Highlights for the quarter ended March 31, 2008
* Wipro revenue increased 32% YoY to Rs 5,700 crore
* Net profit increased 3% YoY to Rs 880 crore. Adjusting for one-time tax reversals in Q4FY07, the YoY profit after tax (PAT) growth will be 11.3%
* Revenue of Wipro's global IT business in rupee terms stood at Rs 3,833 crore - a YoY increase of 26%
* During the quarter, Wipro IT business won three multi-year multi-million dollar deals
* Global IT services & products added 29 new clients in the quarter
* India, Middle East & Asia Pac business recorded 41% YoY growth in revenues to Rs 1,096 crore
* Wipro Consumer Care and Lighting business revenue grew 111% YoY and PBIT grew 136% YoY
Highlights for the year-ended March 31, 2008
* Wipro revenue increased 33% to Rs 19,957 crore
* PAT grew 12% to Rs 3,283 crore
* Revenue of combined IT businesses was $4.3 billion - a 43% YoY growth
* Revenue of Wipro's Global IT business in dollar terms was $3.39 billion - a YoY growth of 38%. In rupee terms,revenue stood at Rs 13,642 crores - a YoY growth of 23%
* Technology business in Global IT services segment crossed a landmark of $1 billion (around Rs 4,000 crore) of annual revenue and business from the Americas and Europe crossed $2 billion and $1 billion, respectively. Revenue from India, Middle East and Asia Pacific business grew by 51% to Rs 3,746 crore.
* Wipro Consumer Care and Lighting business, including acquisition of Unza, increased revenue 86% YoY
* The board recommended a final cash dividend of Rs 4 per share/ADS. This, added with an interim dividend of Rs 2 per share, will take the total dividend to Rs 6 per share
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.
1 comment:
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