UCO Bank today reported a 32.67 per cent decline in its net profit at Rs 82.78 crore for the third quarter ending December 31, 2007 as against Rs 122.95 crore recorded during the corresponding quarter last year.
According to S K Goyel, chairman and managing director of the bank, this dip in the net profit is mainly due to restructuring of accounts, which accounted for Rs 22 crore, and Rs 34 crore provisioned for taxation.
Ironically, during the period under review, total business of the bank grew by 20.85 per cent to Rs 1,22,262 crore from Rs 1,01,167 crore reported a year ago.
This include 24.33 per cent rise in deposits to Rs 72,402 crore from Rs 58,232 crore and 16.13 per cent increase in advances to Rs 49,802 crore from Rs 42,877 crore reported a year ago.
Total income of the bank stood at Rs 1,824 crore for the quarter ended December 31, 2007, up 25.67 per cent from Rs 1,451.97crore registered in the corresponding quarter last year.
In the same period, the net NPA of the bank stood at Rs 2.37 per cent, a marginal decrease from 2.17 per cent reported in the corresponding period last year.
“This decline has been mainly due to some pockets where natural calamities hindered the recovery process. The government has approved Rs 50 crore as compensation on this count,” Goyel said.
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.
No comments:
Post a Comment