Overnight Risk Premium in Equity and Commodity Markets

Over the last 20 years equity markets and ETFs did a significant part of their total performance over night. This article will examine the relationship of in-session moves vs. the out-of-session moves of ETFs and commodities.

The overnight risk premium

As an investor you can expect to get paid for taking risk. If someone sell its stock to you he gets the risk free return for holding cash,  but you will have to finance the risk of the stock moving against you. This risk is quite low when the market is open and liquid, as you could always sell the stock in case of an adverse movement. But when markets are closed you have to bear a higher risk as you will be bound to your position until the markets opens on the following day.

According to this theory the market returns over night should be positive, to compensate you for the higher risk of holding a position you can’t liquidate immediately. Let’s see if there is some truth in this theory and how big the overnight risk premium might be.

Test code and data

To test the theory I took daily market data from Refinitiv and used the Tradesignal code below to sum up the percent values of daily and overnight moves.

Tradesignal overnight performance test code

Tradesignal overnight performance test code

ETFs overnight risk premium

The chart below shows the outcome of the calculation for the QQQ ETF.  As it can be seen, the good performance over the last years has happened mostly when markets where closed. Even during the financial crisis the overnight returns have mostly been positive.

QQQ overnight risk premium

QQQ overnight risk premium

 

Having a look at the distribution of returns you see quite a different behaviour on e.g. a rolling sum of 10 day or night moves. The daily open to close returns show a higher tendency for big moves than the overnight move. So from a risk perspective the day session bears more risk than the night session.

QQQ overnight returns distribution

QQQ overnight returns distribution

 

QQQ is not the only ETF showing this excess overnight performance. The overview below gives you the data. The numbers show the sum of percent moves since 2001. (starting at 100)

SPY ETFs overnight performance analysis

SPY ETFs overnight performance analysis

A look at commodities

With futures and commodities this overnight effect is not as prolonged as with equities. Sometimes it even is non existent at all.

The chart below shows the overnight and daytime performance of the German Bund future. Beside the phase from 2015 to 2017 the overnight movement did not add to the total performance.

Bund Future FGBL overnight risk premium

Bund Future FGBL overnight risk premium

 

The december future on emission certificates (chart below) shows no significant overnight movement at all.

CFI2 Emissions overnight performance

CFI2 Emissions overnight performance

German power, yearly contract, shows a strong negative overnight performance.

F1BY overnight performance

F1BY overnight performance

Implications for trading

As the overnight move has got a significant impact on the total performance of equity markets, it will also have implications on the design of a trading strategy. A first implication of this overnight effect might be that you should not be short over night in equity markets, and you might not want to open your long position at the beginning of the day.  But keep in mind, if everyone knows the trick, this overnight movement will have implications for the first and last hour of trading. This will be a topic for another article…

 

Profit from large daily moves

Whenever the market shows an exceptional day ranges it is time to take bite. See how you can profit from large daily market moves.

Open-Close Range

When looking at any chart, you will surely notice that the large candles tend to close near the high or low. This is due to herding. Once the market is moving significantly, everyone hops on and the large move becomes even larger. This is true for daily, weekly and intraday candles.

The chart shows an indicator which plots the daily move. Every opening is set to zero and the absolute move of the day is drawn. Around these normalised candles a long term 2 standard deviation volatility band is drawn.  Right now the 2 standard deviation volatility for SPX is about +/- 46 points.

Take a bite before the market closes

As you can see this +/-46 point barrier above/below the opening of the day is a wonderful entry point. If you enter long 46 points above the opening and go short 46 points below the opening nearly all entries would have lead to a profitable trade. To get an even higher probability of success you can volume as a confirmation. Large moves must also show high volume. The exit is done at the end of the session. This analysis does not give any indication for the next days move. So be fast, take your bite and go home with a small profit and no overnight position.

No free lunch

On the chart it looks easy, but be careful. As an example the last bar shown on the chart first crossed the band to the downside, reversed and crossed above the upper band. So you will need to use a trailing stop to lock in profits and avoid to take the full -46 to +46 points trade as a loss!

 

 

 

 

VIX Futures spread trading

VIX futures are usually in contango, meaning that the next month future is quoting at a higher price than the current month VIX future. But this spread in not constant, and at the end of the expiry cycle an interesting VIX future spread trading idea comes to my mind…

End of cycle VIX futures spread trading

Having a look at the chart below you hopefully see the spread trading idea by yourself: Continue reading

The Probability of Normality

When selling implied volatility you want the market to stay within the  expected range. But what is the historic probability that markets behave as expected? And what other analysis could be done to enhance your chances and find the periods when it is wise to sell an at the money straddle? This article will try to give some answers to this question.

The normal distribution cone

Continue reading

Daily Extremes – Significance of time

Analyzing at which time daily market extremes are established shows the significance of the first and last hours of market action. See how different markets show different behavior and see what can be learned from this analysis.

Probability of Extremes

A day of trading usually starts with a lot of fantasies for the future, then we try to survive the day and end it with a lot of hope for tomorrow. This psychological pattern can also be shown when analyzing intraday market data. A high level of fantasies usually leads to a strong market movement, and thus market extremes can often be seen near the beginning or the end of the trading session. Continue reading

Noisy Data strategy testing

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 of strategy returns

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

Overnight vs Daytime Performance & Volatility

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

Bullish? Buy stock or sell put option?

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.

Bullish probability

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

An Algorithmic Stock Picking Portfolio

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.

Alpha and Beta

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

Market crash or market correction?

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

Bollingerband: The search for volatility

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

Tradesignal Implied Volatility and IV Percentile Scanner

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

IV Percentile – when to sell volatility

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)

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

Implied vs. Realized Volatility for NASDAQ100 stocks

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

Comparing implied and realised volatility

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 kvolfair 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

Distribution of Returns

“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

Bet on Bollinger

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