Correlation Confound (Part 2)

In the last post, I defined both words in the title. Today I continue by describing the correlation confound of portfolio diversification.

Combining assets with low correlations in a portfolio may allow me to get more return while taking on the same level of risk. It may also allow me to get the same return with less risk. This is diversification.

Risk, or variability of returns, is what causes people to close positions for the worst possible losses.  Averaging +10% per year is great for a portfolio but if, at some point during the year, you were down 80% then would you still be in the market? In 2012 I described this scenario in terms of maximum adverse excursion. Diversification helps to lower risk and while that may lower returns as well, if it can keep me in the trade mentally then time has repeatedly been shown to work its magic and allow the market to rebound.

To build a diversified portfolio, we are advised to look for assets whose returns have not historically moved in the same direction. What I do not see in most of these discussions is the fact that correlation can change.  Jim Fink addressed this in a 2013 article:

> A large portion of the disappointment can be traced to
> the severe bear markets… when correlations among asset
> classes increased markedly at the worst possible time,
> resulting in all declining in price at the same time.
> [Mebane] Faber uses 2008 as a prime example:
>

>   "The normal benefits of diversification 
>    disappeared as many non-correlated asset 
>    classes experienced large declines 
>    simultaneously. Commodities, REITs, and 
>    foreign stock indices all suffered 
>    drawdowns over 50%."

>
> If only there were a way to avoid exposure to risk assets
> during the most severe bear markets, the problem of
> converging correlations could be avoided and the
> diversification benefits of different asset classes with
> normally low correlations could be fully realized . . .

Correlation confound #1 is changing correlations. If this happens then your best efforts to diversify and minimize losses may not be effective.

Correlation Confound (Part 1)

Correlation is mentioned as a key factor in two different trading/investing contexts. In this mini-series, I’m going to describe correlation, how traders can make use of it, and a couple missing pieces (confounds) to avoid unexpected failures.

I will begin by explaining both words in the title.

Correlation is a measure of how often two variables change together. A correlation of +1 between two stocks means historically, when one stock was up 5% the other was also up 5%. A correlation of -1 means historically, when one stock was up 5% the other was down 5%. A correlation of zero means historically, no relationship between the stocks’ price changes occurred. Correlation can range from -1 to +1.

In science, a confounding variable is “an extraneous variable in an experimental design that correlates with both the dependent and independent variables.”

Ice cream [example] can better help me illustrate this. Suppose a correlation between murder rates and ice cream sales is observed. If murder rates go up (down) when ice cream sales increase (decrease) then ice cream sales drive murder rates, right? This is less likely if some other variable is also found to be correlated with murder rates. That variable would then confound our initial model. Suppose it is also observed that as seasonal temperature increases (decreases), people buy more (less) ice cream and spend more (less) time outdoors where criminals run the streets. It makes logical sense for seasonal temperatures, not ice cream sales, to affect murder rates. Seasonal temperature is a confounding variable.

In the next post I will start to explain confounding variables that prevent correlation from doing its job.

Protect Your Nakeds!

I subscribe to a mailing list that focuses on covered call writing. I often see people fail to acknowledge risk and it makes me a bit uneasy.

This was taken from a 2014 post:

> I will be happy to buy QCOR at 65 if it is put to me.
> Based on reading many of the QCOR reviews I believe
> QCOR is fundamentally very strong… If put to me I
> appreciate Citron’s work that adds to volatility and
> will reward me if and when I sell a CC for a high
> premium.

People short puts on Enron or any other stock that ultimately went bankrupt said the same thing before it went to zero. When the stock is well on its way to zero, no stockholder, naked put trader, or covered call writer will be happy.

Some people use explicit wording instead of a smug “I’ll be fine because I feel comfortable owning the shares” attitude. An example is often given by people advertising covered call services or option educators who say “sell the put at a strike price at which you would be happy to purchase the stock.”

I think either of the above clouds the real issue: risk management.

The bottom line is if I take assignment on a naked put then I’m probably losing money. If I don’t have an exit strategy then I better hope to high heaven the stock doesn’t go to zero! Regardless of how “happy” I say I’ll be if assigned, I’ll feel more and more heat if the stock continues to slide further. If the stock tanks substantially and then trades sideways then I will be highly frustrated sitting on what feels like dead money because I won’t be able to collect meaningful premium on the [now] deep OTM calls.

The Myth of “Unusual Option Activity” (Part 1)

The financial media often treats unusual option activity as a predictor of how large institutions are trading. This may or may not be very misleading, which in my view casts doubt over the entire strategic approach.

Traders will sometimes study the option flow for a stock because they believe this helps them to understand sentiment. Particularly when a stock is extended, some believe option activity can offer predictive signals. For example, if one large block is going against the trend, it can mean the institutions are starting to think trend reversal. On the other hand, increased small-lot activity in the direction of the trend conveys a message that can fool the beginning trader.

What options are predictive of trend persistence versus trend reversal is not at all obvious. For example, heavy put volume on a beaten down stock could be a trader(s) shorting puts in expectation of mean reversion: either reversal to the upside or at least a temporary reprieve before the downtrend resumes. If this trader(s) is also shorting stock against the put sale then the overall position is actually bearish rather than bullish. The trader(s) took advantage of the high implied volatility to collect some extra premium in the hedge but the primary profit generator is downward stock movement (upside has unlimited risk).

Married puts and covered calls are two other examples of misleading option activity. Buying puts in the former suggests a bearish position but having purchased the stock, this is really a bullish position with downside protection. Selling calls in the latter suggests a bearish position but having purchased the stock, this is also a bullish position with [limited] downside protection. In fact, if the stock is purchased before the option is traded then the stock price may be higher to allow for a cheaper put purchase or more expensive call sale: both advantageous to the combined position.

I will conclude with the next post.