The selection of a best element from some set of available alternatives. Typically consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function.

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26
votes
12answers
11k views

Why does the minimum variance portfolio provide good returns?

I've been a researching minimum variance portfolios (from this link) and find that by building MVPs adding constraints on portfolio weights and a few other tweaks to the methods outlined I get ...
17
votes
5answers
13k views

What are some useful approximations to the Black-Scholes formula?

Let the Black-Scholes formula be defined as the function $f(S, X, T, r, v)$. I'm curious about functions that are computationally simpler than the Black-Scholes that yields results that approximate ...
16
votes
6answers
8k views

Python library for Portfolio Optimization

Does anyone know of a python library/source that is able to calculate the traditional mean-variance portfolio? To press my luck, any resources where the library/source also contains functions such as ...
15
votes
4answers
1k views

Does mean-variance portfolio optimization provide a real edge to those who use it?

Mean-variance optimization (MVO) is a 50+ year concept, and perhaps the first seminal idea of quantitative finance. Still, as far as I know, less than 25% of AUM in the US is quantitatively managed. ...
15
votes
1answer
1k views

Portfolio optimization with monte carlo sampling from predictive distribution

Let's say we have a predictive distribution of expected returns for N assets. The distribution is not normal. We can interpret the dispersion in the distribution as reflection of our uncertainty (or ...
12
votes
5answers
3k views

portfolio optimisation with VaR (or CVaR) constraints

I would like to optimize a portfolio allocation (maximizing the exposure or the expected return), but with VaR or CVaR contraints. (some parts of my portfolio cannot exceed a certain VaR) How can I ...
12
votes
3answers
3k views

Techniques to optimize the placement of orders in market making strategy?

Market making often requires placing and canceling a lot of orders. You have to buy and sell nearly simultaneously, so you need to move orders pretty often to beat other traders. But I would like to ...
11
votes
3answers
1k views

Role of skewness in portfolio optimization?

What is the role of skewness in portfolio optimization?
10
votes
5answers
857 views

How can higher co-moments be applied to portfolio optimization in an asset allocation context?

Traditional portfolio optimization involves mean variance optimization, where only the mean and covariance matrix of returns are estimated. What asset allocation and portfolio optimization techniques ...
10
votes
3answers
743 views

What is the expected return I should use for the momentum strategy in MV optimization framework?

As all research on the momentum strategies are focused on the indicator, i.e. the entry point, there seems not much discussion on its expected return? Though there are some discussions on the exit ...
8
votes
5answers
2k views

Why is the Drawdown measure not used for portfolio optimization?

I was asked yesterday by a colleague why we are doing asset allocation using optimizers which target, for a minimum expected return: the portfolio with the minimum variance or the portfolio with ...
7
votes
4answers
1k views

Library to solve optimization problems

I'm working with C# and I start being bored writing optimization algorithm. Do you know of any free library containing this sort of algorithms. In particular I'm cutrently working with Semidefit ...
7
votes
2answers
2k views

robust portfolio optimization re-balancing with transaction costs

The optimal re-balancing strategy takes account of factors including i) objective function, ii) current portfolio weights, iii) expected return vector containing updated views/alpha forecasts, iv) ...
7
votes
1answer
986 views

Optimal execution and reinforcement learning

Suppose a fairly simple problem: You have to buy (resp sell) a given number of shares V in a fixed time horizon H with the aim to minimize your capital spent (resp maximize your revenue). There are ...
7
votes
2answers
1k views

How to apply risk-parity portfolio construction to a dollar-neutral portfolio?

Long-only risk-parity portfolios have proliferated in recent years. An optimized long-only risk-parity portfolio requires that the asset weight * marginal contribution to risk of the asset is ...
7
votes
0answers
198 views

Portfolios from Sorts

Some time ago Almgren and Chriss proposed a method for portfolio optimization based on sorting criteria such as $r_1 > r_2 >... > r_N$ instead of explicit expected returns: see portfolios ...
6
votes
5answers
801 views

portfolio optimization from empirical return distributions

I'd like to do a portfolio optimization of a set of ETF's but want to avoid traditional problems with normality assumptions in returns etc. Are there techniques that let me sample 'draws' from the ...
6
votes
2answers
917 views

Comparing MVO with Resampled Efficient Frontier

My question: How can I compare the Resampled Frontier (REF) to the standard MVO frontier when I have been provided with $\mu$, $\Omega$, and don't have access to true future data to test real out of ...
6
votes
2answers
245 views

How to represent constraints for optimization problems in a data model?

I am at the moment writing a program focusing on asset allocation and I am thinking about how I should represent my constraints in the data model. The first approach that came to mind was to define ...
6
votes
4answers
630 views

How to cluster ETFs to reduce cardinality for portfolio selection

I'm looking to run portfolio optimizations using various optimization goals - e.g. minimum variance, max diversification etc. My challenge is if I want to do this on ETF's which ones do I pick to run ...
6
votes
4answers
1k views

Fastest solver possible for portfolio optimization

I am using quadprog in MATLAB for very simple mean-variance optimization, with less than 100 assets. It is quite fast but if I run a strategy with daily ...
6
votes
1answer
1k views

How can I use Entropy-pooling of Atillio Meucci to constuct a portfolio?

I am trying to get my hands on Entropy Pooling which was introduced by Meucci in this paper. As an example, assume I want to construct a portfolio with five stocks and I have my view on CVaR. How ...
6
votes
3answers
269 views

What is the canonical reference for Minimum Variance Portfolio's uniqueness?

I am writing a white paper in which I am trying to compare a strategy to different well-known - and classic - asset allocation optimization approaches. One of the methods I chose is the minimum ...
6
votes
2answers
866 views

optimal re-balancing strategy with asynchronous alpha signal

You want to construct an optimal portfolio. Let's say you have an alpha signal that arrives with some period (say quarterly). The alpha signal predicts arithmetic returns one-year ahead. You have ...
5
votes
1answer
1k views

Optimizing a portfolio of ETFs

I am aware of how to do mean-variance or minimum-variance portfolio optimization with constraints like weights must add to 1.0 no short sells max weight in any ticker using basic quadratic ...
5
votes
1answer
313 views

Min VaR and Min TE as second order cone program

The quadratic optimization (min variance) $$ w^{T} \Sigma w \rightarrow \text{min}, $$ where $w$ is the vector of portfolio weights and $\Sigma$ is the covariance matrix of asset returns, is a well ...
5
votes
1answer
346 views

Optimal trading strategy in toy world of simple Hidden Markov model with Gaussians

I want to solve the following optimization problem: What is the optimal general trading strategy (in the sense of the highest Sharpe ratio) on a time series which is the result of a Hidden Markov ...
5
votes
0answers
1k views

Algorithm to fit AR(1)/GARCH(1,1) model of log-returns

I am fitting numerically an AR(1)/GARCH(1,1) process to index and stock log-returns, $r_t=\log(P_t/P_{t-1})$, where $P_t$ is the price at time $t$, and thus far am not clear on where the observed log ...
5
votes
4answers
703 views

How to optimize a portfolio under *both* maximum diversity ratio and minimum variance

I have a follow-on question to questions that appeared here and was not sure if the right way was to ask in the comments or post a new question. My question is: how can I optimize a portfolio to suit ...
4
votes
3answers
1k views

Markowitz mean-variance optimization as “error maximization”

I hear it said a lot that standard MV optimization "maximizes errors". But I can't find a good explanation for what exactly they mean by this "maximization" of estimation error. I understand that if ...
4
votes
2answers
420 views

Choice of prior as a shrinkage target in portfolio construction?

There's various research showing how priors such as the minimum variance portfolio turn out to be a surprisingly effective shrinkage target in portfolio construction. The sell point of these priors ...
4
votes
2answers
102 views

Portfolio Optimization to include ALL Securities?

I'm currently optimizing portfolio weights for an investment team with N stocks. We buy stocks with a conviction it will generate a return and it is up to me to determine weighting. However, with ...
4
votes
1answer
242 views

Mean-variance portfolio & quadratic programming

I am somewhat confused when it comes to modern portfolio theory, mean-variance portfolio optimization and its quadratic programming formulation. Issue 1: Formulation of mean-variance portfolio ...
4
votes
2answers
2k views

Typical risk aversion parameter value for mean-variance optimization?

What are typical values for risk aversion parameters $\lambda$ used in mean-variance optimization? Please provide references. Just to be clear, I'm talking about the $\lambda$ in $U(w) = w'\mu - ...
4
votes
1answer
139 views

pricing of heat rate-linked derivative

It's a simplified model. Suppose $U_t$ is a random variables subject to Lognormal($x_1$, $z_1^2$)distribution. $V_t$ is a random variables subject to Lognormal($x_2$, $z_2^2$)distribution. Suppose ...
4
votes
2answers
556 views

Which objective function should I choose to minimize tracking error?

Let say I have $n$ assets and their returns over $m$ periods which are represented by a matrix $X \in \mathbb{R}^{m \times n}$, and I have some other asset with return over the same period which is ...
4
votes
3answers
215 views

multiperiod optimization using R

I'm interested in multistage optimization problems. Are there any good R packages around to solve such problems over time? I'm not at all an expert in it, so maybe someone knows a good paper / lecture ...
4
votes
0answers
228 views

Optimization: Factor model versus asset-by-asset model

In portfolio management one often has to solve problems of the quadratic form $$ w^T \Sigma w + w^T c \rightarrow Min $$ with portfolio weights $w \in \mathbb{R}^N$ a constant $c \in \mathbb{R}^N$ and ...
4
votes
0answers
388 views

Formula for the efficient portfolios (mean-variance optimisation)?

Consider the setting of mean-variance portfolio optimisation: $n$ assets with expected returns $\overline{r}_1,...,\overline{r}_n$ and standard deviations $\sigma_1,...\sigma_n$. For a certain fixed ...
4
votes
0answers
305 views

Shrinkage Estimator for Newey-West Covariance Matrix

I like to apply the Newey-West covariance estimator for portfolio optmization which is given by $$ \Sigma = \Sigma(0) + \frac12 \left (\Sigma(1) + \Sigma(1)^T \right), $$ where $\Sigma(i)$ is the lag ...
4
votes
0answers
248 views

Analyzing the angle between vector of weights and vector of returns in mean-variance optimization

I am using the paper "A Sharper Angle on Optimization" by Golts and Jones (2009) as a basis for my (minor) masters thesis in mathematical finance. The paper focuses on the mean-variance analysis of ...
3
votes
2answers
2k views

How to define the objective function for a custom optimization problem?

I would like to find the allocations that would minimize some user-defined metric (Sortino, minimum drawdown, etc) for a portfolio of assets. How would one go about formulating the objective ...
3
votes
2answers
1k views

How to implement Maximum Diversification in R?

I am trying to code up the optimization problem for Max Diversification Portfolios. The main problem I am having is properly translating the objective function in to code and port it in to the ...
3
votes
2answers
266 views

MPT: Adding constraint on minimum asset weight

I'm new to finance in general, and recently read about Modern Portfolio Theory. Now I'm wondering how to add the following constraint on asset weights: Each asset weight $w_i$ should either be $w_i ...
3
votes
3answers
264 views

Determining optimal trading signals (buy/sell) from past data

Let's say we have a stock which our only actions are buy, sell and hold (with or without shorting). If we have sufficient past data of the stock, how can you determine the optimal trading action ...
3
votes
1answer
127 views

Optimal Choice of exceeding time

Suppose you hold a share from company $Z$ whose vaue at time $t$ is $S_0+\sigma B_t$ where $B_t$ is Brownian Motion and $\sigma$ denotes some volatility. Now lets assume that company $Z$ may go ...
3
votes
2answers
4k views

What do the terms in-sample and out-of-sample estimates mean in MVO?

How do the in-sample estimates and out-of-sample estimates I so often hear authors refer to in emperical analysis of MVO differ?
3
votes
1answer
162 views

Parameter estimation using martingale measures - include real world data?

Please note: I posted this in nuclearphynance first, but didn't get any replies. For desks which sell exotics it is common practice (as far as I know it) to calibrate the model (Stochastic ...
3
votes
0answers
93 views

Optimal mortgage rate strategy

When buying a mortgage, you can choose to "lock in" a rate at any point within 60 days of your closing date. Once locked in, you can't revert. This makes it a secretary problem - in the traditional ...
3
votes
0answers
318 views

Is there a standard method of scaling alpha forecasts to t-cost estimates?

Given a set of monthly alpha forecasts (i.e. standardized z-scores from a multi-factor return model) and a non-linear market impact model (or more specifically, its piecewise-linear approximation), is ...