Despite wage hikes, an appreciating rupee, and fewer working days in the quarter nibbling at its net profit margins, the soaps to IT major, Wipro recorded a consolidated net profit (Indian GAAP figures) of Rs 854 crore for the third quarter ended December 31, 2007 -- a 11.6% growth over the corresponding quarter last financial year. The company attributed the growth in profit to addition of new clients and improvement in price realisation.
The consolidated revenue for the quarter went up 33.5% to Rs 5,303 crore when compared with the same period last financial year. On a sequential basis, the net profit of the company went up 4% while consolidated revenue increased 11%.
"The results for the quarter are satisfying. We continue to see good momentum in all our businesses. Revenues from our global IT services at $910.1 million were ahead of our guidance ($905 million). Our financial services business grew nearly double digit sequentially during the quarter despite this challenging times for the sector," said Azim Premji, chairman, Wipro.
On the operational front, the company saw a 200 basis points increase sequentially in the mix of revenues from fixed price projects. "Our price realisation improved during the quarter by about 50 basis points sequentially. We had strong growth in our BPO business and testing services. Our top 10 clients grew at a healthy rate during the quarter," he added.
Chief financial officer Suresh Senapathy said improved realisation and rationalisation of bulge mix helped Wipro in fully mitigating the pressure on profitability on account of foreign exchange impact. The drop in the global IT margins by 100 basis points sequentially was attributed, primarily to the Infocrossing acquisition. The company has seen an increase in the number $50 million clients and now has its first $100 million client.
During the quarter, Wipro’s IT business won five multi-year multi-million dollar deals. The company’s India, Middle East and APAC IT business recorded 49% YoY growth in PBIT and 39% YoY growth in revenues (Rs 971.6 crore). Wipro Consumer Care and Lighting business revenue (Rs 434.7 crore) grew 107% YoY and PBIT grew 99% YoY. It crossed Rs 400 crore in revenue per quarter.
The company added 39 new clients during the quarter of which nine were technology clients with the rest 30 being enterprise clients. The number of employees as of December 31, 2007, was 79,832. It includes 59,925 employees in the IT services and product business and 19,907 in the BPO services business. The company added 2,389 employees in the IT services and products business during the quarter.
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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