# 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 math and statistics.

### Scatter Charts

A scatter chart is a simple to read chart style to see the correlation between two input values. A regression line on the scatter chart gives you a visual idea if the two securities are positively or negatively correlated, the “cloud structure” of the scatter points tell you if this correlation is tight or loose.

This sample scatter shows the correlation between the DAX and DOW levels, and it can be easily seen that these two markets are tightly correlated in a positively way.

The horizontal scale is used for the second security (dax), the vertical scale is used for the first security (dow). This chart type is predefined in Tradesignal, just drag&drop it onto the securities on the chart and select the right amount of data to get the analysis you want to see. (eg. 2000-now). If you see a tight and positive correlation like on the chart above, It migt be used to select the instrument you want to trade. If market A is easier to predict than market B, select A.

### Scatter on Indicators

Although a scatter chart is usually used to show the correlation between two markets, it can also be used to show the correlation between two indicators.

The chart above shows the correlation between digital stochastic and momentum. Have a look at the clustering of points in on the right side of the scatter, a high level in digital stochastic usually goes with a high momentum. This insight enables you to get rid of momentum, as digital stochastic is easier to read than the shaky momentum. Less indicators = less parameters = less curve fitting.

### Scatter prognosis

Doing this analysis and getting rid of parameters is great if you want to minimize the dangers of curve fitting, but it does not tell you if your indicator is of any use at all, when it come to describing tomorrows move of the market. Surely it is valuable insight that a high level of stochastics corresponds to a high momentum, but does a high momentum today also mean that the market will move up tomorrow? And this question about tomorrow is the key question I ask myself when searching for some edge.

To get a glimpse on the prognosis quality of an indicator we will have to add some colour to our scatter chart. This colour tells me what the market has done after a specific indicator level has been reached. Green for an up move, red for a down move, black for not decided by now.

This chart shows the prognosis quality of the stochastic indicator. The left chart shows the 1 day prognosis of a 5 day stochastic, the right chart gives you the 5 day prognosis of a 21 day stochastic. Observe the clustering of the red and green dots. (black for not decided by now) As you can see on the left chart, the one day prognosis using a 5 day stochastic is not the thing to do. Regardless if stochastic is high or low, you get a nice mixture of red and green dots. This means the market, at a given stochastic level, sometimes moved up, sometimes moved down. Not this behaviour is not very useful for trading. Only in the extreme, near 0 and 100, this indicator seems to implicate a bearish next day movement.

The right chart, showing the longer term prognosis of a long term stochastic seems to be more useful. High levels of the indicator also show positive returns on the 5 days after, unfortunately you can not reverse the logic, as low indicator levels give a rater mixed prognosis. This visual analysis can give you an idea which areas of the indicator might be useful for further analysis.

A one dimensional analysis like on the chart above could also be done without this scatter chart. Going from one dimension to two dimensions is more useful, as it directly can be translated to do a kNN machine learning trading strategy. Have a look at the following chart. It shows the scatter of two indicators and the implication on the next days market move.

Lets start with he right chart. As you can see the red and green dots are evenly distributed, meaning there is no useful correlation between the used indicators and the movement of the market on the day after. If you would use a kNN algorithm with these two indicators, I would bet it would not return great results. Even if you would get a positive return, it might just be a lucky hit or curve fitting.

The opposite is true for the chart on the left. Here you can see some nice clustering of the red and green dots. Low indicator levels seem to predict a bearish move, high indicator levels result in a bullish move on the next day. A distribution like this is the perfect starting point for investing some time in a kNN machine learning  trading strategy. The kNN algorithm would give you a strong prognosis with high or low indicator levels, and most probably only a weak or no prognosis when the indicators are around 50. The returns will be stable, no curve fitting problems should be expected.

### Conclusion

Using a scatter chart can give you a nice visual indication if your indicator might be useful for prognosing the next days market move. This is valuable insight, as you can see the whole data universe with one glimpse, even before you do a thoroughly statistical analysis. Numbers can deceive you, pictures usually tell the complete story.

# Using Autocorrelation for phase detection

Autocorrelation is the correlation of the market with a delayed copy of itself. Usually calculated for a one day time-shift, it is a valuable indicator of the trendiness of the market.

If today is up and tomorrow is also up this would constitute a positive autocorrelation. If tomorrows market move is always in the opposite of today’s direction, the autocorrelation would be negative.

### Autocorrelation and trendiness of markets

If autocorrelation is high it just means that yesterdays market direction is basically today’s market direction. And if the market has got the same direction every day we can call it a trend. The opposite would be true in a sideway market. Without an existing trend today’s direction will most probably not be tomorrows direction, thus we can speak about a sideway market.

### Autocorrelation in German Power

But best to have a look at a chart. It shows a backward adjusted daily time series of German Power.

The indicator shows the close to close autocorrelation coefficient, calculated over 250 days. You will notice that it is always fluctuating around the zero line, never reaching +1 or -1, but let`s see if we can design a profitable trading strategy even with this little bit of autocorrelation.

### The direction of autocorrelation

Waiting for an autocorrelation of +1 would be useless. There will never be the perfect trend in real world data. My working hypothesis is, that a rising autocorrelation means that the market is getting trendy, thus a rising autocorrelation would be the perfect environment for a trend following strategy. But first we have to define the direction of the autocorrelation:

To define the direction of the autocorrelation I am using my digital stochastic indicator, calculated over half of the period I calculated the autocorrelation. Digital stochastic has the big advantage that it is a quite smooth indicator without a lot of lag, thus making it easy to define its direction. The definition of a trending environment would just be: Trending market if digital stochastic is above it`s yesterdays value.

### Putting autocorrelation phase detection to a test

The most simple trend following strategy I can think about is a moving average crossover strategy. It never works in reality, simply as markets are not trending all the time. But combined with the autocorrelation phase detection, it might have an edge.

Wooha! That`s pretty cool for such a simple strategy. It is trading (long/short) if the market is trending, but does nothing if the market is in a sideway phase. Exactly what I like when using a trend following strategy.

To compare it with the original moving average crossover strategy, the one without the autocorrelation phase detection, you will see the advantage of the autocorrelation phase filter immediately: The equity line is way more volatile than the filtered one and you got lots of drawdowns when the market is sideways.

### Stability of parameters

German power has been a quite trendy market over the last years, that`s why even the unfiltered version of this simple trend following strategy shows a positive result, but let`s have a test on the period of the moving average.

Therefore I calculated the return on account of both strategies, the unfiltered and the autocorrelation filtered, for moving average lengths from 3 to 75 days.

Return on account (ROA) =100 if your max drawdown is as big as your return.

The left chart shows the autocorrelation filtered ROA, the right side the straight ahead moving average crossover strategy. You don`t have to be a genius to see the advantage of the autocorrelation filter. Whatever length of moving average you select, you will get a positive result. This stability of parameters can not be seen with the unfiltered strategy.

### Autocorrelation conclusion:

Trend following strategies are easy to trade, but only make sense when the market is trending. As shown with the tests above, autocorrelation seems to be a nice way to find out if the market is in the right phase to apply a trend following strategy.

# 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…

### Conclusio

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.

# NASDAQ 100 long term candlestick scanner

## A short update on the long term Candlestick Scanner.

The Candlestick Scanner scans the Nasdaq 100 stocks for long term bullish or bearish reversal patterns.

The basic idea is to search for hammer and hanging man candlestick patterns. Usually these patterns work nicely on daily charts. My Candlestick Scanner searches for these two patterns on every time frame, from a 1 day per bar compression up to a  250 days per bar compression. This enables me to use a simple, well defined and documented pattern as a description of short to long term reversal setups.

But see for yourself which Nasdaq stocks seem to change the direction according to the long term Candlestick Scan. The list gives you the duration of the reversal formation (expect about the same time to either reach the target or get stopped out) The detected pattern becomes a valid entry signal if a new high (hammer) or low (hanging man) is established.

Bullish reversals on the left side, bearish reversals on the right side.

# NASDAQ Stock Scan

A short update on my long term candlestick scan.

It candlestick scan scans the Nasdaq 100 stocks for long term bullish or bearish reversal patterns. The basic idea is to search for Hammer or hanging man candlestick patterns, but not only on a daily chart, but on any compression, from daily to yearly compression (Yes, that’s one year of data per candle, the resulting reversal pattern would be valid for at least 3 years)

But see for yourself which Nasdaq stocks seem to change the direction according to the long term candlestick scan. The list gives you the duration of the reversal formation (expect about the same time to either reach the target or get stopped out)

Bullish on the left side, bearish on the right side.

Interview

# “Automate the search for promising assets”

The use of trading systems means, among other things, that more markets and smaller time levels can be considered with the same team. The higher trading frequency and diversification into more markets and time levels will in turn lead to better performance and reduced risk for the investor. Philipp Kahler von Tradesignal chatted at the 143rd Hedgework from the sewing box of a technical analyst. He answers the most important questions here.

HEDGEWORK: Mr. Kahler, you represent the quantitative side of portfolio management. Has fundamental analysis become obsolete?
Philipp Kahler: Quantitative analysis deals with the creation of investment rules, which are so clearly defined that you can even teach them to a computer. Whether these rules are based on price or fundamental data is the same. The only important thing is that you can test the rules and regulations in a meaningful way and that the result is convincing.

HEDGEWORK: What are the advantages of technical analysis?
Kahler: Compared to fundamental data, technical indicators have the advantage that they are available in real time. It is not the distributions in the last quarter that are decisive, but rather what the market is doing today. My market-to-market result is then also evaluated on the basis of current prices. Whether the technical indicators are better than the fundamental analysis indicators is unclear, but as a trader, the most important thing for me as a trader is to have my risk under control NOW – and that’s easier with technical analysis.

HEDGEWORK: In your presentation, you talk about the transition from technical to evidence-based technical analysis. What’s behind it?
Kahler: I mean quantitative models that make use of classical technical analysis in the toolbox. Indicators and simple price patterns are ideal for searching markets for opportunities. However, even the best technical analysis indicator alone will hardly justify a successful trading approach. The combination of several indicators, perhaps even combined with pre-screening by fundamental analysis – this is the best basis for creating a stable, quantitatively controlled portfolio.

HEDGEWORK: In which areas are quantitative systems particularly useful?
Kahler: If the holding period of a position is somewhere between five minutes and two weeks, then there is no way around technical analysis. If your holding period is between two weeks and several months, the technical analysis will at least provide you with valuable services for timing your decisions. What you do is not decisive.

HEDGEWORK: Quantitative systems can, in a first step, bring structure to investment decisions?
Kahler: Yes, you can automate the search for promising values, improve the timing of trading activities, and you will also see an improvement in the delivered performance by avoiding emotional decisions.

HEDGEWORK: What role do FinTechs and Robo Advisor play? Has their increased market presence already made a significant difference?
Kahler: Yes and no. Of course, flash-crashs are caused by the increased use of machines, but if you look at the Dow Jones for more than 100 years, you will soon find that the market hasn’t changed. The daily/weekly/annual volatility has been almost constant for more than 100 years. These new technologies have the strongest influence not on market behaviour, but on the business model of traditional asset managers.

HEDGEWORK: What added value can an investor expect from a quantitatively controlled portfolio?
Kahler: One advantage is that the use of trading systems means that more markets and smaller time levels can be viewed with the same team. The higher trading frequency and diversification into more markets and time levels will then lead to better performance and reduced risk for the investor.

HEDGEWORK: Could you please describe how you proceed with a new product offering or a new investment strategy?
Kahler: This can be done in two ways. Either I have a trading system that I am convinced of. I then look for all the markets in which it functions and combine them into a quantitatively managed portfolio. Or I get a market given. Then I try to develop systems that work without adapting the parameters, e. g. in the hour/day and week range. Several such approaches are then combined to form a portfolio.

HEDGEWORK: Backtesting is an essential part of a product launch. These are sometimes not very reliable in retrospect. What is important to note here? What are the pitfalls?
Kahler: The baking test is not the problem. The adaptation of the strategy to the market – the parameterization and weighting of the individual components of the trading system – is critical. Since only a few adjustment screws lead to a high degree of adaptability of the trading system, there is a high risk that one adapts too much to past data, called curve fitting, without the system’s set of rules really saying anything decisive about the market.

HEDGEWORK: What method do you propose for testing the robustness of a strategy?
Kahler: On the one hand, you can first test the stability of the parameters. If a system includes the 200-day line, then it should work roughly as well with the 150-day and 250-day line. In a further step, the system must then be tested with unknown data. If a trend-following model works in Germany, for example, then it should not fail in the USA either. And finally, you should let the system disappear in the drawer for half a year and then check again to see if the real-time results were as expected.

HEDGEWORK: Maybe we can take a little more look at your sewing box. What practical tips can you give prospective quants?
Kahler: It’s easy: Learn to trade! Without a computer, with real money, so losses really hurt. Even though studying science is an advantage, I do have the experience that traders who are not blinded by numbers because of their own experience will eventually develop the more stable systems.

HEDGEWORK: Finally, perhaps a glimpse into the future?
Kahler: Computers will take on more and more tasks, the worldwide availability and comparability of brand names will in many cases make brand names unimportant. Investors no longer ask for a certain fund, but want to invest their money with manageable risk and limited correlation to other markets. Whether an algorithm or an analyst does this is information that will not reach the investor at some point. Since the computer often delivers better performance and is paid less than the classic fund manager, it doesn’t take much imagination to estimate future developments.

The interview was conducted by Ronny Kohl, automatic translation by DeepL

Vita:

Philipp Kahler is Senior Quantitative Analyst at Tradesignal Ltd. and advises financial institutions and energy trading companies on the development of quantitative-based trading strategies. He gained professional experience as a trading system developer in proprietary trading at Berliner Landesbank. There, he managed a wide range of very successful, systematic trading systems for several years.

Interview

# “I believe in self-fulfilling prophecy”

Algorithmic trading is often surrounded by the nimbus of mysterious and impenetrable. But with the right tools and methods, the opportunities and risks of automated trading strategies can be exploited. Philipp Kahler, Senior Quantitative Analyst at Intalus Group, showed the way to systematic investment at the 120th Hedgework in Frankfurt.

Philipp Kahler,
Intalus Group
Hedgework: Mr. Kahler, in short: What is Algorithmic Trading?
Philipp Kahler: Algorithmic Trading is trading with pre-defined and tested rules. The rules can come from higher mathematics, where game theory has its roots or is based on technical analysis.

Hedgework: Why should institutional investors focus on technical analysis and algorithmic trading?
Kahler: The technical analysis displays information quickly and clearly. Contrary to this are the many investment recommendations in the subjunctive; that the stock XY next week should be bullish for the reasons and could reach a new high. Then a purchase might be advisable. The rule-based technical analysis does not dare to speculate. The software simply pings when a situation arises that is in line with the rules. In real time, and not maybe and next week.

Hedgework: How does it work?
Kahler: I like to program rule-based strategies with indicators and chart patterns. One or two classical indicators define the market phase, a chart pattern or an oscillator signal then gives the final GO for entry. The position is then hedged by a sales and time stop. If nothing happens or if it goes wrong, the position is closed. Any accumulated profits and any counter-signals then lead to new exit instructions for the following day at the end of the day.
So I’m not trying to predict what might happen tomorrow, but my algorithm contains a number of rules for scenarios that stand for and against my position. Just as an emotionless and deliberate professional would do.

Hedgework: What indicators do you look for?
Kahler: I like to use classics such as moving averages, Directional Movement Index, Parabolic or ADX for trend determination. For entry or exit, significant high and low points, candlestick formations, oscillators. Generally speaking, I use indicators that other traders use, but I don’t always use them in the classic way. And I believe in self-fulfilling prophecy (laughs).

Hedgework: Why do you use technical analysis to develop algorithms?
Kahler: Technical analysis shows me how the others see the market. One can now argue whether the markets are efficient and whether every available information is reflected in the price, but this is a theoretical discussion. In practice, I see that other traders use technical analysis to determine entry and exit. And I don’t want to ignore that information.

Hedgework: You are thus betting very heavily on the right time to buy and sell. The latest research is more in the direction that market timing is not possible or does not bring anything.
Kahler: Let’s assume this hypothesis is correct. Timing is not possible. Then the movements of the markets are a purely random walk. Yesterday’s events have no influence on today’s events. And this is clearly contradicted by every insight into one’s own experience and behavioral finance. Yesterday influences how we think and act today. And that gives me the foundation of technical analysis.
If the market then falls by 20 percent in one day and they don’t stop because timing doesn’t work, they can do so tomorrow at -30 percent. Or write an article about why this was the right thing to do at that time, as the market is now back to baseline again.

Hedgework: How can the market universe be searched for promising values using algorithms?
Kahler: Define promising! Values that have been in trend for a long time and for which you hope that they will rise for a few more days? Or values that are at least 75 percent below their high and now trade at twice as much volume as a year ago? Values where a reversal pattern has occurred today that every retailer knows?
The beauty of scanning the markets is that you can find out from thousands of values exactly those that meet your own rules.

Hedgework: You compare the values at different time levels. What is the reason for or statement can the user draw from the comparison?
Kahler: I think that mass psychology works best where there are masses. So, if only the people who see a candlestick pattern on the 60-minute chart come into this market, then the following movement will probably not be so great. However, if the same candlestick pattern appears on the weekly, daily and 60-minute charts, there is likely to be more movement as more traders are involved. Since this is not easy to find, I have to rely on automated scans of my software. Manually looking for these scenarios would degenerate into work.

Hedgework: Be long when the chart is green and short when it is red. That sounds trivial. Is that really it?
Kahler: When the pedestrian lights switch to green, do you walk blindly across the street? Or maybe you want to check again if there is no car coming?
Same with one of my red-green models. The colour is comparable to the traffic light. The second step is to confirm the trend with a new high or low. Then there is also the question of positionsizing and risk management. All these are simple building blocks that combine to form a rather complex trading model.

Hedgework: Is this approach also suitable for institutional investors who do not have a large investment team?
Kahler: Technical Analysis is a useful tool for this type of analysis. It allows me to automate a lot of things, such as scanning markets and baking strategies. Automatically generated trading signals and alarms are then the mechanical assistants that enable the Portfolio Manager to monitor a universe of markets and strategies in a short period of time. Fortunately, the software industry has reached the point where there is hardly any need for dedicated programmers, but at least the first prototype can be created by the dealer himself.

Hedgework: In volatile markets in particular, this sounds like a lot of reallocations and transactions and transaction costs. This is at the expense of performance. What is your experience?
Kahler: But in volatile markets, however, there are also the best opportunities. If the markets move, money can be earned well.
However, the cost of reallocations and the associated work involved are clearly an important criterion in system development. The number of transactions can be adjusted by selecting the time levels and trading approaches in such a way that it can be done with the given trading team.

Hedgework: How long is the average holding period?
Kahler: If it goes wrong, it only takes a few seconds. In my strategies, however, I usually work several days to weeks.

Hedgework: Does the approach also work at portfolio level?
Kahler: It works particularly well at portfolio level thanks to diversification. It is almost impossible to achieve a steady performance with only one traded value. However, if I am dealing with a universe of non-correlated values, then continuous performance is possible with relatively simple strategies.

Hedgework: How do you determine the optimal position size in a portfolio?
Kahler: I risk the same amount per trade, depending on the planned trading frequency and within certain limits for the invested capital. The various systems are also weighted according to the volatility of the results.

Hedgework: What happens to the money that does not flow into the stock market due to negative signals?
Kahler: No absolute return approach will always be invested. That is why it makes sense – irrespective of the investment issue – to be active in several markets and time levels. Cleverly chosen, with little correlation to each other, the investment ratio then remains fairly constant and the problem is eliminated.

Hedgework: What is the equity/bond ratio in a portfolio? Does the stock market always have priority?
Kahler: No, no, not just stocks or pensions. Absolute return means that at the end of the year you want to see a certain return at a given risk. It is not known which market this will bring me in the future. Surely the Bund Future has been good at trend-following strategies in recent years, but what about next year? Perhaps the return on investment then comes from oil, gold or other sources. That is why the idea is to search markets for certain rules and then act where the traffic lights turn green.

Hedgework: In which market environment does this approach work best and where not?
Kahler: I like working with trend-following strategies. They are easy to develop and implement on the market. In order to ensure that the yield is right, the trends should not be too small, both in terms of time and volatility. And this is where the scanning method comes into play again. I have to look for the markets and time levels in which the markets meet my criteria. Or I need to have a switch for another strategy, one that works well in sideways markets.

Hedgework: How do you deal with black swans and chance?
Kahler: There’s not much you can do about a real Black Swan within the trading system world. After all, by definition, it is a risk that has not been known to date or has been completely misinterpreted. Only a strategy outside the stock market can help.
But all the market shocks that have occurred in history must be looked at very carefully. Not only on the chart, but best in conversation with participants. It doesn’t look so wild on the chart, but when you see how everything else goes wrong on such days, you don’t automatically invest everything in a market-system combination.

Kahler: It’s my strategy. I developed it according to my convictions and it does what I would do by hand. This doesn’t have to be any better than all the other strategies on the market, but the trader’s psychology also comes into play in system trading. If you don’t believe in your strategy, you leave it at the first setback and then you’re not in the good phase. A good system only makes losses – simply because it is used in the wrong environment or by the wrong dealer. My advice: always be honest with yourself. The rule-based technical analysis supports this, as it leaves no room for interpretation.

The interview was conducted by Alexander Heintze, translated by Deepl Übersetzer

# Sutton’s law: Go where the money is

There is an apocryphal story about the famous american bank robber and jail breaker William Sutton being asked why he was robbing banks. His genius answer was “That`s where the money is”.

There is a second famous quote of William Sutton, asked why he used a machine gun for robbing a bank: “You can’t rob a bank on charm and personality,” Both quotes come up to my mind when I am asked about the key things in trading.

### Sutton’s law #1: Go where the money is

I am a trend follower, just because it is easier to do than picking tops or bottoms. Robbing a bank might not be a good idea, but going where the big money is, certainly is. Big money is invested over a long time, markets are just not liquid enough so that pension funds and other big players could switch their position every day, so once a trend, or call it bullish market environment, is established, chances are great that people come in, stay in and fuel the further movements. It becomes a self fulfilling prophecy. That`s where the money is, that`s where I can do my day-to-day small scale market robbery.

### Sutton’s law #2: You can’t rob a bank on charm and personality

Sutton’s law #2 is my reason for being an algorithmic traders. The market basically is a fight of everybody against everybody, all weapons and tricks allowed (well, there have been some regulations introduced..) It would be suicide to risk your money on just your charm or personal beliefs. If there is big data available, use it. If you got an algorithmic trading software available, use it. If you lose, don`t blame the market, blame yourself for not being prepared.

# Monthly Seasonal Performance of Stocks

Seasonality changes over time!

First have a look at a screenshot of one of my favorite website investopedia.com They have some nice articles about the seasonal performance of stocks and the effects in trading. But unfortunately the information is not precise, and therefore misleading.

The chart shown suggests that the average return for the S&P500 (index or stocks?) has been positive, except for September. Further down they speak about the January effect, suggesting an average positive performance of stocks in January.

# Bitcoin – end of the bullish bubble

Bitcoin has come a long way but now it is time to say good bye.

Being a trend following trader on the long side, the chart right now suggest anything else but a trend following long strategy. It might all look completely different in a few weeks or months, but right now the bitcoin market is done. The ichimoku scanner indicator still shows 100% bullish, but have a look at the history and the formed indicator-market patterns:  As marked on the chart we can see a nice bearish divergence. This is not a long entry signal!

Lower highs, lower lows; goodbye bitcoin, loved to trade you, but with a bearish behavior like now you are not my friend any more.

# The rhythm of the market

Usually we chart the market at it’s absolute level. But what, if we would just chart the net daily, weekly, monthly movement? Would this be an advantage? Would this show us new trading opportunities?

The short answer is: Yes! The trend is not everything, and it seems to be of some significance for further movements, if the market has moved more than x % from the beginning of the day, week or month.

But let’s have a look at some charts – and you will see how well it works:

The first chat is an intraday chart of EuroDollar, 8am-5pm CET. It shows you the daily net movement.

# STA – Society of Technical Analysts

I am happy to announce that Trevor Neil will be presenting my “VIX Timing for SP500” at the next STA meeting in London.

Meetings & Events

I wrote the strategy for the IFTA conference in Tokyo and published it on this site It performed well, and now it is on Trevor to use it for educational purposes and spread the word about the advantages of algorithmic trading.