Bagavad Gita

“Bound by your own Karma, born out of your nature, deeds which out of delusion you wish not to do, you shall do helplessly against your will” O Kaunteya --Bhagavad Gita - Chap: 18 ; Verse: 60

Tuesday, October 25, 2011


Shares I would like to buy for MUHURAT SESSION

For Long Term Investment Only

Caution:  Look for the technical’s before buying

Price as on 25.10.2011 – NSE

Aban Offshore 400.00

Bannariamman Sugars 582.00
Bombay Dyeing and Manufacturing Company 419.00

Century Textiles and Industries 315.80

Century Enka 147.80

City Union Bank 43.50


Dabur India 95.50

Dena Bank 73.05


Electrotherm (India) 185.30


Garden Silk Mills 74.50
Gitanjali Gems  372.05
Gujarat State Petronet 97.70

Hindalco Industries 125.35
Hindustan Oil Exploration Company 108.95

IVRCL 35.90

Jain Irrigation Systems 115.10
Jaiprakash Associates 72.30
Jaiprakash Power Ventures 38.05
Jaypee Infratech 60.50
JSW Steel 601.00

Kalyani Investment Company 506.15
Kalyani Steels 47.35

LG Balakrishnan and Brothers 305.60
LGB Forge 2.90

Nahar Spinning Mills  61.25

Pantaloon Retail 178.90

Punj Lloyd 54.55

Revathi CP Equipment 350.05

Sintex Industries 109.20
Siyaram Silk Mills 275.85
Su-raj Diamonds and Jewellery 45.50

Tata Steel 452.05

United Phosphorous 146.30

Vardhman Textiles 205.15


There is no clear technical signal observed for the upward direction of the market yet. Many gaps are seen in the daily bar chart of the past months. Hence any buying should be done in small lots over a period of time. Give importance to fundamental strength of each stock as well as the percentage of retracement from the previous high.




Successful investing is anticipating the anticipations of others. 

                                                                                        John Maynard Keynes



Moving Average is an indicator frequently used in technical analysis showing the average value of a security's price over a set period. Moving averages are generally used to measure momentum and define areas of possible support and resistance. Moving averages are used to emphasize the direction of a trend and to smooth out price and volume fluctuations, or "noise", that can confuse interpretation.


A moving average is commonly used with time series data to smooth out short-term fluctuations and highlight longer-term trends or cycles.

 Typically, upward momentum of a stock is confirmed when a short-term average (e.g.20-day) crosses above a longer-term average (e.g. 200-day). Downward momentum is confirmed when a short-term average crosses below a long-term average.

There are many kinds of moving averages used for different types of analysis. But in stock market two types are used often. They are Simple Moving Average and Exponential Moving Average.

1. Simple Moving Average (SMA)

A simple or arithmetic moving average is calculated by adding the closing price of the security for a number of time periods and then dividing this total by the number of time periods.
Short-term averages respond quickly to changes in the price, while long-term averages are slow to react.

Usually traders watch for short-term averages to cross above longer-term averages to signal the beginning of an uptrend.
 Short-term averages (20 days SMA) also act as levels of support when the price experiences a pullback after an uptrend.

Support levels become stronger and more significant as the number of days used in the calculations increases.

In technical analysis there are various popular values for n, like 10 days, 20 days, 50 days, or  200 days. The period selected depends on the kind of movement one is concentrating on, such as short, intermediate, or long term. In any case moving average levels are interpreted as support in a rising market, or resistance in a falling market.

In all cases a moving average lags behind the latest data point, simply from the nature of its smoothing. SMA can lag to an undesirable extent, and can be disproportionately influenced by old data points dropping out of the average. This is addressed by giving extra weight to more recent data points, as in the weighted and exponential moving averages.

2. Exponential Moving Average (EMA)

An exponential moving average (EMA), also known as an exponentially weighted moving average (EWMA), is a type of infinite impulse response filter, that applies weighting factors which decrease exponentially. The weighting for each older data point decreases exponentially, never reaching zero.

 Exponential moving averages (EMAs) work the same way as a simple moving average, except they place greater weight on the more recent closing prices. The mathematics of an exponential moving average is complex, but fortunately for trackers, most charting packages calculate them automatically and instantaneously.

Moving Averages in Trading

A. Enter or Exit on a moving average crossover
B. Enter or exit when a strong trend pulls back to a   
     Moving  Average  line.

Assess the overall trend.

In order to assess the strength of a trend in a market, plot the 20 and 200 day SMA’s. In an uptrend, the shorter term averages should be above the longer term ones, and the current price should be above the 20 day SMA. A trader’s bias in this case should be to the upside, looking for opportunities to buy when the price moves lower rather than taking a short position.
Confirmation of price action.

As always, traders should look at candlestick patterns and other indicators (which shall be discussed in our forthcoming sessions) to see what is really going on in the market at that time. The chart above points out the Bullish engulfing pattern that occurs just as the pair bounces off the 20 day EMA. Hitting the 20 day EMA, in conjunction with the candlestick pattern, suggests a bullish trend. Traders should enter once the Bullish Engulfing candle is cleared.

Crossovers – to look for buy and sell timings:

When a shorter moving average crosses a longer one (i.e. if the 20 day EMA crossed below the 200 day EMA), this may be seen as an indication that the pair will move in the direction of the Shorter MA ( it is likely to  move down – Sell indication). Accordingly, should the short EMA crosses back above the longer EMA (i.e. the 20 day EMA crossed above the 200 day EMA), this may be viewed as a possible change in the trend (it is likely to move up – Buy indication).

Time Lag

Historically, moving average crossovers tend to ‘lag’ the current market action. The reason being is that the moving averages give us an ‘average’ price over a given period of time. Therefore the moving averages tend to reflect the market’s action, only after at least some time has passed. As the short moving average crosses over and above the longer moving average, this can be interpreted as a change in trend to the upside. The opposite also holds true, as the short moving average crosses down and below the long moving average, a new downtrend may emerge in the near future. Moving average crossovers tend to generate more reliable results in a trending market that tends to accomplish either new highs or new lows.
 In a range bound market environment, the moving averages may cross one another many times, and may tend to give us false trading signals. It is important for this reason, that we first identify the market as either trending or range bound.

The chart below show an example of how moving averages, when confirmed by price action, can signal trading opportunities.



Moving averages smooth the price data to form a trend following indicator. They do not predict price direction, but rather define the current direction with a lag. Moving averages lag because they are based on past prices. Despite this lag, moving averages help smooth price action and filter out the noise. They also form the building blocks for many other technical indicators and overlays, such as Bollinger Bands, MACD and the McClellan Oscillator.