O Ashuji....
Role of luck is least appreciated in stock market where it plays the largest role. It plays the largest role in fundamental analysis (it is no way to say that analyzing financial statements is not needed but linking that with price outcome of stock can be dangerous). In past, I had put a blog as to why analyzing stock price movement fundamentally is very difficult. (Blog - Analyzing Price Moves Fundamentally is The Most Difficult Thing.....dated - 17th March, 2013, Link - http://speculationanart.blogspot.in/2013/03/analyzing-price-moves-fundamentally-is.html). In his latest memo, Howard Marks does great job in explaining the role of luck in investing. Excerpt from the Memo...
The point is that we assemble our
portfolios, and future events determine whether our performance will be
rewarded or punished. People whose expectations are borne out generally make
money, and those whose aren't lose. That process sounds very fact-based,
meritocratic and luck-free, and thus dependable. But that’s only the case on
average and in the longest-term sense.
1) Sometimes, even though an
investor’s projections may be far too optimistic relative to what he should
have expected – a.k.a. “wrong” – the investor is bailed out by unforeseeable
positive developments, or even by non-fundamentally based price appreciation.
Either way, the stock rises and the investor is applauded. I’d say he was “right
for the wrong reason” (or "lucky).
2) Alternatively, a prudent,
skillful investor may formulate a reasonable view of the future, only to see
the world go off the rails and his investments fail. He might be described as
“wrong for the wrong reason”(or "unlucky”).
3) An investor may take an
appropriately cautious stance – let’s say toward tech stocks in 1997 or residential
mortgage backed securities in 2005 – only to see an irrationally overpriced
market become more so, as prices soar
for years. He looks terrible, a victim of the old adage that “being too far
ahead of your time is indistinguishable from being wrong.”
4) Further, in a special case of
being wrong as to timing although perhaps not fundamentals, an investor may
take a concentrated position in a laughably underpriced stock, using a huge
amount of borrowed money. But before the expected appreciation can take place,
a market crash brings on a margin call, and he’s wiped out. As John Maynard
Keynes said, “The market can remain irrational longer than you can remain
solvent.”
Stock prices are subject outcome based on wide range of issues, only thing constant is that they will move. Forecasting of stock prices is thus very difficult if not impossible job. Odds of price swings can be estimated due to nature of price clustering. Again we are only talking about Odds.
2014 - BIG BINARY YEAR FOR NIFTY (INDIA)
Before we get into numbers, I will once again put certain points about nature of price move in stock market.
Markets are Risky – Extreme price
swings are the norm in financial markets. Price movements do not follow the
well-mannered bell curve assumed in modern finance; they follow more violent
curve that makes and investor’s ride much bumpier.
· 1) Trouble runs in streaks – Market turbulence
tends to cluster.
· 2) Markets have a personality – Prices are not
driven solely by real world events, news and people. When investors,
speculators, industrialists, and bankers come together in a real marketplace, a special, new kind of dynamic emerges – greater than, and different from, the
sum of the parts. Fundamental process by which prices react to news does not
change. Mandelbrot analysis of cotton price over the past century shows the
same broad pattern of price variability at the turn of last century when prices
were unregulated, as there was in the 1930’s when prices were regulated as part of the New Deal.
· 3) Markets mislead – Patterns are the fool’s gold
of financial markets. The power of chance suffices to create spurious patterns
and pseudo-cycles that, for the entire world, appear predictable and bankable.
But a financial market is especially prone to such statistical mirages. Bubbles and crashes are inherent to markets.
They are the inevitable consequence of the human need to find patterns in the
pattern less.
· 4) The size of price changes clearly clusters
together. Big changes often come together in rapid succession, and then come
long stretches of minor price changes. (Trouble runs in streaks)
Price levels/changes exhibit some
kind of irregularity regularly. The charts sometimes rise or fall in long
waves, or with small waves superimposed on bigger waves. But none of this
phenomenon – clusters of volatility, or irregular trends – resembles any of the
cycles, waves, or other patterns that characterise those aspects of nature
controlled through well-established science. There are no familiar sine or
cosine waves, with regular periods.
These peculiar patterns cannot be predicted; and so humans who bet on
them often lose. Yet there clearly is a system to them. It is as if the charts
have a memory of past. If the price changes start to cluster, or the prices
themselves start to rise, they have a slight tendency to keep doing so for a
while – and then, without warning, the stop. They may even flip to opposite
trend.
(Source - The (Mis)Behavior of Markets - Benoit Mandelbrot)
Let the Data Talk....
One can try to estimate odds of price swings based on how price swings has been. Compressed price movement will be followed by wider swings in prices. Just like spring,when its compressed or stretched, the force it
exerts is proportional to its change in length. Compression/Expansion of price moves can be measured through price swings based on various time frames (daily, weekly, monthly, yearly).
Daily Compression
Table 1- Number of days with more than 3% move (Nifty)
1) 2012 was historic with none trading days having more than 3% move in a single day.
2) Last 4 years 2010-2013 have been relatively compressed as can be seen from lesser number days with move greater than 3%.
Weekly Compression
Table 2 - Number of weeks with more than 4% move (Nifty)
Extreme compression in this data point in last 2 years. 2013 had just one week with more than 4% move.
Monthly Compression
Table 3 - Absolute % Move on Monthly Basis and Cumulative Score
Very low score for last 4 years (2010-13) as can be seen from last column.
Yearly Compression
1) 2013 most compressed year in terms of high low range. 2012 and 2013 were back-to-back compressed years.
2) Extremely ranged market for last 4 years given the returns.
Conclusions
1) Data is largely self explanatory in terms of compressed markets.
2) Market's range (excluding years when bull market started or ended - 2000, 2001, 2003, 2008 & 2009) is typically 40%+. This is range not returns. Even if one were to apply 30% range for market for 2014, Outcome of Nifty could be very different than what most expect. There could be 4 scenarios - Trending market on upside or downside, Choppy market with move up and then down or other way round. Under all 4 scenarios with 30% range, Nifty levels would take most by surprise. 30% range is relatively modest (lower than typical range and coming out of compressed years).
3) Best way to play such scenario is buying out of the money options. Since Indian markets are not liquid beyond one month, one can play straddles (3-5% pair) in a step up way till a month which clicks in a big way.