The major market indices like the Sensex and Nifty are up by about 33 per cent in the first ten months of this calendar year. Midcaps and small caps have gained even more. It is quite possible that 2014 will see still more in the way of gains in the two remaining months.
This is the third calendar year in a row that the market has seen net gains, assuming that there is no huge crash in the two remaining months. In fact, there have been net gains in eleven years of the period 2000-2014.
The longest winning streak of this period was the six years between 2002-2007 (both years inclusive) when the Nifty moved from around 1000 to over 6000. The last losses came in 2011 when the Nifty/ Sensex pair fell by around 25 per cent. Prior to that, the market fell by about 50 per cent in 2008. It also fell by 16 per cent in 2001 and by 15 per cent in 2000. Overall, the CAGR over this 15 year period was about 12 per cent exclusive of dividends (Jan 2000 to Oct 2014 = 178 months).
The stock market is influenced by many variables. For example, GDP growth rates, and trends have some influence on share prices. So do corporate earnings trends, money supply, interest rates, inflation and forex rates. Global growth conditions and global liquidity also have correlations with stockmarket movements.
The textbook technique to try and figure out what factors have high correlation is to run a multiple regression where the variables are checked in turn. A multi-regression would tell us in theory, if there were strong relationships between any or all the above variables and the Indian stockmarket.
Unfortunately, a "multi" doesn't tell us a great deal in this particular case. There are far too many factors involved and all the above variables have some sort of correlation with the Nifty, and many of them have correlations with each other as well. Also, it's a very long period. The Indian economy went through enormous changes between 2000-2014. For that matter, the global economy also saw huge changes and so did geopolitics. Correlation between different variables did not remain stable through this entire period.
However, while rigorous regression analysis is difficult, some observations can be made. The stockmarket return does not seem to correlate very closely to GDP trends, at least in terms of GDP as measured in India.
India measures GDP as growth exceeding Wholesale Price Index (WPI) inflation. In those terms, GDP grew year-on-year every year through 2000-2014 though there were periods of slowdown. But the market did not go up every year. (Graph: Indian GDP Vs Sensex yrly gains?)
Also, GDP may not have grown every year in dollar terms, given periods of currency depreciation. For example, GDP shrank in dollar terms in 2012-13 and earlier in 2008-9, (the Nifty rose by 8 per cent and fell by 38 per cent respectively).
In fact, if we examine the World Bank estimates of Indian GDP in nominal USD, we realise that GDP growth measured in USD was extremely volatile because the exchange rate fluctuations also came into play. There were periods when USD denominated GDP shot up sharply and there were periods when the GDP shrank in USD terms. However, there is divergence even if we compare GDP change in USD -denomination to Sensex returns. (Graph: GDP Vs GDP in USD)
Also GDP may not have grown every year if measured against retail inflation as indicated by consumer price indices. There were times when CPI seemed to be running much higher than WPI. Unfortunately, reliable CPI data doesn't exist covering this entire period.
Index returns and earnings growth also don't correlate as tightly as one would hope. There are periods (like the fiscal 2013-14) when EPS growth was slow but the market gained a lot. Conversely, there are periods (such as the Q4, 2007-8 and the first half of 2008-9) when EPS grew strongly but the market lost a lot of ground. This lack of correlations to earnings is due to the well-known fact that investors always base decisions on future expectations rather than current earnings.
Some correlations do exist between FII attitude and stock market movements. FIIs have much deeper pockets than domestic investors and generally contribute a larger fraction of the trading volumes. Since FII attitude is heavily influenced by global liquidity, and in turn, FII attitude impacts forex rates, there are are also correlations between those variables.
This year (Jan 1, 2014 to Nov 5, 2014) for instance, FIIs have net equity buying of `60,414 crore versus domestic institutional sales of `27,242 crore. Clearly the FII contribution has been a big driver of the 33 per cent gains registered since Jan. Arguably, the index gains of the past three fiscal years have been driven very largely by FII buying.
However, if we go back till April 2006 (FII data is not easily available prior to that date) , the correlations are less marked. There were fiscal years when FIIs were net sellers and the market rose.
At the monthly level, which is probably more useful for traders, the correlations and trends are more strongly marked. There has never been a very extended period when FII attitude has been headed in one direction while the market indices went in the other direction.
Between April 2006- Oct 2014 , across a total of 103 months, FIIs were net buyers in 56 months buying total equity of `201,743 crore. They were net sellers in 47 months. The Sensex went up in 60 of those months and it lost ground 43 times. On 45 occasions, a month of net FII buying coincided with net gains in the sharemarket. On 31 occasions, a month of net FII selling coincided with net losses in the index. This is quite significant.
GDP data and earnings records have lead-lag relationships with stock prices. FII attitude directly influences stock prices without any lags. So it is a more immediate impact. If there is one single key variable that a trader should track and analyse, it is probably FII attitude.
Unfortunately, FII attitude is not that easy to pick up in real time. The analyst needs to work through data and leads from multiple sources including institutional research reports, public statements from FIIs , global allocations, prior track records, changes in the composition of commonly followed global market indices, etc. There is some degree of predictability to FII allocations but it's not easy to decipher.
FIIs generally operate in herds. They tend to be bullish on India (or bearish) by consensus and they also tend to be interested in the same stocks when they are bullish. Given that 3:1 ratio, where the stockmarket moves in tandem with FII allocations three times out of four, going with the FII herd is a paying proposition.
The writer is an independent financial analyst.
This article was originally published on January 02, 2015.
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