Leverage and Volatility

Suppose a trader predicts a given stock to rise by 25% over the next 10 days. Of course, if he is unleveraged, if the stock does indeed rise by 25% in 10 days, his 10-day return will be 25% irrespective of how volatile the stock price was in the interim. This, however, is far from true were he leveraged (i.e.trading on margin, as opposed to trading unleveraged while taking outside loan for providing capital). If he was 300% leveraged, then his return at the end of 10 days, is far from 100% (4 times 25%) as one would naively imagine, but a devastating -47%, in the volatile scenario 1. It is only in the non-volatile scenario 2 that leverage actually multiplied his returns.

Notes to myself on Investing

The biggest enemy of an otherwise prudent investor is an inability to sit tight. If he only acts upon his strongest convictions, in terms of putting on trades, and lets the low conviction trades pass by without feeling compelled to "see what happens once I put it on", he will over the long term be profitable. I have learned this from experience, but it is echoed by such great investors as Warren Buffett, that I do not have to worry as much about depending solely on my experience. Another note: don't depend solely on anything, irrespective of what thing it is. Well, depend on it at times, but don't bet the bank on it.

Of course, all this assumes that he is otherwise prudent, that is, understands the mechanics of the global markets well. This again, is not a 'talent'. It is a skill developed through self-effort. Self-effort, again, does not translate to merely working hard, although working hard is an indispensable part of it. In the context of investing, working hard entails reading a lot: books, academic research, market research. If hard-work was all, you could just maximize your profits by maximizing the numbers of pages read. However, this indiscriminate focus on quantity falls short on three things:

(1) Separating wheat from chaff: Deciding what to absorb and what to ignore is important, because much of what is out there has greater potential to harm than to benefit. Partly, this discrimination comes from experience, but I hope that not all of it must come through experience, because experience in this case often means trading losses. There is some respite. Discrimination also comes from a general attitude of thinking for oneself, even when reading. Too much reading is no better than gluttony: you become so busy eating you forget you have to clean and eat. Arthur Schopenhauer expresses it very will in his essay "On Thinking For Oneself":

The visible world of a man’s surroundings does not, as reading does, impress a single definite thought upon his mind, but merely gives the matter and occasion which lead him to think what is appropriate to his nature and present temper. So it is, that much reading deprives the mind of all elasticity; it is like keeping a spring continually under pressure. The safest way of having no thoughts of one’s own is to take up a book every moment one has nothing else to do. 

(2) Reading is not understanding: You have got to leave enough time to mull over things you have read, but perhaps this belongs to the previous bullet point. What definitely belongs here is to emphasize that it is very easy to misunderstand content when your fundamentals are not strong. Therefore, as important as it is to read, it is of greater primacy to study. Study entails not reading the latest book of economic wisdom acclaimed by one and all, but reading and solving problems from your boring, old textbooks. It is important that you have studied back in college (other than being rejected by a hot (to you, at any rate) girl) if you are to take away the important lessons from all the reading you will do as an investor. If you didn't, do that first. Depending on the kind of investor you are, it may include macroeconomics, accounting, statistics, financial mathematics, or all of them.

(3) Being wary of confirmation bias: Irrespective of what or how much you read, it is easy to come out of it with just your prior opinions solidified, as the mind has a tendency to read every little reaffirmation of your prior beliefs in bold, life-sized print, and read everything that's not so agreeable in Arial Narrow. So be careful. It is also important to emphasize breadth, than to read five books about the same thing, your favorite topic. Investing is a complex subject, it lacks the hard rules governing the physical sciences like Physics, and it is often tempting to ignore this aspect of investing, especially the more mathematical your training is. Don't. Because of this nature of investing, breadth has a depth all its own. Read widely. Read about things not immediately applicable to your next trade. CLR James and Harsha Bhogle rightly re-ignite Rudyard Kipling's famous sentence on England by applying it to Cricket: "What do they know of Cricket who only Cricket know?" The essence of this wisdom has a central place in investing. "What do they know of Equities who only Equities know?" Replace 'Equities' with any specific part of financial economics, and you will see what I mean.

In essence, make the goal of your reading be "to improve your perspective", and the three points above will largely be taken care of.

The fine difference between GDP deflator and CPI

GDP Deflator and CPI or Consumer Price Index are both price level indices, with two crucial differences in the way they are calculated:

1) GDP deflator keeps quantities fixed at the "current year", whereas CPI keeps quantities fixed at the "base year".

So, going from 2013 (assuming that is the base year) to 2014 (current year), the value of the deflator in 2014 will be calculated using weights for different goods that correspond to their weights as observed in the 2014 economy. 

Deflator as of 2014 = Σ [P2014 (i) * X2014 (i)] / Σ [P2013 (i) * X2014 (i)] 

Or in other words, Deflator= (Nominal GDP in 2014 / Real GDP in 2014)

On the other hand CPI keeps quantities fixed at the "base year", so in this case:

CPI as  of 2014 = Σ [P2014 (i) * X2013 (i)] / Σ [P2013 (i) * X2013 (i)] 

(Fairly obvious, but let's note that P's represent prices, X's represent quantities)

2) In both cases above, I used a summation with variable i. It is important to note that in the case of deflator, the "i" loops over all the goods and services produced in the economy of that country, whereas in the case of CPI it loops over a well defined basket of goods that are identified as consumer goods.

This distinction is important for quite a few reasons. Inflation can be calculated both as the rate of change of deflator or as the rate of change of CPI, but the purpose for which that inflation estimate is required determines which of the two methods to use. For example, policy decisions often take CPI into account as it is a better indicator of inflation as it is felt by the general population. 

Secondly, CPI is much more volatile than Deflator. You would expect that to be the case since statistically the Deflator calculation seems to average (weighted-average, to be precise) a whole lot more quantities, and you'd expect the law of large numbers to kick in. But there's also an intuitive explanation on top of that: CPI has a large percentage presence of some of the most volatile sectors, such as, housing, energy and food.

For this reason there is another important measure, commonly called "core inflation", which when considering the rate of change of CPI excludes its volatile components like energy and food which vary a lot merely as a result of short term vagaries of weather, yields etc while not representing any structural change in economic trends.

A word of caveat. Both these measures are hard to estimate with precision, the GDP deflator more so because it has so many more moving parts. CPI estimations, although relatively simpler, have long been tainted with accusations of manipulation by government bodies that estimate them, and often have agendas that outweigh the pursuit of precision. Recently, the startup premise dot com has employed crowdsourcing principles to estimate food inflation from the ground up by having people send prices to them of food they buy everyday while their engine does the almost real time number crunching. You would be surprised at how much their estimates of food inflation differ from the "official" figures, especially for developing, populous countries like Brazil and India. 

When historical correlations fail to hold up

This summer had investors across asset classes and geographies puzzled by the "wrong" correlation between treasury yields and risk assets (such as corporate credit and equities). Historically, it was argued, that the correlation has been strongly positive. That is, when the treasury yields rise (or fall), the prices of risky assets rise (or fall). I would argue that the dismay with the rationality of this year's correlation was misguided in more ways than one. Firstly, when we talk of historical correlations, we tend to think of a continuous time series between, let's say, 40 years ago (assuming that to be a ballpark time at which markets, at least US markets, decisively matured) to today. While it is true that this correlation shows itself to be markedly positive, a strong positive correlation needn't necessarily allude to an economic thumb-rule. And in this case it doesn't. It is important to see that there have been pockets of time in the last 40 years when the correlation was negative, but since they weren't the norm, they don't affect your long term coefficient of correlation in any big way. But just because they weren't the norm does not mean they were periods of random noise. It might do us good service to identify those specific time-periods and then analyze the difference between those time periods and the rest of history. From a study such as the one I just outlined, my far from exhaustive observations suggest an element of causality as a big differentiator in the correlation behavior. That is, it is important to consider what's causing the rates to rise - good economic outlook (in which case the positive correlation does indeed make complete sense and holds up almost always) or something else (lack of confidence in the government (as in 2008), or Bernanke sneaking away his Santa Claus hand (this summer)).

Traditional wisdom for the positive correlation goes like this: The rise of treasury yields (or in other words the falling of treasury bond prices) reflects a transfer of the world's funds from riskless to risky assets and vice versa. Naturally, as a result of this transfer of funds into risky assets such as high-yield credit and equities, they rise. All very well, except this and that and that. We saw this in 2008 at the time of the financial crisis that the treasuries fell (yields rose) and equities fell too. Any positive correlation between yields and equities was thrown out of the window. Now lets try to see why the traditional wisdom is far from a holistic perspective. Most of all, it's because it relies too much on correlation and correlation alone, while only superficially digging into causality. At its core this conventional wisdom makes one grand assumption, that money either flows from risky assets (HY, Equities) to riskless assets (treasuries, gold) or the other way. Such a transfer always gives us a conveniently positive correlation between treasury yields and risky assets, and we rejoice. What it does not take into account is that in times of unprecedented uncertainty (such as Bernanke leaving the markets alone, in the present case) people don't necessarily merely shift their money from one asset class to the other - they may wait for the uncertain period to pass, holding cash, and taking off again only when the sky gets clearer. In such times, it is not uncommon to see both sovereign bonds and equities falling, as we saw this summer, and have before. This is also the reason why the 'aberrations' or breaks in the utopian positive correlation between yields and equities are much more common in the rising rates environment (associated with things going wrong) than in the falling rates environment.