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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Is optimising for the Final Wealth is the same as optimising log of growth rate in Kelly Criterion?
A direct, brute force approach could be used to find the Optimal Portfolio.
Consider simple play. There's a biased coin with 55% probability of win. The simulator play as a single person with 100$ ...
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Fixed Income Portfolio Optimization
I'm trying to solve for a maximum sharpe ratio portfolio in the fixed income space. To do so, i use CVXPY in python. I use this Paper as reference.
This is my "setup":
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Create a hedging portfolio
If, given a return stream of unknown composition, what is the best find a portfolio of assets that replicates that return stream from a universe of assets?
In other words, what is the best ...
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Portfolio optimization - maximize variance with exposure to risk factors equal to zero
Optimize a portfolio such that the exposure to risk factors is zero and the variance is maximized (instead of traditional minimization problem).
so the optimization problem look like:
$$maximize\;w^...
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Starting values for constrOptim() in R
I want to perform a constraint optimization for Maximum Likelihood Estimation in R to forecast volatility of returns. The probleme is that my initial values aren't in the permitted region. Is there ...
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Segmented investment to yield same monthly return in each segment
Not an investment specialist, so please excuse the very basic math.
Given a lump sum, I need to distribute this lump sum over (x) segments, each lasting (y) years (years can be different for each ...
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How to implement Konno's Mean-Absolute Deviation Portfolio Optimization Model using LP methods in Excel
Konno proposed a LP method for portfolio optimization using the Mean Absolute Deviation (MAD)
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Optimization metric that takes into account number of trades vs expectancy
In optimizing my automated trading system I find that certain combinations while increasing the expectancy:
...
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quadratic programming portfolio optimisation
I am using MATLAB to do an optimisation. The QP minimisation problem is set up in the standard form shown below. The optimisation is used to calculate the weights (x vector in the equation below) of a ...
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What do "Exposure Bounds" mean in Portfolio Optimization?
I've just started reading up on Portfolio Optimization models and have come across the use of exposure bounds to mitigate the sensitivity of the optimized model solution, owing to parameter estimation ...
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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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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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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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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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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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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$\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|=\...
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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.
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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 ...
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CVaR portfolio optimization with risk aversion parameter
I'm trying to implement the Rockafellar's function described in this paper http://past.rinfinance.com/agenda/2009/yollin_slides.pdf with a risk aversion parameter for my thesis.
The function to ...
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Error in optimize.portfolio with transaction costs constraint
I am experimenting with the PortfolioAnalytics package to optimize portfolio with dollar neutral and transaction costs as constraints to the quadratic utility objective function. A sample R snippet is ...
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PortfolioAnalytics: Training window based on entire history before rebalancing in 'optimize.portfolio.rebalancing'?
I am fairly new to PortfolioAnalytics and R in general. I am trying to do some backtesting of a minimum variance portfolio.
I have weekly, monthly, quarterly and yearly return data of 3 selected ...
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Framework for hedging fx and utilizing correlation between asset returns
Can anyone point me in a direction (research paper, books, ..) which developes a framework/strategy for hedging currency exposure for an international bond portfolio?
This paper finds optimal ...
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Achieving desired fx exposure with using minimum pairs possible
Let say my algorithm tells me to get the following positions through opening fx positions:
CUR NET POSITIONS
GBP 236.96379
USD -310.58000
CHF 0.02000
There are 2 ways to achieve this:
Long ...
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Minimizing Correlation to Index
In his PhD thesis in the chapter Market Neutral Portfolios, page 69, [1] Valle sets up an optimization problem which minimizes the absolute correlation of the portfolio log returns to the log returns ...
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How to choose trades over time when capital is limited
Say I'm in the business of trading forward contracts. So at some point in time, I look at the markets, and determine a number of trades I could make. For each trade, I know the profit I expect to make,...
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Generate P Value from stationary bootstrap following Politis & Romano (1994)
For my master thesis I am analyzing the performance of trading strategies. For this I need to avoid data snooping by utilising the FDR approach. I follow closely the procedure presented by Bajgrowicz &...
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Dynamic counterpart for model tunneling/optimization using past data
When we tune a model to optimize parameters for a strategy using past data, even if controlling for overfitting (checking out of sample performance) and refreshing the analysis from time to time, we ...
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How to Implement an optimal Stochastic Control Optimization? [closed]
I'm currently working on an stochastic optimal control problem applied to a portfolio asset allocation. In principle, the problem is to maximize the return of a fixed income portfolio under certain ...
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Improvement of Alpha Expression [closed]
I'm newbie user of Websim (websim), given
Alpha Expression : (est_eps * (cashflow/sharesout) * (est_sales/sharesout))/est_dividend_ps
Settings-Region:USA, Universe:TOP3000, delay:1,MAX stock weight :...
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Solution for Markowitz problem with Safety-First Ratio
What is the solution for the following markowitz unconstrained problem?
The sum of the entries of the weights vector $w$ should always be requied to sum one? Or if we use the risk-free asset it can be ...
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Confusion about Assumptions in Markowitz Optimization
Setup and Definition of Terms
Supposed that we have a universe of possible securities $\mathcal{S}$. We wish to construct an "optimal" portfolio, which will be represented by proportional weights $\{...
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Maximum likelihood for lognormal mixture
I have a collection of historical data that I want to fit to the following model
$$
y_{t+1} - y_t = \alpha + (\rho + \sigma_2 Z_{t+1} )y_t + \sigma_1 Z_{t+1}
$$
where everything except the y's are ...
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Optimize a trading strategy created in excel with R
I have created quite a complex back test in excel spanning 15 years with 17 parameters. I would like to optimize the parameters which would give me maximum return given a maximum draw-down percentage. ...
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Continous-time portfolio allocation optimization for a given consumption rate
I have the following PDE
$0 = V_t - c(t)V_x - \lambda^2 V_x^2/V_{xx} + rxV_x + 1/2\lambda^2x^2V_{xx}$
where $t\mapsto c(t)$ is some given function and $r,\lambda$ are given constants.
If necessary, ...
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How to hedge an ETF position with a basket of its underlying components
In practice, when one takes on a large equity ETF position, I would imagine it's not necessarily "optimal" to hedge using a basket of all the constituents even though that should be a perfect hedge. ...
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Smoothening yield curve by minimizing forward curve slope
I am using government bullet bond data and have bootstrapped a yield curve by solving the following optimization which minimizes unweighted price error:
$$\text{min}\sum_i\left(P_i-\sum_t\frac{F_{it}}...
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Is there any theoretical work to find an optimum size for the size of horizon in finite-horizon optimization or control?
we learn a lot about finite and infinite horizon control in dynamic programming. but I was wondering if we want to minimize the cost per time(discrete time) is there any work to find the optimum size ...
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Implementing Minimum Leverage in an SOCP Portfolio Optimization
I'm optimizing a portfolio of n assets and my optimization variable is of the form
$$x = [t,w,w_L,w_S]$$
where
$$t:= \text{slack variable for turning my QP objective into SOCP constraint}$$
$$w:=\...
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Multi-objective optimization: Where to find qualified examples for portfolio management?
I am looking for qualified examples of multi-objective optimization applied to a portfolio management situation in non-normal markets. Where can I find one or more examples of such a multi-objective ...
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Model-independent dynamic portfolio optimization techniques
For a problem where we need to optimize the portfolio based on the data, going for Markowitz MPT has the following advantage: we only have to estimate mean and covariance to find optimal weights. I'd ...
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Transform MPT optimization problem
I am trying to teach myself about MPT and optimization.
I understand that MPT solutions can be found using three equivalent optimization problems:
Minimizing variance for given return limit
...
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What are the roles of "Game theory" and "optimisation (linear, integer, conic)" in Finance, Mathematical Finance? [closed]
Would you please give me some information about application of "Game theory" and "Optimisation" in Finance and Mathematical Finance? which is more important to know and learn?
How about "multi-...
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Standard errors clustered along the time dimension in pooled panel logit model
I'm trying to estimate a logit model on pooled panel data set (unit of observation is firm-year). My dependant variable is default indicator and I have several macro variables as independant variables....
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Doubt on risk cost criterion
I want to minimize some kind of risk sensitive cost. But, I am confused what cost criterion should I use. I am aware of only expected exponential utility. I want to know what are the other such ...
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