# Category: Investing Insight

Investing insight to make you a better investor.

## Nifty Statistical Study

### Returns vs. Log Returns

We had discussed how the most important assumption in finance is that returns are normally distributed. Also, the benefit of using returns, versus prices, is normalization. All your variables are now on the same scale and can be compared easily. But if you pick up any book on financial statistical modelling, you’ll run into log returns more often.

As you can see from the charts above, visually, they don’t make a difference. However, taking the log of returns makes the math easier:

1. If we assume that prices are distributed log normally, then log(1+ri), where ri is the ith period return, is normally distributed. And we know how to work with normal distributions.
2. When returns are very small, log(1+ri) ≈ r
3. Calculating compounding return goes from series multiplication (∏) to series summation (∑).

### Quantiles

The easiest way to summarize a frequency distribution is through quantiles. Quantiles are values which divide the distribution such that there is a given proportion of observations below the quantile. For example, the median is a quantile such that half the points are less than or equal to it and half are greater than or equal to it.

Raw-returns (%):

 1% 5% 25% 50% 75% 95% 99% -4.1986 -2.4994 -0.6992 0.0967 0.8585 2.4387 4.4465

Log-returns:

 1% 5% 25% 50% 75% 95% 99% -0.04289 -0.0253 -0.0070 0.0009 0.0085 0.0240 0.0435

### Q-Q Plot

Once we know the qunatiles of our log returns, we can compare it to that of a normal distribution. When you plot the quantiles of the sample (Nifty daily log returns) to the quantiles of a theoretical normal distribution, you get a visual feel for the outliers – the fat tails.

This plot shows that both tails are heavier than the tails of the normal distribution. So, although using log returns and assuming that prices are distributed log normally makes the math easier, we should always be aware that it is a sleight of hand.

To be continued…

Sources:

## Musings on stock-market forecasts

### Traffic jams

Say there’s a traffic jam on a busy road. When new vehicles try to enter the same route, the drivers hear on the radio that there’s a jam ahead and adapt by finding another route. Suppose there is only one alternate route. What happens now? The alternate route forms a second jam!

Later entrants have to choose between the two jams. Predicting the actions of this new group is very hard to do. Maybe the second jam is worse than the first. By the time we hit this third layer of participants, predicting the behavior of the system has become extremely difficult, if not impossible.

Weather is a complex system. However, if, on Thursday, the forecast is for rain on Sunday, is the rain any less likely to occur? No. The act of predicting has not influenced the outcome. Although near-term weather is extremely complex, with many interacting parts leading to higher order outcomes, it does have an element of predictability.

The stock-market is a complex adaptive system. Traders and investors in the market are interacting with one another constantly and adapting their behavior to what they know about others’ behavior. The key element of a complex adaptive system is the social element.

For example, Meredith Whitney predicted the crash of Citibank in late 2007.

She went on to setup her own advisory firm, Meredith Whitney Advisory Group, and made a similar call on American municipal bonds in late 2010 on national television. Retail investors sold in panic. But for the the most parts, nothing happened.

### Reflexivity

Reflexivity refers to circular relationships between cause and effect. A reflexive relationship is bidirectional with both the cause and the effect affecting one another in a situation that does not render both functions causes and effects. It flies in the face of equilibrium theory, which stipulates that markets move towards equilibrium and that non-equilibrium fluctuations are merely random noise that will soon be corrected.

Reflexivity asserts that prices do in fact influence the fundamentals and that these newly-influenced set of fundamentals then proceed to change expectations, thus influencing prices; the process continues in a self-reinforcing pattern.

### Takeaway

Behavioral dynamics is key to understanding complex adaptive systems. One should have a mental model that incorporates higher-order thinking when it comes to navigating the markets.

The big question is, how different is listening to stock-market predictions from listening to an astrologer, reading horoscopes or believing in vastu?

To quote German theologian and martyr Dietrich Bonhoeffer:

“…how wrong it is to use God as a stop-gap for the incompleteness of our knowledge. If in fact the frontiers of knowledge are being pushed further and further back (and that is bound to be the case), then God is being pushed back with them, and is therefore continually in retreat. We are to find God in what we know, not in what we don’t know.”

## What if: abki baar NO modi sarkar?

What if Modi fails to become the prime minister of India? Some are expecting the Nifty to crack by 1000 points in such a scenario. Although not a perfect hedge, a bear spread makes sense – think of it as insuring your portfolio against the adverse outcome.

### NIFTY May 6600/6750 Long Put Spread

The Nifty will have to expire below 6695.00 for the trade to be profitable. The max profit is Rs. 4750.00 and the cost to enter the trade (and max loss) is Rs. 2750.00.

### Thought process

This trade can be best described as buying a limited form of insurance. You are assuming that the Nifty will not fall too far below 6600 and losses are not going to be catastrophic. You could go farther down the option chain if you are feeling too nervous, but then your δs will get smaller so you will have to buy more spreads to cover your portfolio.

For example, if you did a NIFTY May 6500/6600 Long Put Spread instead, you will be moving the break-even to 6569.70, pay less (Rs. 1515.00) for a max profit of Rs. 3485.00. But the delta of this spread is -0.08 vs. -0.15 for spread described above.

The result of this election is expected to be declared on 16 May (Friday). Exit soon after election results are announced or right before it if the trade is profitable.

## Of whatsnexters, horoscopes and personal experiences

### Can Stock Market Forecasters Forecast?

It’s time we stopped listening to the “whatsnexters.” These folks are everywhere in the financial media pontificating confidently about what they can’t possibly know — what’s next for the economy or the stock market.

### Good to Great

The story of success swarms statistics. And there’s always enough random success to justify almost anything to someone who wants to believe.

### A case for rules-based investment methodology

Our personal experiences disproportionately impact our investing behavior. By simply repeating investing behaviors that resulted in good outcomes for us in the past, and avoiding those that resulted in poor outcomes, we’re potentially eliminating important information that could help future investment performance.

## Long term ≠ Always

Previously, we had highlighted the difference between ‘Long-Term Investing vs. Buy And Hold Forever’ (src) Economies shift, competition catches up, moats wither away. So it is essential to have a periodic review of your portfolio.

Recently, in a post titled ‘The answer is that there is no answer’ (src) we saw the inherent contradictions that exist in asset management.

James Osborne over at Bason Asset Management brings it together brilliantly:

The world is a complex place and how each generation of investors experiences these long term truths may be very different. This is simply a reminder that in some periods, we may have a different experience than these long-term facts.

Most importantly we should be aware that “over the long term” doesn’t mean “always” in advance so that we aren’t surprised when we experience the opposite result of our long-term beliefs.

The whole thing is worth a read.