Underlining the uncomfortable situation on the price front, the wholesale price index (WPI) rose to a near three and a half year high of 7.41% for the week ended March 29, 2008. Inflation had last stood above this level, at 7.68%, in the week ended November 12, 2004.
The latest spike is on account of a continued price upsurge increase in primary articles like vegetables, fruit and pulses, as well as a sharp increase in manufactured products like foundries, iron, steel, as well as basic metals. Delayed revisions to prices of some items in the WPI basket have also contributed to the spike seen this March (the index rose 2.3 percentage points within the month).
With today’s release of WPI inflation numbers for the last week of fiscal 2007-08, average annual inflation for the year stands at 4.44%, below the Reserve Bank of India’s tolerance level of 5% for the year. The WPI estimate for the week ended February 2 was also revised upwards to 4.74%, a sizeable revision from the earlier estimate of 4.07%.
“The manufactured products sub-index increased 0.9% week-on-week owing to an outsized jump of 3.8% in the prices of base metals, alloys and metal products, and a 0.8% increase in manufactured food items. The primary articles sub-index rose 0.2% week-on-week to be up 8.9% over year ago,” said Rajeev Malik, senior economist, JP Morgan.
The price spike comes even as industrial production growth picked up in February, prompting Malik to say he expects a 50 basis points hike in the cash reserve ratio in the on or before the April 29 monetary policy review.
Dharmakirti Joshi, principal economist, Crisil, said the price situation remained “very uncomfortable” on the food and vegetables front. “The data is surprising and beyond my imagination. People will have to wait for interest rates to ease and the RBI may actually tighten rates,” he said, adding that inflation would moderate in coming weeks as the impact of recent fiscal measures taken to cool prices of items like edible oil get reflected in the WPI.
The data once again underscores the problems that the United Progressive Alliance (UPA) government on trying to control prices of politically sensitive items like food, a point underscored by World Bank president Robert Zoellick in a recent speech at Washington. “Since 2005, the prices of staples have jumped 80%. Last month, the real price of rice hit a 19-year high; the real price of wheat rose to a 28-year high”, he had 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.
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