RSI Hellfire Heatmap Indicator

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

The Edge of an Entry Signal

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

A simple algorithm to detect complex chart patterns

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

Continue reading

Noisy Data strategy testing

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 of strategy returns

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

Overnight vs Daytime Performance & Volatility

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

An Algorithmic Stock Picking Portfolio

In this article I will discuss a simple algorithmic stock picking approach based on momentum and volatility. The goal will be to generate excess returns versus a capital weighted stock basket.

Alpha and Beta

Investing in assets with low volatility and high return is on a lot of peoples wish list. Portfolios which archive this goal will have a high Sharpe ratio and in the end get the investors money. By reverse engineering this criteria, one can find promising stocks to invest in and out perform a given capital weighted index.

Alpha and beta are measures to describe an assets performance relative to its index. Both are used in the CAPM – capital asset pricing model.

Alpha is a measure for an assets excess return compared to an index. Continue reading

Weis Wave indicator code for Tradesignal

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: Continue reading

Tradesignal Implied Volatility and IV Percentile Scanner

Implied volatility data is key in options trading. This article shows how to access free volatility data in the Tradesignal software suite.

Implied Volatility and IV Percentile

Thanks to  implied volatility and IV percentile data is available. For free on a weekly basis. Using this data and the given code the data can be loaded into Tradesignal. This enables you to do your custom market scans, combining Tradesignal technical analysis and the implied volatility data from the optionstrategist website.

Free implied volatility data

The first step to use the optionstrategist data would be to safe it into a text file. Just copy and paste the data, no additional formatting is required. The free data on the website is updated every Continue reading

Implied vs. Realized Volatility for NASDAQ100 stocks

(1) You shall only trade when the chances are on your side

Comparing implied and realised volatility

Selling volatility can be a profitable game, but only if you sold a higher volatility than the market realises later on. Comparing realised and current implied volatility gives you an idea if the chances are on your side.

We already had a look at realised volatility and what the fair price for a straddle might be. Have a look at the kvolfair bet articles. These articles present a way to calculate the historically correct price for a straddle. Whenever you sell a straddle (to sell volatility), implied volatility should be higher than the fair bet price. Only then you will win on a statistical basis. Also have a look at the statistics of VIX, to get a clue when a downturn in volatility can be expected. Continue reading

Seasonal trouble ahead

If a bitchy prime minister and a crazy president weren’t enough, for the upcoming months the seasonal chart is also indicating further price setbacks.

Seasonality of DAX

Analyzing the average monthly performance of the German DAX index a distinct pattern of seasonality can be observed. On average June has been down 0.6%, but the big trouble is yet to come.

Continue reading

A graphical approach to indicator testing

A graphical approach to indicator testing

The first step in algorithmic strategy design usually is to find some indicators which give you an edge and tell you something about tomorrow’s market behaviour. You could use a lot of statistics to describe this edge, but I like to take a graphical approach in indicator testing first, and only later on worry about the maths and statistics.

Scatter Charts

Continue reading

Ranking: percent performance and volatility

When ranking a market analysts usually pick the percent performance since a given date as their key figure. If a stock has been at 100 last year and trades at 150 today, percent performance would show you a 50% gain (A). If another stock would only give a 30% gain (B), most people now would draw the conclusion that stock A would have been the better investment. But does this reflect reality?

Percent Performance and Volatility

In reality and as a trader I would never just buy and hold my position, I would always adjust my position size somehow related to the risk in it. I like instruments that rise smoothly, not the roller coaster ones which will only ruin my nerves. So ranking a market solely by percent performance is an useless statistic for me.

Lets continue with our example from above: if stock A, the one who made 50% has had a 10% volatility, and stock B, the 30% gainer, only had a 5% volatility, I surely would like to see stock B on top of my ranking list, and not the high vola but also high gain stock A.

Risking the same amount of money would have given me a bigger win with stock B.

Combining Performance and Volatility

To get stock B up in my ranking list I will have to combine the absolute gain with the market volatility in between. This can be done quite simple. Just add up the daily changes of the stock, normalized by market volatility.Have a look at the formula of this new indicator:

index(today)=index(yesterday)+(price(today)-price(yesterday))/(1.95*stdev(price(yesterday)-price(2 days ago),21))

In plain English: Today’s Vola Return Index equals yesterdays Vola Return Index plus the daily gain normalized by volatility

So if the index has been at 100, the volatility (as a 95% confidence interval over 21 days) is 1 and the stock made 2 points since yesterday, then today’s index would be 100 + 2/1 = 3

Vola Return Index vs. Percent Return Index

Lets have a look at a sample chart to compare the 2 ranking methods. I therefore picked the J.P.Morgan stock.

The upper indicator shows you a percent gain index. It sums up the daily percent gains of the stock movement, basically giving you an impression what you would have won when you would have kept your invested money constant.

The indicator on the bottom is the Vola Return Index. It represents your wins if you would have kept the risk invested into the stock constant. (=e.g. always invest 100$ on the 21 day 95%confidence interval of the daily returns)

Have a closer look at the differences of these two indicators up to October 2016. JPM is slightly up, and that`s why the percent change index is also in the positive area. During the same time the Vola Return Index just fluctuates around the zero line, as the volatility of JPM picked up during this period of time. To keep your risk invested constant over this period of time you would have downsized your position when JPMs volatility picked up, usually during a draw down. No good.

The same can be observed on the upper chart, showing the last months movements of the index. Right now, after the recent correction the percent change index is, like the JPM stock, up again. On the other side the Vola Return Index is still down, due to the rising volatility in JPM.

Vola Return Index – Ranking

Lets put this to a test and rank the 30 Dow Jones industrial stocks according to the percent return index and using my Vola Return Index as a comparison, calculated since 01/01/2015.

The first three stocks are the same, they got the highest vola and highest percent return. But JPM and Visa would get a different sorting. Just see how low the JPM Vola Index is, it would not be the 4th best stock.

Percent returns says JPM and Visa are abou the same, only the Vola Return Index shows that VISA would have been the better investment vehicle compared to JPM. But see for yourself on the chart…


Make sure your indicators show what you actually can do on the market. There is no use in just showing the percent gains of a stock if you trade some kind of VAR adjusted trading style.

Keeping you risk under control is one of the most important things in trading, and using the Vola Return Index instead of just plotting the percent performance can give you some key insights and keep you away from bad investment vehicles. Also have a look at this stock picking portfolio based on similar ideas.


Tradesignal Equilla Code for Vola Return Index:



EEX Phelix Base Yearly – Buy Wednesday, short Thursday?

When it comes to simple trading strategies, the day of the week is surely one of the best things to start with. That’s nothing new when it comes to equity markets. Everybody knows about the calendar effects, based on when the big funds get and invest their money. I do not know about any fundamental reason for the day-of-week effect in German power trading, but is seems to be a fruitful approach.

First of all I have to point out that it is not only the day of the week which is important. A strategy that just buys on Wednesdays and sells 1 or 2 days later would be doomed. But if you add a little filter which confirms the original idea, you will end up with a profitable trading strategy.

This filter will just be a confirmation of the expected move: If you suspect that Wednesday ignites a bullish movement, then wait until Thursday and only buy if the market exceeds Wednesdays high. Same for the short side, wait for a new low before you enter!

Have a look at the chart. The strategy shown buys on Thursdays if Wednesdays high is exceeded. The position is closed 2 days after the entry.

If you run a simple test which day of the week is the best to get ready for a long trade the day after then the next chart shows the return on account of the strategy using data from 2012 up to now: (exit one day after entry)

Continue reading

Digitale Stochastic

Die slow stochastic ist ein alter Begleiter für alle Trader. Zuverlässig zeigt dieser Indikator die Überkauft und Überverkauft Bereiche an. Doch leider hat der Indikator einen entscheidenden Nachteil – er hat einen sehr unruhigen Kurvenverlauf.

Stochastic Digital – mehr als nur Überkauft / Überverkauft


Die Digitale Stochastic glättet die normale Stochastic nicht nur, sie sorgt mit einer digitalisierung auch für einen ansprechenden Kurvenverlauf.

Hier ein Beispiel für den DAX Future im Stundenchart.

Digitale Stochastic DAX Stunde

Unter der digitalen Stochastic sehen Sie die altbekannte slow Stochastic mit der selben Parametereinstellung. Der Chart ist grün gefärbt wenn die digitale Stochastic steigt, ansonsten ist der Chart rot hinterlegt.

Digitale Stochastic Trading

Continue reading

Ichimoku Scanner

Der Ichimoku Kinko Hyo ist in Japan einer der beliebtesten Indikatoren. Es ist ein Indikator der Informationen über Trendrichtung und Trendstärke kombiniert.

Zudem gibt er schon heute seinen zukünftigen Wert an. Damit ist er ein Unikum unter den Chart Indikatoren.


Karin Roller Ichimoku Analyse

Wie dieser großartige Indikator interpretiert wird, habe ich hier aus der gestrigen DAX Tagesanalyse von Karin Rollers Webseite kopiert. Sie definiert im Wesentlichen 5 Kriterien nach denen der Ichimoku Indikator zu bewerten ist.

Ichimoku Scanner

Anhand dieser 5 Kriterien habe ich einen Oszillator entwickelt, der ihnen auf einen Blick zeigt, wie der Ichimoku Indikator aktuell zu interpretieren ist.

Dreht man die Logik dieser 5 Ichimoku Kriterien um, erhält man einen Oszillator der immer zwischen -5 und +5 pendelt. (Den Tradesignal Code dazu finden Sie am Ende des Artikels)

Neben dem absoluten Wert des Indikators ist natürlich auch seine Richtung von Interesse.  Sehen Sie am nächsten Bild, wie selbsterklärend die Interpretation dieses Ichimoku Oszillator ist.

DAX Ichimoku Chart

Aktuell steht der Oszillator, wie auch Karin Rollers Ichimoku Analyse, auf plus 5 – alles bullish.

Ichimoku DAX Scanner

Continue reading

Opening Range Breakout

Das Opening Range Breakout System wurde im Magazin “Technical Analysis of Stocks&Commodities” im Juli 1994 besprochen, und wie es scheint, funktioniert es, zumindest ohne slippage uns Speasen, noch immer.

Ein Opening Range Breakout System von Perry Kaufmann.

Es wurde im Magazin “Technical Analysis of Stocks&Commodities” im Juli 1994 besprochen, und wie es scheint, funktioniert es noch immer. (ohne slippage) Auch Tony Crabel schrieb zu diesem Opening Breakout System im selben Magazin

Das System wartet die erste Handelsstunde ab und geht dann bei Erreichen eines neuen Hochs oder Tiefs  long oder short.  Die Einstiegs Order (Stop Buy / Stop Sell) wird nicht exakt auf das Hoch / Tief gelegt, sondern ein paar Punkte darüber /darunter. (hier 20 Ticks)

Tradesignal Programmierung des Opening Range Systems

Durch das laden von drei Zeitreihen, 10min, Stunden- und Tagesdaten gestaltet sich die Programmierung sehr einfach. Dies schränkt jedoch die Flexibilität deutlich ein.

Prinzipiell ist die Strategie der Afternoon Trader Strategie sehr ähnlich, sie weist auch mehr Flexibilität in der Programmierung auf. Auch der Artikel über Range Breaks im intraday Markt basiert auf einer ähnlichen Idee.

TSM(S) 1st hour breakout detail

Da die hier vorgestellte Systemversion  ursprünglich für dieTradestation 2000i in Easy Language geschrieben wurde, ist das Laden von 3 Zeitreihen ein wenig kompliziert gelöst. Aber es funktioniert.

Strategie Backtest mit adjustiertem DAX Future:

TSM(S) 1st hour breakout backtest

zum Opening Range Tradesignal Equilla Code Passwort “code”