I am happy to announce that I will be hosting a free webinar series on quantitative analysis and algorithmic trading. Dates and times for the first shows can be found over here: Tradesignal Webinar Series
Year: 2020
A Neural Network based trading strategy
I always dreamed about the machine which tells me to enter long right before the market starts to go up. Might a neural network be this machine? Using Tradesignal and the free Python Neural Net library Pyrenn it is easy to find out…
Part one: Classification of data
A Simple Neural Network for Indicator Prognosis
Technical indicators are the base of algorithmic trading. So wouldn’t it be nice to know tomorrows indicator value in advance? This article is about how to use a simple neural network to do so. Python and Tradesignal will be used to do the programming.
A single linear neuron
Detecting Support and Resistance Levels
Support & Resistance levels are essential for every trader. The define the decision points of the markets. If you are long and the market falls below the previous support level, you most probably have got the wrong position and better exit.
The detection of support and resistance levels is usually highly subjective and based on the analysts experience. In this article I will use a simple algorithm to detect the levels and show them on the chart. Continue reading
Overnight Risk Premium in Equity and Commodity Markets
Over the last 20 years equity markets and ETFs did a significant part of their total performance over night. This article will examine the relationship of in-session moves vs. the out-of-session moves of ETFs and commodities.
The overnight risk premium
Charting Probabilities
Charting is all about where you are and what might happen next. Seeing the statistical probabilities of further poves is surely a big help when thinking about the market. This article gives you a free set of indicator which will help you differ the likely from the unlikely. Continue reading
The magic of implied volatility
VIX and implied volatility in general is a measure of the expected market move. If VIX is trading at 50, the option market expects that the market will stay within 50% up or down within the next year. Continue reading
This is the end of the world as we know it
I don’t know what the future will bring, but there is one thing I know for sure. The bubble has burst and the party is over.
Read your charts
Profit from large daily moves
Whenever the market shows an exceptional day ranges it is time to take bite. See how you can profit from large daily market moves.
Open-Close Range
When looking at any chart, you will surely notice that the large candles tend to close near the high or low. This is due to herding. Once the market is moving significantly, everyone hops on and the large move becomes even larger. This is true for daily, weekly and intraday candles.
The chart shows an indicator which plots the daily move. Every opening is set to zero and the absolute move of the day is drawn. Around these normalised candles a long term 2 standard deviation volatility band is drawn. Right now the 2 standard deviation volatility for SPX is about +/- 46 points.
Take a bite before the market closes
As you can see this +/-46 point barrier above/below the opening of the day is a wonderful entry point. If you enter long 46 points above the opening and go short 46 points below the opening nearly all entries would have lead to a profitable trade. To get an even higher probability of success you can volume as a confirmation. Large moves must also show high volume. The exit is done at the end of the session. This analysis does not give any indication for the next days move. So be fast, take your bite and go home with a small profit and no overnight position.
No free lunch
On the chart it looks easy, but be careful. As an example the last bar shown on the chart first crossed the band to the downside, reversed and crossed above the upper band. So you will need to use a trailing stop to lock in profits and avoid to take the full -46 to +46 points trade as a loss!
Python Regression Analysis: Drivers of German Power Prices
German Power prices can be explained by supply and demand, but also by causal correlations to underlying energy future prices. A properly weighted basket of gas, coal and emissions should therefore be able to resemble the moves of the power price. This article will introduce multivariate regression analysis to calculate the influence of the underlying markets on a given benchmark. It is an example of a machine learning algorithm used in analysis and trading.