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BITCOIN AND VOLATILITY

With all the mug punters of the world seemingly going all a flutter in their neither regions over Bitcoin and all the talk about how volatile it is, I thought I would take a quick and dirty look at how volatile it is in comparison with other instruments and whether the current level of volatility was historically high for Bitcoin. Below is a table comparing the 30 day historical volatility of some commonly traded instruments as well as the 250 day average HV of the 30 day HV. This serves as a dirty (read lazy) proxy for the true mean HV.

BC

As you can see Bitcoin displays a remarkable level of volatility when compared to other instruments. However, currently it is below its own long term average HV. Trouble starts when people begin to ascribe a characteristic to these sorts of measures. The only thing we can rationally say based upon the evidence at hand is that Bitcoin does display a level of volatility well beyond that shown by more traditional instruments but it is below its own long term HV. This situation is neither good no back and is in no way reflective of the utility of Bitcoin as a trading instrument within a portfolio. I have been over the fact that trend and volatility are in no way related so I wont labour the point here. Suffice to say all that matters is how well an instrument trades – volatility in many respects is an irrelevancy and a needless distraction.

Life is getting ever more volatile – or is it?

We live in an age of unrelenting change. That, at least, is what we are told by a consulting industry that thrives on a gospel of disruption, and journalists who overgeneralise from the earthquake in their own profession.

Anecdotal evidence of volatility is easy to find: the financial crisis; the cultural dominance of inventions such as Facebook (barely a teenager) and the iPhone (younger still); the rise of fringe political parties and a maverick president.

But the statistical evidence for disruption is less compelling. The most straightforward evidence of that is low productivity growth in many advanced economies. If the pace of change is really so frenetic, how come we don’t see it in the productivity statistics?

More here – Tim Harford

Gold Vs S&P500

I am still intrigued by the US markets reaction to the results of the US election when viewed in tandem with an instrument such as gold which is generally seen as a hedge against uncertainty (in this instance read outright dickheadedry) As such I though I would look at the relative returns of both instruments over a series of times frames if that told me anything about the market currently being uncertain about its own uncertainty. In looking at these two instruments I have cheated a little bit in that I am using a proxy for gold. I am using GLD which is an ETF that tracks the physical price of gold. I accept that this is a broad brush approach given the nature of the construction of GLD. However, I am looking for at a battleaxe approach not a rapier so the small inconsistencies dont bother me. I am more interested in looking at the broad pattern. If you have to look too hard then there is no pattern at all. If the relationship is not then when being as subtle as a sledgehammer then it is not there at all.

The firts thing I wanted to do was to look at the relative performance of the two since the US election and this can be seen in the chart below.

gld 1

My reading of this from left to right is that Trump wins the election and the long term rally that has been in place since 2009 reasserts itself with equities taking off and GLD drifting. A few weeks later the ramifications of electing a buffoon become apparent and the market stalls and GLD rallies slightly. We now have the situation where the market is rallying in the short term as is GLD. A cynic might suggest that trades are hedging their bets a little.

However, it is important to note that these sorts of performance comparisons are dependent upon the starting date. If I roll the starting date back a year a different picture emerges.The big picture alters every time you change the starting date.

gld2

We can see that GLD actually begins to drop off in the second half of 2016 as physical gold runs into a wall and begins to fall back. The out performance of the S&P500 over this time becomes even more apparent but the bounce in GLD is still there but the performance of the S&P500 is so much more apparent. This raises the question as to whether this sort of analysis whilst mildly interesting on an academic basis actually provides any insight that is worthwhile. Such a question also highlights a simple fact of analysis and of system design in general. Everything you do needs to add some form of value to the system. Unfortunately academic interest does not add value to a system so on this basis my feeling is that this sort of thing doesn’t add any value outside of curiosity and the vague conclusion that traders are uncertain about being uncertain. To be blunt you have to ask the question does it help make money since that is the aim of trading. For some it might but for me it just kept me occupied for half an hour.

 

 

 

Are We Scared Yet?

Apparently, the world is ending because the media says so. The source of much of this hysteria is that the media seemed to have discovered a tool known as the S&P/ASX200 VIX indicator which is also known as the fear indicator. One somewhat hysterical report claimed that it was the highest it had ever been, which it is not. What they saw was obviously the ASX chart that only goes back to 2012. Punters will know that I have mixed feelings about volatility based tools. I tend to regard them in much the same way that General George S Patton regarded the French Resistance. Not as good as advertised but better than expected.  There are two things that are important when looking at volatility based tools, particularly those that are based upon implied volatilities such as VIX in all its domestic forms.

The first thing we need to be aware of is basic context – volatilities are relative values so whilst a number might sound high in isolation, context might provide a slightly more nuanced view. Consider the chart below of the S&P/ASX200 with a 30 period historical volatility plotted.

Screen Shot 2015-09-04 at 10.00.37 am

In the indicator box I have plotted two lines. The unbroken blue line represents the average historical volatility for all the data on the chart whereas the broken line represents average historical volatility since the GFC. This tells us an interesting story – volatility in terms of is historical volatility is not that bad. In fact it is sitting below the average volatility of the market post the GFC. This of course comes with all the caveats that using simple averages come with, nonetheless it is an interesting picture. This raises the question of why the hysteria over volatility and I think the answer to that is found in the age old problem that people confuse trend with volatility. The belief being that if the market is going down then it must be more volatile. Unfortunately, this is the default narrative of talking heads in the media.

The picture is slightly different when we look at the local version of the VIX over the long term.

Screen Shot 2015-09-04 at 10.00.17 am

The solid read line represents the average for the entire data set whereas the broken line represents the average since the GFC. The picture with the local VIX is a little different to that of the underlying index with its historical volatility plotted. The reason for this difference brings me to my second important point when viewing such tools. When you look at the VIX you are seeing the markets expectation of volatility over the next 30 days based upon a blended average of expectations generated from index option prices. So you are seeing in effect an opinion about what volatility might be in the near future. However, this opinion is based upon the past and is an attempt to project into the future. In its most basic form there is nothing wrong with this because this is how we all construct our views of the market. The issue I have with this is the near quasi religious status that such tools have and the belief that somehow they predict the future of the market. What they offer is an expression of opinion about volatility not trend and if you look at the historical distribution of prices you see that the VIX rises after an event – not before it. It has to be this way, if volatility rose before any change in the underlying you would have problems with the notion of cause and effect.

This raises issues for the average punter because they are being bombarded by somewhat breathless pronouncements about the level of fear in the market. The easiest solution is isolation and ignorance. It is all too easy to be swept up in the overthinking and prognostication that goes on when markets begin to move. This is simply noise. Noise is in many ways a function of volatility – the more markets move in a short period of time the noisier they become. From my perspective noise is a common crowd response to activity and can be compared to what happens a sporting events. As the action increases so too does the volume of the crowd. This increase in volume produces a series of emotional responses in the crowd. These responses are generally always subconscious – people when influenced by crowds often do things for which they have no rational explanation. The same is true in trading.

As the Japanese are fond of saying. To take no action is an action. Unfortunately, traders believe somewhat falsely they must always being doing something, even if it is the wrong thing.

Charts Of Interest 28/08/15

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That Must Have Stung…..Just A Little

This has been a tough week for the 0.01% out there.

For the world’s billionaires, this week is already proving rough. The Chinese stock market dropped 8.5 percent Monday, the biggest single-day decline since 2007, and the world’s 400 richest people lost about $124 billion collectively. Chinese billionaires lost more than $14 billion of their net worth Monday alone, while the Shanghai composite index dropped by another 7.6 percent Tuesday, Bloomberg reported.

Wang Jianlin, the richest person in Asia and chairman of the Dalian Wanda Group, was the hardest hit. He lost $3.6 billion Monday, more than any other billionaire. Of that, $2 billion was lost when shares of the Dalian Wanda Commercial Properties Co. sank 17 percent since going public in December. Another $1 billion in losses came from declines in the Wanda Cinema Line Co.

Bill Gates, the former Microsoft chairman, was the second-most affected person, losing more than $3.2 billion Monday. In Asia, billionaires in mainland China suffered the most, losing 6 percent of their total net worth. 

More here – International Business Times

Well….Somebody Woke Up

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