Coastlines are fractal curves. When you zoom in, you will see similar shaped curves on every scale. The same is true for market data. On a naked chart you can hardly tell if it is a daily or hourly chart. This article will explore this feature of crinkly curves and show how much markets and coastlines have in common.
The coastline paradox
When trying to measure the length of the British coastline you will quickly notice, that the length measured depends on the length of the ruler you use. The shorter the ruler, the longer the measured length of the coastline.
When measuring a straight line, the length of the ruler has no influence. You can measure 1 meter with a 1cm ruler applied 100 times or with a 50cm ruler applied 2 times. Both methods will give you the same result. Not so when measuring a crinkly line like a coast.
British coastline length paradox (c) wikipedia
In 1967 Benoit Mandelbrot wrote a famous article in Science magazine about this problem. This was the birth of fractal geometry. The basic assumption was, that if a curve is self similar, this self similarity can be described by the fractal dimension of a curve. Self similarity means, that if you zoom into a curve, it looks similar on all zoom levels.
Coastline paradox in financial markets
The Hurst exponent is a measure for the behaviour of the market. It shows if the market behaves in a random, trending or mean-reversion manner. This can be used to select the right trading strategy for your market.
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
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
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 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
Whenever the market shows an exceptional day ranges it is time to take bite. See how you can profit from large daily market moves.
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!
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.
Multivariate regression analysis
Chart analysis is all about visualizing data. The RSI hellfire indicator uses a heat-map to visualizes how overbought or oversold the market is on a broad scale. This helps to get a broad picture of the current market setup.
Multiple Time-frame Relative Strength Index
Wells Wilder’s RSI is an old timer of technical indicators. It tries to find out if markets are overbought or oversold. Usually it is calculated using a 14 bar setting. But a 14 bars RSI on a daily chart will give a different reading than 14 bars on an hourly or weekly chart. As it is always nice to see what traders on a different time-frame see on their charts, you could simply display several RSI settings on your chart. Continue reading
When developing a new trading strategy you are usually confronted with multiple tasks: Design the entry, design the exit and design position sizing and overall risk control. This article is about how you can test the edge of your entry signal before thinking about your exit strategy. The results of these tests will guide you to the perfect exit for the tested entry signal (entry-exit combination)
Quality of an Entry Signal
When you develop a new idea for an entry signal there are two things you would like to see after the entry: no risk and fast profits. This would be the perfect entry with the highest possible edge. In reality the market response to your entry will be risk and chance. With a good entry the upside would outnumber the downside. Continue reading
Finding complex chart patterns has never been an easy task. This article will give you a simple algorithm and a ready to use indicator for complex chart pattern recognition. You will have the freedom to detect any pattern with any pattern length. It has been described as Fréchet distance in literature. This article shows a simple adaptation for chart pattern analysis.
Defining a chart pattern
Classical technical indicators like RSI and Stochastic are commonly used to build algorithmic trading strategies. But do these indicators really give you an edge in your market? Are they able to define the times when you want to be invested? This article will show you a way to quantify and compare the edge of technical indicators. Knowing the edge of the indicator makes it an easy task to select the right indicator for your market.
The edge of an indicator
Any technical indicator, let it be RSI, moving averages or jobless claims, has got a primary goal. It should signal if it is a wise idea to be invested or not. If this indicator signal has any value, on the next day the market should have a higher return than it has on average. Otherwise the usage of no indicator and a buy and hold investing approach would be the best solution.
The edge of an indicator in investing consists of two legs.
- the quality of the signal
- the number of occurrences
Adding some random noise to historic market data can be a great way to test the stability of your trading strategy. A stable strategy will show similar profits with noisy and original data. If the noise has a great impact on your results, the strategy might be over fitted to the actual historic data.
Synthetic market data?
Generating completely synthetic market data to test algorithmic trading strategies is a dangerous endeavour. You easily lose significant properties like classic chart patterns or the trend properties of your market. Continue reading
Monte Carlo Simulation uses the historic returns of your trading strategy to generate scenarios for future strategy returns. It provides a visual approach to volatility and can overcome limitations of other statistical methods.
Monte Carlo Simulation
Monte Carlo is the synonymous for a random process like the numbers picked by a roulette wheel. Continue reading
Analysing the market performance of the day session vs. the overnight movement reveals some interesting facts.
Daytime vs. Overnight Performance
The chart below gives a visual impression on where the performance of the SPY ETF is coming from.
The grey line represents a simple buy and hold approach. The green line shows the performance if you would have held SPY only during daytime, closing out in the evening and re-opening the position in the morning. Continue reading
So you are bullish on a specific stock, but you also have realised that timing is major problem? So what would be the best strategy to implement your bullish opinion but avoid the problems of any timing strategy?
Selling a put option might be the answer.
For discussing this question let’s use the current Apple chart as an example. The question is, if you are bullish on apple, should you buy 100 Apple stocks right away or should you sell an at-the-money put option. To find the pros and cons of these two possibilities let’s have a look at some charts. Continue reading
“The stock market is never obvious. It is designed to fool most of the people, most of the time” Jesse Livermore
Technical analysis is a form of market analysis based on historic price patterns. The basic assumption of technical analysis is, that human behaviour does not change over time, and thus similar historic market behaviour will lead to similar future behaviour. Technical analysis is a predictive form of analysis, a technical analyst will try to estimate what the market might most probably do over the next period of time. Continue reading
Over the last days and weeks some traders have been worried if the currently ongoing correction in the markets will evolve into a crash, or if it is just a normal correction.
Crash or correction
The main difference between a correction and a crash is the panic level. But it is not the absolute level of .VIX, the CBOE implied volatility meter. It is the difference between realized and implied volatility that defines a crash which defines real panic. Continue reading
Usually it makes no sense to fight against normal distribution. But there are setups which have got a high probability of unexpected behaviour. Volatility can be the key to future market movements.
Bollinger bands width percentile
Bollinger Bands are a great tool to describe market volatility. And my favourite tool to measure the width of Bollinger Bands is Bollinger percentile.
Like the IV percentile indicator my Bollinger percentile indicator is a probabilistic indicator. It gives the probability of Bollinger Bands having a narrower upper band – lower band range than currently given. Continue reading
The Weis Wave indicator combines trend and volume information. It seems to be of some interest for timing short term market reversals. Here comes a version of this indicator for usage in Tradesignal.
The Weis Wave indicator for Tradesignal
The basic idea of the Weis Wave indicator is to sum up the traded volume, as long as the market moves in the same direction. The bullish volume wave is displayed in green. As soon as the market changes direction, a red wave is constructed. by comparing the magnitude of the Weis wave with the magnitude of the market move, valuable insights for short term market timing can be found.
More information can be found via a web search or from the page I got the idea form: https://weisonwyckoff.com/weis-wave/ Continue reading