Sugar mill owners in Uttar Pradesh will have to pay cane growers between Rs 115 and Rs 123 per quintal, depending upon the quality, the Supreme Court said today in an interim order while fixing the price for the crushing season 2006-07.
A bench, headed by Justice Arijit Pasayat, directed that the dues have to be paid within six weeks.
The court passed the order on a bunch of petitions filed by sugarcane farmers and the Uttar Pradesh government challenging the Allahabad High Court's order that had quashed the government's decision to fix the price of sugarcane at Rs 125-130 per quintal.
The court said the lowest quality cane, which falls in the category of "suitable variety", would command a price of Rs 115 per quintal while the "general variety" would get Rs 118 per quintal and the "early variety" would get Rs 123 per quintal.
The bench, also including Justice P Sathasivam, however, made it clear that if the payment had been done above the fixed price then no recovery would be made by the mill owners and also no interest would be paid to the farmers for the delay in payment.
The petitioners had appealed against the December 19 order of the High Court quashing the state advised price (SAP) of sugarcane fixed by Uttar Pradesh for crushing season 2006-07 and directing its revision within three months.
The high court had also suggested the constitution of an expert committee, including representatives of cane unions, the union Government and other agencies.
The high court order was passed on petitions filed by several private sugar mills, challenging fixation of SAP, alleging that the price was fixed arbitrarily without any guidelines or norms.
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