If you're on either side of the silver trade, you're wondering the same thing: is this a bull market correction or the beginning of the reversion to the historical inflation adjusted mean? ($10.83 according to the silvercointrader.com)
In fact, looking at the nice but slightly dated graphic the Silver Coin Trader has created, we haven't seen inflation adjusted price action like this in silver since the Hunt brothers tried to corner the market:
While likely feeling stepped on after the approximately 30% stumble silver took the week of May 2nd, bulls have remained rather resilient and have typically kept the price above $32 since the fall. Using logic and psychology, I'll explain why this is only the beginning of the silver bear market, even if the price stays stable over the short term.
The Bear Market Short List
Here are the reasons we will continue to see silver deflate:
1. Strengthening of the dollar, potentially catalyzed by the euro crisis and lower realized inflation
Will Greece need to restructure their debt? Doesn't really matter, because either way the dollar will continue to strengthen. If they do, we will see funds pour in to dollar denominated assets as investors shift away from the euro, and if we see risks rising in Europe we'll likely see outflows from emerging markets as investors trade to safety. If they don't, and there is no other bad news on the PIIGS front we'll still see the dollar strengthen as a slack job market prevents the kind of wage increases needed for the inflation commodity markets appear to be pricing in.
2. "Out of the woodwork" supply creation
The meteoric rise in silver from $18 to $48 took place in less than a year, with the biggest push upward in the last three months or so. This was far too quick of a run up before we saw supply-side really respond, but you better believe if these silver prices continue where they're at we're going to see money flood in to mining companies and mining sites with economics that didn't make sense at $18 but do at $35 an ounce. A similar process took place during oil's major rise in the summer of 2008. Whether it be recycling, existing supply or new mining, supply creation will continue to weigh on silver if it stays where it is.
3. Demand destruction
One pro silverbugs will give you regarding silver is that it has industrial applications. That may be true, but I guarantee you those using silver now are scrambling to find alternative commodities or other processes altogether to avoid it. Over the short- to intermediate-term this likely won't have much impact as this isn't something you can change overnight, however if silver stays at its currently levels we will see practically all industrial applications for silver disappear as other processes are developed or silver is substituted with cheaper alternatives.
4. Price Benchmarking and the fear of losing
If you bought at $40 when silver was still climbing, how stupid did you feel when it crashed 30%? Now how likely would you be to buy again if it hit $40?
And in there lies the problem. For the price to climb above $40 again, someone would have to buy at that price, and continue buying above that. In markets where it's felt that the price can only go up, when there is a sudden plunge it spooks the slow money that was just getting to the party. This was the money that was going to pump the market to further levels, and now it will likely sit on the sidelines after getting burned once.
We've already seen volatility rise in silver, as serious retail investors start to leave through the door many hedge funds already exited through. With that volatility will bring in the traders, which will likely continue to shake investors out.
The Moral of the Story
If you're still long silver at this point, you're really just picking up nickels in front of a steam roller, since the factors I laid out above will unravel the price over a long enough time horizon. So even if we see silver for some unknown reason rise above $40 again in the near future, it will be short lived, and will only make the fall that much sharper.
Disclosure: long ZSL
The Sane Investor
My insights on investing, business, marketing and human behavior
![](http://1.bp.blogspot.com/_nzgCwCGVjh0/S3M-HqL1ISI/AAAAAAAAABc/1F_1ObxYKKY/S640/title.jpg)
Sunday, May 15, 2011
Sunday, December 19, 2010
The Role of Investor Selection Bias In Volatility Levels
This article is the second in a series of three articles investigating volatility as "the" measure of risk. To read the first article, "A Thought Exercise: Is Volatility Really an Asset's Risk?", please click here.
In Richard Thaler and Cass Sunstein's Nudge: Improving Decisions About Health, Wealth, and Happiness
, one of the most valuable parts of the book is the authors' separation of humans as they behave in economic models and as they behave in real life. TL;DR: quite differently.
In the realm of investments, financial scholars have largely described investors in their models as being essentially the same while retaining varying inherent risk appetites. In a world where more risk is rewarded with more return (an issue I will address in the third article), this makes sense: some people are willing to risk more to make more, and vice versa.
This is where the "Econ" (human as they behave in economic models) vs. "Human" (human as they actually behave) dynamic that Thaler et. al. introduce becomes relevant. The first important difference between the financial model human and the actual human is the tendency to benchmark with assets, leading to a world where payoffs are expressed as relative to a basket of securities such as the S&P 500 (this is exactly how the Motley Fool ranks their participants). In a paradigm where indexing is rampant, perceptions of risk are strongly different than what modern financial theory would lead us to believe.
The second difference is a strong preference for relative wealth: i.e. a level that places one ordinally higher than others. This has been seen in game theory experiments where participants preferred lower absolute payouts that were higher relative to other participant's payouts (i.e. $40 and everyone else getting $20 versus $70 where everyone else gets $80). This further leads to a logarithmic preference scale as you compare the 1st to 2nd, 50th to 51st and 99th to 100th percentiles of wealth. The change in the number of people you are now better off than in the first interval is much higher than the third interval, suggesting that the risk you'd be willing to take in the first instance (i.e. to jump from the 1st percentile to 2nd percentile in terms of wealth) would be much higher than in the third interval.
To change the interval size, and now look at the change from 1st to 75th percentile in relative wealth demonstrates why lottery payouts are so popular, even though from a high level perspective they're effectively like throwing money away (your probability adjusted return is less than the initial capital outlay). They represent the greatest possible delta in relative wealth for the least cost.
High Volatility Stocks: Another Form Of Lottery
This translates to a preference for assets with high volatility, which in conventional terms are seen as the riskiest/most lottery-like. Authors such as Eric Falkenstein have covered this relationship rather extensively, but as it pertains to volatility as a measure of intrinsic risk I would like to go a step further. In our market, investors searching for these lottery-like payouts are going to go in search of assets with already high volatility. In this scenario, volatility is going to beget more volatility, as more lottery seekers pile in. The lottery seeker, by preference for the highest relative wealth delta for the lowest cost, is going to prefer the assets with the highest ordinal ranking in terms of potential payout. This would lead these investors to dramatically favor, say, the 10th decile of assets in terms of volatility over all other assets.
Why is this a problem for volatility's connection to risk? The key is the self-selection going on when picking assets. If the lottery payout seekers had a slope to their preference, this might still plausibly lead to an efficient market where volatility measures intrinsic risk of an asset, as the lottery seekers become more concentrated in higher risk assets. But the preference for the highest risk stock in ordinal rank is going to lead to a disproportionate asset allocation, leading to a breakdown in volatility in its connection with risk.
The final article in this series will serve as an exploration in to the problems with the risk/return correlation
In Richard Thaler and Cass Sunstein's Nudge: Improving Decisions About Health, Wealth, and Happiness
In the realm of investments, financial scholars have largely described investors in their models as being essentially the same while retaining varying inherent risk appetites. In a world where more risk is rewarded with more return (an issue I will address in the third article), this makes sense: some people are willing to risk more to make more, and vice versa.
This is where the "Econ" (human as they behave in economic models) vs. "Human" (human as they actually behave) dynamic that Thaler et. al. introduce becomes relevant. The first important difference between the financial model human and the actual human is the tendency to benchmark with assets, leading to a world where payoffs are expressed as relative to a basket of securities such as the S&P 500 (this is exactly how the Motley Fool ranks their participants). In a paradigm where indexing is rampant, perceptions of risk are strongly different than what modern financial theory would lead us to believe.
The second difference is a strong preference for relative wealth: i.e. a level that places one ordinally higher than others. This has been seen in game theory experiments where participants preferred lower absolute payouts that were higher relative to other participant's payouts (i.e. $40 and everyone else getting $20 versus $70 where everyone else gets $80). This further leads to a logarithmic preference scale as you compare the 1st to 2nd, 50th to 51st and 99th to 100th percentiles of wealth. The change in the number of people you are now better off than in the first interval is much higher than the third interval, suggesting that the risk you'd be willing to take in the first instance (i.e. to jump from the 1st percentile to 2nd percentile in terms of wealth) would be much higher than in the third interval.
To change the interval size, and now look at the change from 1st to 75th percentile in relative wealth demonstrates why lottery payouts are so popular, even though from a high level perspective they're effectively like throwing money away (your probability adjusted return is less than the initial capital outlay). They represent the greatest possible delta in relative wealth for the least cost.
High Volatility Stocks: Another Form Of Lottery
This translates to a preference for assets with high volatility, which in conventional terms are seen as the riskiest/most lottery-like. Authors such as Eric Falkenstein have covered this relationship rather extensively, but as it pertains to volatility as a measure of intrinsic risk I would like to go a step further. In our market, investors searching for these lottery-like payouts are going to go in search of assets with already high volatility. In this scenario, volatility is going to beget more volatility, as more lottery seekers pile in. The lottery seeker, by preference for the highest relative wealth delta for the lowest cost, is going to prefer the assets with the highest ordinal ranking in terms of potential payout. This would lead these investors to dramatically favor, say, the 10th decile of assets in terms of volatility over all other assets.
Why is this a problem for volatility's connection to risk? The key is the self-selection going on when picking assets. If the lottery payout seekers had a slope to their preference, this might still plausibly lead to an efficient market where volatility measures intrinsic risk of an asset, as the lottery seekers become more concentrated in higher risk assets. But the preference for the highest risk stock in ordinal rank is going to lead to a disproportionate asset allocation, leading to a breakdown in volatility in its connection with risk.
The final article in this series will serve as an exploration in to the problems with the risk/return correlation
Saturday, December 18, 2010
A Thought Exercise: Is Volatility Really An Asset's Risk?
Over the next three articles (this article being one of them), I will be covering why I believe volatility comes up wanting as a proxy for risk.
Throughout a classic education in finance and economics, one core concept that became an assumption of my daily life was that volatility was risk. To a certain degree this intuitively makes sense: if I'm buying an asset, and I have little sense what its value is going to be in an hour or two days from now, I should buckle up because it's going to be one hell of a ride.
In a relatively preset environment, volatility would certainly approximate risk. For example, if we were to live on Mount Kenya as a subsistence farmer, where mean daily fluctuations of temperature equate to 11.5 degrees Celsius (20.7 degrees Fahrenheit), this could surely be seen as one approximation of the risk of being able to generate a successful crop, although another might be seasonal weather fluctuation, such as that seen over a year. Still another would be fluctuation in weather over several years. Thus these three time spans (daily, seasonal and yearly) of weather fluctuation could probably closely approximate your risk of survival (of course there would be others: see bears).
So why might a security's volatility not closely approximate its risk? One answer would be the failure to translate observed volatility to actual volatility, although we would certainly run in to this problem when observing weather. The other problem would come with what this volatility actually represents. In the case of weather, it is the state of our atmosphere, something far beyond our control (although the aggregation of humans is doing a pretty good job: see climate change)
Is An Individual Investor Equivalent to a Subsistence Farmer?
In an asset market, for volatility to approximate "risk of survival" like it does in the natural world, it would have to retain some key characteristics:
Throughout a classic education in finance and economics, one core concept that became an assumption of my daily life was that volatility was risk. To a certain degree this intuitively makes sense: if I'm buying an asset, and I have little sense what its value is going to be in an hour or two days from now, I should buckle up because it's going to be one hell of a ride.
In a relatively preset environment, volatility would certainly approximate risk. For example, if we were to live on Mount Kenya as a subsistence farmer, where mean daily fluctuations of temperature equate to 11.5 degrees Celsius (20.7 degrees Fahrenheit), this could surely be seen as one approximation of the risk of being able to generate a successful crop, although another might be seasonal weather fluctuation, such as that seen over a year. Still another would be fluctuation in weather over several years. Thus these three time spans (daily, seasonal and yearly) of weather fluctuation could probably closely approximate your risk of survival (of course there would be others: see bears).
So why might a security's volatility not closely approximate its risk? One answer would be the failure to translate observed volatility to actual volatility, although we would certainly run in to this problem when observing weather. The other problem would come with what this volatility actually represents. In the case of weather, it is the state of our atmosphere, something far beyond our control (although the aggregation of humans is doing a pretty good job: see climate change)
Is An Individual Investor Equivalent to a Subsistence Farmer?
In an asset market, for volatility to approximate "risk of survival" like it does in the natural world, it would have to retain some key characteristics:
- Unchangeable by one or several individuals
- Relatively constant over time
With the first item, we find little support that a small subsection of the population cannot move prices and ergo influence volatility. By its nature, asset markets are a wealth adjusted voting machine, so were one to be so inclined, with the proper amount of money one could dramatically influence the price environment of one particular asset. This further topples the second characteristic as big money moving in and out of trades can dramatically affect the volatility of individual assets.
Because volatility is easily manipulated and not an inherent characteristic of an asset, its value as an accurate predictor of risk is severely diminished if not totally obliterated. Thus, while volatility might be high for an asset currently, there is no inherent dynamic that suggests that it might or should stay at this level for any amount of time going forward.
The next article in this series will look at sticky volatility induced by selection bias followed by an article exploring problems with the risk/return correlation.
Subscribe to:
Posts (Atom)