Matesk today reported a 65% increase in net profit at Rs 35 crore for the third quarter ended March 31, 2007 from Rs 21.22 crore (excluding the contributions from Deloitte joint venture) in the corresponding quarter of the last fiscal.
Revenue for the quarter ended March 31, 2008 at Rs 238.9 crore was up 22% from Rs 195.3 crore (excluding Deloitte JV) for the quarter ended March 31, 2007.
If the Deloitte JV numbers are taken into account, the company’s net profit was down 13% from Rs 40.23 crore and revenue was up 11% from Rs 214.79 crore.
According to a release issued by Mastek today, total income, in dollar terms, increased 33% to $59.9 million in the quarter under review from $44.9 million in the corresponding period of the last fiscal. PAT was higher by 80% at $8.8million when compared with $4.9 million.
For the April-June 2008 quarter, Mastek expects consolidated total income (inclusive of other income) to be in the range of Rs 245-250 crore. Net profit after tax and minority interest is likely to be in the range of Rs 37-38 crore.
Sudhakar Ram, chairman and managing director, Mastek, said: "Other than the STG acquisition, we also had two major deals that added to the quarter numbers. Going ahead, for the full year in dollar terms, we are expecting a growth of 38-39%. For the April-June quarter we are expecting a topline of Rs 240-250 crore and net profit in the range of Rs 37-38 crore."
The acquisition of US-based System Task Group (STG) contributed close to Rs 16 core to the topline due to which the company surpassed its own guidance of Rs 220-225 crore. Its net profit, on sequential basis, also crossed the guidance of Rs 29-30 crore.
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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