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Friday, February 22, 2008

Bajaj Hindusthan`s Rs 150 cr stock seized

As the company failed to pay last season's cane price to farmers.

The Uttar Pradesh government has seized stocks from three sugar mills owned by Bajaj Hindusthan, the country’s largest sugar producer, for non-payment of last season’s sugarcane price to farmers.

Of Rs 580 crore that sugar mills in the state owe cane-growers for the last season (October-September), Bajaj accounts for almost Rs 300 crore.

The three mills from which stocks have been seized are located in Kinauni in the Meerut district, Gola (Lakhimpur Kheri) and Barkheda (Pilibhit). The stocks in these units are valued at Rs 50 crore each.

“The company cannot sell any quantity from these three mills. The district magistrates in each of the three districts will sell these stocks and use the money to clear the company’s dues,” said a state official.

This action by the state government follows the issue of recovery certificates (RC) against these three units last month. Bajaj runs 14 sugar mills in the state. This is the first time the company’s stocks have been seized.

A company official declined to comment. Bajaj Hindusthan’s share price at the Bombay Stock Exchange today closed at Rs 259.40, down 5.26 per cent from the previous close.

The seizure follows several court order. In an order on December 19, the Allahabad High Court had quashed the state’s 2006-07 state advised price (SAP) of Rs 125 to Rs 130 a quintal. The state government was directed to reassess the SAP “backed by reasons giving adequate outlines of norms, criteria or guidelines”.

Pending the new SAP, mills were obliged to pay only the Centre’s statutory minimum price (SMP), which is in the range of Rs 85 to Rs 90 per quintal for 2006-07.

Following this, Bajaj Hindusthan had adjusted its balance sheet using SMP instead of SAP for accounting purposes and reported a net profit of Rs 45.65 crore for the year ended September 30, 2007.

However, the Supreme Court last month passed a stay order on the high court’s order quashing the 2006-07 SAP, after which the state government issued RCs against these units.

The Supreme Court, in its hearing yesterday, asked the state government not to take coercive action against the state mills. “We will not take further action against the mills, but the status quo will be maintained,” the official added.

Arrears to cane farmers have grown principally because of record sugar production in the 2006-07 season that saw prices crash about 35 per cent and impacted sugar companies’ profitability.

The six-month-long export ban imposed by the government in June 2006 to control inflation rate depressed domestic sugar prices further. This led to a slump in the sugar cycle and leading companies began incurring huge losses and, therefore, delayed paying farmers their dues.

The UP sugar mills also delayed their crushing by a month in the current season owing to their differences with the state government over sugarcane prices.

The delay had forced many farmers to dump their sugarcane at jaggery units at throwaway prices in a bid to vacate fields for sowing wheat. Mills agreed to run only after the high court intervened and announced an interim cane price of Rs 110 a quintal against the SAP of Rs 125-130.

Posted by Srivatsan at 10:41 PM

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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.