# Protected: Factor investing in portfolio management

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This article is about the dollar cost averaging investment strategy and the influence of luck in it.

To invest parts of your income into financial markets has been a profitable approach, especially in times when bond yields are low. One approach to do so is the dollar cost averaging investment strategy. Continue reading

Since S&P500 has lost 20% from its top in 2018 and everybody is talking about bear markets. See what has happened in history.

We all have been spoiled by artificially low volatility over the last years.

Now people blame the gone-wild president or algorithmic trading for the market correction, but let us have a look into history to see how common market corrections have been over the last century. Continue reading

Analysing the market performance of the day session vs. the overnight movement reveals some interesting facts.

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

Gentrification has got a new victim; After 33 years my favourite pub in Berlin, Syndikat, has been kicked out by unethical investment company Pears Global Real Estate, run by the family patriarch Mark Pears. 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

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.

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

Markets have a high degree of randomness (and madness), but there are some things which hardly change over time. One is the width of an average market move before a counter-move can be observed. 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.

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 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

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.*

*(Kenny Rogers)*

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.

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.

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

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

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 kvol–fair 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

*“Tomorrow never happens. It’s all the same fucking day, man. ” Janis Joplin*

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.

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.

We are all familiar with oscillators like the RSI indicator. It gives an idea if the market is oversold or overbought. Continue reading

The markets will go up and down, and usually it’s not my business why they do it, I am just interested in making my luck with a position on the right side of the trade. 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.

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.