Operating profit grew 41.7% thanks to the firm's export activities and productivity enhancement.
Apollo Tyres was able to offset the impact of higher input prices and sluggish demand from the domestic auto industry in the December 2007 quarter, thanks to its productivity enhancement measures and export activities.
As a result, the company’s standalone operating profit grew 41.7 per cent y-o-y to Rs 130.9 crore and net sales rose 13.6 per cent to Rs 974.1 crore in the last quarter.
To the company’s credit, its adjusted raw material costs as a percentage of net sales declined 410 basis points y-o-y to 62.6 per cent in Q3 FY08 although the average rubber costs went up 10.8 per cent y-o-y to Rs 94.8 a kg.
The company did not hike the domestic tyre prices in Q3 FY08.
But the export of higher margin passenger car radial tyres helped in offsetting the rising input costs.
The operating profit margin in the last quarter thus went up by a 260 basis points to 13.4 per cent on a y-o-y basis.
The stock however, declined 6 per cent to Rs 52 on Tuesday in line with the sell-off seen on the street.
The company is looking at raising its product prices in Q4 FY07 due to the high rubber prices.
Other inputs such as nylon cord tyre and synthetic rubber have also become dearer thanks to the high crude oil prices.
Meanwhile, Apollo Tyres’ subsidiary Dunlop South Africa reported sales of Rs 265.9 crore in the December 2007 quarter, a growth of 17 per cent y-o-y.
Apollo Tyres is planning to invest Rs 320 crore on expanding its tyre business and Rs 39 crore for setting up an additional wind energy project in Gujarat, in an attempt to leverage the long term growth opportunities.
The stock trades at 13.3 times estimated FY08 and 12.5 times FY09 earnings.
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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