24
votes
Accepted
Why is Markowitz portfolio optimisation so popular considering it is worse than an equal weighted portfolio?
Markowitz's concepts attracted a great deal of interest from theorists (and still do), but never had much application in practice. The results from practical application were always disappointing (...
- 9,462
13
votes
Accepted
cvxpy portfolio optimization with risk budgeting
The underlying problem: your ACTR constraints aren't convex
The $i$th constraint on your risk contribution can be written:
$$ w_i \sum_j \sigma_{ij} w_j \leq c_i s$$
And this isn't a convex ...
- 6,334
13
votes
Accepted
Random Portfolios vs Efficient Frontier
You seem to have two distinct problems:
How to generate random portfolios
How optimal portfolios are structured
Ad 1)
A straightforward way to simulate the weights of random portfolios is to use ...
- 1,933
10
votes
Maximum Sharpe portfolio (no short selling restrictions)
Let $R$ be a random vector of risky returns and let $r_f$ denote the risk free rate. Let vector of expected returns $\boldsymbol{\mu} = \operatorname{E}[R]$ and covariance matrix $\Sigma = \...
- 6,334
10
votes
When looking for arbitrage among a LARGE amount of assets, is there an optimal way?
For example, Thomas H. Cormen, Charles E. Leiserson, Ronald Rivest, Clifford Stein. Introduction to Algorithms, problem 24-3 says:
24-3 Arbitrage
Arbitrage is the use of discrepancies in currency ...
- 9,574
9
votes
What are some useful approximations to the Black-Scholes formula?
The logistic distribution approximates the normal distribution function used in the Black-Scholes. The drawbacks to the normal cumulative distribution function are that it cannot be computed exactly ...
- 2,845
9
votes
Accepted
Application of Control Theory in Quantitative Finance
Of course, optimal control is at the core of math finance. Take few applications:
Option Pricing: you have an exposure to a time dependent combination of market factors; you have some knowledge of ...
- 10.6k
9
votes
Why is Markowitz portfolio optimisation so popular considering it is worse than an equal weighted portfolio?
There has been a split in the community ever since Mandelbrot published his paper "On the Variation of Certain Speculative Prices."
See:
Mandelbrot, B. (1963). The variation of certain speculative ...
- 4,092
9
votes
Why is Markowitz portfolio optimisation so popular considering it is worse than an equal weighted portfolio?
It is more complicated than that: It is not the optimization per se that leads to inferior results but the data you use.
Kritzman et al. makes a strong case in defense of optimization vs. 1/N in this ...
- 26.9k
9
votes
Accepted
Maximum Sharpe portfolio (no short selling restrictions)
There are two cases, where short sales are allowed: With riskless lending and borrowing and without. As mentioned in the comments, you just have to solve a linear system.
With riskless lending and ...
- 2,956
8
votes
Maximum Sharpe portfolio (no short selling restrictions)
To complement @skoestimeier's answer on the shortselling-allowed case, I provide a vectorised version. Using the original notation in my post (you may change $r$ to something like $r-r_f$, but this ...
- 921
6
votes
Do hedge fund trading desks use portfolio optimization?
Portfolio optimization techniques are used quite a bit by hedge funds. I think you misunderstand how portfolio optimization operates in the context of an active trading strategy. Your question ...
- 537
6
votes
Accepted
Maximum Certainty Equivalent Portfolio with Transaction Costs
Seems like a small mistake in the last equation. It should read
$\Delta^* = A^{-1} \left[\mu-\gamma \Sigma \omega_c - \frac{1}{\iota'A^{-1}\iota} \iota' A^{-1}(\mu-\gamma \Sigma \omega_c )\iota\...
- 116
6
votes
Accepted
What's the importance of duality theory in portfolio optimization?
That's a pretty heavy question for this forum, and its answer is worthy of a semester-long discussion in a university course. The short answer is that (for convex optimization) the dual problem can ...
- 511
5
votes
Accepted
How to apply Levenberg Marquardt to Max Likelihood Estimation
An AR(1), once the time series and lags are aligned and everything is set-up, is in fact a standard regression problem. Let's look, for simplicity sake, at a "standard" regression problem. I will try ...
- 693
5
votes
Quantum Computing for Quantitative Finance
Try Quantum for Quants, which has contributions from people working actively in quantum computing, and some small scale examples solved on the D-Wave Systems Quantum Annealer.
The picture below is ...
- 167
5
votes
Proof that linear returns aggregate across securities
I think you are simply confusing percentage weights and number of assets.
In your definition the initial percentage weight of the $m$ assets in the portfolio are given by $w_i^{t - 1}$ and they sum ...
- 5,800
5
votes
Accepted
Derivation of the efficient frontier set (markowitz problem)
To solve this constraint minimization problem, first form the Lagrangian Function
\begin{align}
L(w,\lambda_1,\lambda_2)=w'\Sigma w + \lambda_1(w'\boldsymbol{\mu}-m) + \lambda_2 (w'\boldsymbol{1}-1).
\...
- 177
5
votes
Accepted
Question on Rockafellar's Paper for optimisation of CVaR
On 1, I suspect that is a typo and that the second formula should sum to r.
On 2, that is applying well-known techniques in how to handle piece-wise linear functions in an optimizer. For instance, ...
- 5,311
5
votes
Accepted
Optimisation with strong correlated Assets
This answer will try and outline all the different possibilities I came across over the last couple of years, including drawbacks. But first, let me outline the problem a little.
To appreciate the ...
- 2,874
5
votes
Accepted
Linear Regression vs Mean Variance Optimization
In a linear regression approach you do the following:
$$
(X \beta - y)^2 \rightarrow Min
$$
thus you try to predict something. Your objective is quadratic. You usually add constraints on $\sum \...
- 13.3k
5
votes
Accepted
Question about quadratic form of f* in the Continuous Kelly Criterion
The Kelly Criterion aims to maximise the expected value of the logarithm of terminal wealth. The derivation starts off by assuming that there is a risky asset that is following a Geometric Brownian ...
- 1,356
5
votes
Accepted
Do you optimise models on bootstrapped time series?
Simulation for timeseries data is not a trivial matter and there are a number of methods to ensure you retain some of the relevant properties (mostly called dependent bootstrap methods):
Block ...
- 1,018
5
votes
Accepted
Double objective in portfolio optimization
There is nothing wrong mathematically (nor ethically) with this objective function. However, this objective is weird in a couple of ways.
First, there is no weighting on these which implies you prefer ...
- 2,750
5
votes
Curve fitting under different regions and stitching
I hope I understood you correctly and that the following thoughts help you a bit.
Reference point: Univariate curve fitting using splines
With a univariate function $f(x)$ you can perform 1D spline ...
- 5,763
5
votes
How to minimize Nelson-Siegel parametric form
When we worked with that model several years go, we used Differential Evolution and it worked very well. See Calibrating the Nelson-Siegel-Svensson Model. At least in the standard version, a best-of-...
- 2,876
4
votes
What is the reference python library for portfolio optimization?
Convex Optimisation - CVXOpt and CVXPy. Textbook by Boyd & Vandenberghe
Aside from CVXOPT (known for its cone programming, see http://cvxopt.org/) with extensive documentation by the authors, ...
- 1,018
4
votes
Why is the Drawdown measure not used for portfolio optimization?
In response to the original question:
Drawdown optimization is a convex problem, see our recent article:
http://ssrn.com/abstract=2430918
We do not address the issue of choosing a "good" risk model ...
- 41
4
votes
What are some useful approximations to the Black-Scholes formula?
To answer the question by Robert about existing approximations for the Black-Scholes formula in the non-ATM case: yes there exists a simple and fast converging series representation for the Black-...
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