# Scanning for Support and Resistance Probabilities

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

# Backtesting Market Volatility

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?

## Backtesting volatility

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

# Demystifying the 200 day average

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

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.

# KVOL Volatility part 2

How to calculate volatility based on the expected return of a straddle strategy has been shown in part 1 of fair bet volatility KVOL.

## Using and Displaying K-Volatility:

KVOL uses the given amount of historic returns to calculate an expected value of an at the money put and call option. The sum of these prices are the historic fair value for implied volatility. It can be used to compare current market implied volatility to historic fair values.

Beside calculating KVOL for a specific return period it can also be used to show it as a projection indicator on the chart.

The example on the chart gives such an expectation channel for the s&P500 at the beginning of each month. The 250 days before are used to calculate KVOL. The line underneath the chart is running KVOL for 13 trading days. Continue reading

# 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.

# Position sizing – the easy way to great performance

Working on your position sizing algorithm is an easy way to pimp an existing trading strategy. Today we have a look at an energy trading strategy and how the position sizing can influence the performance of the strategy.

The screenshot shows you the returns of the same trading strategy, trading the same markets, the same time frames and using the same parameters. The returns on the left side look nice, making money every year. The returns on the right side are somehow shaky, and you would have to love volatility of returns if you would think about trading this basket. The only difference between the basket on the right and on the left side is the position sizing.

The basket trades German power, base and peak (yearly, quarterly, monthly), coal, gas, emissions. All instruments are traded on a daily and weekly time frame chart, using the same parameters. If the daily trading uses a 10-period parameter, the weekly trading would use a 10-week parameter. This limits the degrees of freedom I have when doing the strategy-time frame-parameter merge, thus minimizing the curve fitting trap.

# 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.

# 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)

# 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.

# EUR/USD Zyklus Analyse: Ende des Abwärtstrends?

Der EUR/USD kannte seit September nur eine Richtung: nach unten. Doch dies könnte sich jetzt ändern.

## John Ehlers Zyklus Analyse:

Der John Ehlers Corona Cycle Indikator, hier als Tradesignal Indikator verfügbar, deutet auf ein baldiges Ende des Abwärtstrends hin. ( Achtung Wochenchart!)

Dieser Indikator gibt einerseits die Länge des dominanten Marktzyklus an: Im aktuellen Fall beträgt dieser 20 Wochen.

Der Indikator darunter gibt die Position innerhalb des Zyklus an. In Trendphasen wird diese Zyklus Komponente des Marktes zwar durch den Trend überdeckt und ist nicht so klar zu sehen, fällt der trend jedoch weg und der Markt befindet sich in einer Seitwärtsphase, dann kommt die Stärke dieses Zyklus Indikators voll zum tragen.

Wie sieht es aktuell im EUR/USD aus?

Einerseits nähert sich der EUR/USD seinem bisherigen Tief bei 1.04\$, was an sich schon als starker Widerstand gewertet werden kann.

Zudem nähert sich der Zyklus des EUR/USD seinem Tief. Für Anfang Dezember sagen die Ehlers Indikatoren das Zyklustief des EUR/USD voraus;

Und nun müsste sich der EUR/USD schon ganz gegen alle Chartgesetze verhalten damit sein Widerstand bei 1.04\$ nicht zumindest kurzfristig hält. Aber als Spekulant setze ich lieber auf das wahrscheinliche Ereignis…

Handelsempfehlung an alle Shorties: Position absichern, bei 1.05\$ Teilausstieg mit Gewinnmitnahme.

EUR/USD John Ehlers Corona Chart Cycle Analysis – weekly timeframe

# DAX Marktbreite und 200 Tage Linie

Bald ist es wieder so weit und der DAX steigt über seine 200 Tage Linie. Das wäre an und für sich nichts Besonderes, steigt oder fällt der DAX doch jeden Tag über irgendeinen gleitenden Durchschnitt, doch ist die 200 Tage Linie etwas besonders an sich: Sie ist ein selbst erfüllender Indikator!

## Bankberater, Bild, Hausfrauen

Wenn jemand eigentlich nichts über technische Analyse weiß, die 200 Tage Linie kennt er. Jeder Bankberater versucht damit seine Aktien zu verkaufen; Wenn der Markt über der 200 Tage Linie liegt soll das  ein bullishes Signal sein.

Und in der Tat, da jeder diesen Indikator kennt, ist es tatsächlich ein bullishes Signal wenn der Markt über seiner 200 Tage Linie liegt, schlussendlich trauen sich dann alle die fast nix von technischer Analyse wissen in den Markt.

## DAX Marktbreite

Um zu sehen ob so ein Schnitt des DAX über die 200 Tage Linie auch signifikant oder nur ein Strohfeuer ist, kann man die Marktbreite des Index untersuchen.

Marktbreite=Wie viel % der Aktien eines Index liegen über der 200 Tage Linie

Diesen Indikator sehen Sie unter dem DAX Chart abgebildet.

Allgemein gilt für die Interpretation, dass wenn der DAX über der 200 Tage Linie liegt und mehr als 50% der Aktien des DAX ebenfalls über der 200 Tage Linie liegen, man trendfolgend vorgehen kann. Wenn dann einmal 100% der Aktien über der 200 Tage Linie liegen ist die Blase meist zu Ende und man sollte die Position mit einem engen Stop absichern.

# Reality vs. Robert W. Colby, CMT

## Dont`t believe!

Papier ist geduldig, darum ist es oft besser wenn man selbst testet bevor man ein veröffentlichtes Handelssystem mit seinem Geld ausprobiert. Heute geht es hier um einen Handelssystem out of sample Test

Ein schönes Beispiel dafür ist eine Strategie aus Robert Colbys Buch “The Encyclopedia of Technical Market Indicators“, 2nd edition, 2003, page 791ff.

Darin wird ein einfaches moving average crossover Systeme vorgestellt, welches anscheinend seit beinahe 100 Jahren phänomenale Gewinne verspricht.

Hier eine Kopie aus dem Buch: