Methodology in which they are done.

## Thursday, August 7, 2008

### Heart related Disorders and dealing with blockages

Methodology in which they are done.

## Monday, July 14, 2008

### Investing in Potential stocks and setting price targets

You'll need a calculator, but once you get the hang of it, you'll be able to come up with targets for almost any stock in 10 minutes or so.

Why use sales and price-to-sales instead of earnings and price-to-earnings ratios? First, sales growth is easier to predict than earnings growth. Plus, if you look at historical data, you'll find that P/E ratios are a lot more volatile -- and thus, harder to forecast -- than P/S ratios.

Since the process is based on forecasts, and forecasts are always wrong, I won't try to set a precise target price. Instead, I'll estimate a low and high target-price range.

A five-step process You can use the procedure to forecast target prices any number of years ahead. The only stipulation is that the target-price date is always the day after a company reports its fiscal-year results. I call that fiscal year the target year.

Developing my target price consists of five steps:

Estimate sales in the target year.

Estimate the number of shares outstanding in the target year.

Use the results from steps 1 and 2 to compute estimated target-year sales per share.

Estimate expected range of price/sale ratios.

Use No. 3 and No. 4 to compute the estimated target price range.

Now, we'll set a target for Oracle.

The company's fiscal year ends in May, so I'll use its 2007 fiscal year. Oracle will probably report its May 2007 fiscal year results in June or July 2007.

I've found that the calculations go faster if I first print MSN's key ratios 10-year summary and financial statements 10-year summary reports for stocks I analyze.

Step 1: Start with sales Start by estimating a company's target fiscal-year sales. The 10-year financial statements summary shows each company's fiscal-year sales going back 10 years. Most analysts forecast sales growth in terms of year-over-year percentage increase. However, I've found that it's more useful to look at recent historical sales growth in terms of actual dollars instead of percentages.

Oracle's recent sales growth has been volatile, ranging from a $1.3 billion year-over-year gain in fiscal 2000 to a $1.2 billion drop in fiscal 2002. In its most recent fiscal year, ending in May 2004, sales climbed $681 million. I calculated Oracle's five-year average growth at $266 million, which isn't much compared to its $10.2 billion fiscal-year 2004 sales total.

Starting with Oracle's 2004 sales of $10.156 billion, I added $266 million to get $10.422 billion for 2005. Adding another $266 million results in $10.688 billion for its May 2006 fiscal year.

Finally, adding $266 million to that figure yields estimated sales of $10.954 billion for its May 2007 target year.

Oracle target year sales: $10.954 billion

My sales estimate assumes that recent annual historical sales growth will continue. Obviously, that's not always the case. So modify your target-year sales if you have more reliable numbers.

Step 2: Shares outstanding Next, I estimate a company's total shares outstanding at the end of its target year. Again, I use history as my guide. Many companies consistently increase their number of shares outstanding as they issue stock to raise cash, make acquisitions or allocate shares for employee stock options.

Oracle has reduced its number of shares outstanding in recent years. On average, its total dropped by 100 million shares annually over its past five fiscal years. Using that figure, I estimated that Oracle's average 5.2 billion shares outstanding in 2004 would drop to 4.9 billion by its fiscal 2007 target year.

Oracle target year shares outstanding: 4.9 billion

Step 3: Sales per Share Just as earnings per share is annual earnings divided by the number of shares outstanding, sales per share is annual sales divided by the number of shares out.

I estimated Oracle's target-year sales of $10.954 billion and shares outstanding at 4.9 billion. So my estimated target year sales per share ($10.954 divided by 4.9, rounded down) is $2.20.

Oracle sales per share: $2.20

Step 4: Price/sales ratios Investors frequently compare valuation ratios to evaluate the relative merits of companies in the same industry. For instance, Company A is the best buy if its P/E is only 20, while Company B's P/E is 35.

Competing firms often consistently trade at different valuations depending on their popularity with investors. For instance, pharmaceutical maker Pfizer almost always trades at higher valuations than competitor Merck. This is true no matter what valuation ratio you choose. In terms of price/sales ratios, Pfizer's 6.6 average P/S over the past five years is almost double Merck's 3.5 figure. Similarly, chip maker Intel has traded at an average 5.8 P/S over the past five years compared to 1.3 for competitor Advanced Micro Devices.

Thus, instead of comparing valuation to the overall market or to its sector, I've found that a stock's own history is the best indicator of its likely future trading ranges.

MSN's Key Ratios report shows the average annual price/sales ratios going back 10 years. I think the most recent five years' data are the most relevant, and that's what I use to determine the range of anticipated P/S ratios at my target date.

Over nine of the past 10 years, Oracle has traded at P/S ratios ranging from 4 to 7.9. However, in its May 2000 fiscal year, MSN lists its average P/S at 20. It's best to ignore an obviously out-of-range figure.

Disregarding the 2000 figure, Oracle's last five P/S ratios ranged from 4 to 7.9.

Oracle target P/S: 4 to 7.9

Step 5: Doing the numbers If you remember your algebra, you'll know that share price can be calculated by multiplying the sales per share by the price-to-sales ratio. For instance, a stock would be trading at $20 if its sales per share were $10, and the P/S ratio was 2 (it works: price/sales = 20/10 = 2).

Target Price = sales x P/S

In step 3, I estimated that Oracle would have sales of $2.20 per share. In step 4, I estimated its price/sales range at 4 to 7.9. Multiplying by sales per share by P/S:

Oracle target price range: $8.80 to $17.40.

Oracle recently changed hands at $11.70; already within my $8.80 to $17.40 summer 2007 estimated trading range. I'd abandon Oracle for better prospects.

This simple target-price calculation is intended to help you evaluate stocks that you're researching. But it doesn't take changing economic or competitive conditions into account. In short, it's no substitute for doing your own due diligence.

source: msn

Why use sales and price-to-sales instead of earnings and price-to-earnings ratios? First, sales growth is easier to predict than earnings growth. Plus, if you look at historical data, you'll find that P/E ratios are a lot more volatile -- and thus, harder to forecast -- than P/S ratios.

Since the process is based on forecasts, and forecasts are always wrong, I won't try to set a precise target price. Instead, I'll estimate a low and high target-price range.

A five-step process You can use the procedure to forecast target prices any number of years ahead. The only stipulation is that the target-price date is always the day after a company reports its fiscal-year results. I call that fiscal year the target year.

Developing my target price consists of five steps:

Estimate sales in the target year.

Estimate the number of shares outstanding in the target year.

Use the results from steps 1 and 2 to compute estimated target-year sales per share.

Estimate expected range of price/sale ratios.

Use No. 3 and No. 4 to compute the estimated target price range.

Now, we'll set a target for Oracle.

The company's fiscal year ends in May, so I'll use its 2007 fiscal year. Oracle will probably report its May 2007 fiscal year results in June or July 2007.

I've found that the calculations go faster if I first print MSN's key ratios 10-year summary and financial statements 10-year summary reports for stocks I analyze.

Step 1: Start with sales Start by estimating a company's target fiscal-year sales. The 10-year financial statements summary shows each company's fiscal-year sales going back 10 years. Most analysts forecast sales growth in terms of year-over-year percentage increase. However, I've found that it's more useful to look at recent historical sales growth in terms of actual dollars instead of percentages.

Oracle's recent sales growth has been volatile, ranging from a $1.3 billion year-over-year gain in fiscal 2000 to a $1.2 billion drop in fiscal 2002. In its most recent fiscal year, ending in May 2004, sales climbed $681 million. I calculated Oracle's five-year average growth at $266 million, which isn't much compared to its $10.2 billion fiscal-year 2004 sales total.

Starting with Oracle's 2004 sales of $10.156 billion, I added $266 million to get $10.422 billion for 2005. Adding another $266 million results in $10.688 billion for its May 2006 fiscal year.

Finally, adding $266 million to that figure yields estimated sales of $10.954 billion for its May 2007 target year.

Oracle target year sales: $10.954 billion

My sales estimate assumes that recent annual historical sales growth will continue. Obviously, that's not always the case. So modify your target-year sales if you have more reliable numbers.

Step 2: Shares outstanding Next, I estimate a company's total shares outstanding at the end of its target year. Again, I use history as my guide. Many companies consistently increase their number of shares outstanding as they issue stock to raise cash, make acquisitions or allocate shares for employee stock options.

Oracle has reduced its number of shares outstanding in recent years. On average, its total dropped by 100 million shares annually over its past five fiscal years. Using that figure, I estimated that Oracle's average 5.2 billion shares outstanding in 2004 would drop to 4.9 billion by its fiscal 2007 target year.

Oracle target year shares outstanding: 4.9 billion

Step 3: Sales per Share Just as earnings per share is annual earnings divided by the number of shares outstanding, sales per share is annual sales divided by the number of shares out.

I estimated Oracle's target-year sales of $10.954 billion and shares outstanding at 4.9 billion. So my estimated target year sales per share ($10.954 divided by 4.9, rounded down) is $2.20.

Oracle sales per share: $2.20

Step 4: Price/sales ratios Investors frequently compare valuation ratios to evaluate the relative merits of companies in the same industry. For instance, Company A is the best buy if its P/E is only 20, while Company B's P/E is 35.

Competing firms often consistently trade at different valuations depending on their popularity with investors. For instance, pharmaceutical maker Pfizer almost always trades at higher valuations than competitor Merck. This is true no matter what valuation ratio you choose. In terms of price/sales ratios, Pfizer's 6.6 average P/S over the past five years is almost double Merck's 3.5 figure. Similarly, chip maker Intel has traded at an average 5.8 P/S over the past five years compared to 1.3 for competitor Advanced Micro Devices.

Thus, instead of comparing valuation to the overall market or to its sector, I've found that a stock's own history is the best indicator of its likely future trading ranges.

MSN's Key Ratios report shows the average annual price/sales ratios going back 10 years. I think the most recent five years' data are the most relevant, and that's what I use to determine the range of anticipated P/S ratios at my target date.

Over nine of the past 10 years, Oracle has traded at P/S ratios ranging from 4 to 7.9. However, in its May 2000 fiscal year, MSN lists its average P/S at 20. It's best to ignore an obviously out-of-range figure.

Disregarding the 2000 figure, Oracle's last five P/S ratios ranged from 4 to 7.9.

Oracle target P/S: 4 to 7.9

Step 5: Doing the numbers If you remember your algebra, you'll know that share price can be calculated by multiplying the sales per share by the price-to-sales ratio. For instance, a stock would be trading at $20 if its sales per share were $10, and the P/S ratio was 2 (it works: price/sales = 20/10 = 2).

Target Price = sales x P/S

In step 3, I estimated that Oracle would have sales of $2.20 per share. In step 4, I estimated its price/sales range at 4 to 7.9. Multiplying by sales per share by P/S:

Oracle target price range: $8.80 to $17.40.

Oracle recently changed hands at $11.70; already within my $8.80 to $17.40 summer 2007 estimated trading range. I'd abandon Oracle for better prospects.

This simple target-price calculation is intended to help you evaluate stocks that you're researching. But it doesn't take changing economic or competitive conditions into account. In short, it's no substitute for doing your own due diligence.

source: msn

## Tuesday, July 8, 2008

### Pivot level and stock trading, Find out the Support and resistance level in your trade

Pivot level trading technique which was many years back used mostly

in Forex markets in Western countries, especially in Europe and USA. It’s still popular there, as currencies are the most heavily traded instruments in the world.

Now a Days Pivot levels are used in stock trading too.

- If a stock price remains below its Pivot level for more than 15min then consider it weak and short selling can be initiated, And if a stock price remains above it pivot level for more than 15min then consider it strong and buying can be initiated in it.

- If a stock price falls below its S1 level then short selling should be done for target as S2 level, and if a stock price moves above its R1 level then buying should be done for target R2 level.

- Stop loss for all trades will be 1% of the price of the stock in hich trading is initiated. Stop loss columns have also been published for the convenience of the trader in the table, so one doesn’t need to calculate and can trade instantly.

- Stop loss column in Red color is for short selling, and stop loss columns in green color is for buying/going long in the particular stock.

For years floor traders and market makers have done this by computing a set of pivot point support and resistance levels between which price can be expected to fluctuate. In a way, it is not so important that you know where these support and resistance levels are, but rather, that you know the floor traders or market makers know where they are.

For example, if the floor traders are gunning for money-management stops, guess what price levels they will test? Clearly, the pivot point support and resistance levels are the prices at which many stops are placed because everyone knows where these expected trading limits are.

The central pivot point (CPP) is the equilibrium point around which trading is expected to occur. The calculation for tomorrow’s CPP is simply the average of today’s high, low and close. When prices move away from the CPP there are zones of support and resistance that define the expected value area of the market. Because these zones are known, penetration and market moves beyond these support and resistance levels bring new players into the market who give further momentum to the buying or selling pressure.

PIVOT POINT CALCULATION

The pivot point for the current trading session is calculated as:

Pivot Point = (Previous High + Previous Low + Previous Close) / 3

The pivot point can then be used to determine levels of estimated support and resistance levels for the day:

Resistance Level 1 = (2 * Pivot Point) - Previous Low

Support Level 1 = (2 * Pivot Point) - Previous High

Resistance Level 2 = (Pivot Point - Support Level 1) + Resistance Level 1

Support Level 2 = Pivot Point - (Resistance Level 1 - Support Level 1)

Resistance Level 3 = (Pivot Point - Support Level 2) + Resistance Level 2

Support Level 3 = Pivot Point - (Resistance Level 2 - Support Level 2)

Trading for today will usually remain between the first support and resistance levels as the floor traders and market makers make their markets. The second resistance or support levels come into play only upon failure of the first resistance or support levels to contain price.

If either of the first levels is penetrated, off-floor traders are attracted to the market. In this event, the breakout levels reverse their functions and serve as test points for continued trading. In a bullish breakout, the first resistance level now becomes a support level and the second resistance level becomes a new resistance level. In a bearish breakout, the first support level now becomes the resistance level and the second support level is now the new support level.

It is clear that money-management stops placed within the range between the first support and resistance levels have a high probability of being hit. This is most likely the reason why almost all off-the-floor traders believe with absolute certainty that floor traders are gunning for their stops. To come to grips with this, some traders have used the "four-tick rule" by which a money-management stop is placed four ticks below the first support line or four ticks above the first resistance line.

However, in the cat-and-mouse game of trading, if the floor traders know where everyone calculates support and resistance it doesn’t take a giant mental leap to figure out they can pick off all the stops snuggled just outside these ranges as well.

The primary value of these support and resistance levels is that they enable you to know what the floor traders and market makers know. As technical trading tools, they should only be used in conjunction with other technical indicators to improve their efficiency.

In general, I evaluate stocks before the open to determine the recent momentum for the stock. I will consider a trade in that stock if the recent momentum of the stock, the current market momentum are going the same way. I like to catch the stock just after it moves through the pivot point.

In addition to determining where to place stops, I use the pivot/support/resistance to minimize getting into momentum trades at false tops & bottoms. I also use the support resistance levels to estimate what the potential profit will be, often keeping me out of trades with low potential.

Forex Day Trading

Because the forex market is a 24-hour market, there is often confusion about what time of day to use when calculating the closing price of one trading session and the opening of another. The generally accepted times used when calculating pivot points is 23:59 GMT for the close of a trading session, and 00:00 GMT for the opening of the new session.

The forex day trader can use daily data to calculate pivot points and support and resistance for the upcoming trading day. Weekly, swing forex currency traders can use weekly data to calculate pivot points and support and resistance for the upcoming trading week. Longer term forex currency traders can use monthly, yearly, or even longer time frames when calculating pivot points and support and resistance levels on their charts.

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