Tata Steel Q3 net flat at Rs 1,069cr
Tata Steel today reported a net profit (standalone) of Rs 1,068.58 crore for the third quarter ended December, 2007 when compared with Rs 1,063.75 crore reported in the corresponding quarter of the previous fiscal.
According to a release issued by the company to the BSE today, total income for Q3FY08 increased 10.3% to Rs 5,040.95 crore from Rs 4,568.72 crore in Q3FY07.
BPCL Q3 net down marginally at Rs 291cr
Bharat Petroleum Corporation (BPCL) today announced a 4.01% decline in net profit at Rs 291.3 crore for the quarter ended December 31, 2007 when compared with Rs 303.5 crore in Q3FY07.
According to a release issued to the Bombay Stock Exchange, total income increased to Rs 29,118.8 crore for the quarter ended December 31, 2007 from Rs 24,354.3 crore for the quarter ended December 31, 2006.
RCom Q3 consolidated net up 48%
Reliance Communications today reported a 48.5% increase in consolidated net profit at Rs 1,372.83 crore for the third quarter ended December 31, 2007 when compared with Rs 924.45 crore in Q3FY07.
According to a release issued by the company to the BSE today, total income for Q3FY08 was up 29.8% at Rs 4,874.20 crore as against Rs 3,755.30 crore in Q3FY07.
On a standalone basis, the net profit for the quarter ended December 31, 2007 dropped 43% to Rs 436.48 crore from Rs 771.04 crore in the quarter ended December 31, 2006. Total income increased 12% to Rs 3,410.82 crore from Rs 3,044.49 crore in Q3FY07.
Tata Motors Q3 net up 9% at Rs 655cr
Tata Motors today reported a 8.75% increase in consolidated net profit at Rs 654.79 crore for the third quarter ended December 31, 2007 when compared with Rs 602.07 crore in Q3FY07.
According to a release issued to the BSE, the company's total income has increased to Rs 9,324.69 crore for the quarter ended December 31, 2007 from Rs 8,189.66 crore in Q3FY07.
The company, on a standalone basis, reported a 2.75% decline in net profit at Rs 499.05 crore for the quarter ended December 31, 2007 as compared to Rs 513.17 crore in Q3FY07.
The company's total income increased to Rs 7,343.64 crore for the quarter ended December 31, 2007 from Rs 6,910.07 crore for the quarter ended December 31, 2006.
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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