May close branches, bank relocates ATMs.
The sub-prime loss-hit Citigroup is on a cost-cutting exercise in its Indian operations.
CitiFinancial, its consumer finance unit, which is also reeling under the burden of rising bad loans, is considering closing about 100 of its 450 branches in India.
Meanwhile, Citibank, the commercial banking arm, has begun shifting its ATMs from prime locations to less expensive ones. Banking sources said private sector banks like Yes Bank and HDFC Bank have bought some of the locations.
“In terms of cost-cutting, the bank is relocating ATMs. Citibank is relocating around 30 ATMs from high-cost locations to low-cost areas,” said banking sources.
These steps are in tune with Citigroup’s global efforts at substantially reducing costs according to plans drawn up by Vikram Pandit, who took charge as CEO of the world’s largest financial services group after Chuck Prince exited following a $17.4 billion write-down on sub-prime related exposures.
In response to a mail sent by Business Standard, a Citigroup India spokesperson preferred not to comment on the closure of branches,
“CitiFinancial is not exiting the consumer finance business. We are committed to growing it further by adding new products to its portfolio. To service customers better, we are in the process of relocating some branches in select geographic locations,” the response said.
The spokesperson added that CitiFinancial has not sold any ATM locations. “We have relocated some ATM premises, which is an ongoing process to better serve larger numbers of customers. We will continue to operate 480 ATMs across the country.”
CitiFinancial India saw a 64 per cent drop in net profit in the first half of 2007-08. For the whole of 2006-07, CitiFinancial’s net profit was at Rs 220 crore against Rs 170 crore in 2005-06.
In its rating rationale, rating agency CRISIL has said the decline in CitiFinancial’s net profit in the first half of 2007-08 was largely due to higher delinquencies in the unsecured personal loans segment.
Spreads have also been under pressure due to increased borrowing costs and a shift in its loan portfolio towards a higher proportion of mortgage products, which have a lower yield than unsecured personal loans.
To contain credit costs in the unsecured personal loan segment, CitiFinancial is shifting focus to customers with better credit profiles but lower yields.
It is also increasing its focus on fee-based income through insurance distribution. However, the rating agency said the initiatives will benefit the company in the medium term and the pressure on profitability will continue in the near future.
According to reports, Citigroup is also in the process of closing its CitiFinancial unit in Japan and scaling down operations of the consumer lending arm in Mexico. CitiFinancial Japan has already reduced its branches to 51 from 324 in 2006.
Recently, GE Money, another US-based consumer lender, expressed its intentions to exit the personal loans and housing loans business in India.
Anil Ambani-promoted Reliance Capital, Kishore Biyani’s Future Capital, Birla Group and Fullerton are believed to be potential buyers. Private equity players like JP Morgan and Goldman Sachs are also in the race. HDFC Bank, which has set up its own non-bank finance company, is also keen to acquire the business.
GE Money had exited the consumer durable and auto loan business in India earlier.
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Friday, February 29, 2008
Citi India arms feel sub-prime pinch
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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.
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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