Modern portfolio theory, as laid down by Markowitz, gives a mathematical recipe for asset allocation. However, the solutions of this method suffers from instabilities arising from parameter uncertainties. At Zorc Finance we have developed Bayesian tools to conduct asset allocation that is both optimal and stable.
An important problem in algorithmic finance is finding the optimal trading trajectory for a set of financial instruments that jointly maximizes the expected profits, reducing risk and accounting for trading costs. Through our research efforts, we have developed the Robobroker to find the optimal trajectory under realistic market conditions.
A high diversified, algorithmically created portfolio produces large volumes of statistical data that is difficult to grasp by the human mind. We developed financial and statistical visualizations employing VR technologies to solve this problem. Our tool allows for the rapid extraction of visual insights, such as the statistical parameters influencing your portfolio. This free tool can be used to benchmark and backtest the results of a manually chosen portfolio with the results from the IAA.