A day after Minister for Steel, Chemicals and Fertiliser Ram Vilas Paswan told Parliament that steel prices would come down by Rs 500 a tonne on account of the 2 percentage point reduction in Cenvat, makers of flat and long products quietly raised prices by Rs 1,500 to Rs 3,000 a tonne on March 4.
Producers have raised prices by Rs 1,500 to Rs 3,000 a tonne for long products, which are used in the construction industry. For flat products, which go into consumer durables and automobiles, the increase is Rs 2,500 to Rs 3,000 a tonne.
The price increase kicks in with immediate effect and has been implemented by both public and private sector producers.
However, apart from Tata Steel, the world’s sixth largest steel producer, and cold-rolled and galvanised steel maker Uttam Galva Steels, no producer is officially acknowledging the price rise.
“We were waiting for the meeting with the steel minister. Even though the agenda for the meeting was review of projects, we were expecting some directive on prices,” said an industry source.
Paswan, however, told an Assocham meeting in Mumbai yesterday that his ministry would not intervene in pricing decisions owing to the strong criticism it has attracted on this account.
He, however, qualified the statement by saying that non-interference would hold if steel producers did not raise prices at a higher rate than the rise in input costs.
With this increase, the ruling price of TMT bars, a widely-used long product segment, now stands at Rs 43,000 a tonne and that of hot rolled coil (HRC) in flat products around Rs 42,000 a tonne.
Yesterday’s price rise comes a month after steel producers partially rolled back prices in February at Paswan’s behest. Prices had been raised by Rs 600 to Rs 900 a tonne in January and again by an average of Rs 2,500 a tonne in February on account of steep increases in raw material costs such as coking coal and iron ore.
Producers were made to roll back prices by Rs 500 a tonne for TMT bars and rounds and Rs 1,000 a tonne for other products.
Costs between April 2007 and January 2008 had increased by Rs 6,000 to Rs 7,000 per tonne. Government-owned NMDC Ltd, the main domestic supplier of iron ore, raised prices 48 per cent in October and another increase of at least 65 per cent is expected in April, in line with the international iron ore prices.
Most steel producers without captive mines source their iron ore from NMDC.
Spot coking coal prices between April and February have almost doubled and international companies are looking at a 40 to 50 per cent increase in prices from April 2008.
Among the public sector steel producers, Steel Authority of India Ltd is covered 35 per cent for coking coal and 100 per cent for iron ore through captive sources.
Rashtriya Ispat Nigam Ltd (RINL), the other public sector producer, has no captive resources.
Among the major private producers, Tata Steel with Corus has 20 per cent iron ore security and 15 per cent in coal, JSW Steel has 30 per cent iron ore security and imports 100 per cent of its coking coal.
Essar Steel’s only captive raw material source is its 1.4 billion tonne reserves via its acquisition of Minnesota Steel, which is yet to be commercially developed. Ispat Industries has no captive mines.
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Wednesday, March 5, 2008
Steel prices raised on the quiet
Posted by Srivatsan at 6:17 PM
Labels: India Steel Sector
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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.
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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