Our last meetup before Christmas was a venture into a new venue, new audience and a new challenging field, all at the same time thanks to Angel Marchev, Jr. and his father Angel Marchev. The presenter, Angel Marchev Jr., is an assistant professor at the University for National and World Economy, where he also graduated his BSc in Finance with distinction and defended his PhD. In between he managed to obtain a MSc degree at the Burgas Free University and gain experience as a bank analyst. Marchev Jr. is a fourth generation lecturer – his co-author and father, Prof. Angel Marchev provided valuable insights during the discussion.
The event itself was held at the alma mater of Marchev, Jr. – UNWE, which attracted visitors new to our meetings. They witnessed an ambitious project determined to leave a trail in an overcrowded field – Portfolio Management Theory. The goal is to bring the tools and techniques of the science of Cybernetics into the portfolio management process. To do this, the authors reformulated the investment portfolio problem as a cybernetic system where the investor is the controlling system and the portfolio is the controlled system. Another building block of the approach is the introduction of models of investors – simulating the behavior of an imaginary investor following a certain initially defined investment strategy. The strategies are ranging from investing in a single security, investing an equal amount into each available security, to the classical Markowitz optimization and the model invented by Prof. Angel Marchev, the Multi-stage selection procedure. The investor models based on these strategies are all tested on the same historical data – all instruments traded on the Bulgarian stock exchange between 1997 and 2011.
The nature of the selected data poses a great challenge typical for data science – missing data due to the poor trading activity. The authors went through a process of meticulous data cleaning in order to obtain useful data – most typically by trimming outliers and imputing the missing quotes by using the Last value carried forward approach. As usual, a single best approach to this problem does not exist, as illustrated by Marchev Jr. with the distorted results from the Markowitz optimization strategy due to spikes in returns for certain securities. These spikes were responsible for crashing the model and were remedied only after applying linear interpolation for imputing the missing data.
The models of investors were compared based on the risk-weighted return that the strategy yielded for every investment horizon. Overall, the best-performing strategy is the Multi-stage selection procedure of Marchev Sr., which is also the most computationally intensive.
On the top of all the information condensed into two hours of presentation, the audience also learned an interesting finding – all the popular investment strategies can be broken down into building blocks – predictors, solution generator and solution selector. This makes it possible to recombine these elements and obtain totally new strategies – a process called by the authors “heuristic restructuring”.
For the readers that already regret bitterly missing this great presentation – not all is lost. Thanks to our innovative and tech-oriented team, a complete video recording is available on Youtube and the slides are uploaded on our website and Slideshare. Stay tuned for updates, visit our website, follow us on Twitter and Facebook!
Written by: Vladimir Labov