Příspěvky nebo odpovědi uživatele gold pattern pattern

Understanding Fear

When traders get bad news about a certain stock or about the economy in general, they naturally get scared. They may overreact and feel compelled to liquidate their holdings and sit on the cash, refraining from taking any more risks. If they do, they may avoid certain losses but may also miss out on some gains.

Traders need to understand what fear is: a natural reaction to a perceived threat. In this case, it's a threat to their profit potential.

Quantifying the fear might help. Traders should consider just what they are afraid of, and why they are afraid of it. But that thinking should occur before the bad news, not in the middle of it.

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 Fear and greed are the two visceral emotions to keep in control.

By thinking it through ahead of time, traders will know how they perceive events instinctively and react to them, and can move past the emotional response. Of course, this is not easy, but it's necessary to the health of an investor's portfolio, not to mention the investor.

Overcoming Greed

There's an old saying on Wall Street that "pigs get slaughtered." This refers to the habit greedy investors have of hanging on to a winning position too long to get every last tick upward in price. Sooner or later, the trend reverses and the greedy get caught.

Greed is not easy to overcome. It's often based on the instinct to do better, to get just a little more. A trader should learn to recognize this instinct and develop a trading plan based on rational thinking, not whims or instincts.

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Setting Rules

A trader needs to create rules and follow them when the psychological crunch comes. Set out guidelines based on your risk-reward tolerance for when to enter a trade and when to exit it. Set a profit target and put a stop loss in place to take emotion out of the process.

In addition, you might decide which specific events, such as a positive or negative earnings release, should trigger a decision to buy or sell a stock.

It's wise to set limits on the maximum amount you are willing to win or lose in a day. If you hit the profit target, take the money and run. If your losses hit a predetermined number, fold up your tent and go home.

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Snap Decisions

Traders often have to think fast and make quick decisions, darting in and out of stocks on short notice. To accomplish this, they need a certain presence of mind. They also need the discipline to stick with their own trading plans and know when to book profits and losses. Emotions simply can't get in the way.

Avoid emotional trading

Trading psychology describes how a trader handles generating gains and handling losses. It represents their ability to deal with risks and not deviate from their trading plan. The emotional aspects of investing will attempt to dictate your every transaction, and your ability to handle your emotions is part of your trading psychology.

It is impossible to eliminate emotions in trading, but this should not be the goal in the first place. Instead, traders should understand how certain biases or emotions can affect their trading and use this information to their advantage. Every trader is different, and there is no simple rulebook that everyone should follow.

Identify your personality traits

Develop and follow a trading plan

Have patience

Be adaptive

Take a break after a loss

Accept your winnings

Keep a trading log

Identify your personality traits

One of the keys to developing successful trading psychology is identifying your personality traits early on. You will need to be honest with yourself and say if you have impulsive tendencies or if you are prone to acting out of anger or frustration.

If this is the case, it is important to keep these traits in check while you are actively trading because they can lead you to make rash and ill-advised decisions that have little analytical backing. However, it is also important to play to your personal strengths. For instance, if you are naturally calm and calculated, you can take advantage of these personality traits during your time on the markets.

Equally as important as identifying and being aware of your personality traits and emotions is recognising your biases, as listed above. Biases are an innate aspect of human nature, but you should be aware of what your individual biases are before opening or closing any trades.

Develop and follow a trading plan

Having a trading plan is paramount to ensuring that you achieve your goals. A trading plan acts as the blueprint to your trading, and it should highlight your time commitments, your available trading funds, your risk-reward ratio and a trading strategy that you feel comfortable with.

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For instance, a trading plan could say that you were going to commit one hour every morning and evening to trading, and that you will never commit more than 2% of the total value of your portfolio to any one trade. This can help minimise losses and limit the effect of emotions on your trading as the rules for opening or closing a position are already highlighted for you.

Trading plans should also take into account individual factors that could affect your trading discipline such as your emotions, biases and personality traits. If you make clear what your biases are before you start trading, you might be less inclined to act on them.

Have patience

Patience is integral to discipline and it is crucial that you have patience with your positions. Acting on emotions like fear can lead you to miss out on a profit by closing a position too early. Trust your analysis and remain patient and disciplined. Equally, when looking to enter a trade, it is important to be patient and wait for the opportune moment rather than just jumping into a trade right then and there.

For instance, if you were wanting to speculate on some GBP currency pairs like EUR/GBP or GBP/USD, you may want to wait until just before a Bank of England (BoE) announcement as there tends to be increased volatility at this time.

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Be adaptive

While it is important to have a trading plan, remember that no two days on the markets are the same, and winning streaks don’t exist in trading. With this in mind, you should become comfortable in assessing how the markets are different from day to day and adapt accordingly.

If there is more volatility on one day compared to the day before and the markets are moving particularly unpredictably, you may decide to put your trading activity on hold until you’re sure you understand what is happening. Being adaptive can help to limit your emotions and rule out representative and status quo biases, enabling you to assess each situation on its own merits – ensuring that you are pragmatic during your time on the markets. ...

Trading cycle

Once identified and understood, cycles can add significant value to the technical analysis toolbox. However, they are not perfect. Some will miss, some will disappear and some will provide a direct hit. This is why it is important to use cycles in conjunction with other aspects of technical analysis. Trend establishes direction, oscillators define momentum and cycles anticipate turning points. Look for confirmation with support or resistance on the price chart or a turn in a key momentum oscillator. It can also help to combine cycles. For example, the stock market is known to have 10-week, 20-week, and 40-week cycles. These cycles can be combined with the Six Month Cycle and Presidential Cycle for added value. Signals are enhanced when multiple cycles nest at a cycle low.

A cycle is an event, such as a price high or low, which repeats itself on a regular basis. Cycles exist in the economy, in nature and in financial markets. The basic business cycle encompasses an economic downturn, bottom, economic upturn, and top. Cycles in nature include the four seasons and solar activity (11 years). Cycles are also part of technical analysis of the financial markets. Cycle theory asserts that cyclical forces, both long and short, drive price movements in the financial markets.

Price and time cycles are used to anticipate turning points. Lows are normally used to define cycle length and then project future cycle lows. Even though there is evidence that cycles do indeed exist, they tend to change over time and can even disappear for a while. While this may sound discouraging, trend is the same way. There is indeed evidence that markets trend, but not all the time. Trend disappears when markets move into a trading range and reverses when prices change direction. Cycles can also disappear and even invert. Do not expect cycle analysis to pinpoint reaction highs or lows. Instead, cycle analysis should be used in conjunction with other aspects of technical analysis to anticipate turning points.

The Perfect Cycle and stock signals

The image below shows a perfect cycle with a length of 100 days. The first peak is at 25 days and the second peak is at 125 days (125 - 25 = 100). The first cycle low is at 75 days and the second cycle low is at 175 days (also 100 days later). Notice that the cycle crosses the X-axis at 50, 100 and 150, which is every 50 points or half a cycle.

Chart 1 - Cycles

Crest: Cycle high

Trough: Cycle low

Phase: Position of the cycle at a particular point in time (the example cycle is at .95 on day 20)

Inflection Point: This is where the cycle line crosses the X-axis

Amplitude: Height of the cycle from X-axis to peak or trough

Length: Distance between cycle highs or cycle lows

Observe that this is merely a blueprint for the ideal cycle; most cycles are not this well-defined.

Cycle Characteristics

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Cycle Length: Lows are usually used to define the length of a cycle and project the cycle into the future. A cycle high can be expected somewhere between the cycle lows.

Translation: Cycles almost never peak at the exact midpoint nor trough at the expected cycle low. Most often, peaks occur before or after the midpoint of the cycle. Right translation is the tendency of prices to peak in the latter part of the cycle during bull markets. Conversely, left translation is the tendency of prices to peak in the front half of the cycle during bear markets. Prices tend to peak later in bull markets and earlier in bear markets.

Harmonics: Larger cycles can be broken down into smaller, and equal, cycles. A 40-week cycle divides into two 20-week cycles. A 20-week cycle divides into two 10-week cycles. Sometimes a larger cycle can divide into three or more parts. The inverse is also true. Small cycles can multiply into larger cycles. A 10-week cycle can be part of a larger 20-week cycle and an even larger 40-week cycle.

Nesting: forex signals  A cycle low is reinforced when several cycles signal a trough at the same time. The 10-week, 20-week, and 40-week cycles are nesting when they all trough at the same tim ...

chart patterns

There are hundreds of thousands of market participants buying and selling securities for a wide variety of reasons: hope of gain, fear of loss, tax consequences, short-covering, hedging, stop-loss triggers, price target triggers, fundamental analysis, technical analysis, broker recommendations and a few dozen more. Trying to figure out why participants are buying and selling can be a daunting process. Chart patterns put all buying and selling into perspective by consolidating the forces of supply and demand into a concise picture. As a complete pictorial record of all trading, chart patterns provide a framework to analyze the battle raging between bulls and bears. More importantly, chart patterns and technical analysis can help determine who is winning the battle, allowing traders and investors to position themselves accordingly.

In many ways, chart patterns are simply more complex versions of trend lines. It is important that you read and understand our articles on Support and Resistance as well as Trend Lines before you continue.

Chart pattern analysis can be used to make short-term or long-term forecasts. The data can be intraday, daily, weekly or monthly and the patterns can be as short as one day or as long as many years. Gaps and outside reversals may form in one trading session, while broadening tops and dormant bottoms may require many months to form.

An Oldie but Goodie

Much of our understanding of chart patterns can be attributed to the work of Richard Schabacker. His 1932 classic, Technical Analysis and Stock Market Profits, laid the foundations for modern pattern analysis. In Technical Analysis of Stock Trends (1948), Edwards and Magee credit Schabacker for most of the concepts put forth in the first part of their book. We would also like to acknowledge Messrs. Schabacker, Edwards and Magee, and John Murphy as the driving forces behind these articles and our understanding of chart patterns.

forex signals  Pattern analysis may seem straightforward, but it is by no means an easy task. Schabacker states:

The science of chart reading, however, is not as easy as the mere memorizing of certain patterns and pictures and recalling what they generally forecast. Any general stock chart is a combination of countless different patterns and its accurate analysis depends upon constant study, long experience and knowledge of all the fine points, both technical and fundamental, and, above all, the ability to weigh opposing indications against each other, to appraise the entire picture in the light of its most minute and composite details as well as in the recognition of any certain and memorized formula.

Even though Schabacker refers to “the science of chart reading”, technical analysis can at times be less science and more art. In addition, pattern recognition can be open to interpretation, which can be subject to personal biases. To defend against biases and confirm pattern interpretations, other aspects of technical analysis should be employed to verify or refute the conclusions drawn. While many patterns may seem similar in nature, no two patterns are exactly alike. False breakouts, bogus reads, and exceptions to the rule are all part of the ongoing education.

Careful and constant study are required for successful chart analysis. On the AMZN chart above, the stock broke resistance from a head and shoulders reversal. While the trend is now bearish, analysis must continue to confirm the bearish trend.

Some analysts might have labeled this Novellus (NVLS) chart as a head and shoulders pattern with neckline support around 17.50. Whether or not this is robust remains open to debate. Even though the stock broke neckline support at 17.50, it repeatedly moved back above its support break. This refusal might have been taken as a sign of strength and justified a reassessment of the pattern.

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Continuation Patterns vs. Reversal Patterns

Two basic tenets of technical analysis are that prices trend and that history repeats itself. An uptrend indicates that the forces of demand (bulls) are in control, while a downtrend indicates that the forces of supply (bears) are in control. However, prices do not trend forever and as the balance of power shifts, a chart pattern begins to emerge. Certain patterns, such as a para ...

Investor Behavior

In 2001, Dalbar, a financial-services research firm, released a study entitled "Quantitative Analysis of Investor Behavior," which concluded that average investors consistently fail to achieve returns that beat or even match the broader market indices. The study found that in the 17-year period to December 2000, the S&P 500 returned an average of 16.29% per year, while the typical equity investor achieved only 5.32% for the same period—a startling 9% difference!2 It also found that during the same period, the average fixed-income investor earned only a 6.08% return per year, while the long-term Government Bond Index reaped 11.83%.

In a 2015 follow-up of the same publication, Dalbar again concluded that average investors fail to achieve market-index returns. It found that "the average equity mutual fund investor underperformed the S&P 500 by a wide margin of 8.19%. The broader market return was more than double the average equity mutual fund investor’s return (13.69% vs. 5.50%)."2 Average fixed income mutual fund investors also consistently underperformed—returning 4.81% less than the benchmark bond market index.

Why does this happen? Behavioral finance provides some possible explanations.

Fear of Regret and stock signals

Fear of regret, or simply regret theory, deals with the emotional reaction people experience after realizing they've made an error in judgment. Faced with the prospect of selling a stock, investors become emotionally affected by the price at which they purchased the stock.3 So, they avoid selling it as a way to avoid the regret of having made a bad investment, as well as the embarrassment of reporting a loss. We all hate to be wrong, don't we?

What investors should really ask themselves when contemplating selling a stock is: "What are the consequences of repeating the same purchase if this security were already liquidated and would I invest in it again?" If the answer is "no," it's time to sell; otherwise, the result is regret in buying a losing stock and the regret of not selling when it became clear that a poor investment decision was made—and a vicious cycle ensues where avoiding regret leads to more regret.

Regret theory can also hold true for investors when they discover that a stock they had only considered buying has increased in value. Some investors avoid the possibility of feeling this regret by following the conventional wisdom and buying only stocks that everyone else is buying, rationalizing their decision with "everyone else is doing it."

Oddly enough, many people feel much less embarrassed about losing money on a popular stock that half the world owns than about losing money on an unknown or unpopular stock.

stock signals and Mental Accounting Behaviors

Humans have a tendency to place particular events into mental compartments, and the difference between these compartments sometimes impacts our behavior more than the events themselves.

Say, for example, you aim to catch a show at the local theater and tickets are $20 each. When you get there, you realize you've lost a $20 bill. Do you buy a $20 ticket for the show anyway? Behavior finance has found that roughly 88% of people in this situation would do so.4 Now, let's say you paid for the $20 ticket in advance. When you arrive at the door, you realize your ticket is at home. Would you pay $20 to purchase another? Only 40% of respondents would buy another. Notice, however, that in both scenarios, you're out $40: different scenarios, the same amount of money, different mental compartments. Pretty silly, huh?

An investing example of mental accounting is best illustrated by the hesitation to sell an investment that once had monstrous gains and now has a modest gain. During an economic boom and bull market, people get accustomed to healthy, albeit paper, gains. When the market correction deflates investor's net worth, they're more hesitant to sell at the smaller profit margin. They create mental compartments for the gains they once had, causing them to wait for the return of that profitable period.

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Prospect Theory and Loss-Aversion

It doesn't take a neurosurgeon ...

Perfect Cycle

Once identified and understood, cycles can add significant value to the technical analysis toolbox. However, they are not perfect. Some will miss, some will disappear and some will provide a direct hit. This is why it is important to use cycles in conjunction with other aspects of technical analysis. Trend establishes direction, oscillators define momentum and cycles anticipate turning points. Look for confirmation with support or resistance on the price chart or a turn in a key momentum oscillator. It can also help to combine cycles. For example, the stock market is known to have 10-week, 20-week, and 40-week cycles. These cycles can be combined with the Six Month Cycle and Presidential Cycle for added value. Signals are enhanced when multiple cycles nest at a cycle low.

A cycle is an event, such as a price high or low, which repeats itself on a regular basis. Cycles exist in the economy, in nature and in financial markets. The basic business cycle encompasses an economic downturn, bottom, economic upturn, and top. Cycles in nature include the four seasons and solar activity (11 years). Cycles are also part of technical analysis of the financial markets. Cycle theory asserts that cyclical forces, both long and short, drive price movements in the financial markets.

Price and time cycles are used to anticipate turning points. Lows are normally used to define cycle length and then project future cycle lows. Even though there is evidence that cycles do indeed exist, they tend to change over time and can even disappear for a while. While this may sound discouraging, trend is the same way. There is indeed evidence that markets trend, but not all the time. Trend disappears when markets move into a trading range and reverses when prices change direction. Cycles can also disappear and even invert. Do not expect cycle analysis to pinpoint reaction highs or lows. Instead, cycle analysis should be used in conjunction with other aspects of technical analysis to anticipate turning points.

The Perfect Cycle and stock signals

The image below shows a perfect cycle with a length of 100 days. The first peak is at 25 days and the second peak is at 125 days (125 - 25 = 100). The first cycle low is at 75 days and the second cycle low is at 175 days (also 100 days later). Notice that the cycle crosses the X-axis at 50, 100 and 150, which is every 50 points or half a cycle.

Cycle Characteristics and Best Signals

Cycle Length: Lows are usually used to define the length of a cycle and project the cycle into the future. A cycle high can be expected somewhere between the cycle lows.

Translation: Cycles almost never peak at the exact midpoint nor trough at the expected cycle low. Most often, peaks occur before or after the midpoint of the cycle. Right translation is the tendency of prices to peak in the latter part of the cycle during bull markets. Conversely, left translation is the tendency of prices to peak in the front half of the cycle during bear markets. Prices tend to peak later in bull markets and earlier in bear markets.

Harmonics: Larger cycles can be broken down into smaller, and equal, cycles. A 40-week cycle divides into two 20-week cycles. A 20-week cycle divides into two 10-week cycles. Sometimes a larger cycle can divide into three or more parts. The inverse is also true. Small cycles can multiply into larger cycles. A 10-week cycle can be part of a larger 20-week cycle and an even larger 40-week cycle.

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Nesting: A cycle low is reinforced when several cycles signal a trough at the same time. The 10-week, 20-week, and 40-week cycles are nesting when they all trough at the same time.

Inversions: Sometimes a cycle high occurs when there should be a cycle low and vice versa. This can happen when a cycle high or low is skipped or is minimal. A cycle low may be short or almost non-existent in a strong uptrend. Similarly, markets can fall fast and skip a cycle high during sharp declines. Inversions are more prominent with shorter cycles and less co ...

What Is a Technical Indicator?

A technical indicator is a series of data points that are derived by applying a formula to the price data of a security. Price data includes any combination of the open, high, low or close over a period of time. Some indicators may use only the closing prices, while others incorporate volume and open interest into their formulas. The price data is entered into the formula and a data point is produced. For example, the average of 3 closing prices is one data point [(41 + 43 + 43) / 3 = 42.33].

However, one data point does not offer much information and does not make for a useful indicator. A series of data points over a period of time is required to create valid reference points to enable analysis. By creating a time series of data points, a comparison can be made between present and past levels. For analysis purposes, technical indicators are usually shown in a graphical form above or below a security's price chart. Once shown in graphical form, an indicator can then be compared with the corresponding price chart of the security. Sometimes indicators are plotted on top of the price plot for a more direct comparison.

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What Does a Technical Indicator Offer?

A technical indicator offers a different perspective from which to analyze the price action. Some, such as moving averages, are derived from simple formulas and the mechanics are relatively easy to understand. Others, such as Stochastics, have complex formulas and require more study to fully understand and appreciate. Regardless of the complexity of the formula, technical indicators can provide a unique perspective on the strength and direction of the underlying price action.

A simple moving average is an indicator that calculates the average price of a security over a specified number of periods. If a security is exceptionally volatile, then a moving average will help to smooth the data. A moving average filters out random noise and offers a smoother perspective of the price action. Veritas (VRTSE) displays a lot of volatility and an analyst may have difficulty discerning a trend. By applying a 10-day simple moving average to the price action, random fluctuations are smoothed to make it easier to identify a trend.

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Why Use Indicators?

Indicators serve three broad functions: to alert, to confirm and to predict.

An indicator can act as an alert to study price action a little more closely. If momentum is waning, it may be a signal to watch for a break of support. Alternatively, if there is a large positive divergence building, it may serve as an alert to watch for a resistance breakout.

Indicators can be used to confirm other technical analysis tools. If there is a breakout on the price chart, a corresponding moving average crossover could serve to confirm the breakout. If a stock breaks support, a corresponding low in the On-Balance-Volume (OBV) could serve to confirm the weakness.

According to some investors and traders, indicators can be used to predict the direction of future prices.

Tips for Using Indicators

Indicators indicate. This may sound straightforward, but sometimes traders ignore the price action of a security and focus solely on an indicator. Indicators filter price action with formulas. As such, they are derivatives and not direct reflections of the price action. This should be taken into consideration when applying analysis. Any analysis of an indicator should be taken with the price action in mind. What is the indicator saying about the price action of a security? Is the price action getting stronger? Weaker?

Even though it may be obvious when indicators generate buy and sell signals, the signals should be taken in context with other technical analysis tools. An indicator may flash a buy signal, but if the chart pattern shows a descending triangle with a series of declining peaks, it may be a false signal.

On the Rambus (RMBS) chart, MACD improved from November to March, forming a positive divergence. All the earmarks of a MACD buying opportunity were present, but the stock failed to break above the resistance and exceed its pr ...

The signal is generated by a human analyst supplied to a subscriber of the  forex signal  service
Exact entry, exit and stop loss figures for trades on currency pairs.

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Moving averages

The advantages of using moving averages need to be weighed against the disadvantages. Moving averages are trend following, or lagging, indicators that will always be a step behind. This is not necessarily a bad thing though. After all, the trend is your friend and it is best to trade in the direction of the trend. Moving averages ensure that a trader is in line with the current trend. Even though the trend is your friend, securities spend a great deal of time in trading ranges, which render moving averages ineffective. Once in a trend, moving averages will keep you in, but also give late signals. Don't expect to sell at the top and buy at the bottom using moving averages. As with most technical analysis tools, moving averages should not be used on their own, but in conjunction with other complementary tools. Chartists can use moving averages to define the overall trend and then use RSI to define overbought or oversold levels.

Price Crossovers

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Moving averages can also be used to generate signals with simple price crossovers. A bullish signal is generated when prices move above the moving average. A bearish signal is generated when prices move below the moving average. Price crossovers can be combined to trade within the bigger trend. The longer moving average sets the tone for the bigger trend and the shorter moving average is used to generate the signals. One would look for bullish price crosses only when prices are already above the longer moving average. This would be trading in harmony with the bigger trend. For example, if price is above the 200-day moving average, chartists would only focus on signals when price moves above the 50-day moving average. Obviously, a move below the 50-day moving average would precede such a signal, but such bearish crosses would be ignored because the bigger trend is up. A bearish cross would simply suggest a pullback within a bigger uptrend. A cross back above the 50-day moving average would signal an upturn in prices and continuation of the bigger uptrend.

Gold Forecast

The next chart shows Emerson Electric (EMR) with the 50-day EMA and 200-day EMA. The stock crossed and held above the 200-day moving average in August. There were dips below the 50-day EMA in early November and again in early February. Prices quickly moved back above the 50-day EMA to provide bullish signals (green arrows) in harmony with the bigger uptrend. MACD(1,50,1) is shown in the indicator window to confirm price crosses above or below the 50-day EMA. The 1-day EMA equals the closing price. MACD(1,50,1) is positive when the close is above the 50-day EMA and negative when the close is below the 50-day EMA.

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Moving averages smooth the price data to form a trend following indicator. They do not predict price direction, but rather define the current direction, though they lag due to being based on past prices. Despite this, 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. The two most popular types of moving averages are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA). These moving averages can be used to identify the direction of the trend or define potential support and resistance levels.

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