In many countries a mortgage shall be completely redeemed to the end of its duration and may be refinanced anytime. In USA one additionally can foreclose his mortgage by mailing his house-keys to a bank. In Germany is different.
First of all, one may completely refinance a mortgage only after 10 years (otherwise one have to pay Vorfälligkeitsentschädigung - a compensation to a bank for missed interest). But taking a long-term mortgage (20 or 30 years) implies a higher mortgage rate, thus it is not uncommon to take several consequent 10- (or sometimes even 5-) year mortgages. In order to optimize mortgage costs / rate change risk relation one can take several submortgages with different durations. Last but not least there is no requirement to amortize a mortgage completely: normally one refinances the residual debt (Restschuld) with a follow-up mortgage (Anschlussfinanzierung).
In this post we discuss the challenges of mortgage optimization and show how two popular programming languages - R and Python - can help us together Continue reading "Interbreeding R and Python to Give Birth to an Optimal German Mortgage"
QuantLib development often lags the version of Visual Studio. Thus you need to do some manual tuning to build QL v1.14 in VS 2019. Generally, if you can, you shall so far stay by VS2017. Continue reading "Building QuantLib 1.14 with Visual Studio 2019 preview"
Recently I have read the results of salary survey among Russian-speaking software developers in Germany, published on dou.ua. I was skeptical about the validity of conclusions and expressed my critics (a bit less polite than I should have done it). But the survey author reasonably pointed out that he did his best in his free time and did provide the raw survey data. Recalling a popular motto in Soviet Union: if you are disagree then criticize but if you criticize then do it better I try to interpret the survey results more correctly. Continue reading "Salaries in German IT Branch – a Case Study of Critical Statistics Review"
The idea that the stock picking makes less and less sense since the markets are more and more driven by the macroeconomic factors is quite popular.
Especially right now, as the markets are falling (like on todays FEd decision to increase the rates), this idea may seem to be plausible. However, we show that in the long term the stocks do show enough of individuality. Continue reading "PCA, Autoencoders and the Feasibility of Stockpicking"
We have successfully migrated from Ubuntu 16 to Ubuntu 18, assuring stable and secure functioning of letYourMoneyGrow.com for the next several years. We had to disable social login but the users that registered with their social network accounts can use our services as before (they merely need to reset their passwords). Continue reading "letYourMoneyGrow.com Serves You on Ubuntu 18.04.1 LTS Linux"
On the fateful Wednesday of November 1st, 2017 Yahoo decided to stop their – until then – free service of delivering real time market data as a text stream through a special URL. For hundreds of businesses and individuals who had relied for years on Yahoo's benevolent free service, this single action meant only one thing: Instant death! Continue reading "Yahoo Finance Live Feeds in Excel after their API Discontinuation in November 2017"
In our previous post on Nelson-Siegel model we have shown some pitfalls of it. In this follow-up we will discuss how to circumvent them and how machine learning and artificial intelligence can[not] help. Continue reading "Pitfalls of Nelson-Siegel Yield Curve Modeling – Part II – what ML and AI can[not] do"
The Nelson-Siegel-[Svensson] Model is a common approach to fit a yield curve. Its popularity might be explained with economic interpretability of its parameters but most likely it is because the European Central Bank uses it. However, what may do for ECB will not necessarily work in all cases: the model parameters are sometimes extremely unstable and fail to converge. Continue reading "Pitfalls of Nelson-Siegel Yield Curve Modeling – Part I"
The Open Source Risk Engine is an opensource software project for risk analytics and xVA. It is written (mostly) in C++ and based on QuantLib. In this post we explain how the ORE can be built from source in Visual Studio 2017. Continue reading "Building Open Source Risk Engine (Quaternion ORE) in VS2017 without Git"
QuantLib Python - a port of C++ library to Python via SWIG - provides a lot of advantages for a practical usage. In particular, it gives a great flexibility due to interactive python console and allows a seamless integration with the AI libraries like Keras and Tensorflow. However, it seems to be challenging to debug the C++ code, called from Python side. So far we found out a quick but dirty solution. Continue reading "QuantLib Python – debugging C++ side with Visual Studio and PyCharm – a dirty way"