Tuesday, December 23, 2014

2015, Risk and the Moon

Being prepared for when things do not work out as planned is important.  But planning for failure, is not planning to fail.

"Fate has ordained that the men who went to the moon to explore in peace will stay on the moon to rest in peace."

This is the opening of the speech President Nixon would have given the world, had the Apollo moon landings failed in 1969.  At the time it was one of the most complex endeavours humans had ever attempted, with high risk, but an immense preparation for these risks, and the many measures to control them.

I hope 2015, brings you the best of outcomes, from the risks you choose to take, in full knowledge that they may not work out as perfectly as planned.  But being prepared to minimise these bad events, will make the chance of many more good outcomes likely.

Its always good to shoot for the stars.  But be ready and able to have the resources for a second and third Shot!


Thursday, December 18, 2014

Leverage – The Bringer of Destruction. Risk vs Return.

I recently saw this chart of “Max Drawdown % Risk” verses “Return %”, of a large number of traders on the SaxoBank website.





Interesting!

Firstly and obviously, zero risk is zero return.  Returns rise from this point until the number of 50% return-makers flatlines from 8% - 30% max drawdown risk, (lower horizontal green line).  It then seems to start to fall along the top of the cluster above the red trend.

As risk increases, the red trend is far more significant to the downside in an almost linear relationship.  Over 80% max drawdown risk seems to imply a return approaching 100% loss.

If you look at the overall cluster running along the top of the red line, it seems safe to say, that increasing risk does not constitute increasing returns for most traders.

The top performers (who must take some risk to generate a return) sit in the 40-55% max drawdown risk range.

No-one with 75% max drawdown risk or more has doubled their money.

The greatest cluster of 100% return-makers, sits somewhere around the 20-30% max drawdown risk range, (upper horizontal green line). This seems to be a reasonable place to be when you include the possible returns below it as well.

Importantly, these are just subjective eyeball observations, and the traders here are most likely using a variety of strategies, and are of varying skill/experience.  A bigger sample size would also be great to have, (820 on the website).

Humans have a great awareness of risk through survival instincts, but this does not seem to translate into the markets!




Sunday, December 14, 2014

China – Causes for Concerns.

A few weeks ago I wrote a blog about the parallels between The Japanese Bubble Economy of the 90’s and how I see China now.


Today another concern to add to the list popped up, after the recent run-up of the Shanghai Exchange.

China is adding money to its financial system to fuel growth, as forecast growth rates continue to fall.  While doing this, China’s leaders and state media are using the statement of a “new normal” of slower growth as expectation management on investors’ appetites.

I love the term “new normal” as a contrarian signal, telling me that it will not end anywhere like what is being expressed in relation to it.  (As example: a “new normal” of low volatility from now on – I would see as high volatility to come!)  The more “new normal” talk there is, and belief in the concept – the more it is impossible to be true.

A new normal of “slower, high quality growth,” is coming to China.  Uhuh-sure! 

When you pump money into banks to ensure liquidity, as recent history shows, its usually too late to save a bad outcome.  And I don’t think anyone knows the depths to how bad the banking and property sectors are in China really – not even the government.   There seems to be way too much regional government intervention and corruption for that.

Share buybacks, and state-owned company share investments, that were “encouraged” by the authorities, have pushed up stock prices enticing local and now foreign investors into the share market at elevated prices.

Due to this recent run in Chinese stocks (17% this month, 35% this year), China banks have suffered investor withdrawals to fund their entry into the stock market.  Much of that has then been leveraged.  Margin use in total trading has almost doubled since May, and non-bank trust companies are lending up to 300% of capital!

Loose margin requirements, which have not been tightened recently despite liquidity concerns, threaten only to cause more big drops similar to the decline Tuesday, that was the biggest one-day drop since the GFC, on fears of tightening requirements for margin credit.

Japanese use of margin at ridiculous levels, especially in property prices tells us that this kind of leverage is unlikely to lead to “slower but quality growth.”


This “new normal” could just be masking the high volatility to come.  Clearly, investors do not seem to learn from history.  Nor consider the psychological implications of a run of margin calls as banks with liquidity problems tighten up.


Tuesday, December 9, 2014

Taleb’s “Alternative Histories” and Investing.

“Clearly my way of judging matters is probalistic in nature; it relies on the notion of what could have probably happened….
            If we have heard of {histories greatest generals and inventors}, it is simply because they took considerable risks, along with thousands of others, and happened to win.  They were intelligent, courageous, noble (at times), had the highest possible obtainable culture of their day – but so did thousands of others who live in the musty footnotes of history.”  (Taleb, Fooled by Randomness).

Julius Caesar was a fantastic general, yet was amazingly lucky (until he was not), whereas Erwin Rommel, also a fantastic general was plagued by bad luck on multiple occasions, (with a random and erratic Commander in Chief not helping).
What other outcomes for these generals could have happened?  And, would they be judged by history differently for their decisions, despite no change in their skills?



“Every once in a while, someone makes a risky bet on an improbable or uncertain outcome and ends up looking like a genius,” (Marks, The Most Important Thing),  … or a fool.

But how do I picture these alternative histories that could have occurred but did not? 
(I saw this graph somewhere but couldn’t re-find it, so recreated it below).

At point X now, current conditions are known (as best as available information can be utilized).  The correct decision (always) to take is the one that is logical, intelligent, and informed “at that time” (Marks).

At point X now, all red outcomes are “possible” and unknown, but some are more “probable” than others.

At point Y later, only a single red outcome has eventuated.   At which point it often becomes hard to imagine that any of the others were “possible” to begin with.




(Note: The distribution in reality may be skewed towards one side of possible outcomes.  This is more to highlight the concept of possible and probable only, not the mathematics).

When things go as predicted (luck playing a role), people tend to look like geniuses for their correct actions.  “Coincidences look like causality.  A lucky idiot looks like a skilled investor.” (Marks).   However, the correctness or quality of a decision cannot be judged by its outcome, especially if randomness is involved.  For this reason correct decisions based on a sound process are often wrong, and the macro events that may have caused it, beyond anticipating.  Incorrect decisions and processes can also be seen as correct, with an unanticipated event causing the outcome you wanted.

Whilst the mean is the most “probable” outcome (reversion to the mean?), it is not at all certain, as for any individual situation, all outcomes are “possible”.  In fact the collective likelihood of all the other outcomes is higher than the one we think is most probable!

The most extreme outliers at +3s and - 3s can be the black swans (good and bad). (Maybe there should be black swans AND white knights?).

At least by having a good process at X, we can limit the pain of black swan events and not necessarily experience account destruction when they do occur.  We must trade based on what we think are probable outcomes, while not doing too much damage or loss in the rest that occur.   We need to cut off the bad tails effect on us, or limit it.  Fortunately options do that, yet expose us to the full range of favorable possibilities.

This does not mean to imply not trading a contrarian strategy, or positioning to get lucky etc.  Its what we think are probable and possible, based on our analysis, not probable as in the herd thinks it likely.

I think understanding that we can’t know the outcome of all that is possible, but can try to understand what is probable and position accordingly, whilst protecting the risk of severe damage to my account, is the best thing I have learnt in 2014.  (Possibly! Probably!)

Clearly some “alternative histories” would have been far worse than the one we know.  But in 1940, our now known outcome was nowhere near certain, and one could argue improbable.  The things that HAVE happened in the world are just a “small subset of the things that COULD have happened.”  And finally, “ensure survival” (Marks).



(If you want to think more about alternative histories, watch the Back to the Future movies!)


Friday, December 5, 2014

The Importance of Reversion To the Mean in Investing. (Part 2)

The Three Illusions of Reversion to the Mean. (Part 2)

Reversion to the mean creates three illusions - cause and effect, feedback and declining variance, (Mauboussin, The Success Equation).

1.  Illusion of Cause and Effect – The human mind has an innate programming to want to explain occurrences by finding the cause of them, even if there isn’t one.  Yet, reversion to the mean is a “statistical artifact,” that our minds try to interpret with a cause that often is not there, (Mauboussin).

Reversion to the Mean “happens without the need of a cause.”  This is problematic to our minds with that need to assign one, even if it causes an error.

“The DOW fell 2% on the back of weak employment data.”  No – it probably just regressed back towards its 50 day Moving Average, more likely.

2.  Illusion of Feedback – The idea here is that after an event, you take an action and believe that this causes the next event to occur as a result of that, even though reversion to the mean might be all that is occurring.

Mauboussin’s example of doctors is: You have higher blood pressure than your last consultation, which the doctor treats with a drug.  Blood pressure subsequently lowers towards the average at the next consultation, which the doctor believes is due to his treatment (which it may, or may not be).  But in the whole population, everyone’s blood pressure would revert towards the mean with or without treatment.

The illusion of feedback will persuasively suggest that the treatment was the cause and lower blood pressure the effect,” (Mauboussin).  Clearly the illusion of feedback plays right into the hands of the illusion of cause and effect, and the narrative produced can be a strong and highly erroneous belief.

3.  The illusion of Declining Variance – (the hardest to conceptualize) is the illusion that as something moves to its average, the variation in the numbers shrinks.  This is not necessarily the case, and sets a trap in our analysis.  In other words as stock price reverts to its mean, it does not imply that the individual prices observed will cluster closer together around the mean, as would be evident by a closer standard deviation.




The chart below shows how price reverts to its mean at P from Po, variance increases initially as price begins to move, but then stabilizes, yet does not contract, as the illusion would dictate.
Also, reversion to the mean occurs even when the statistical properties of the distribution remain unchanged (Mauboussin).  According to Bob Jensen at Trinity University it looks like this:





The red line can be flipped to show a declining price reversion to the mean with similar variance results.




Mauboussin’s final point on the Illusion of Declining Variance offers the warning that; “None of this is to say that results cannot exhibit a decline in variance over time… But just because you observe reversion to the mean, that’s doesn’t suggest that individual outcomes are converging toward the average.”


Summary:
Reversion to the Mean does not need a cause.
We fail to predict to an adequate amount its effect when making predictions about the future.
Reversion to the Mean is most pronounced at extremes.  Things that are great won’t stay that great, things that are terrible rarely stay that terrible.
When a lot of luck is involved Reversion to the Mean is stronger, and inevitable.
The paradox of skill, (increases in the skills of investors and access to information, has narrowed the skill variation in the population, making luck more important in success), has lead to an increase in the power of Reversion to the Mean, (Mauboussin).



Monday, December 1, 2014

The Importance of Reversion To the Mean in Investing. (Part 1)

The definition at least, is simple: When something happens that is not average, the following event is likely to be closer to the average.   But, the outcome is difficult to predict, understand and prone to illusions. 

Why is Reversion to the Mean important to consider?  In cases where Luck plays a large role in outcomes, such as prices of a stock, “Reversion to the mean is very powerful,” and “failure to regress outcomes sufficiently” causes people to “buy what has done well and sell what has done poorly” leading to the dumb money effect, (Mauboussin, The Success Equation).  Further: “Any activity that combines skill and luck will eventually revert to the mean.”  Howard Marks, when referring to this uses the term cyclical, but I believe it’s essentially the same.  But it’s important to realize that nothing can go up in price forever and down is only limited by zero, but otherwise cant go down forever.

Spierdijk & Bikker (2012), “Mean Reversion in Stock Prices: Implications for long-term investors,” summarized much of the literature. http://www.dnb.nl/en/binaries/Working%20Paper%20343_tcm47-271856.pdf

Fama & French’s 1988 study explained 25%-40% of the variation in stock returns on mean reversion in long term investments over one year to ten years in duration.  Campbell & Shiller (2001) found that adjustments of the P/E ratio towards an equilibrium level was more by the price of the stock than the company fundamentals (price vs. quality).  Coakley & Fuertes (2006) found mean reversion behavior to be attributable to investor sentiment.  Further, mean reversion in stock indices of whole countries was almost absent in periods of low economic uncertainty, but of course very fast during high uncertainty or crisis.

In investing, mean reversion can occur in essentially every asset class, size of company, investing process, valuation model, and geographical boundary due to the roles of luck or randomness.

Mauboussin argues that people usually fail to revert their predictions sufficiently to the mean, and that its one of the biggest hazards decision makers face.   So it makes sense that when price regresses it should move more to the mean than you think it will, and that price often overshoots the mean.  The bigger the movement from the old price to the mean, and the momentum of that move seems to imply the possibility for a larger overshoot.

If everyone in the market is generally failing to calculate the amount of reversion to the mean that may occur, it seems a great contrarian view to take, that it will be greater than expected.  Howard Marks (The Most Important Thing) discusses a paradox where investors think quality rather than price is the main determinant of whether something is risky, yet price is more correlated with risk than quality.  A high quality stock is likely to be high priced and therefore far more at risk of reversion to the mean, despite its positive sentiment.

Contrarian strategies based on mean reversion in stock prices have been shown to yield excess returns, Balvers et al. (2000).  Further, generating risk adjusted excess returns by selling past winners, and buying past losers was profitable, De Bondt & Thaler (1985).  In other words there is less risk in mean reverting stocks especially over long investment periods. 

However, evidence of the actual existence of mean reverting behavior is harder to prove in stock prices, perhaps due to the difficulties in empirical assessments of mean reversion, and a risk averse investor should base investment decisions on conservative assumptions regarding mean reverting behavior occurring in a given timeframe, especially shorter durations, (Spierdijk & Bikker, 2012).    But once it occurs, expect it to exceed expectations of the magnitude of reversion.


Mean Reversion of a Slinky. (It always overshoots its mean!)


Summary:
Reversion to the Mean does not need a cause.
We fail to predict to an adequate amount its effect when making predictions about the future.
Reversion to the Mean is most pronounced at extremes.  Things that are great won’t stay that great, things that are terrible rarely stay that terrible.
When a lot of luck is involved Reversion to the Mean is stronger, and inevitable.
The paradox of skill, (increases in the skills of investors and access to information, has narrowed the skill variation in the population, making luck more important in success), has lead to an increase in the power of Reversion to the Mean, (Mauboussin).

Untangling Skill & Luck – Mauboussin Article. Legg Mason Capital Management. http://vserver1.cscs.lsa.umich.edu/~spage/ONLINECOURSE/R15SkillandLuck.pdf