# 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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### How do I reformulate this max GMV ratio constraint in convex way?

Assuming I have N stocks. I want to have the following constraint in my optimization problem setup. $|x_i| \le \alpha \sum_{j}^N |x_j|$ where $\alpha$ is known, say 0.6. The intuition here is the GMV ...
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### A quant job interview question about (toy) futures

On Monday, you receive prices for each day of the week: $X_{1,1}, \ldots, X_{1,5}$. On Tuesday, you receive prices for Tuesday, Wednesday, Thursday, and Friday: $X_{2,2}, \ldots, X_{2,5}$. On ...
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### Has work been done on PID controllers for optimal trading?

Commonly, stochastic control is the basis for optimal trading (either in execution or market-making). Has any research been done (or why not, if none) as to PID controllers for these applications?
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### Reverse Optimization: finding the returns that satisfy specific weights given one known return

Here is the premise: I have a three asset portfolio, I know the assets covariance, the client's risk aversion and the expected return of one of the assets. I also have a desired set of weights. So, 1) ...
1 vote
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### 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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### sharpe ratio, convert into convex function, not understand that constraint, [duplicate]

I am reading about tranforming sharpe ratio into convex problem After some following, its converted into min xTxy s.t. (u-rf e)x = 1 ...
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### GARCH for Mean Variance Optimization

I am currently trying to carry out a mean variance optimisation, with the implementation of GARCH. I'm not sure if this is going to make complete sense as my understanding of GARCH is limited. In the ...
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### Robust or Stochastic Optimization Approach for Maximizing Profit with Limited Price Information

I am tackling a linear maximization problem where I need to select the optimal product among several options over a series of weeks, given certain constraints, in order to maximize future profit. The ...
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### Using regression to find optimal parameters for a trading strategy based on market regime

I am still fairly new to the field so forgive me if the whole post and my questions sound stupid. A bit of explanation first. So i have a trading strategy which is an extension of an Avellaneda-...
1 vote
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### Am I overcomplicating this approach to optimal actions based on a forecast?

I have been attempting to implement a simplified version of the model used in this paper which, given a forecast of future data, provides an optimal way of acting on it by choosing an optimal sequence ...
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### Pricing FRA rates from changes in rates due to ECB meetings and vice versa

This is somewhat building on top of my last question: Explicit step by step curve construction using FRAs I'm trying build (in python) and understand something that will allow me to reprice 6M EURIBOR ...
1 vote
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### Duality in conic quadratic programming for good deal measure

I am working on a problem relating to what is known as the "Good Deal risk measure" for production valuation in incomplete markets. I have created the following primal optimization problem, ...
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### Why not inequality constraint in mean-variance portfolio optimization?

Question 1: In Modern Portfolio Theory, the case where we minimize variance given a set return and that the weights sum to 1, why is the return set as an equality constraint, not an inequality? ...
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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. ...
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 $... 3 votes 1 answer 469 views ### How to understand this convex optimization method to find risk budget portfolio Both the short course material coded by the CVXPY developers and an answer on Quant SE suggest that given a desired risk budget$b$, we can find the full-investment portfolio with weights$w$that has ... 0 votes 0 answers 64 views ### how can I linearize a constraint of the form sum(min(x(i),y(i))) for a linear optimisation problem? I have an linear optimisation problem with the objective :$ 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,...
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 ...