EUR/USD : BUY
| Entry | Stop Loss | Take Profit |
| 1.3640->1.3670 | 1.3600 | 1.3720 |
Chủ Nhật, 20 tháng 2, 2011
Candlesticks, Fibonacci, and Chart Pattern Trading Tools: A Synergistic Strategy to Enhance Profits and Reduce Risk by Robert Fischer [MF]
Publisher: Wiley (August 14, 2003) | ISBN-10: 0471448613 | ISBN-13: 978-0471448617 | 256 Pages | File type: PDF | 2 mb
An in-depth examination of a powerful new trading strategy
"Fischer provides an intriguing and thorough look at blending the Fibonacci series, candlesticks, and 3-point chart patterns to trade securities. Backed by explicit trading rules and numerous examples and illustrations, this book is an invaluable tool for the serious investor. Read it."
–Thomas N. Bulkowski author of Encyclopedia of Chart Patterns and Trading Classic Chart Patterns
In this groundbreaking new book, Fibonacci expert Robert Fischer and coauthor Dr. Jens Fischer successfully merge Fibonacci applications with candlestick charting to create an innovative trading strategy that will help you enhance profits and reduce risk.
Filled with in-depth insights, helpful charts and graphs, and practical real-world examples, Candlesticks, Fibonacci, and Chart Pattern Trading Tools reveals how correctly combining these different strategies can give you a noticeable edge in challenging market times–regardless of whether you are a short-term or long-term trader–and improve your chances of success under a variety of market conditions.
You’ll be introduced to the critical aspects of this synergistic approach through in-depth analysis and detailed explanations of:
Core combinations of Fibonacci trading tools with candlesticks and regular 3-point chart patterns
The magic figure "three" and its relevance in pattern recognition
Fibonacci-related trading strategies, selected candlestick chart patterns, and regular 3-point chart patterns
Applications of these trading strategies–double tops, Fibonacci price extensions, PHI-channel applications
PHI-ellipses as trading tools
And much more
From the Inside Flap
If you’re unhappy with the performance of your investment advisors and their choices, it is time to take control of your own trading decisions, and Candlesticks, Fibonacci, and Chart Pattern Trading Tools will provide you with the analytical tools and advice to do just that. Candlestick charting, Fibonacci applications, and 3-point Chart Pattern analysis are three of the most popular technical tools used by stock, options, and futures traders. By merging the three techniques, Fibonacci expert Robert Fischer, along with his son Dr. Jens Fischer, have created a new, cutting-edge trading strategy that will help you enhance profits and reduce risk.
No matter how good a trading approach may be, if you don’t have the proper understanding of yourself as well as other traders, you’ll never be successful. That’s why Candlesticks, Fibonacci, and Chart Pattern Trading Tools opens with a discussion of some basic principles of trading psychology and investor behavior–including ego, discipline, and patience. From here, you’ll be introduced to the heart of this synergistic approach through in-depth analysis and detailed explanations of: Download here
Thứ Bảy, 19 tháng 2, 2011
Standard Deviation (Volatility)
Standard deviation is a statistical term that measures the amount of variability or dispersion around an average. Standard deviation is also a measure of volatility. Generally speaking, dispersion is the difference between the actual value and the average value. The larger this dispersion or variability is, the higher the standard deviation. The smaller this dispersion or variability is, the lower the standard deviation. Chartists can use the Standard Deviation to measure expected risk and determine the significance of certain price movements.
Calculation
Stockcharts.com calculates the Standard Deviation for a Population, which assumes that the periods involved represent the whole data set, not a sample from a bigger data set. The calculation steps are as follows:
The spreadsheet above shows an example for a 10-period Standard Deviation using QQQQ data. Notice that the 10-period average is calculated after the 10th period and this average is applied to all 10 periods. Building a running standard deviation with this formula would be quite intensive. Excel has an easier way with the STDEVP formula. The table below shows the 10-period Standard Deviation using this formula. Here's an Excel Spreadsheet that shows the Standard Deviation calculations.
- Calculate the average (mean) price for the number of periods or observations.
- Determine each period's deviation (close less average price).
- Square each period's deviation.
- Sum the squared deviations.
- Divide this sum by the number of observations.
- The standard deviation is then equal to the square root of that number.
The spreadsheet above shows an example for a 10-period Standard Deviation using QQQQ data. Notice that the 10-period average is calculated after the 10th period and this average is applied to all 10 periods. Building a running standard deviation with this formula would be quite intensive. Excel has an easier way with the STDEVP formula. The table below shows the 10-period Standard Deviation using this formula. Here's an Excel Spreadsheet that shows the Standard Deviation calculations.
Standard Deviation Values
Standard Deviation values are dependent on the price of the under security. Securities with high prices, such as Google (±550), will have higher Standard Deviation values than securities with low prices, such as Intel (±22). These higher values are not a reflection of higher volatility, but rather a reflection of the actual price. Standard Deviation values are shown in terms that relate directly to the price of the underlying security. Historical Standard Deviation values will also be affected if a security experiences a large price change over a period of time. A security that moves from 10 to 50 will most likely have a higher Standard Deviation at 50 than at 10.
On the chart above, the left scale relates to the Standard Deviation. Google's Standard Deviation scale extends from 2.5 to 35, while the Intel range runs from .10 to .75. Average price changes (deviations) in Google range from $2.5 to $35, while average price changes (deviations) in Intel range from 10 cents to 75 cents.
Despite the range differences, chartists can visually assess volatility changes for each security. Volatility in Intel picked up from April to June as the Standard Deviation moved above .70 numerous times. Google experienced a surge in volatility in October as the Standard Deviation shot above 30. One would have to divide the Standard Deviation by the closing price to directly compare volatility for the two securities.
On the chart above, the left scale relates to the Standard Deviation. Google's Standard Deviation scale extends from 2.5 to 35, while the Intel range runs from .10 to .75. Average price changes (deviations) in Google range from $2.5 to $35, while average price changes (deviations) in Intel range from 10 cents to 75 cents.
Despite the range differences, chartists can visually assess volatility changes for each security. Volatility in Intel picked up from April to June as the Standard Deviation moved above .70 numerous times. Google experienced a surge in volatility in October as the Standard Deviation shot above 30. One would have to divide the Standard Deviation by the closing price to directly compare volatility for the two securities.
Measuring Expectations
The current value of the Standard Deviation can be used to estimate the importance of a move or set expectations. This assumes that price changes are normally distributed with a classic bell curve. Even though price changes for securities are not always normally distributed, chartists can still use normal distribution guidelines to gauge the significance of a price movement. In a normal distribution, 68% of the observations fall within one standard deviation. 95% of the observations fall within two standard deviations. 99.7% of the observations fall within three standard deviations. Using these guidelines, traders can estimate the significance of a price movement. A move greater than one standard deviation would show above average strength or weakness, depending on the direction of the move.
The chart above shows Microsoft (MSFT) with a 21-day Standard Deviation in the indicator window. There are around 21 trading days in a month and the monthly Standard Deviation was .88 on the last day. In a normal distribution, 68% of the 21 observations should show a price change less than 88 cents. 95% of the 21 observations should show a price change of less than 1.76 cents (2 x .88 or two standard deviations). 99.7% of the observations should show a price change of less than 2.64 (3 x .88 or three standard deviations. Price movements that were 1,2 or 3 standard deviations would be deemed noteworthy.
The 21-day Standard Deviation is still quite variable as it fluctuated between .32 and .88 from mid August until mid December. A 250-day moving average can be applied to smooth the indicator and find an average, which is around 68 cents. Price moves larger than 68 cents were greater than the 250-day SMA of the 23-day Standard Deviation. These above average price movements indicate heightened interest that could foreshadow a trend change or mark a breakout.
The chart above shows Microsoft (MSFT) with a 21-day Standard Deviation in the indicator window. There are around 21 trading days in a month and the monthly Standard Deviation was .88 on the last day. In a normal distribution, 68% of the 21 observations should show a price change less than 88 cents. 95% of the 21 observations should show a price change of less than 1.76 cents (2 x .88 or two standard deviations). 99.7% of the observations should show a price change of less than 2.64 (3 x .88 or three standard deviations. Price movements that were 1,2 or 3 standard deviations would be deemed noteworthy.
The 21-day Standard Deviation is still quite variable as it fluctuated between .32 and .88 from mid August until mid December. A 250-day moving average can be applied to smooth the indicator and find an average, which is around 68 cents. Price moves larger than 68 cents were greater than the 250-day SMA of the 23-day Standard Deviation. These above average price movements indicate heightened interest that could foreshadow a trend change or mark a breakout.
Conclusions
The Standard Deviation is a statistical measure of volatility. These values provide chartists with an estimate for expected price movements. Price moves greater than the Standard Deviation show above average strength or weakness. The Standard Deviation is also used with other indicators, such as Bollinger Bands. These bands are set 2 standard deviations above and below a moving average. Moves that exceed the bands are deemed significant enough to warrant attention. As with all indicators, the Standard Deviation should be used in conjunction with other analysis tools, such as momentum oscillators or chart patterns.
Thứ Năm, 17 tháng 2, 2011
Signals [18/2/2011]
GPB/USD : BUY
| Entry | Stop Loss | Take Profit 1 | Take Profit 2 |
| 1.6140->1.6160 | 1.6120 | 1.6230 | 1.6270 |
The Complete Practitioner's Guide to the Bond Market
The Complete Practitioner's Guide to the Bond Market
Publisher: McGraw-Hill | pages: 464 | 2009 | ISBN: 0071637141 | P
| 2,4 mb
Publisher: McGraw-Hill | pages: 464 | 2009 | ISBN: 0071637141 | P
| 2,4 mbSpeaking directly to the practitioner, this thorough guide covers everything there is to know about bonds—from basic concepts to more advanced bond topics. The Complete Practitioner’s Guide to the Bond Market addresses the principles of the bond market and offers the tools to apply them in the real world. By tying the concepts of fixed-income products to big-picture aspects of the economy, this book prepares readers to apply specific tools and methods that will help them glean profits from the bond market.
Download Here
Percentage Price Oscillator
The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers and divergences. Because these signals are no different than those associated with MACD, this article will focus on a few differences between the two. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price. See the ChartSchool article on MACD for information on signals common to both MACD and PPO.
Calculation
Percentage Price Oscillator (PPO): {(12-day EMA - 26-day EMA)/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
Click here for download this spreadsheet example.
Standard PPO is based on the 12-day Exponential Moving Average (EMA) and the 26-day EMA, but these parameters can be changed according to investor or trader preferences. Closing prices are used to calculate the moving averages so PPO signals should be measured against closing prices. A 9-day EMA of PPO is plotted as a signal line to identify upturns and downturns in the indicator.
Interpretation
As with MACD, the PPO reflects the convergence and divergence of two moving averages. PPO is positive when the shorter moving average is above the longer moving average. The indicator moves further into positive territory as the shorter moving average distances itself from the longer moving average. This reflects strong upside momentum. The PPO is negative when the shorter moving average is below the longer moving average. Negative readings grow when the shorter moving average distances itself from the longer moving average (goes further negative). This reflects strong downside momentum. The histogram represents the difference between PPO and its 9-day EMA, the signal line. The histogram is positive when PPO is above its 9-day EMA and negative when PPO is below its 9-day EMA. The PPO-Histogram can be used to anticipate signal line crossovers in the PPO. See the ChartSchool article on the MACD Histogram for signal details.
MACD, PPO and Price
MACD levels are affected by the price of a security. A high priced security will have higher or lower MACD values than a low priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages. Chart 2 shows Google with MACD and PPO for comparative purposes. The 12-day EMA is around 495, the 26-day EMA is around 512 and the difference is -17 (double digits). Notice that Google's MACD reached double digits on the upside and the downside, but the Percentage Price Oscillator ranged from +2.5 to -3.5. MACD values appear higher because Google is priced at a relatively high level. MACD for the Dow Industrials, which is above 10,000, hits triple digits on a regular basis. However, the PPO ranges from -2 to +2, which is a much more definable range.
Although the indicator lines look the same, there are often subtle differences between MACD and PPO. In the Google example, notice how the PPO broke below the February low, but MACD has yet to break its February low. The lower low in the PPO shows expanding downside momentum.
Although the indicator lines look the same, there are often subtle differences between MACD and PPO. In the Google example, notice how the PPO broke below the February low, but MACD has yet to break its February low. The lower low in the PPO shows expanding downside momentum.
Large Price Changes
Because MACD is based on absolute levels, large price changes can affect MACD levels over an extended period of time. If a stock advances from 20 to 100, its MACD levels will be considerably smaller around 20 than around 100. The PPO solves this problem by showing MACD values in percentage terms. Chart 3 shows Baidu (BIDU) advancing from 25 to 75 over a 12 month period. MACD values around 25-30 are going to be generally smaller than MACD values around 70-80. Notice that MACD broke above its July and March highs, but the PPO did not break these corresponding highs. Also note that Baidu becomes overbought when the PPO exceeds +5.
Comparing Different Securities
Because the Percentage Price Oscillator (PPO) is a percentage version of MACD, its values can be compared against other securities. Dell (DELL) and Hewlett Packard (HPQ) are in the same industry group, but their stock prices are at different levels. As of late May 2010, DELL was trading in the high teens and HPQ was trading in the mid 40s. The absolute price level has nothing to do with fundamentals, but it does affect the level of MACD. HPQ will no doubt have a higher MACD than DELL. However, we can apply the Percentage Price Oscillator (PPO) to compare momentum. First, notice that the PPO for DELL ranges from -4 to +4 for an 8 point range). The PPO for HPQ ranges from -3 to +2 for a range of 5. Right off the bat we can see that DELL is more volatile than HPQ because its PPO range is greater. Second, we can see that upside momentum for DELL was stronger than HPQ in March-April. The PPO for DELL advanced from negative territory and exceeded 4. The PPO for HPQ turned positive before the PPO for DELL, but did not exceed 1.6.
Conclusions
The Percentage Price Oscillator (PPO) generates the same signals at MACD, but provides an added dimension as a percentage version of MACD. The PPO levels of the Dow Industrials (price ~11000) can be compared against the PPO levels of IBM (price ~122) because the PPO levels the playing field so to speak. In addition, PPO levels in one security can be compared over extended periods of time, even if the price has doubled or tripled. This is not the case for MACD. Despite its advantages, PPO is still not the best oscillator to identify overbought or oversold conditions because movements are unlimited (in theory). Levels for RSI and the Stochastic Oscillator are limited and this makes them better suited to identify overbought and oversold levels.
Thứ Tư, 16 tháng 2, 2011
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