Relative strength index in Stock market; Importance and calculation of RSI

 Like MACD, Relative strength index (RSI) is also a technical indicator used in financial markets. It was introduced in 1970's by Welles Wilder. It is a momentum oscillator which measures the speed and change of price movements. RSI also determines the strength or weakness of a security. It compares the magnitude of gains to losses in a specific period of time. By using this we can identify or confirm over bought and oversold conditions in securities.
 According to Wilder's theory when the price increases very rapidly, at some point it is considered as over bought and when the price decreases, at some point it is considered over sold. At this point a reversal is possible. Wilder suggested a smoothing period of 14.
 In stock market graph RSI moves between 'zero' and 'hundred'. RSI indicator has an upline at 70, a down line at 30 and a midline at 50.Above 70 line the security or financial instrument is over bought and below thirty line it is over sold. The midline 50 shows that there is no trend.
 Wilder also described the divergence in RSI. According to him a bullish divergence happens when price makes a newer low and RSI makes higher low. A bearish divergence happens when price makes a higher high and RSI makes lower high.
 Andrew Cardwell added some new interpretations of RSI which helps us to determine the up and down trends. According to him in up trends RSI usually moving between 40 and 80 and in down trend it moves between 20 and 60. He also observed that when the trend changes in financial instruments, that is from up trend to down trend or from down trend to up trend RSI will pass through a 'range shift'.
 Cardwell also described the positive and negative reversals in the RSI. According to him Reversals are the opposite of divergence. A positive reversal happens when price correction results in a higher low and RSI results in a lower low compared to the prior correction in an uptrend . A negative reversal happens when price correction results in a lower high and RSI makes a higher high compared to the prior rally in down trend.

                          100
    RSI = 100 -  --------
                         1 + RS
    RS = Average of up closes of 'n' days / Average of down closes of 'n' days.

 An example for RSI calculation is given below

Date	Close	Change	Gain	Loss	Average Gain	Average Loss	RS	RSI (14)
01-Jul-13	120.2
02-Jul-13	125.4	5.2	5.2
03-Jul-13	124.8	-0.58		0.58
04-Jul-13	128.4	3.53	3.53
05-Jul-13	129.3	0.92	0.92
08-Jul-13	128.5	-0.82		0.82
09-Jul-13	132.5	4.05	4.05
10-Jul-13	134.2	1.7	1.7
11-Jul-13	133.3	-0.9		0.9
12-Jul-13	135	1.7	1.7
15-Jul-13	136.5	1.5	1.5
16-Jul-13	135.5	-1		1
17-Jul-13	137	1.5	1.5
18-Jul-13	135	-2		2
19-Jul-13	132.5	-2.5		2.5	1.44	0.56	2.58	72.04
22-Jul-13	131	-1.5		1.5	1.33	0.62	2.13	68.10
23-Jul-13	132	1	1		1.31	0.58	2.26	69.31
24-Jul-13	132.7	0.7	0.7		1.27	0.54	2.35	70.16
25-Jul-13	133.4	0.7	0.7		1.23	0.50	2.45	71.02
26-Jul-13	134.2	0.8	0.8		1.20	0.46	2.57	72.02
29-Jul-13	133.7	-0.5		-0.5	1.11	0.40	2.81	73.73
30-Jul-13	135	1.3	1.3		1.12	0.37	3.06	75.37
31-Jul-13	136.1	1.1	1.1		1.12	0.34	3.29	76.69
01-Aug-13	137	0.9	0.9		1.11	0.32	3.49	77.74
02-Aug-13	137.7	0.7	0.7		1.08	0.29	3.66	78.55
05-Aug-13	138.6	0.9	0.9		1.06	0.27	3.90	79.59
06-Aug-13	137	-1.6		1.6	0.99	0.37	2.69	72.88
07-Aug-13	137.5	0.5	0.5		0.95	0.34	2.79	73.63
08-Aug-13	136.3	-1.2		1.2	0.89	0.40	2.20	68.73
09-Aug-13	134.7	-1.6		1.6	0.82	0.49	1.68	62.73
12-Aug-13	135	0.3	0.3		0.78	0.45	1.73	63.38
13-Aug-13	135.9	0.9	0.9		0.79	0.42	1.88	65.32
14-Aug-13	136.5	0.6	0.6		0.78	0.39	1.99	66.59
15-Aug-13	137.8	1.3	1.3		0.82	0.36	2.25	69.22
16-Aug-13	138.5	0.7	0.7		0.81	0.34	2.40	70.56
19-Aug-13	139	0.5	0.5		0.79	0.31	2.51	71.52
20-Aug-13	138	-1		1	0.73	0.36	2.02	66.84
21-Aug-13	138.5	0.5	0.5		0.71	0.34	2.12	67.97
22-Aug-13	139.7	1.15	1.15		0.74	0.31	2.38	70.46

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Moving averages and moving average convergence divergence

  Moving averages is one of the most popular and reliable tool used in stock market technical analysis. In statistics it is also known as rolling average or running average. Some people call this as moving mean or rolling mean. Moving average is the average price of a stock over time. It is calculated by averaging the initial fixed subset of number series or data points.
 In stock market moving average (MA) is used to determine the trend of the market or a security. Upward trend is confirmed when short term moving average crosses above a longer term moving average and downward trend is recognized when short term moving average breaches below longer term moving average. For example if 50 MA crosses above 100 MA it is considered as up trend. If 50 MA falls below 100 MA trend is bearish.
 Simple moving average (SMA), Cumulative moving average (CMA), Weighted moving average (WMA) and Exponential moving average (EMA) are important  types of Moving averages.Modified moving average (MMA) or Running moving average (RMA), or Smoothed moving average is also considered as a moving average.
 As I said above Moving averages allow traders to recognize and confirm the trend. Thus by identifying the trend he can achieve success in his trade.

Moving Average Convergence Divergence (MACD)
MACD or moving average convergence divergence was developed by Gerald Appel in late 1970's. It is also a simplest and useful technical indicator used in stock market. It is based on exponential moving average. In a chart it is a collection of three signals namely MACD line, Signal line and the divergence (difference) line. These signals are calculated from historical prices of a financial instrument (indice or stock).Most people use closing prices to calculate MACD.
 The first signal 'MACD line' is the difference between a short term (fast) exponential moving average , and a longer term (slow) exponential moving average. In a chart MACD line is changing over time along with 'signal line'. MACD histogram time series is an oscillator which shows the divergence between MACD line and Signal line.
 The standard setting for MACD used in stock market is 12,26 and 9. MACD 3,10,16 is also used by some traders.

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Exponential moving average and how to calculate EMA

Exponential Moving Average (EMA)
 Exponential moving average or EMA is also known as exponentially weighted moving average (EWMA). It gives more weight to recent prices in other words the weight of old prices decreases exponentially.
 A seven day EMA applies 25 per cent weighting Calculation of EMA is a complicated one. Stock market traders can get EMA from almost all technical charts.
In order to calculate EMA, first calculate SMA.
SMA = Mean or average of previous n days= Sum of n days / n
For eg, 7 SMA= Sum of Seven days closing price / 7
Then you have to find smoothing factor.
Smoothing factor = (2 / (Time periods + 1) ) = (2 / (7 + 1) ) = 0.25 (25 per cent weighting; ie 0.25*100)
Then calculate EMA by applying the following formula.

EMA= [Close - EMA(Yesterday)] x Smoothing Factor + EMA(Yesterday).

Note that Some people use current price instead of close.

If you know the per cent and want to get time period you can use the following formula.

Time period= (2/Smoothing Factor)-1
Here smoothing factor is per cent divided by 100.
For eg;- If the per cent is 25, smoothing factor is 25/100= 0.25
Then time period= (2/0.25)-1= 7; so seven is the time period.

An example of EMA calculation on a sheet is given below

Day	Close	7 SMA	Smoothing Factor	EMA 7
1	87.50
2	86.00
3	85.00
4	86.20
5	87.00
6	85.00
7	85.70	86.06		86.06
8	86.70	85.94	0.2500	86.22
9	87.20	86.11	0.2500	86.47
10	87.50	86.47	0.2500	86.72
11	87.70	86.69	0.2500	86.97
12	88.00	86.83	0.2500	87.23
13	88.80	87.37	0.2500	87.62
14	89.20	87.87	0.2500	88.01
15	90.20	88.37	0.2500	88.56
16	91.20	88.94	0.2500	89.22
17	91.70	89.54	0.2500	89.84
18	91.90	90.14	0.2500	90.36
19	92.50	90.79	0.2500	90.89
20	93.00	91.39	0.2500	91.42
21	93.50	92.00	0.2500	91.94
22	93.20	92.43	0.2500	92.25
23	92.70	92.64	0.2500	92.37
24	90.50	92.47	0.2500	91.90
25	91.70	92.44	0.2500	91.85
26	92.30	92.41	0.2500	91.96
27	93.80	92.53	0.2500	92.42
28	94.50	92.67	0.2500	92.94
29	94.80	92.90	0.2500	93.41
30	95.50	93.30	0.2500	93.93

EMA 5, 10, 20, 50, 100, and 200 are very common in stock market trading

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What is Simple moving average: How to calculate SMA

As the name indicates Simple moving average (SMA) is the simplest form of all the moving averages. It is the unweighted mean of the previous 'n' data points.
 In stock market SMA is simply calculated by taking the mean (average) of a security over a specified number of days. One can calculate moving averages from open, high, low or close prices. But in most cases, close prices are used to calculate SMA.
 If you want to calculate a seven day simple moving average of a security, add the previous seven day closing prices and divide it by seven (mean or average of last seven days). You can't calculate simple moving average if you don't have last seven days closing price.
 An example of a seven day moving average is given below
 

Day	Close	7 Day SMA
1	58
2	64
3	62
4	60
5	63
6	65
7	65	62.43
8	67	63.71
9	68	64.29
10	67	65.00
11	66	65.86
12	64	66.00
13	65	66.00
14	67	66.29
15	69	66.57
16	70	66.86
17	67	66.86
18	65	66.71
19	62	66.43
20	63	66.14
21	66	66.00
22	68	65.86
23	71	66.00
24	69	66.29
25	70	67.00

 You can also calculate simple moving average of 'n' days using the following formula.

 Suppose  previous 'n' day closing prices are 

 Then Simple moving average



In order to calculate simple moving average in a row (for successive values) use the following formula

  

For short term trading most people use 5, 10, 20 and 50 SMA. For long term 100, 200 SMA's are considered as important.

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Book value per equity and book value per share; its importance

 In accountancy 'book value' is the value of an asset as per balance sheet. It is also called carrying value or net asset value, which is equal to the original cost of the asset less any accumulated depreciation, amortization or impairment costs made against the asset.
 In share market traders use book value to determine the safety level of shares after the payment of all debts.
 Total Book value of an equity is the value that the equity worth after the repayment of all debts and liquidation of all assets.
 Total Book value of equity is calculated by the following formula,
 Total Book value of an equity= Book value of assets- Book value of liabilities

 Book value of all Common shares is calculated as
 Book Value of Equity- Book Value of Preferred Stocks

Book value per share is defined as the value, that share worth after repaying all debts and liquidating all its assets.
  Book value per Common share is calculated by using the following formula
 Book Value per Common Share = (Total stock holder's equity- Preferred Equity)/(Total Number of outstanding Shares)

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