Create a statistically optimized portfolio
The development of stock market values exceeds the development of other investment alternatives (like bonds or money market accounts) over a longer time. But this comes with the greater volatility of stock prices.
RSJ Portfolio loads historic end of day price data, analyzes the return correlation between different stocks and uses it to create an optimized portfolio. This portfolio consists of stocks that have a low correlation — or low downside correlation if configured to do so. Thus the volatility of the portfolio is greatly reduced.
Microsoft Windows 10 or 11, 64 Bit · from USD 99.00 single user license · Watch the explainer video
13+
Risk and allocation methods
10 years
Maximum analysis timeframe
2
Data providers supported
RSJ Portfolio — Recommendation — Data\config\portfolio.json
Recommendation tab: optimization parameters, allocation and statistically expected results.
Overview
Correlation is fairly static — so it can be exploited
Experience has shown that the correlation between individual stock prices is pretty static, because it is based on economic facts like industry or country. RSJ Portfolio analyzes past correlation between stock prices and tries to find a combination of stocks that minimizes the risk of the portfolio as a whole.
Step 1
Select candidates
Search by company name, ticker symbol or ISIN and collect the stocks you consider worthy of an investment. Their currency is determined and stored during search.
Step 2
Load and clean prices
Historic end of day prices are loaded from your data provider, cached locally, cleaned of invalid values and outliers, and converted into your local currency.
Step 3
Optimize and backtest
The optimizer proposes a capital distribution with its statistically expected results. Set a cutoff date to see how that portfolio would have developed since then.
The process is quite simple
You pick the candidates, the software does the arithmetic. It loads the history, cleans it, plots it in the form you need — absolute price, relative price, change, interpolated, converted, logarithmic or as a correlation matrix — and then optimizes a portfolio out of some or all of those candidates.
Every method, risk model and parameter has its own chapter in the documentation. The detail pages here summarise them; the RSJ user guide documents them in full.
Selection tab: search a symbol, add it to the candidate list and compare price series.
How the optimizer works
Minimum volatility, maximum Sharpe ratio, hierarchical risk parity, conditional value at risk, and the eight risk models behind them.
Methods and features →Prices are messy
Negative and infinite prices, gaps, sigma clipping and the USD conversion path for portfolios quoted in several currencies.
Data and currencies →From install to backtest
Requirements, the configuration essentials, a step by step walkthrough and every optimization parameter explained.
Getting started →Features
A complete optimizer, not a single formula
Efficient Frontier Algorithm, Hierarchical Risk Parity, Conditional Value at Risk, Minimum Volatility, Minimum Semi Volatility, Maximum Sharpe Ratio, multi currency support, Capital Asset Pricing Model, backtest, PDF and Excel export.
Five allocation methods
Choose the objective: lowest volatility, best return to risk ratio, smallest downside volatility, risk parity across clusters, or lowest risk at a confidence level.
Eight risk models
The covariance of the selected price series drives everything. Pick the estimator that fits your data set, from plain covariance to Ledoit Wolf shrinkage.
Return models and CAPM
Expected returns feed the Sharpe ratio and the Capital Asset Pricing Model — from a plain historic mean to an exponentially weighted one.
Weights you control
Cap and floor the weight of any holding, set the benchmark for a zero risk investment, and tune the CVaR certainty or the L2 regularization.
Backtest with a cutoff date
Build the portfolio from the data available at a past date and follow how that static portfolio would have developed since then.
PDF and Excel export
Export the graphics as PDF files and the resulting portfolio as an Excel file, so the analysis can be filed or forwarded.
Screenshots
From a candidate list to an optimized portfolio
Three tabs carry the whole workflow. Everything else is a chart or an export away.
Build the candidate list
Search companies by name, ticker or ISIN and collect the stocks you want to analyse. The chart plots the selected series as price, relative price or change over a timeframe between one month and ten years.
Pricing
One license, no subscription
RSJ Portfolio is sold as a standard product. The single user on premises license covers the software and every update within the same major version.
Single user license
RSJ Portfolio
On premises, Windows 10 or 11, 64 Bit
USD 99.00
one time
VAT free
- Single user on premises license for RSJ Portfolio
✓
- All updates with the same major version number
✓
- VAT free
✓
FAQ
Questions that come up before the first optimization
Data providers, methods, backtesting and licensing — answered from the product documentation.
Blog
Notes from the product
Background on the optimizer, the data behind it and how the methods are meant to be used — written by the people who build RSJ Portfolio.
Blog
Opens the product blog.
The detail pages
Methods & features
Allocation methods, risk models, return models and the parameters that constrain them.
Methods and features →Data & currencies
Data providers, price cleaning, caching and the USD conversion path.
Data and currencies →Getting started
Requirements, configuration, a step by step walkthrough and the results you get.
Getting started →Blog
Background articles on the optimizer, the data and the methods, from the team building it.
Product blog →