Oil and Natural Gas Corporation (ONGC), the country’s largest oil exploration company, and the UK-based Hinduja group is lining up investment of close to $20 billion (around Rs 80,000 crore) in exploration assests in Iran and a refinery and LNG terminal in India.
Senior officials in ONGC’s overseas investment arm ONGC Videsh (OVL) and the Hinduja group held two rounds of discussions with Iranian officials in New Delhi late today.
“We are in negotiations,” said Subir Raha, executive vice-chairman of the Hinduja group.
He added that if the negotiations are successful, the total investment from the exploration fields in Iran right down to marketing of gas in India would work out to around $20 billion.
Of the $20 billion, around $10 billion will be invested in upstream assets in Iran, a country in which Indian companies have interest in just one asset — the Farsi block where both oil and gas have been discovered by OVL, Oil India and Indian Oil Corporation.
Studies to establish commercial viability of the reserves in the block are currently being carried out.
The OVL-Hinduja combine is eyeing the gigantic South Pars field in Iran, the country with the world’s second largest gas reserves.
Gas from the South Pars field was also to feed the proposed $7.2 billion pipeline from Iran to India through Pakistan.
The consortium, which had also signed a memorandum of understanding in late 2006 for collaboration in the oil and gas sector, is also keen to develop the Azadegan oilfield in Iran, which is projected to hold over 40 billion barrels of oil.
The consortium is expected to get over 50 per cent in Phase 12 of the South Pars field, which could produce as much as 12 million tonnes of gas per year.
“We also want at least 50 per cent in the Azadegan field,” a senior ONGC official said.
The gas from the South Pars field will be liquefied in a terminal in Iran, and shipped to India.
The combine plans to set up LNG regassification terminal at Mangalore on the west coast of India to receive the gas, and then distribute it.
A 5 million tonne a year (mtpa) LNG regassification terminal is already being planned by ONGC and its subsidiary Mangalore Refinery and Petrochemical Ltd (MRPL) in Mangalore.
The Hinduja group is also expected to pick up a stake in ONGC’s proposed 15 mtpa crude oil refinery at Kakinada in Andhra Pradesh. The financial feasibility study for the refinery is underway and a final report is expected in the next couple of weeks.
An ONGC official said a stake in the Rs 25,000 crore (around $6.25 billion) refinery was likely to be offered to an Iranian company but declined to give the name of the company.
ONGC officials has previously said that the refinery was not financially feasible since another 7.5 mtpa Hindustan Petroleum Corporation-operated refinery exists at Vishakapatnam, which is near Kakinada.
Another 15 mtpa refinery is likely to be set up alongside the existing refinery in Vishakapatnam.
Although the Kakinada refinery is being planned as an export-oriented one, analysts said the export potential from a refinery on the east coast was not very high as the markets in India’s east are already fed by the Singapore refineries.
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Friday, January 4, 2008
OVL-Hinduja plan $20 bn investment
Posted by Srivatsan at 7:12 AM
Labels: Hinduja Group, ONGC
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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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