Pfizer today reported a 220% increase in consolidated net profit at Rs 340 crore for the year ended November 30, 2007 when compared with Rs 106.33 crore in FY06.
According to a release issued to the BSE today, total income increased to Rs 1,019.76 crore for the year ended November 30, 2007 from Rs 726.39 crore for the year ended November 30, 2006.
The company, on a stand-alone basis, posted a net profit of Rs 22.06 crore for the quarter ended November 30, 2007 when compared with Rs 17 crore for the quarter ended November 30, 2006. Total income increased from Rs 182.90 crore for the quarter ended November 30, 2006 to Rs 199.66 crore for the quarter ended November 30, 2007.
The company posted a net profit of Rs 338.93 crore for the year ended November 30, 2007 as against Rs 105.73 crore for the year ended November 30, 2006. Total income has increased from Rs 721.88 crore to Rs 1,015.36 crore.
The board has recommended a total dividend of 275% i.e Rs 27.50 per equity share of Rs 10 each for the financial year ended November 30, 2007 including a normal dividend of Rs 12.50 (125%) per share and an additional dividend of Rs 15 (150%) per share in view of the sale of four consumer healthcare brands to Johnson & Johnson.
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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