Industrial production growth in November declined to 5.3 per cent, against 15.8 per cent in the same month last year, the lowest since October 2006 when it stood at 4.51 per cent and the lowest in the 2007 calendar year.
The decline has been attributed to several factors: a high base effect, fewer working days owing to Diwali and the effects of high interest rates and rapid currency appreciation.
October 2007 had seen healthy industrial production growth of 12 per cent, on account of robust festive demand. With that demand petering out, industrial production growth declined in the month under review.
The decline in industrial production in November 2007 was driven by a dip in production growth of the manufacturing (which comprises 80 per cent of the index of industrial production-IIP), electricity and mining sectors.
Growth in production in the six core infrastructure industries in November dipped to 5.3 per cent, down from 9.6 per cent the same month a year ago. The core sector comprises 26.7 per cent of the index.
"This is a weak rate of growth. RBI's tight monetary policy is manifesting in low industrial production growth numbers," said Shubhada Rao, chief economist, Yes Bank. Rao had forecast a higher, around seven per cent IIP growth for the month.
Economists expect a mild recovery in industrial production in December 2007.
"The December data are likely to show a recovery from the current levels, though the overall trend in industrial production growth would be for moderation, compared to the trend last year," said Rajeev Malik, senior economist, JPMorgan Chase Bank.
JPMorgan had pegged November industrial growth at 5.6 per cent.
Though consumer demand has taken a hit due to high interest rates, investment demand continues to be strong, as indicated by 11.2 per cent growth in the machinery and equipment sector and 24.5 per cent growth in capital goods production over 29.4 per cent a year ago.
Consumer durables production dipped 4.1 per cent in November against 10.1 per cent growth a year ago. Consumer non-durables production also dipped 2.1 per cent from a growth rate of 14.8 per cent in the same month of the previous year.
Goldman Sachs Asia Economic Research Group also expects a bounce-back in December, but said trend IP growth will moderate in 2008.
It does not expect a rate change in the near term . "We expect the central bank will keep interest rates on hold in its January 29 meeting. In FY09 we expect the RBI to start lowering interest rates," the research group said.
Understanding Short Term Trading
Before I begin, this blog is not for intraday traders. My definition of short term implies duration of around 2 to 3 months.
Short Term stock picking is no rocket science, but rather a visual interpretation of technical charts. A basic moving average on a time frame chart will show the direction of the securities movement.
Moving averages is a mathematical results calculated by averaging a number of past data points. Moving averages (MA) in it's basic form is calculated by taking the arithmetic mean of a given set of values on a rolling window of timeframe. Once the value of MA has been calculated, they are plotted onto a chart and then connected to create a moving average line. Typical moving averages used for short term trading are 50 MA and 100 MA.
Types of Moving Averages
1) Simple Moving Average (SMA)
SMA is calculated by taking the arithmetic mean of a given set of values on a rolling window of timeframe. The usefulness of the SMA is limited because each point in the data series is weighted the same, regardless of where it occurs in the sequence. Critics argue that the most recent data is more significant than the older data and should have a greater influence on the final result.
2) Exponential Moving Average (EMA)
EMA overcomes the limits of SMA, where more weight is given to the recent prices in an attempt to make it more responsive to new information. When calculating the first point of the EMA, we may notice that there is no value available to use as the previous EMA. This small problem can be solved by starting the calculation with a simple moving average and continuing on with calculating the EMA.
The primary functions of a moving average is to identify trends and reversals, measure the strength of an asset's momentum and determine potential areas where an asset will find support or resistance. Moving averages are lagging indicator, which means they do not predict new trend, but confirm trends once they have been established.
A stock is deemed to be in an uptrend when the price is above a moving average and the average is sloping upward. Conversely, a trader will use a price below a downward sloping average to confirm a downtrend. Many traders will only consider holding a long position in an asset when the price is trading above a moving average.
In general, short-term momentum can be gauged by looking at moving averages that focus on time periods of 50 days or less. Looking at moving averages that are created with a period of 50 to 100 days is generally regarded as a good measure of medium-term momentum. Finally, any moving average that uses 100 days or more in the calculation can be used as a measure of long-term momentum.
Support, resistence and stoploss can be infered by referring the closet MA below or above the market price. The other factor that is used in short term momentum is the trading volume. The moving averages along with the trading volume can provide a better insight to short term movement.
Markets are moved by their largest participants - I believe this is the single most important principle in short-term trading. Accordingly, I track the presence of large traders by determining how much volume is in the market and how that compares to average. Because volume correlates very highly with volatility, the market's relative volume helps you determine the amount of movement likely at any given time frame--and it helps you handicap the odds of trending vs. remaining slow and range bound.
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