Investing
The title of the talk is a homage to
a great psychologist (B.Gigerenzer).
Here is his book:
Simple Heuristics That Make Us
Smart