Stock Optimizer brings a growing set of mathematical and statistical investment tools to help you make more informed investment decisions on the stock market. The key features are:
Stock Optimizer is aimed anyone considering investing in the stock market, from first time investors to experienced professionals.
Monte Carlo simulations of Your Portfolio based on historic or forecasted returns. Value-At-Risk and risk de-composition.
Forward-looking analyses based on crowd-sourced estimates of future returns.
Stock returns are taken as the geometric average of daily returns over your chosen look-back period.
Volatility (or standard deviation) is a measure of how much a stock price fluctuates. It is a standard measure of investment risk and is calculated from the variation of stock returns around their historic average.
In finance, the correlation coefficient is a statistic that measures the relationship between the changes of two securities over time. It varies between -1 and 1.
If two securities have a correlation coefficient of 1, this implies that as one security moves, either up or down, the other security moves in lockstep, in the same direction. A correlation coefficient of -1 means they move in opposite directions, while a zero correlation implies no relationship at all.
An optimal portfolio is a portfolio of stocks that is designed with a perfect balance between risk and return. It provides the highest possible return for a given level of risk.
The points on the plot of risk versus return where optimal portfolios lie is known as the efficient frontier. These portfolios all offer the highest possible return for that level of risk.
Portfolios that lie below the efficient frontier are sub-optimal, because they do not provide enough return for the level of risk.
Stock Optimizer uses a mathematical framework called Mean Variance Optimization to calculate optimal portfolios. Economist Harry Markowitz introduced the formula behind Mean Variance Optimization in his 1952 paper on Portfolio Selection for which he was later awarded a Nobel Prize.
Stock Optimizer uses historic stock returns, forward looking returns estimates set by you, volatility of returns and correlations of returns to calculate optimal portfolios and the efficient frontier.
Critics of Mean Variance Optimization question its use because its model of markets does not match the real world in many ways.
Stock Optimizer is intended for investors who understand these limitations but believe Mean Variance Optimization it still offers useful additional information, to compliment their existing research and processes, and help them make more informed investment decisions.
You can use the Portfolio Back-Test tool to check the realized return of Mean Variance Optimization strategies and compare these to the realized historic performance of Your Portfolio and portfolio’s with simple 1/N stock weightings.