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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22 views

How to augment lpsolve R optimization solution to run on a hadoop cluster? [closed]

I posted this question initially on stackexchange.com...posting it here as that was suggested to me on stackexchange website I am using R lpsolve package to optimize my transportation model. My code ...
4
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1answer
110 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 ...
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0answers
36 views

How do I determine what is a separate objective in a multi-objective portfolio optimization?

Is there a general rule to determining when to separate objectives when developing a multi-objective portfolio optimization? For example, one might start with a standard portfolio optimization of ...
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0answers
20 views

Compute the average efficient frontiers with estimated parameters from generated time series

My overall objective is to analyse the impact of error in mean-variance analysis from historical data. I am given the returns and standard deviation for the five assets under consideration, as well as ...
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0answers
26 views

Approaches to check/validate the output of an optimization algorithm

Let's say we want to optimize the a function $f(x_1,\dots, x_n)$ with $(x_1, \dots , x_n) \in \mathbb{D}^n$. For the sake of simplicity let $\mathbb{D}^n$ be the unit sphere. We chose an optimization ...
4
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2answers
168 views

Is there any academic material regarding robust optimization with fixed transaction costs?

I'm looking to piece together a robust optimization model that handles robust optimization with fixed transaction costs and other combinatorial variables (e.g. asset count constraints). Here's what ...
6
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4answers
511 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 ...
3
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3answers
2k views

Derivation of the tangency (maximum Sharpe Ratio) portfolio in Markowitz Portfolio Theory?

I have seen the following formula for the tangency portfolio in Markowitz portfolio theory but couldn't find a reference for derivation, and failed to derive myself. If expected excess returns of $N$ ...
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2answers
250 views

Optimizing Principal Component factor weightings over time

I was given the returns of a cross-asset class portfolio of ETFs and I conducted PCA to obtain factors on dates from T-n, T-3, T-2,..., T. What I would like to do is decompose the market moves from ...
2
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0answers
69 views

What R-packages for SOCP problems are there?

Currently, I am looking deeper into the topic of second-order cone programming. Could you suggest packages that solve SOCP-problems in R? With your answer, please provide a short description of ...
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0answers
65 views

A doubt about Evans and Jovanovic (1989) economic model for entrepreneurs with credit constraints

[I already posted this question on the math forum of stackexchange and I was advised that I should post this question here] In Evans and Jovanovic (1989) you will find a model for entrepreneurs with ...
4
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0answers
160 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
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0answers
216 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 ...
7
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0answers
123 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 ...
5
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1answer
235 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 ...
4
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0answers
263 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 ...
3
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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
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0answers
75 views

Optimizing stochastic functions numerically

Is there an efficient and commonly used optimization method for "more complex" investment strategies. For instance, say you have a function $f(X_1,...,X_n,c,v)$ where the $X_k$'s are your random ...
4
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2answers
871 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 - ...
0
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1answer
96 views

Parameters for numerically fitting t-distribution to log-returns

I am fitting the t-distribution to log-returns numerically (not using R, MATLAB, Stata, etc.), but rather using general programming. Assuming the log-return values are $r_t$, and the $t$-variates are ...
5
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0answers
481 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 ...
4
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260 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 ...
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4answers
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 ...
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1answer
217 views

Blackbox Optimization + Bootstrapping = Parameter Selection?

Most automated trading systems have a number of embedded parameters such as the lookback periods, entry and exit thresholds, etc. This is like the moving average crossover system or any of the systems ...
6
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2answers
715 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 ...
5
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4answers
599 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 ...
3
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0answers
88 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 ...
4
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1answer
118 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 ...
3
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2answers
991 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 ...
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0answers
496 views

portfolio optimization with a loop

I am attempting to minimize the variance of a 3 stock portfolio using optimization within a loop. What I have done is calculated the stock returns and cov matrix from dates 1980-01-01 to 1989-12-31 ...
14
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5answers
6k 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 ...
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0answers
228 views

Call options portfolio: what would the underlyings' moments to be maximized?

Let you have only three underlyings, like SPY, TLT and GLD, and you want to buy $n_{1}$ Call options on SPY, $n_{2}$ Call options on TLT and $n_{3}$ Call options on GLD... with a limited budget, that ...
22
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9answers
8k 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 ...
2
votes
1answer
194 views

Is Optimization ignoring correlation valid?

I have a fairly pedestrian optimization problem: Max sharpe, subject to a x% vol target. I have a set of expected returns, asset vols and a correlation matrix. I am finding that when i set the ...
10
votes
3answers
679 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 ...
2
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2answers
2k 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?
4
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0answers
222 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 ...
6
votes
3answers
248 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 ...
12
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5answers
2k 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 ...
6
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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 ...
2
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3answers
384 views

Optimizing a currency only portfolio with negative weights

I am testing various optimization methods for a currency-only portfolio. I have a vector of expected returns for the major developed currencies vs. the USD each week (based on a proprietary model). I ...
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 ...
6
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1answer
970 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
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5answers
540 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 ...
4
votes
2answers
385 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 ...
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2answers
150 views

How can I estimate the parameters of an option value model of retirement?

I am modelling an option value model of retirement, see for instance Stock and Wise (1990). I am however not sure to which class of problems this model falls into and hence which optimization method I ...
17
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5answers
9k 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 ...
10
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5answers
687 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 ...
3
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2answers
1k 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 ...