Market growth hinges on IIP support

The gains during December and January suggest increased economic activity. If the IIP does not confirm this, there could be correction

The release of new macro economic data influences short-term sentiment. There is always a sense of anticipation in the stockmarket on days when new are released. Price volatility on those days is definitely driven by data.

Are there sustainable long-term correlations with shareprice movements? In theory, is more predictable than stockprices. Hence, if one finds correlations, there could be an edge in investment decisions.

There are difficulties to investigating this. The analyst looks at lagged data releases and makes forward projections. This is akin to looking in the rear view mirror and driving forward. Price movements in contrast, anticipate data and the market often moves before data shows clear trends.

Two key macro-economic time series are the Index of Industrial Production (IIP) and the Wholesale Price Index (WPI). Both are widely followed by market players. Both and have major data-gathering problems. In the WPI, price changes are often incorporated late. In the IIP, too, manufacturing unit numbers are often left unchanged for months. In both series, a preliminary number is released and later revised, and the revisions can be large.

There are additional issues with data presentation and focus. The market generally looks at the point-to-point (P2P) change over the levels of a year ago. This P2P method is easy to compute and automatically deseasonalises. But P2P produces odd statistical results if the base month had unusually high or low levels. Hence, it can introduce distortions and often masks trends.

There are better ways to track or IIP. But those are a little more complex even if more accurate. For example, moving average systems, or regression, present smoother and more accurate views of trends, by removing base effects and reducing the effect of temporary fluctuations.

However, the bulk of market players never bother with such nuanced approaches. So you have to take note of the P2P numbers. You may personally develop a better understanding of the data by using better tools and maybe, find instances where interpretation based on P2P is wrong.

Another point is often forgotten. The analyst has to drill down, comparing specific segments and components to specific sectors. The is a composite of several broad groups and many individual items with different weights. Few corporates are affected by food prices. But the prices of minerals, non-food commodities such as metals, energy fuels and of manufactured goods do affect specific listed companies.

In the case of the IIP, mining, manufacturing and electricity are the three broad groups with different weights. Again changes in production levels in each of these areas affect different corporate sectors in different degrees. Disaggregation is necessary to pick up those details.

Comparing the series to the Sensex, we run into another difficulty. The current extends back to April 2005. Since then, the has fallen only for a few months during the global recession of 2008 and 2009. At other times, inflation has been high, moderate or low, but never negative. We don't know what could happen to stock prices during an extended period when inflation was low or downtrending.

Since 2005, the stockmarket has gone through two complete cycles of bull-bear and is now into a third cycle. It would be safer to assume there is no great correlation in the long-term between inflation data and share index movements.

The is more interesting. Since tracks business cycles, it has seen several periods of negative movements like the stockmarket. There is definite correlation between the and the IIP. But the stock market leads the by several months both in uptrends, as well as in downtrends. Specific sectors like capital goods manufacturers and power utilities are more sensitive to changes in the IIP.

The is, therefore, a lagging indicator. It can confirm if the market is trending in a sustainable fashion or not, as the case may be. If there are divergences when the market is trending up and the values are negative or flat, one has to be watchful and wait for the to move up, or shareprices to move down.

As of now, the has trended up since August 2012, whereas the has been flat or rangebound between August-November 2012. That's a four month long divergence at the least. Sharemarket gains through December and January suggest economic activity picked up. If the doesn't confirm this soon by jumping in December-January, the market could correct down.

image
Business Standard
177 22
Business Standard

Market growth hinges on IIP support

The gains during December and January suggest increased economic activity. If the IIP does not confirm this, there could be correction

Devangshu Datta  |  New Delhi 

The release of new macro economic data influences short-term sentiment. There is always a sense of anticipation in the stockmarket on days when new are released. Price volatility on those days is definitely driven by data.

Are there sustainable long-term correlations with shareprice movements? In theory, is more predictable than stockprices. Hence, if one finds correlations, there could be an edge in investment decisions.

There are difficulties to investigating this. The analyst looks at lagged data releases and makes forward projections. This is akin to looking in the rear view mirror and driving forward. Price movements in contrast, anticipate data and the market often moves before data shows clear trends.

Two key macro-economic time series are the Index of Industrial Production (IIP) and the Wholesale Price Index (WPI). Both are widely followed by market players. Both and have major data-gathering problems. In the WPI, price changes are often incorporated late. In the IIP, too, manufacturing unit numbers are often left unchanged for months. In both series, a preliminary number is released and later revised, and the revisions can be large.

There are additional issues with data presentation and focus. The market generally looks at the point-to-point (P2P) change over the levels of a year ago. This P2P method is easy to compute and automatically deseasonalises. But P2P produces odd statistical results if the base month had unusually high or low levels. Hence, it can introduce distortions and often masks trends.

There are better ways to track or IIP. But those are a little more complex even if more accurate. For example, moving average systems, or regression, present smoother and more accurate views of trends, by removing base effects and reducing the effect of temporary fluctuations.

However, the bulk of market players never bother with such nuanced approaches. So you have to take note of the P2P numbers. You may personally develop a better understanding of the data by using better tools and maybe, find instances where interpretation based on P2P is wrong.

Another point is often forgotten. The analyst has to drill down, comparing specific segments and components to specific sectors. The is a composite of several broad groups and many individual items with different weights. Few corporates are affected by food prices. But the prices of minerals, non-food commodities such as metals, energy fuels and of manufactured goods do affect specific listed companies.

In the case of the IIP, mining, manufacturing and electricity are the three broad groups with different weights. Again changes in production levels in each of these areas affect different corporate sectors in different degrees. Disaggregation is necessary to pick up those details.

Comparing the series to the Sensex, we run into another difficulty. The current extends back to April 2005. Since then, the has fallen only for a few months during the global recession of 2008 and 2009. At other times, inflation has been high, moderate or low, but never negative. We don't know what could happen to stock prices during an extended period when inflation was low or downtrending.

Since 2005, the stockmarket has gone through two complete cycles of bull-bear and is now into a third cycle. It would be safer to assume there is no great correlation in the long-term between inflation data and share index movements.

The is more interesting. Since tracks business cycles, it has seen several periods of negative movements like the stockmarket. There is definite correlation between the and the IIP. But the stock market leads the by several months both in uptrends, as well as in downtrends. Specific sectors like capital goods manufacturers and power utilities are more sensitive to changes in the IIP.

The is, therefore, a lagging indicator. It can confirm if the market is trending in a sustainable fashion or not, as the case may be. If there are divergences when the market is trending up and the values are negative or flat, one has to be watchful and wait for the to move up, or shareprices to move down.

As of now, the has trended up since August 2012, whereas the has been flat or rangebound between August-November 2012. That's a four month long divergence at the least. Sharemarket gains through December and January suggest economic activity picked up. If the doesn't confirm this soon by jumping in December-January, the market could correct down.

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Market growth hinges on IIP support

The gains during December and January suggest increased economic activity. If the IIP does not confirm this, there could be correction

The release of new macro economic data influences short-term sentiment. There is always a sense of anticipation in the stockmarket on days when new macro-economic data are released. Price volatility on those days is definitely driven by data.

The release of new macro economic data influences short-term sentiment. There is always a sense of anticipation in the stockmarket on days when new are released. Price volatility on those days is definitely driven by data.

Are there sustainable long-term correlations with shareprice movements? In theory, is more predictable than stockprices. Hence, if one finds correlations, there could be an edge in investment decisions.

There are difficulties to investigating this. The analyst looks at lagged data releases and makes forward projections. This is akin to looking in the rear view mirror and driving forward. Price movements in contrast, anticipate data and the market often moves before data shows clear trends.

Two key macro-economic time series are the Index of Industrial Production (IIP) and the Wholesale Price Index (WPI). Both are widely followed by market players. Both and have major data-gathering problems. In the WPI, price changes are often incorporated late. In the IIP, too, manufacturing unit numbers are often left unchanged for months. In both series, a preliminary number is released and later revised, and the revisions can be large.

There are additional issues with data presentation and focus. The market generally looks at the point-to-point (P2P) change over the levels of a year ago. This P2P method is easy to compute and automatically deseasonalises. But P2P produces odd statistical results if the base month had unusually high or low levels. Hence, it can introduce distortions and often masks trends.

There are better ways to track or IIP. But those are a little more complex even if more accurate. For example, moving average systems, or regression, present smoother and more accurate views of trends, by removing base effects and reducing the effect of temporary fluctuations.

However, the bulk of market players never bother with such nuanced approaches. So you have to take note of the P2P numbers. You may personally develop a better understanding of the data by using better tools and maybe, find instances where interpretation based on P2P is wrong.

Another point is often forgotten. The analyst has to drill down, comparing specific segments and components to specific sectors. The is a composite of several broad groups and many individual items with different weights. Few corporates are affected by food prices. But the prices of minerals, non-food commodities such as metals, energy fuels and of manufactured goods do affect specific listed companies.

In the case of the IIP, mining, manufacturing and electricity are the three broad groups with different weights. Again changes in production levels in each of these areas affect different corporate sectors in different degrees. Disaggregation is necessary to pick up those details.

Comparing the series to the Sensex, we run into another difficulty. The current extends back to April 2005. Since then, the has fallen only for a few months during the global recession of 2008 and 2009. At other times, inflation has been high, moderate or low, but never negative. We don't know what could happen to stock prices during an extended period when inflation was low or downtrending.

Since 2005, the stockmarket has gone through two complete cycles of bull-bear and is now into a third cycle. It would be safer to assume there is no great correlation in the long-term between inflation data and share index movements.

The is more interesting. Since tracks business cycles, it has seen several periods of negative movements like the stockmarket. There is definite correlation between the and the IIP. But the stock market leads the by several months both in uptrends, as well as in downtrends. Specific sectors like capital goods manufacturers and power utilities are more sensitive to changes in the IIP.

The is, therefore, a lagging indicator. It can confirm if the market is trending in a sustainable fashion or not, as the case may be. If there are divergences when the market is trending up and the values are negative or flat, one has to be watchful and wait for the to move up, or shareprices to move down.

As of now, the has trended up since August 2012, whereas the has been flat or rangebound between August-November 2012. That's a four month long divergence at the least. Sharemarket gains through December and January suggest economic activity picked up. If the doesn't confirm this soon by jumping in December-January, the market could correct down.

image
Business Standard
177 22

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