Rising steel price is becoming a major cause of concern for the $15 billion auto components sector that is already in trouble due to a lower demand in the domestic market, while exports have also suffered because of a stronger rupee.
Automotive Component Manufacturers’ Association (AMCA) members said the rising price of steel has started affecting their profitability and the situation could get worse in the next two to three quarters.
While components makers said that the price of steel used in the component sector has risen by as much as 25 per cent in the last three months, a steel industry source said that prices of cold rolled coil were up from Rs 38,500 a tonne to Rs 44,000 a tonne (inclusive of taxes), while that for hot rolled coil were up from Rs 34,500 a tonne to Rs 40,000 a tonne since April 2007.
A further increase of steel price by Rs 6,000 a tonne is expected by April 1, according to a component industry source.
“Given the continuous push in input cost, we do not rule out a further price hike in the coming months,” said a steel industry source.
Vishnu Mathur, executive director of ACMA said that a survey of 53 of ACMA’s members showed a clear downward trend in profitability. ACMA represents the interest of 558 large and medium sized parts makers in the country.
“There are another 1000 or 1500 small and medium sized component makers who are not members of ACMA but are also affected by the rising steel price,” said Srivats Ram, chairman of ACMA’s southern region.
An estimated 3,00,000 people are directly and indirectly employed in the auto component business in the country, he said.
Parts makers said that export incentive on steel was inappropriate at this point, as the availability in the domestic industry has already been affected due to rising prices and inadequate supply.
“Since there is an incentive for exports, steel makers tend to benchmark the price in the local market after providing for incentives that they would have earned had they exported,” said a Chennai-based component maker.
The rising steel prices could not have been more badly timed given that the demand for automobiles has also been on the decline. The overall automobile industry shrunk by 5.3 per cent between April 2007 and February 2008.
While sales of passenger vehicles grew by 12 per cent during this period, two wheeler sales fell by 9 per cent and medium and heavy commercial vehicles by 4 per cent.
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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