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
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 https://www.optionstrategist.com/calculators/free-volatility-data 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
Volatility trading: when to buy and when to sell volatility
You got to know when to hold ’em,
Know when to fold ’em,
Know when to walk away,
And know when to run.
When to sell implied volatility
Volatility is a nicely reverting time series. If it is high chances are good that it will come down again. The only problem is to find out when volatility is high, and when it is low. Unfortunately there are no absolute levels, you can’t say that 50% implied volatility is high, as this specific stock might have an implied volatility of 80% most of the time. So you can only compare the current volatility level to historic levels and so define if volatility is currently high or low. Continue reading
The Hindenburg Omen is an indicator which is believed to forecast market crashes. Unfortunately it does not work, but the idea behind this indicator is worth to be discussed.
Market Breadth – Hindenburg Omen
The Hindenburg Omen is a market breadth indicator. It describes how correlated stocks are within a market behave.
I already had a market breadth indicator in this blog a long time ago, the percentage of stocks within a market above the 200 day average. The Hindenburg Omen does not use moving averages, it is based on the number of new highs and lows in the market.
Hindenburg Omen: idea and calculation
To get a warning signal for an upcoming stock market crash the Hindenburg Omen indicator observes the number of stocks making new 54 week highs and the number of stocks making 54 week lows. In a strong bull market you will usually see a lot of new highs but hardly any new lows, in a bear market you will see new lows, but no new highs. Continue reading
“Tomorrow never happens. It’s all the same fucking day, man. ” Janis Joplin
Distribution of Returns
Analysing history and hoping it will somehow repeat itself is the big hope of all quantitative traders. This article is about the distribution of market returns, but not about normal distribution, Gauss and standard deviation. This article is about the visualisation of market returns and what can be learned from it.
Probability distribution diagrams show the probability of a specific outcome. How likely is it that the market will be at a specific price sometimes in the future? How does a specific bullish or bearish indicator signal affect the future market behaviour on a statistical basis? An approaching visualisation of the statistical probabilities are the best way to understand market behaviour and find your chances in trading. Continue reading
Ever since John Bollinger introduced his Bollinger Bands in the early 1980s the bands have been a favourite indicator to all technical trades. This article is about the prediction capabilities of Bollinger bands.It researches the Bollinger breakout probability.
How good are the chances to be outside or inside of the bands in the future? How do these probabilities relate to the current position the market has got relative to today’s Bollinger band? What impact has overall volatility on these statistics? These questions will be answered below.
Bollinger Bands Breakout Probability
By definition of the indicator most of of the times the market will trade inside the Bollinger band. But this is only of minor interest to me. As a trader I am more interested on what will happen in a few days from now. Where will the future market be? Shall I bet on a breakout or sell a straddle?
So I did some tests on the forward prediction qualities of the Bollinger band indicator.
For all tests I used the 20 day, 2 standard deviations setting, which is the standard setting for most charting packages. Then I analysed the positioning of the market in 20 days form now to see if Bollinger bands can be of any help with these questions. Continue reading
I have been in search for a signal I could use for a short vertical spread or naked short option strategy. So my main concern has been to find a level, which will most probably not be penetrated over the next few bars.
This is what I came up with.
Algorithmic RSI Support and Resistance Levels
We are all familiar with oscillators like the RSI indicator. It gives an idea if the market is oversold or overbought. Continue reading
If you want to trade volatility, you can place a bet on the option market. Just buy an at the money put and call, and at expiry day you will either win or lose, depending on the actual market move since you bought the straddle and the price you paid for the straddle. To put it simple, if the market moves more than you paid for the two options you will win, otherwise you will lose. This article is about a back test of volatility.
The fair price for volatility
When I look at the S&P500 I could buy or short a straddle with 16 business days until expiry right now for around 70$. That’s the implied volatility.
When I look at the standard deviation of 16 day returns, using the last 30 days to calculate it, it shows me a volatility of around 30$. That’s historical volatility.
When I use my own fair bet KVOL Volatility, it gives me a volatility of about 50$
Now I got three measures for volatility, but which one is the best prediction for future market volatility? And how big will the error (=wins and losses) be if we place this bet over and over again?
Placing an perpetual bet on future volatility using the payback profile of a short straddle will give me an idea on how good historical volatility and Kahler’s volatility was able to predict future volatility. In a perfect world this virtual test strategy should be zero sum game; if not, future volatility is either over or underestimated by these 2 indicators. Continue reading
The 200 day average is considered as a key indicator in everyday technical analysis. It tells us if markets are bullish or bearish. But can this claim be proved statistically, or is it just an urban legend handed down from one generation of technical analysts to the next? Let’s find out and demystify the 200 day moving average.
The 200 day moving average