Questions tagged [optimization]

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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Constraints in a Mean-Variance Optimization Case

Might be a repeat question, feel free to close if it is. I am trying to perform a mean-variance optimization (maximizing the Sharpe ratio) for lets say 5 assets. Besides the weights of the assets ...
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Adjusting the p-value of a strategy for number of parameters

Let's say I have some metric and I'm trying to evaluate whether it's predictive with respect to returns. I plan to only take trades where the value of the metric is above a certain threshold, such ...
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Calibration of $\rho$ in the heston model

When calibrating the Heston model, the gradient of the price of the call/cost function wrt $\rho$ (correlation between $S$ and $V$), is a lot less than the other parameters like $v_0$ and $\bar{v}$. ...
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Calibrating the Heston with the Levenberg-Marquardt algorithm

I am trying to implement the Levenberg-Marquardt algorithm similarly to Cui et al. Full and fast calibration of the Heston stochastic volatility model, 2017 here (although using a different method to ...
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Wrt speed, how optimised is QuantLib's Heston pricing class?

I have a pricing formula that is 300x the speed of the QuantLib's Heston pricing class. Is it incredibly slow? For context, on a slow 1.6 GHz Dual-Core Intel Core i5 processor, my method can reliably ...
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Which C++ implementations of Levenberg-Marquardt does the "industry" use?

According to your various experience, is there an industry consensus about which C++ implementation of the Levenberg-Marquardt algorithm to use ? I came across two places where it was the C numerical ...
EricFlorentNoube's user avatar
3 votes
1 answer
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Optimal Fitting Criteria of SABR

I was reading about SABR Model and curious about this. The process of fitting the SABR model involves finding values for the parameters α, β, ρ, ν that minimize the difference between model-implied ...
Starlord22's user avatar
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Optimal portfolio as combination of target and minimum tracking error portfolios?

Dear Quant StackExchange I seek some intuition for how my portfolio behaves given constraints. In a universe of say 5 assets, I have a "target portfolio" with weights that are found from ...
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Parameters in Nelson-Siegel model and Nelson-Siegel-Svensson model

I am trying to determine the parameters for the Nelson Siegel and Nelson Siegel Svensson model and try to solve SE=$\sum_{i=1}^{n_{i}}(y_{t_{i}}-\hat{y}_{t_{i}}(X))^{2}$ where $y_{t_{i}}$ denotes the ...
Martin N.'s user avatar
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How do your solve for trader's optimal demand in market similar to Kyle's model?

Suppose that $(\Omega,\mathcal{F},\mathbb{P})$ is a standard probability space and $Z_t=(Z_t^1,Z_t^2)$ is a two dimensional Brownian motion with the filtration $\mathcal{F}^Z_{t}$ and $Z_t^1$, $Z_t^2$ ...
Oliver Queen's user avatar
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Optimal leverage for strategy with normal returns

Given a strategy with normal returns with mean 5% and standard deviation 10% what is the optimal leverage (up to a maximum of 2x) to maximize the expected wealth? With the same setting, if trading is ...
Mattiatore's user avatar
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Transform non-linear HJB PDE into system of linear ODEs [closed]

I am reading this market making paper, and am trying to understand the transformation presented on page 6. A good resource for background relevant to the transformation is this other market-making ...
V0ltair3's user avatar
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Calibration for CIR Model Discretization for Predictor Corrector and Milstein method

I'm new to Quantitative Finance. I've data which I need to fit a CIR model and estimate its parameters. $ dX_{t+1} = a(b-X_{t})dt + \sigma \sqrt{X_t}dW_{t} $ While I can fit and obtain ...
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Is "extreme CVaR" (CVaR from extreme value theory) elicitable or conditionally elicitable with some other statistical mapping (like VaR)? [closed]

I am not able to find loss function (scoring function) extreme CVaR (CVaR from extreme value theory) which is a conditionally elicitable statistical mapping (conditioned on VaR). In this regard, can ...
Moiz Ahmad's user avatar
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What is the meaning of the following mathematical equations? [closed]

Let's say that we have a discrete probability distribution, where $$ x_i $$ represents each of the possible outcomes (discrete set of possible outcomes), and $$ L $$ represents the expected value we ...
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How to use simplex method for initial estimates of parameters in Nelson-Siegel-Svensson

I came across a BIS note about the estimation of the Nelson-Siegel-Svensson method. Currently, I'm trying to implement this. However, one step is not fully clear to me. Let me outline the steps of the ...
math's user avatar
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Optimal consumption process [Munk (2011)]

I'm trying to solve problem 4.4 in Munk (2011). The problem is as follows: Assume the market is complete and $\xi = (\xi_{t})$ is the unique state-price deflator. Present value of any consumption ...
John Stevens's user avatar
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Binomial Tree for CDF

I'm tasked with solving an optimal stopping problem relating to stochastic process representing a firms profit namely $X_t = X_0 + \mu t + \sigma Wt$ where $X_0, \mu$ and $\sigma$ are constants. ...
lt12's user avatar
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3 votes
1 answer
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How to understand this convex optimization method to find risk budget portfolio

Both the short course material coded by the CVXPY developers and an answer on Quant SE suggest that given a desired risk budget $b$, we can find the full-investment portfolio with weights $w$ that has ...
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how can I linearize a constraint of the form sum(min(x(i),y(i))) for a linear optimisation problem?

I have an linear optimisation problem with the objective : $ max PortfolioSpread(x_1,x_2,....x_N) = ∑_{i=0}^N(x_i*s_i)/budget$ s.t. $∑_{i=0}^N x_i = budget$ (+ other constraints) $∑_{i=0}^N min⁡(x_i,...
democrit's user avatar
1 vote
1 answer
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Finding optimal option to maximise gains under given price hypothesis

Let's have Stock S at \$100 on January and my hypothesis is S will be trading at \$150 in July. Is there any Python/R package that I can feed with option prices from my broker and it would return the ...
user3507584's user avatar
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Nonlinear Constrained optimization for a CIR model

I want to calibrate a CIR model which is commonly used to model the evolution of interest rates. Briefly speaking, we know that its dynamics is of the form \begin{equation} dr_t = \kappa (\theta - r_t)...
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Optimal Entry, Exit, And Stop Loss From Historical Stock Data

I'm trying to build a system that recommends stock trades. My goal is calculate optimal values for the following: Entry Parameter: expressed as a percentage change downwards from the opening price. ...
user61123's user avatar
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linear optimization problem with non-linear constraint

I have the following optimisation problem which I want to solve using linear optimisation. Is there a way to represent the second constraint in a linear form in order to be able to use linear ...
democrit's user avatar
1 vote
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147 views

SciPy Calibrating Heston call option

I have been attempting to calibrate my Heston model, but I am running into issues with scipy.optimize module. I have tried various scipy optimizers, but they all return the error "TypeError: can ...
DiracsCallOption's user avatar
3 votes
3 answers
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mean-variance optimization === max sharpe ratio portfolio?

Noobie here. I just wanna ask a simple question: in the context of portfolio optimization, is Mean-Variance optimization the same as the max sharpe ratio portfolio?
Nygen Patricia's user avatar
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How to solve an optimization problem with absolute constraint?

The optimization problem is shown below $$ \min_{\boldsymbol{w}}\boldsymbol{w}^T\boldsymbol{Sw}\\ s.t. |\boldsymbol{w}^T\boldsymbol{a}_i|>1, i=1,2,\cdots, n $$ , where $\boldsymbol{w}, \boldsymbol{...
Andy's user avatar
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3 answers
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What is the definition of "cheapest collateral"?

Optimizing collateral is a hot topic in the financial industry. I came across the term cheapest collateral. What does it actually mean in the context of collateral optimization, please ?
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Portfolio optimization with Python/CVXPY: DCPError

I'm trying to implement a script for portfolio optimization on a sample universe of 3 future contracts. I have the following inputs: current allocation --> number of contracts currently held for ...
younggotti's user avatar
3 votes
2 answers
512 views

How to minimize Nelson-Siegel parametric form

Problem I am given the following function to minimize (w.r.t. $\theta$) $$f= \sum_{k=1}^5 \Big [ \sum_{i=1}^{N_k} CF_{k, i} \cdot e^{-r(t_{k, i}, \theta)\cdot t_{k, i}} - P_k^* \Big]^2$$ where $\...
ElonMuskofBadIdeas's user avatar
1 vote
1 answer
326 views

Multivariable objective function optimization similar to optimx in R

I have an optimization model in R that utilizes a single variable in my objective function. See below: ...
Jcarl's user avatar
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1 answer
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How to set a fixed return for mean-CVaR portfolio optimization?

I'm using the timeSeries and fportfolio package in R to minimize the CVaR with different constraints for a given portfolio. Everything is working out so far. However, I can't manage to set a fixed ...
ironymike's user avatar
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establishing an optimal take profit

Please let me know what you thoughts are on this. Say for example that you have a perpetuity, which guarantees you indefinite payments of a certain amount. Say then that you also have the opportunity ...
adriano's user avatar
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1 answer
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Mixed-integer programming approach for index tracking

Suppose you currently own a portfolio of eight stocks. Using the Markowitz model, you computed the optimal mean/variance portfolio. The weights of these two portfolios are shown in the following table:...
statwoman's user avatar
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Minimize Composite Dispersion

Let's say that we have a composite of 10 fixed income portfolios, each with the same benchmark, the US Aggregate. Additionally, let's say that each portfolio has a position in Corporation ABC. The ...
Wadstk's user avatar
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1 vote
2 answers
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When looking for arbitrage among a LARGE amount of assets, is there an optimal way?

Looking for arbitrage opportunities when looking at 3 pairs of related currencies is easy. However if we assume that we have a large amount of currencies, is there an optimal way to swipe through them ...
Hiperfly's user avatar
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1 answer
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Curve fitting under different regions and stitching

Is there a way to fit a 2D curve under the following conditions: The curve is defined by 2 functions for x>a, and x<a Prefer a fit that is continuous and differentiable at x=a
d3rk_knight's user avatar
2 votes
4 answers
268 views

Cant replicate minimum variance portfolio variance by simulating many random portfolios in R

I have computed the theoretical minimum variance portfolio using the 30 stocks in the Dow. The formula used is: $$\underset{N\times 1}{\omega_{mvp}}=\frac{\lambda}{2}\cdot \Sigma^{-1}\iota=\frac{\...
Emil Bille's user avatar
1 vote
0 answers
137 views

MatLab code does not work for Heston model calibration

I am trying to calibrate Heston model on some data and I have the following code. Code is supposed, after it reads the data, to give back 5 parameters. However, I get an empty answer from MatLab. Does ...
Francesco Bova's user avatar
2 votes
1 answer
960 views

Optimal Strategy in 3 Dice Game

In a recent interview I received the following question (an optimisation/strategy game)...which left me a bit stumped. The rules of play, you start with 0 points, then: Roll three fair six-sided dice;...
bob's user avatar
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Optimal withdrawal rate based on alpha and drawdown

My trading returns is about 50% monthly(alpha) and maximum drawdown is about 20%. Is there a mathematical way to define the optimal withdrawal rate X%(say when profit level reach y%) to avoid risk of ...
Gazillionaire's user avatar
1 vote
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118 views

An example that mixes the stock market, game theory and linear programing

First of all i am not entirely sure if this is the correct place to discuss this problem but i shall give it a try. I'm currently doing an assignment for a degree in Linear Programing. My objective ...
riemannfanboy's user avatar
1 vote
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Interest Expense Optimization

So I have a problem I need to solve and no idea how to approach it. Its a verbal problem without any specific numbers given except for those below. So it is up to me to determine how to structure the ...
thenoobie's user avatar
1 vote
0 answers
162 views

Optimising returns weighted by Sharpe ratio in the context of Supervised Learning

In the Kaggle Jane Street market prediction competition we are put in a Supervised Learning Framework to deal with 'trade opportunities'. That is, we are given instances of previous trade ...
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Optimize Bollinger Bands Strategy

I was proving a very simple strategy with Bollinger Bands for a intraday timeframe (1 minute) that buy on lower band and sell in a higher band (Very common strategy), but in backtesting in E-Mini SP ...
Caeta's user avatar
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$\epsilon$-arbitrage model

In the model here described, Bertsimas says that we can use the Robust Optimization to find the replicating portfolio the value of which is such that minimize the difference $|P(\widetilde{S},K)-W_T|=\...
Marco Pittella's user avatar
1 vote
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135 views

There are several ways optimize portfolio, why use Black Litterman rather than Mean variance

I know there are two ways to optimize portfolio. What are the limitations and advantages by using Black Litterman over Mean variance.
Guifan Li's user avatar
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Conic optimization in finance

Linear programming and quadratic programming are types of convex optimization that are often used. Does conic optimization or programming have any applications in finance? Or for where the previous ...
develarist's user avatar
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1 vote
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Maximizing sharpe ratio using cvxpy or cvxopt

I have a dataframe $n$ by $m$ representing $m$ timeseries of returns (each column is a different time series) with total $n$ number of observations, I want to find weight vector of length $m$ such ...
qwer's user avatar
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5 votes
1 answer
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Derivation of mean-variance portfolio weights as closed-form analytical solution from Lagrangean equations

I am trying to find a closed form solution for the constrained MVO problem below. $\max_w w'\mu - \frac{\lambda}{2}w'\Sigma w $ s.t. $w'$1 = 1 The Lagrange for the objective is $L(w, \gamma) = w'\mu ...
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