Market were really turbulent during the last weeks. We committed a lot of trades with Elle and did some important calculations of our trading costs. Continue reading "JuniorDepot7c – Lots of Actions and Calculations"
In this essay I try to figure out the most fair reward system for a wealth manager. I don't appeal to the notorious utility functions or mathematical optimization models that fail in practice due to the errors of parameter estimation. Rather I rely on best practices and common sense. Continue reading "The Fairest Reward System for a Wealth Manager"
A very important question, which every trader or investor encounters is how many trades to commit or how many stocks to hold in portfolio. Whereas the law of the large numbers readily gives a [naive] answer "the more the better", in practice the answer is often better less but better. Continue reading "Optimal Number of Trades: better less but better"
Our simulator allows you to simulate 100 future scenarios of your portfolios, estimate the expected risk, return and correlations, helping you to improve the diversification of your portfolios. The simulator projects the historical returns in future and is completely model-free (in particular, we don't make an unrealistic assumption of Normally-distributed returns). Though the past doesn't capture all possible future scenarios, it provides a good idea of possible outcomes.
Continue reading "Portfolio Simulator – estimate the expected risk and return of your investments"
My wikifolio ("Somewhat better than DUCKS", ISIN: DE000LS9HDK3) is investable from 28.10.2016. It surely beats the DAX (main German stock index) both on absolute and risk-adjusted performance. Though I am very proud of my performance, I provide a closer look at it and show that sometimes I had just luck and sometimes I could have done better. I always preach for the rigorous and cold-blooded performance analysis and the best sermon is to demonstrate it by the example of myself.
The maximum drawdown (MDD) is likely the most important measure of risk in practice. We explain how to calculate it and why you should keep it under control. Remember, if the MMD reaches -50% the portfolio have to grow +100% in order just to compensate the previous loss!
There is yet another Roboadvisor from Vanguard Group. As any RoboAdvisor, its recommendations are far from perfection. However, I like it (at least more than others) because the Vanguard guys managed to make it simple. On the other hand I am quite disappointed that they do not show how a suggested portfolio may evolve (and I am quite sure that legendary John Bogle would be disappointed too). That's why I made a simple scenario simulator on my own. It is based on sample with replacement.
Continue reading "A simple scenario simulator for Vanguard optimal portfolio"
- Sometimes (esp. to fool inexperienced retail investors) the diversification is claimed to be a silver bullet (even in a financial crisis). I show that in crises the diversification effect weakens significantly but still persists (esp. for "defensive" stocks).
- I argue that in a normal (non-turbulent) market the diversification is very helpful in theory but also critically consider its applicability in practice.
- The results that we obtained for the DAX / German stock market should be extrapolated with caution for other markets. You will also see why it is better to watch and know the market (rather than to blindly rely on quantitative analysis and common sense).
- Robo-advisors promise the risk profiling in a few easy steps, which is unrealistic both from mathematical and behavioral points of view.
- The "optimal" portfolios are usually based on Markowitz-like models, which are inapplicable in practice due to their extreme numerical sensitivity to the market parameters estimation errors.
- Robo-advisors lure investors with low management fees but minimizing fees and maximizing the wealth is not the same. Moreover, the compound costs are not so small in the long term.
- A positive side: Robo-advisers do not (yet) foist toxic financial products upon you.