Software Downloads for "Portfolio Optimization Binary"

The Portfolio Optimization template identifies the optimal capital weightings for a portfolio of financial investments that gives the desired risk and return profile based on the correlation between individual investments. The design of the portfolio optimization model enables it to be applied to either financial instrument or business stream portfolios with long and short positions. The portfolio optimization template is intuitive and flexible with help icons throughout to assist with input and interpretation of output results.

SmartFolio is a state-of-the-art asset management software for investment professionals and private investors. It contains advanced portfolio optimization and risk management techniques, based on the latest achievements in portfolio theory. The software combines highly advanced and innovative analytics with a user-friendly, intuitive interface, perfectly suited to any level of expertise and experience. Most of the mathematical algorithms utilized by SmartFolio have only emerged in the last few years.

SmartFolio is the most powerful asset allocation software aimed at all types of investors and investment professionals. It contains state-of-the-art portfolio optimization and risk management techniques, based on latest achievements in portfolio theory. The software combines highly advanced and innovative analytics with a user-friendly, intuitive interface, perfectly suited to any level of expertise and experience. Most of the mathematical algorithms utilized by SmartFolio have only emerged in the last few years.

A .zip file contains a series of scripts that were used in the MathWorks webinar "Using MATLAB to Develop Portfolio Optimization Models." The scripts generate 3D efficient frontiers for a universe of 44 stocks with time as the third axis. Additional scripts perform various ex-ante and ex-post analyses. Results are generated with and without market adjustments in the data. A readme.txt. file in the .zip folder describes each script and how to use it..

  • Platform: Matlab, Scripts
  • Publisher: Bob Taylor
  • Date: 27-05-2013
  • Size: 205 KB

Create a Portfolio Optimization Software
OptiPort License - Qt Public License (QPL).

  • Platform: WinOther
  • Publisher: Optiport
  • Date:

A force.com appexchange application that helps you align your IT portfolioa€”the collection of IT proposals, current projects, and established assetsa€”with your business strategy and thereby maximize the portfolioa€™s value.
Portfolio Optimization on Force.com License - GNU General Public License version 3.0 (GPLv3).

Pitchlet is a ready-to-use wealth management analytics presentation in which financial analytics can be created rapidly and distributed instantly through various channels. It is the final output of Applied Financial Engineering. Pitchlet offers free equity correlation, performance analysis, real-time portfolio optimization, market and industry browsers, as well as ETF explorer. With Pitchlet, you have what you need as a financial institution to maximize returns on intellectual property, which is created by financial engineers, analysts, and quantitative developers.

  • Platform: Linux, Mac, MS-DOS, Unix, Windows
  • Publisher: macroaxis.com
  • Date:
  • Size: 10 KB

The files in this folder solve the optimization case studies described in the paper "VaR vs CVaR in Risk Management and Optimization" by Sarykalin,S., Serraino,G., and Uryasev,S., in Tutorials in Operations Research, INFORMS 2008 (download www.ise.ufl.edu/uryasev/VaR_vs_CVaR_INFORMS.pdf ). Optimization problems are solved with Portfolio Safeguard (PSG) MATLAB subroutines developed by American Optimal Decisions (www.aorda.com). We show how to use PSG MATLAB functions: riskprog, riskconstrprog, functionvalue and others.

  • Platform: Matlab, Scripts
  • Publisher: Gaia Serraino
  • Date: 12-04-2013
  • Size: 225 KB

Powerful market scan and portfolio optimization software tailored to batch forecasting of big collections of market instruments.Extensive databse connectivity with Equis MetaStockT«, Yahoo Finance, CSV text worksheets, TC2000T« and QuotesPlusT« data warehouses as well as own native SQL drivers to Microsoft AccessT« and Microsoft SQL Server, IBM DB2 UDB, Oracle 9i. It esures direct online data acquisition and smooth operation on huge datasets up to hundredts of thousands symbols.Built-in forecasting expert works on wide collection of elaborate predictors, technical indicators, digital filters and statistical tests to achieve top forecasting accuracy and reliability in full automated unattended mode.

Five Excel Add-Ins For Business.Excel add-ins provide ready made solution for forecasting, investment economics, portfolio optimization, business resource optimization and material planning.Forecasting.xla. Calculates moving averages, exponential smoothing moving averaging, linear regression and seasonal trend analysis.Investment Economics.xla. Calculates net present values and internal rate of return after tax for any capital investment projects. Selects projects that in aggregate meet users objectives.

Are you having difficulty understanding how to do option pricing modesl and numerical procedures within Excel? Do you want to see practical examples? The Numerical Searching Methods and Option Pricing Set solves these problems. It contains practical and well explained examples of: 1. Numerical Searching Method - Newton-Ralphson 2. Numerical Searching Method - Secant Method 3. Implied Standard Deviation For Black/Scholes Call - Newton Approach 4. Implied Standard Deviation For Black/Scholes Call - Secant Approach 5.

This extremely easy and simple to use Excel Time Sheet will keep track of your employees hours. It allows you to specify and set unpaid breaks in 5 minute intervals on a daily and employee basis. The Timesheet can incorporate up to a 12 week period with any week and/or day being optional. All you do is enter your employee names once, save as a Template and you are set. 1.Enter your employee names in the cells below Employee Name on Week1 only. The same names will automatically flow through Weeks 2 to 12.

Do you want to see how random numbers from different probability distribution are generated? The Random Numbers Generator and Statistics Set can show you how. It contains practical and well explained examples of: 1. Log Normal Distribution 2. Log Pearson Type III Distribution 3. Normal Distribution 4. Chi-Square Distribution 5. F-Distribution 6. Student-T Distribution 7. Multivariate Standard Normal Distribution8. Gamma Distribution 9. Beta Distribution 10. Hypergeometric Distribution 11. Triangular Distribution12.

This zip file contains the Presentation (PDF) and M-files that were demonstrated in the MathWorks Webinar: Using Genetic Algorithms in Financial Applications delivered on Dec 11 2007. The purpose of the webinar was to highlight how Genetic Algorithms may be used to supplement portfolio optimization problems. The Genetic Algorithm contains custom evolution algorithms that were built specifically for this webinar. They allow the user to explore subsets of fixed size from a larger universe of stocks to search for a minimum variance portfolio with a given return.

  • Platform: Matlab, Scripts
  • Publisher: Oren Rosen
  • Date: 06-05-2013
  • Size: 2724 KB

Please see PORTOPTGADS, by following link 'Published m-files' below. PS. The cool picture is a visualization of Rastrigin's function, taken from Genetic Algorithm and Direct Search Toolbox documentation..

  • Platform: Matlab, Scripts
  • Publisher: Dimitri Shvorob
  • Date: 26-06-2013
  • Size: 41 KB

Particle swarm optimization (PSO) is one of the modern heuristic algorithms that can be applied to continuous and discrete optimization problems. The original binary PSO (BPSO) has got some disadvantages that make the algorithm not to converge well. To deal with these disadvantages, a new BPSO (NBPSO) is introduced. The results provided in the fallowing papers show the superiority of the NBPSO. [1]. M.Rostami Shahrbabak and H.Nezamabadi-pour, " New Approach to Binary PSO Algorithm" 14th Iranian Conference on Electrical Engineering, may 2006.

Various quantitative finance algorithms in areas related to asset allocation and portfolio simulation. Includes Black-Litterman model, State/Preferencem Interior points, and Active Set quadratic optimization..

  • Platform: Linux, Mac, Windows
  • Publisher: akutan.org
  • Date: 14-10-2012
  • Size: 691 KB

Exercises and case studies for a rigorous approach to risk- and portfolio-management. This booklet stems from the review sessions of the six-day ARPM bootcamp. Contents include: Advanced multivariate statistics; copula-marginal decomposition Annualization/projection (FFT, cumulants, simulations) Pricing: exact; first order (delta/duration); second order (gamma/convexity) Quest for invariance (stationarity, volatlity clustering, cointegration) Mutlivariate estimation - Non-parametric; MLE; shrinkage; robust; Bayesian; missing data - Generalized hypothesis testing Dimension reduction - Statistical (random matrices; principal components; factor analysis) - Cross-sectional / time-series factor models - Factors on Demand Risk management - VaR/CVaR (marginal Euler decomposition; extreme value theory; Cornish-Fisher; elliptical) -...

  • Platform: Matlab, Scripts
  • Publisher: Attilio Meucci
  • Date: 14-02-2013
  • Size: 1495 KB
  • KP01
  • License: Freeware
  • Rating

[FMAX,X] = KP01(W,P,C) solves the combinatorial optimization problem maximize F = SUM(P.*X), subject to SUM(W.*X) <= C, where the solution X is a binary vector of 0s and 1s. W and P are vectors of weights and profits and C is the capacity of the knapsack. Weights must be positive integers. The knapsack solver uses preprocessing with estimation of lower and upper bounds to reduce the problem to a core problem. The core problem is solved by standard dynamic programming. P = [] invokes the subset-sum solver.

  • Platform: Matlab, Scripts
  • Publisher: Jonas Lundgren
  • Date: 15-02-2013
  • Size: 10 KB

Files used in the Webinar: Build a Portfolio Analysis Production Application in MATLAB using Object-Oriented Programming Techniques. The focus of this demo is to introduce the design and development of a complete MATLAB application from concept through to completion. The GUI-based tool provides functionalities to import price series from various data sources; and to define complex optimization constraints on the data. Furthermore, the tool provides extensive interactive visualization capabilities for the optimization results and key risk metrics.

  • Platform: Matlab, Scripts
  • Publisher: Patric Schenk
  • Date: 05-01-2013
  • Size: 522 KB
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