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The market has been incredible this year. Not only the corona virus, but also the dynamics of specific industries such as elektromobility and the oil and gas trading.


Now the Dow Jones is putting in a quite long sideways move, which is correlated with a time of the year ending and an end of the US presidential election cycle. In addition the future problem of corona virus could be solved better than expected. This is a lot of news. It makes no sense at all that the indices rallies just from the lows in march 2020. There could be several reasons for this, for example: investors have no idea what else to invest in. The governments take more and more the functions of insurance and a wider variety of basic consumer trading. There might be a time lag in the decisions, which could lead to the safety allocation much later (eg 1-2 years later). Due to this, maybe the bond markets will become very interesting in the next few decades, but it is not possible to judge this. Of course gold markets have worked as a hedge, but the fundamental underlying trade of gold is questionably since we have digital currencies such as Bitcoins.


If fact we can see the first sign of volatility again after one decent move into Christmas. It will remain unclear in the dynamic of how it will evolve. For sure I recommend you read my two books on the topic of trading short term and volatility dynamics again. Here is the link: https://www.amazon.com/Valentin-Rossiwall/e/B004FNPO3Q


Volatility and Dow Jones





Source: www.finviz.com

A very modern programming language used by more and more quantitative trading firms is R. It actually proves the opportunity to work and display very interesting concepts for traders and investors.


It is possible to do own calculations according to personal wishes and preferences. It is also possible to scale, analyse and calculate data with a lot of information and then send signals to the broker. In between there can be specific trading models for performance, risk and modeling.


There are some packages (there are more than 30.000 pre developed packages for this programming language R) even for daily trading (day-trading, per se similar to high frequency trading), when decision makers want to make their allocation decision daily on an more advanced basis, rather than a simple buy and hold strategy.


Check this out:


https://cran.r-project.org/web/packages/highfrequency/highfrequency.pdf


Description Provide functionality to manage, clean and match highfrequency trades and quotes data, calculate various liquidity measures, estimate and forecast volatility, detect price jumps and investigate microstructure noise and intraday periodicity.


https://github.com/algoquant/HighFreq


Package ‘TTR’ allows almost all typical indicator variations in broker platforms available, only that if you can do R, you can make customized solutions and fine tune it.

September 1, 2020 Type Package Title Technical Trading Rules Version 0.24.2 Author of this package: Joshua Ulrich Suggests

Description A collection of over 50 technical indicators for creating technical trading rules. The pack- age also provides fast implementations of common rolling-window functions, and several volatility calculations. URL https://github.com/joshuaulrich/TTR


ATR; ADX over Volatility, TRIX, Moving Averages ect. all possible within this environment.

Ansonsten ist das TTR Package ganz nützlich für technische Signale, PerformanceAnalytics für alle Art von Performancerechnung.


Erwähnenswert sind auch quanttools und quantstrat:


https://quanttools.bitbucket.io/_site/index.html

Enhanced Quantitative Trading Modelling

QuantTools is all in one R package designed to enhance quantitative trading modelling. It allows you to download and organize historical market data from multiple sources like Yahoo, Google Finam and IQFeed. Code your trading algorithms in modern c++11 with powerful event driven tick processing API including trading costs and exchange communication latency and transform detailed data seamlessly into R. In just few lines of code you will be able to visualize every step of your trading model from tick data to multi dimensional heat maps.




Transaction-oriented infrastructure for constructing trading systems and simulation. https://github.com/braverock/quantstrat


Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.



Overview

quantstrat provides a generic infrastructure to model and backtest signal-based quantitative strategies. It is a high-level abstraction layer (built on xts, FinancialInstrument, blotter, etc.) that allows you to build and test strategies in very few lines of code. quantstrat is still under heavy development but is being used every day on real portfolios. We encourage you to send contributions and test cases via the appropriate GitHub mediums (Pull requests and Issue tracker).


Mit Yahoo Daten kann man sich mit der API die Kursdaten der börsengelisteten Wertpapier in die Software Entwicklungsumgebung einladen.

Unter folgendem Link finden Sie einen kostenlosen Research zum Thema


Auswirkungen von EU Richtlinien auf Asset Manager.


Der Beitrag hat keine Empfehlungen in rechtlicher Hinsicht und stellt keine Beratung dar. Es ist ein kostenloser Research Beitrag der im Rahmen einer Universitätsarbeit erstellt wurde.


Unter folgendem Link können Sie meinen Research kostenlos lesen:



ESG Richtlinien Auswirkung auf Asset Man
.
Download • 242KB


© 2020 by Valentin Rossiwall .