Amid fears of recession following weak economic data – increase in unemployment to a two-year high and decline in manufacturing, the US stocks slumped to five month low. The first week of the New Year started on disastrous note, as the S&P 500 retreated 4.5 per cent to 1,411.63 last week – the steepest fall in five months. The Dow Jones Industrial Average slumped 4.2 per cent to 12,800.18. That brought its loss since December 31 to 3.5 per cent, the worst first three days of any year since 1904, according to Bloomberg data. The Nasdaq Composite Index declined 6.4 per cent to 2,504.65, the lowest since April.
Indian market
In contrast, the domestic benchmarks – the BSE Sensex and the NSE’s S&P CNX Nifty – witnessed sharp surge and registered their new peaks. Expectation of good third quarter performance from Indian Inc and the ensuing Reliance Power IPO ensured that the bullish momentum sustains.
The BSE Sensex closed at a record high of 20,686.89, a gain of 2.38 per cent over last weekend’s close of 20,206.95, while the NSE’s S&P CNX Nifty soared 2.21 per cent to end the week at an all-time high of 6,274.30 from previous weekend’s close of 6,079.70.
It was mixed show by Indian ADRs.
IT turns weak
Information technology stocks were worst performers. Indian software majors, which depend mainly on the US, were affected following the weak US economic data. Besides, fears of cut in IT budget by US Inc and appreciation of rupee against the greenback, also turned the sentiment weak for the IT majors.
Satyam Computer was the biggest loser by 11.66 per cent at $24.02 ($27.19) followed by Wipro which fell 10 per cent at $13.66 ($15.18). Infosys and Patni Computers slipped by 7.5 per cent and 6 per cent respectively. Infosys is scheduled to announce its Q3 numbers on January 11 that could set trend for the IT companies.
MTNL – the star
Even with the counters witnessing severe selling pressure, MTNL jumped about 11 per cent at $10.25 ($9.24) after registering its new peak at $10.75 during intra-week tradings.
Tata Motors also ended on positive note; it gained 4.4 per cent at $19.32 ($18.5). Ford Motor last week named Tata Motors as the preferred buyer for Jaguar and Land Rover.
Another counter that bucked the trend was Sterlite Industries, which gained marginally by 0.15 per cent, on account of firm metal prices.
HDFC Bank and ICICI Bank displayed a divergent trend at the US bourses. While the former slumped 7.7 per cent, the latter finished a tad better by 0.26 per cent.
Dr. Reddy’s Lab, Rediff.com and Sify also finished in the red.
Premium declines
The divergent trend of the Indian and the US bourses also reflected in the premium/discount of Indian ADRs. While discount widened for the counters that were trading in discount last week, the premium tumbled for those trading in premium.
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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