Some of QuantLib functionality is ported to R in RQuantLib. In particular the pricing of Barrier options. Unfortunately, only European. But we need American in order to price and simulate future scenarios for the so-called KO-Zertifikate (Knock-Out Warrants), which are quite popular among German retail traders. We show how to quickly adopt the code from QuantLib testsuite, compile it under Linux and integrate with R and web.
Continue reading "Integrating QuantLib with R and Web – Barrier Options Pricer"
On 25.12.2016 I bought a put on nVIDIA since I found the stock extremely overpriced. I called it "nearly perfect trading decision", inter alia, because the implied volatility was though plausible but still high. Yesterday after the publication of Q1 financial report the stock jumped 18%. My put option is about 50% down since purchase time. But due to a strict money management I have capital for the 2nd and even fors 3rd attempt and I still consider nVIDIA as heavily overpriced.
Continue reading "PUT on nVIDIA turned out to be far from perfect trade, but…"
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"
A common belief: adding extra asset to a portfolio will automatically reduce the portfolio risk. We provide a counter-example resorting only to the simplest algebra and explain why this erroneous belief is so common.
Continue reading "Perfect diversification means no asset can be dropped from (rather than added to) a portfolio"
Quantopian is a very interesting FinTech project for virtually everybody, who wants to try the algorithmic trading. Yet I explain why I myself - a successful trader, experienced quant and good programmer - don't take part. Continue reading "Quantopian – why I don’t take part"
Investing in a "globaly demanded" product or service seems (at first glance) to be a nice idea. However, it may be (too) dangerous: not all global trends turn into profit and even if they do, you need to get in early since most of global trends (even genuine) turn into bubbles and do burst.
Continue reading "Why I am skeptical about investing in “global trends”"
Usually I warn against making conclusions from fiction books or films about financial markets. However, the Big Short gives some genuine lectures, at least between the lines.
Continue reading "Five lessons to learn from The Big Short (film)."
- 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.
Continue reading "Stripping down the robo-advisors: sparrow-brains inside"
Fractions is a topic from elementary mathematics but surprisingly even some Ph.Ds in math have problems with them. After this lesson you will be able to read pie diagrams, calculate portfolio weights and weighted average returns. This lesson does not substitute systematic learning but helps you to recall fractions and demonstrates their usage in trading context.
Continue reading "Numeracy for Traders- Lesson 1 – Fractions"
- The martingale strategy asymptotically implies infinite capital or infinitely divisible stake. In reality you have a limited capital and there is a lower (in casino also an upper) bound of the stake.
- In a fair game (with 50/50 chance of profit and loss) the probability of profit after a series of losses is still 50% (because the outcomes of bets or trades are independent from each other).
- Typically, if you win then your profits are moderate but if you lose, the losses are severe (you can lose your capital just after a small series of unlucky bets).
- If you make pretty many bets, you might make a good profit but the probability to make profit at all decreases with the number of bets. Losses stays severe.
Continue reading "Mystery and misery of the martingale betting system: why it will not make you rich"