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.
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 energy basket:
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.
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.
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.
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 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.
Bitcoin is not as bullish as it used to be. May it be due to fundamental reasons like transaction cost and slow speed, or maybe the herd found a new playground, whatever it might be, it is a good time to have a look how my bitcoin trading strategy performed.
The bitcoin trading strategy uses two moving averages for the trend detection, and, when the averages say bullish, the strategy will buy if the market moves above it`s old swing high.
The position is protected with an exit at the last swing low and a 3% trailing stop.
But have a look how this simple strategy performed over the last two years:
Trading on a daily timeframe and investing 10000€ with each entry, the strategy managed to get more than a 100% return over the last 2 years.