Price-to-earnings ratio or PE; An equity evaluation tool for stock market investors

 The price-to-earnings ratio, which is commonly known to us as P/E ratio, often called P-E ratio or PE is used to calculate the value of equities through relative evaluation. In other words it is an equity valuation multiple and the valuation ratio of a company's current share price compared to its earnings per share (net profit). It is the most simplest and common method used for valuation.
It can be calculated by using the following formula




 Suppose, the shares of the company 'XXXX' is trading at 975 Rupees (per share) and the earnings over last one year was 45 Rupees then PE ratio is 21.7
 Different methods are used to calculate PE depending upon the type of earnings.
 'Trailing PE' or 'historical PE' is calculated by using the net income for the most recent one year (last four quarters or two half years) divided by the weight-age average of common shares in issue during this period. It is the most common form of PE.
 'Trailing PE from continued operations' uses operating earnings only to calculate PE. That means earnings from discontinued operations and extra ordinary items are excluded from calculation.
 Another form of PE is called 'forward PE' or 'projected PE' or 'prospective PE', in this method estimated net earnings (published by a selected group of analysts) over next one year is used to calculate PE.

Features of PE

 Higher PE ratio indicates that the company may get higher growth in earnings compared to the companies with lower PE.
 As I said above it is an equity valuation multiple. For example, If the PE ratio of a security is 25, it means that people are willing to pay 2500 RS for a company whose earnings per share is 100 Rupees.
A security with an average PE of 20-25 is considered as a good one. Above that the stock is not advisable.
 Comparing the PE ratio of the companies in the same sectors are useful. The PE ratio of its sector and the whole index may also help investors to identify whether the security is expensive.
 The companies which bear losses do not have a PE ratio.

Read More

William's %R; Calculation and how to use in financial markets

In previous posts we have discussed about  some important technical indicators used in stock markets such as fibonacci levels, moving averages, stochastics and bollinger Bands. In this topic let us try to learn about 'Williams %R'. Like 'Stochastic Oscillator', Williams %R is also a momentum indicator used to  measure overbought and oversold conditions in financial markets. It is the inverse of the Fast Stochastic Oscillator. This method was developed by Larry Richard Williams, an American author and commodity trader.
 'Williams %R' is also called '%R', which shows the current closing price in relation to the high and low of the past N days* (usually 14 days). It is used to know where the financial markets are trading, near the high or near the low, or somewhere in between high and low, of its recent trading range. In other words it is used to calculate the entry and exit points. The values are from '0' (zero) to '-100' (minus hundred). Above '80' it is considered as oversold and below '20' it indicates over bought.

According to the rule a security or financial instrument is considered as a good buy when the following conditions satisfy,
1. '%R' touches -100%
2.  Then wait for 5 days after -100% reached
3.  When '%R' once again rises above -95% to -85% levels it is a buy.
 A security or financial instrument is considered as a good sell if the following conditions satisfy,
1. '%R' touches 0%
2.  Wait for 5 days after 0% reached
3.  When '%R' once again falls below -5% to -15% levels it is a sell.

'Williams %R' is calculated by using the following formula.

%R = (high of look-back period- current close / high of look-back period - low of look-back period) * -100 

A chart showing William's %R levels is given below.

A spreadsheet showing 'Williams %R' levels is given below.

* Instead of days you can use weeks or months to calculate medium term to  long term over bought or over sold conditions and buy or sell signals.

Read More

Stochastic Oscillator a momentum indicator; Fast, slow and full stochastics

'Stochastic Oscillator' is a momentum indicator developed by George C. Lane in late 1950s.It uses the support and resistance levels. Stochastic compares the security's current closing price to its price range over a specific time period. But it does not blindly follow price, volume. Instead it is purely based on the speed or  momentum of price.

 Stochastic Oscillator is used to identify the bullish bearish trend and a possible future reversal. It also indicates the over sold and over bought levels.
 The Stochastic Oscillator can be defined as
%K = 100 * (Current close price - Lowest price of the period) / (Highest price of the period - Lowest price of the period)
%D = 3-period Simple moving average of %K
There are three types of Stochastic Oscillator. Fast stochastic oscillator, Slow stochastic oscillator and the Full stochastic oscillator. Among them the fast stochastics is the original stochastic oscillator based on the above said formula of Dr. George Lane. The fast stochastics is very choppy and more sensitive (too responsive to price changes) compared to slow stochastic. This will result in the premature unwinding of positions. So some traders prefer slow stochastics than fast stochastics.
 The slow stochastics uses three-period simple moving average smoothed fast stochastic's %K instead of '%K basic calulation' of the fast stochastics.
After the first simple moving average is applied to the fast stochastic's %K, another three-period moving average is applied to get the slow stochastic's %D.
The formula is
        Slow %K = Fast %K smoothed with 3-period Moving average
        Slow %D = 3-period Moving average of slow %K
Using slow stochastics reduces the chances of false crossovers and thus prevents false unwinding of positions.
 The full stochastics is more advanced type of stochastic oscillator. It is the generalization of fast stochastic oscillator and the slow stochastic oscillator.
The formula is,
    Full %K = N1 Period simple moving average of the fast %K
    Full %D = N2  period Simple moving average of Full %K
Here N1 is the number of periods used to calculate the fast %K and N2 is the number of periods by which the full %K line is smoothed.
 Unlike the The fast stochastic oscillator and the slow stochastic oscillator, the full Stochastic oscillator has three parameters.The first one is the look back period, second one is the number of periods for slow %K and the third one is the number of periods for %D moving average. In a full stochastic oscillator with parameters 14,3,3 , (14,3) is the fast stochastic oscillator parameters and (14,3) is the slow stochastic oscillator parameters.
 There are three different ways to trade using stochastic oscillators.
1. Crossover method-
 The first one is based on the crossing of %K and %D signals. When stoch %K crosses above stoch %D 'buy' signal occurs. When %K line crosses below %D line 'sell' signal occurs.
 The second one is based on the 50 level cross over. When %K line crosses above 50 a 'buy' signal occurs and when %K line crosses below 50 a 'sell' signal occurs.
2. Divergence in Stochastics and Price method-
 In this method traders uses the divergence between price and stochastic oscillator. When lower lows in price and higher lows in stochastic oscillator is formed it is called bullish divergence and here a 'buy' signal occurs. When higher highs in price and lower highs in stochastic oscillator is formed it is called bearish divergence and here 'sell' signal occurs.
3. Over sold and Over bought levels method-
 If the stochastic oscillator is higher than or equal to 70% level it  is called over bought. To confirm the condition wait till it crosses 80% level. After crossing 80% level if it moves back to 70 level a 'sell' signal occurs. When the stochastic oscillator is lower than or equal to 30% level it  is called over sold. To confirm Wait till it crosses 20% level. After crossing 20% level if it moves above to 30% level a 'buy' signal occurs.

Read More

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

Read More

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

Read More

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.

Read More