JuniorDepot31 – Experiment Termination

Since DeGiro announced closure of Elle's depot on May 15, 2022 she had to optimally close her positions before this date. Unfortunately, the announcement of depot termination coincided with market correction and further macroeconomic risks due to Russian invasion of Ukraine.
Thus the achieved CAGR is just 2.06%, not 6% as pursued. Still it is much better than a bank deposit with zero (or even negative) rate and given the permanent deterioration of DeGiro the result is not that bad.
Continue reading "JuniorDepot31 – Experiment Termination"

JuniorDepot30 – The Final Degradation of DeGiro

On 10.02.2022 DeGiro notified Elle that her Depot is going to be closed due to inability to run a bank account for an underage person.
This is a very illustrative case of the operational risk.
Continue reading "JuniorDepot30 – The Final Degradation of DeGiro"

(Снежная) Королева Этери Тутберидзе и причем тут Трейдинг и Инвестиции

Напряжение, надрывы и колоссальная ошибка выжившего роднят фигурное катание и финансовую отрасль. Но возраст, в котором приходит успех - в пользу финансов. Continue reading "(Снежная) Королева Этери Тутберидзе и причем тут Трейдинг и Инвестиции"

JuniorDepot29 – (Over)archieving the Financial Plan (thanks to AI and NI)

Since we did not report about Elle's progress for more than a year, the readers of letYourMoneyGrow.com might have thought that we have terminated our experiment of growing a 7 (currently 11) years young girl as an investor. Nope, not at all! As a matter of fact we worked hard on creation and test of a deep neural network for the stock (pre)selection. And it did work, our CAGR goal is (over)achieved!
Continue reading "JuniorDepot29 – (Over)archieving the Financial Plan (thanks to AI and NI)"

GPUs in AI – are they always cool? No, sometimes they are hot!

Finally I harnessed Tesla K80 for my AI modeling but unfortunately the overheat brings much overheads and not by all models the GPU is superior over CPU. Continue reading "GPUs in AI – are they always cool? No, sometimes they are hot!"

Affordable Hardware for Stockpicking AI – BeerWulf’s eBay Adventure

In my previous post I reported howto build and install TensorFlow and horovod from sources and howto setup a BeerWulf (BeoWulf) cluster. Building this BeerWulf cluster is though a good exercise to make a (resilient) system of a commodity hardware, however, it is not the most efficient way for a practical purpose (in my case: for creating an AI model, which helps me to pick up stocks). In this post I consider the hardware alternatives in the sense of making them both as efficient and as cheap as possible. Continue reading "Affordable Hardware for Stockpicking AI – BeerWulf’s eBay Adventure"

Building TensorFlow 2.5 (CPU only) and Horovod from source in Ubuntu 20.04.2 LTS

Short summary:

sudo swapoff /swapfile
sudo dd if=/dev/zero of=/swapfile bs=1M count=65536 oflag=append conv=notrunc
sudo mkswap /swapfile
sudo swapon /swapfile

sudo update-alternatives --install /usr/bin/python python /usr/bin/python3 1
sudo apt update
sudo apt install python3-dev python3-pip
sudo apt install python3-testresources
pip install -U --user pip numpy==1.19.5 wheel
pip install -U --user keras_preprocessing --no-deps
sudo apt install git
git clone https://github.com/tensorflow/tensorflow.git
cd tensorflow
git checkout r2.5
sudo apt install npm
sudo npm install -g @bazel/bazelisk

bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
pip install /tmp/tensorflow_pkg/tensorflow-2.5.0-cp38-cp38-linux_x86_64.whl

sudo apt-get install openssh-server
sudo systemctl enable ssh
sudo systemctl start ssh
ssh-copy-id vasily@SERVER2
ssh-copy-id vasily@SERVER1

sudo snap install cmake --classic
sudo apt install openmpi-bin
mpirun -H SERVER1:1,SERVER2:1 hostname

git clone --recursive https://github.com/uber/horovod.git
cd horovod
python setup.py clean
python setup.py bdist_wheel
HOROVOD_WITH_TENSORFLOW=1 pip install ./dist/horovod-0.22.1-cp38-cp38-linux_x86_64.whl[tensorflow,keras]
mpirun -H SERVER1:3,SERVER2:3 python3 /home/vasily/horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
Continue reading "Building TensorFlow 2.5 (CPU only) and Horovod from source in Ubuntu 20.04.2 LTS"

Howto Install Tensorflow-GPU with Keras in R – A manual that worked on 2021.02.20 (and likely will work in future)

A brief instruction:
0. Update your Nvidia graphic card driver (just driver; you need NOT install/update CUDA but make sure that your card has cuda compute capability >= 3.5)
1. install Anaconda (release Anaconda3-2020.11 from anaconda.org)
2. open anaconda prompt and run
>conda create -n tfgpu210p37 python==3.7
>conda activate tfgpu210p37
>conda install cudatoolkit=10.1 cudnn=7.6 -c=conda-forge
>conda install -c anaconda tensorflow-gpu
3. in R run
>reticulate::use_condaenv("tfgpu210p37", required = TRUE)
4. If you wanna understand what is going on under the hood, read further
Continue reading "Howto Install Tensorflow-GPU with Keras in R – A manual that worked on 2021.02.20 (and likely will work in future)"

Häusle oder Aktien? – Die Antwort gibt es aber man muss immer adhoc berechnen

Am häufigsten kommen zwei Empfehlungsarten von "Experten" vor: entweder in die Aktien zu investieren weil sie eine höhere erwartete Rendite bringen oder die Immobilien zu kaufen weil die stabiler sind.
Beide Aussagen sind lediglich ein kleiner Teil der komplizierten Wahrheit. In diesem Post zeigen wir anhand eines Beispiels, wie man - mittels Zahlen und Berechnungen - eine mehr oder weniger vollständige Antwort für seinen persönlichen Fall bekommen kann.
Sehr hilfreich dafür ist das kostenlose Toolset von letYourMoneyGrow.com
Continue reading "Häusle oder Aktien? – Die Antwort gibt es aber man muss immer adhoc berechnen"

Interbreeding R and Python to Give Birth to an Optimal German Mortgage

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"