Posts Tagged ‘trading’

The Pioneers of Technical Analysis

Written by admin. Posted in Technical Analysis

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Whether you consider yourself a technical analyst or not, there are very few investing techniques that do not at least give a nod to the technical side of investing. Some investing styles use nothing but technical analysis, with their practitioners often claiming that they know nothing of stock fundamentals because all they need is in the charts. This segment of investing didn’t sprout from nothing. In this article, we will look at the men that pioneered the field of technical analysis. (See also: Technical Analysis.)

All Things Flow From Dow

Charles Dow occupies a huge place in the history of finance. He founded The Wall Street Journal – the benchmark by which all financial papers are measured – and, more importantly for our purpose, he created the Dow Jones Industrial Index. In doing so, Dow opened the door to technical analysis. Dow recorded the highs and lows of his average daily, weekly and monthly, correlating the patterns with the ebb and flow of the market. He would then write articles, always after the fact, pointing out how certain patterns explained and predicted previous market events.

However, Dow can’t take all – or even a majority of – the credit for the theory bearing his name. Dow Theory would have only acted as a hindsight confirmation of loose principals if it weren’t for William P. Hamilton. (See also: Giants of Finance: Charles Dow.)

First One Into the Water: William P. Hamilton

Dow Theory was a collection of market trends linked heavily to oceanic metaphors. The fundamental, long-term trend of four or more years was the tide of the market – either rising (bullish) or falling (bearish). This was followed by shorter-term waves that lasted between a week and a month. And, lastly, there were the splashes and tiny ripples of choppy water insignificant day-to-day fluctuations.

Hamilton used these measures in addition to a few rules – such as the railroad average and the industrial average confirming each other’s direction – to call bull and bear markets with laudable accuracy. Although he did call the 1929 crash too early (1927, 1928), he made a final appeal on Oct. 21, 1929, three days before the crash and mere weeks before his death at the age of 63.

The Practitioner: Robert Rhea

Robert Rhea took Dow Theory and turned it into a practical indicator for going long or short in the market. He literally wrote the book on the topic: “The Dow Theory” (1932). Rhea was successful at using the theory to call tops and bottoms – and able enough to profit from those calls. Very soon after mastering Dow Theory, Rhea didn’t need to trade on his knowledge. He only had to write it down.

After calling the market bottom in 1932 and a top in 1937, the fortunes made by subscribers to Rhea’s investment letter, Dow Theory Comments, brought in thousands more subscribers. As with Hamilton, however, Rhea’s life as a market prognosticator was short – he died in 1939. (See also: Dow Theory Tutorial.)

The Wizard: Edson Gould

Perhaps the most accurate forecaster with the longest track record, Edson Gould, was still making calls up to 1983 at the age of 81. Gould also made most of his money from writing newsletters rather than investing, selling subscriptions for $500 in 1930. He caught all of the major bull and bear market points, making several eerily accurate predictions, such as the Dow rising 400 points in a 20-year bull market, that the Dow would top 1,040 in 1973 and so on.

Gould used charts, market psychology and indicators including the Senti-Meter – the DJIA divided by the dividends per share of the companies. Gould was so good at his trade that he continued to make accurate calls from beyond the grave. Gould died in 1987, but in 1991, the Dow hit 3,000, as he’d predicted. At the time of his prediction in 1979, the Dow had yet to break 1,000.

[The work of these pioneers formed the foundation for a huge array of technical tools used by traders today to develop profitable trading strategies. To learn more, check out the Technical Analysis course on the Investopedia Academy, which includes interactive content and real-world examples to boost your trading skills.]

The Chartist: John Magee

John Magee wrote the bible of technical analysis, “Technical Analysis of Stock Trends” (1948). Magee was one of the first to trade solely on the stock price and its pattern on the historical charts. Magee charted everything: individual stocks, averages, trading volumes – basically anything that could be graphed. He then poured over these charts to identify broad patterns and specific shapes like weak triangles, flags, bodies, shoulders and so on.

Unfortunately for Magee, early on, he was better at looking after his clients than his own portfolio, often selling out in his own portfolio based on gut feelings despite strong hold signals from his charts. From his 40s to his death at 86, however, Magee was one of the most disciplined technical analysts around, refusing to even read a current newspaper lest it interfere with the signals of his charts. (For more, see: Analyzing Chart Patterns.)

The Omissions

There is bound to be some controversy with a list like this. Where is the infamous Jesse Livermore, the trader whose gut calls on price ticks are arguably the first successful technical trades? What about R. N. Elliott? What about WD Gann?

Well, Livermore did little in the area of theorizing and died broke. Elliott tweaked technical analysis with his own hypothesis, but his theories are difficult to test and even harder to trade – involving something of mysticism piled on top of numbers. Similarly, Gann’s lines, while seemingly useful in concept, are so sensitive to error that their practicality is questionable. Both of these men were purported to have made fortunes trading on their theories, but there is no solid record to back that up as there is for Livermore. Certainly no multi-million-dollar estate was left behind by either.

The Bottom Line

Dow, Hamilton, Rhea, Gould and Magee are on the main track of technical analysis, each carrying the theory and practice a little further. There are of course, many branching side paths that, while interesting detours, didn’t advance this main thrust. Every time an investor – fundamental or technical – talks about getting in low or picking entry and exit points, they are paying homage to these men and the techniques for which they laid the foundation. (See also: Introduction to Types of Trading: Technical Traders.)

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Understanding Trend Analysis and Trend Trading Strategies

Written by admin. Posted in Technical Analysis

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What Is Trend Analysis?

Trend analysis is a technique used in technical analysis that attempts to predict future stock price movements based on recently observed trend data. Trend analysis uses historical data, such as price movements and trade volume, to forecast the long-term direction of market sentiment.

Key Takeaways

  • Trend analysis tries to predict a trend, such as a bull market run, and then ride that trend until data suggests a trend reversal, such as a bull-to-bear market.
  • Trend analysis is based on the idea that what has happened in the past gives traders an idea of what will happen in the future.
  • Trend analysis focuses on three typical time horizons: short-; intermediate-; and long-term.

Understanding Trend Analysis

Trend analysis tries to predict a trend, such as a bull market run, and ride that trend until data suggests a trend reversal, such as a bull-to-bear market. Trend analysis is helpful because moving with trends, and not against them, will lead to profit for an investor. It is based on the idea that what has happened in the past gives traders an idea of what will happen in the future. There are three main types of trends: short-, intermediate- and long-term.

A trend is a general direction the market is taking during a specified period of time. Trends can be both upward and downward, relating to bullish and bearish markets, respectively. While there is no specified minimum amount of time required for a direction to be considered a trend, the longer the direction is maintained, the more notable the trend.

Trend analysis is the process of looking at current trends in order to predict future ones and is considered a form of comparative analysis. This can include attempting to determine whether a current market trend, such as gains in a particular market sector, is likely to continue, as well as whether a trend in one market area could result in a trend in another. Though a trend analysis may involve a large amount of data, there is no guarantee that the results will be correct.

Types of Trends to Analyze

There are three main types of market trend for analysts to consider:

  1. Upward trend: An upward trend, also known as a bull market, is a sustained period of rising prices in a particular security or market. Upward trends are generally seen as a sign of economic strength and can be driven by factors such as strong demand, rising profits, and favorable economic conditions.
  2. Downward trend: A downward trend, also known as a bear market, is a sustained period of falling prices in a particular security or market. Downward trends are generally seen as a sign of economic weakness and can be driven by factors such as weak demand, declining profits, and unfavorable economic conditions.
  3. Sideways trend: A sideways trend, also known as a rangebound market, is a period of relatively stable prices in a particular security or market. Sideways trends can be characterized by a lack of clear direction, with prices fluctuating within a relatively narrow range.

How to Perform a Trend Analysis

In order to begin analyzing applicable data, it is necessary to first determine which market segment will be analyzed. For instance, you could focus on a particular industry, such as the automotive or pharmaceuticals sector, as well as a particular type of investment, such as the bond market.

Once the sector has been selected, it is possible to examine its general performance. This can include how the sector was affected by internal and external forces. For example, changes in a similar industry or the creation of a new governmental regulation would qualify as forces impacting the market. Analysts then take this data and attempt to predict the direction the market will take moving forward.

Trend Trading Strategies

Trend traders attempt to isolate and extract profit from trends. There are many different trend trading strategies using a variety of technical indicators:

  • Moving Averages: These strategies involve entering into long positions when a short-term moving average crosses above a long-term moving average, and entering short positions when a short-term moving average crosses below a long-term moving average.
  • Momentum Indicators: These strategies involve entering into long positions when a security is trending with strong momentum and exiting long positions when a security loses momentum. Often, the relative strength index (RSI) is used in these strategies.
  • Trendlines & Chart Patterns: These strategies involve entering long positions when a security is trending higher and placing a stop-loss below key trendline support levels. If the stock starts to reverse, the position is exited for a profit.

Indicators can simplify price information, as well as provide trend trade signals or warn of reversals. They may be used on all time frames, and have variables that can be adjusted to suit each trader’s specific preferences.

Usually, it is advisable to combine indicator strategies or come up with your own guidelines, so entry and exit criteria are clearly established for trades. Each indicator can be used in more ways than outlined. If you like an indicator, research it further, and most importantly, test it out before using it to make live trades.

Trend following is a trading system based on using trend analysis and following the recommendation produced to determine which investments to make. Often, the analysis is conducted via computer analysis and modeling of relevant data and is tied to market momentum.

Advantages and Disadvantages of Trend Analysis

Advantages

Trend analysis can offer several advantages for investors and traders. It is a powerful tool for investors and traders as it can help identify opportunities for buying or selling securities, minimize risk, improve decision-making, and enhance portfolio performance.

Trend analysis can be based on a variety of data points, including financial statements, economic indicators, and market data, and there are several different methods that can be used to analyze trends, including technical analysis and fundamental analysis. By providing a deeper understanding of the factors that are driving trends in data, trend analysis can help investors and traders make more informed and confident decisions about their investments.

Disadvantages

Trend analysis can have some potential disadvantages as a tool for making investment decisions. One of these disadvantages is that the accuracy of the analysis depends on the quality of the data being used. If the data is incomplete, inaccurate, or otherwise flawed, the analysis may be misleading or inaccurate.

Another potential disadvantage is that trend analysis is based on historical data, which means it can only provide a limited perspective on the future. While trends in data can provide useful insights, it’s important to remember that the future is not necessarily predetermined by the past, and unexpected events or changes in market conditions can disrupt trends. Trend analysis is also focused on identifying patterns in data over a given period of time, which means it may not consider other important factors that could impact the performance of a security or market.

Finally, trend analysis often relies on statistical measures to identify patterns in data, which can be subject to interpretation. Different statistical measures can yield different results, and it’s important to be aware of the limitations and assumptions of the statistical methods being used.

Critics of trend analysis, and technical trading in general, argue that markets are efficient, and already price in all available information. That means that history does not necessarily need to repeat itself and that the past does not predict the future. Adherents of fundamental analysis, for example, analyze the financial condition of companies using financial statements and economic models to predict future prices. For these types of investors, day-to-day stock movements follow a random walk that cannot be interpreted as patterns or trends.

Trend Analysis Pros and Cons

Pros

  • Can help identify opportunities for buying or selling securities

  • Can identify potential risks or warning signs that a security or market may be headed for a downturn

  • Provides insight into market psychology and momentum

Cons

  • If markets are efficient, trend analysis is not as useful

  • If the data is incomplete, inaccurate, or otherwise flawed, the analysis may also be misleading or inaccurate

  • May not take into account changes in a company’s management, changes in industry regulations, or other external factors that could affect the security’s performance

  • Different statistical measures can yield different results

Example of a Trend Analysis

Say that an investor is considering buying shares of a particular company, and they want to use trend analysis to determine whether the stock is likely to rise in value. To conduct their analysis, the investor gathers data on the company’s financial performance over the past five years, including its revenues, expenses, profits, and other key metrics. They also gather data on the overall performance of the stock market and on the company’s industry.

Using this data, the investor creates charts to visualize the trends in the data. They notice that the company’s revenues have been steadily increasing over the past five years, and that its profits have also been trending upward. They also notice that the stock market has been generally trending upward over the same period.

The investor then uses linear regression to model the relationship between the company’s profits and its stock price, and they find that there is a strong positive correlation between the two variables. This suggests that as the company’s profits have increased, its stock price has also tended to rise.

Based on their analysis, the investor concludes that the company’s stock is likely to continue trending upward in the future, and they decide to buy shares of the stock.

What Is a Trend?

A trend is the overall direction of a market during a specified period of time. Trends can be both upward and downward, relating to bullish and bearish markets, respectively. While there is no specified minimum amount of time required for a direction to be considered a trend, the longer the direction is maintained, the more notable the trend. Trends are identified by drawing lines, known as trendlines, that connect price action making higher highs and higher lows for an uptrend, or lower lows and lower highs for a downtrend.

What Is the Formula or Model for Trend Analysis?

There is no one formula for trend analysis, as the specific methods used to analyze trends can vary depending on the data being analyzed and the goals of the analysis. However, there are several statistical measures that are commonly used in trend analysis to identify patterns and trends in data.

Here are a few examples of statistical measures that might be used in trend analysis:

  • Moving averages: A moving average is a statistical measure that is used to smooth out fluctuations in data over time. A simple moving average (SMA) is calculated by taking the average of a set of data points over a given period of time, such as the past 10 days or the past 50 weeks. Moving averages can be used to identify trends by smoothing out short-term fluctuations in data and highlighting longer-term patterns.
  • Linear regression: Linear regression is a statistical method that is used to model the relationship between two variables. It can be used to identify trends by fitting a line to the data and determining the slope of the line, which can indicate the direction and strength of the trend.
  • Correlation: Correlation is a statistical measure that indicates the strength and direction of the relationship between two variables. A positive correlation means that the variables are moving in the same direction, while a negative correlation means that they are moving in opposite directions. Correlation can be used to identify trends by analyzing the relationship between two variables over time.

It’s important to note that these are just a few examples of statistical measures that might be used in trend analysis, and there are many other methods and measures that could also be used depending on the specific needs of the analysis.

What Are Examples of Trend Trading Strategies?

Trend trading strategies attempt to isolate and extract profit from trends by combining a variety of technical indicators along with the financial instrument’s price action. Typically, these include moving averages, momentum indicators, and trendlines, and chart patterns.

Moving averages strategies involve entering into long, or short, positions when the short-term moving average crosses above, or below, a long-term moving average. Momentum indicator strategies involve entering into positions when a security is exhibiting strong momentum and exiting when that wanes. Trendlines and chart pattern strategies involve entering long, or short, positions when a security is trending higher, or lower, and placing a stop-loss below, or above, key trendline support levels to exit the trade.

How Do You Prepare a Trend Analysis?

To prepare a trend analysis as a trader, you will typically need to follow these steps:

  1. Identify the security or market you want to analyze: Decide which security or market you want to analyze in order to identify trends that could inform your trading decisions. This could be a specific stock, bond, currency, commodity, or other financial instrument, or it could be a broader market index or sector.
  2. Gather the data: Collect data on the security or market you have identified. This may involve accessing financial statements, downloading market data, or accessing databases or other sources of data.
  3. Organize the data: Organize the data in a way that makes it easy to analyze. This could involve creating spreadsheets, charts, or graphs to visualize the data.
  4. Analyze the data: Use your chosen method of analysis to identify trends in the data. This could involve looking for patterns in the data, calculating statistical measures such as averages or standard deviations, or using graphical tools such as charts to identify trends.
  5. Interpret the results: Once you have identified trends in the data, interpret the results to determine what they mean for your trading decisions. This could involve making predictions about the future direction of the security or market, identifying risks or opportunities, or making recommendations for buying, selling, or holding the security.
  6. Use the results to inform your trading decisions: Use the insights gained from your trend analysis to inform your trading decisions. This could involve adjusting your portfolio, placing trades, or making other decisions based on the trends you have identified.

What Are Some Criticisms of Trend Analysis?

Critics of trend analysis, and technical trading in general, argue that markets are efficient, and already price in all available information. That means that history does not necessarily need to repeat itself and that the past does not predict the future. Adherents of fundamental analysis, for example, analyze the financial condition of companies using financial statements and economic models to predict future prices. For these types of investors, day-to-day stock movements follow a random walk that cannot be interpreted as patterns or trends.

The Bottom Line

Trend analysis is the study of data to identify patterns or trends that can be used to make investment decisions. This type of analysis is typically used to analyze the performance of a particular security, such as a stock or bond, over a given period of time. By studying trends in data, investors can make informed decisions about whether to buy, sell, or hold a particular security. There are several different methods that can be used to analyze trends, including technical analysis, which uses charts and other graphical tools to identify patterns in price and volume data, and fundamental analysis, which focuses on a company’s financial health and industry conditions to make investment decisions. Trend analysis can thus incorporate a variety of data sources, including price charts, financial statements, economic indicators, and market data.

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Best Technical Indicators for Rookie Traders

Written by admin. Posted in Technical Analysis

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Starting out in the trading game? Looking for the best technical indicators to follow the action is important. It affects how you’ll interpret trends—both on positions and in the broad averages—as well as the type of opportunities that pop up in your nightly research. Choose wisely and you’ve built a solid foundation for success in speculation. Choose poorly and predators will be lining up, ready to pick your pocket at every turn.

Key Takeaways

  • In general, technical indicators fit into five categories: trend, mean reversion, relative strength, volume, and momentum.
  • Leading indicators attempt to predict where the price is headed while lagging indicators offer a historical report of background conditions that resulted in the current price being where it is.
  • Popular technical indicators include simple moving averages (SMAs), exponential moving averages (EMAs), bollinger bands, stochastics, and on-balance volume (OBV).

Novice Trading Strategies

Most novices follow the herd when building their first trading screens, grabbing a stack of canned indicators and stuffing as many as possible under the price bars of their favorite securities. This “more is better” approach short circuits signal production because it looks at the market from too many angles at once. It’s ironic because indicators work best when they simplify the analysis—cutting through the noise and providing usable output on-trend, momentum, and timing.

Instead, take a different approach by breaking down the types of information you want to follow during the market day, week, or month. In truth, nearly all technical indicators fit into five categories of research. Each category can be further subdivided into leading or lagging. Leading indicators attempt to predict where the price is headed while lagging indicators offer a historical report of background conditions that resulted in the current price being where it is.

  • Trend indicators (lagging) analyze whether a market is moving up, down, or sideways over time.
  • Mean reversion indicators (lagging) measure how far a price swing will stretch before a counter impulse triggers a retracement.
  • Relative strength indicators (leading) measure oscillations in buying and selling pressure.
  • Momentum indicators (leading) evaluate the speed of price change over time.
  • Volume indicators (leading or lagging) tally up trades and quantify whether bulls or bear are in control.

So, how can a beginner choose the right setting at the start and avoid months of ineffective signal production? The best approach in most cases is to begin with the most popular numbers—while adjusting one indicator at a time—and seeing if the output helps or hurts your performance. Using this method, you’ll quickly grasp the specific needs of your level.

Now that you understand the five ways that indicators dissect market action, let’s identify the best ones in each category for novice traders.

Trend Indicators

50-Day EMA and 200-Day EMA

Image by Sabrina Jiang © Investopedia 2020

We’ll start with two indicators that are embedded within the same panel as the daily, weekly, or intraday price bars. Moving averages look back at price action over specific time periods, subdividing the total to create a running average that’s updated with each new bar. The 50- and 200-day exponential moving averages (EMAs) are more responsive versions of their better-known cousins, simple moving averages (SMAs). In a nutshell, the 50-day EMA is used to measure the average intermediate price of a security, while the 200-day EMA measures the average long term price.

U.S. Oil Fund (USO)’s 50- and 200-day EMAs rose steadily into the summer of 2014, while the instrument pushed up to a 9-month high. The 50-day EMA turned lower in August, with the 200-day EMA following suit one month later. The shorter-term average then crossed over the longer-term average (indicated by the red circle), signifying a bearish change in trend that preceded a historic breakdown.

Mean Reversion Indicators

Bollinger Bands

USO buying and selling impulses stretch into seemingly hidden levels that force counter waves or retracements to set into motion. Bollinger bands (20, 2) try to identify these turning points by measuring how far price can travel from a central tendency pivot—the 20-day SMA in this case—before triggering a reversionary impulse move back to the mean.

The bands also contract and expand in reaction to volatility fluctuations, showing observant traders when this hidden force is no longer an obstacle to rapid price movement.

Relative Strength Indicators

Stochastics

Image by Sabrina Jiang © Investopedia 2020

Market movement evolves through buy-and-sell cycles that can be identified through stochastics (14,7,3) and other relative strength indicators. These cycles often reach a peak at overbought or oversold levels and then shift in the opposite direction, with the two indicator lines crossing over. Cycle alternations don’t automatically translate into higher or lower security prices as you might expect. Rather, bullish or bearish turns signify periods in which buyers or sellers are in control of the ticker tape. It still takes volume, momentum, and other market forces to generate price change.

SPDR S&P Trust (SPY) oscillates through a series of buy-and-sell cycles over a 5-month period. Look for signals where:

  1. A crossover has occurred at or near an overbought or oversold level
  2. Indicator lines then thrust toward the center of the panel.

This two-tiered confirmation is necessary because stochastics can oscillate near extreme levels for long periods in strongly trending markets. And, while 14,7,3 is a perfect setting for novice traders, consider experimenting to find the setting that best fits the instrument you are analyzing. For example, experienced traders switch to faster 5,3,3 inputs.

Momentum Indicators

MACD

Image by Sabrina Jiang © Investopedia 2020

Moving average convergence divergence (MACD) indicator, set at 12, 26, 9, gives novice traders a powerful tool to examine rapid price change. This classic momentum tool measures how fast a particular market is moving while it attempts to pinpoint natural turning points. Buy or sell signals go off when the histogram reaches a peak and reverses course to pierce through the zero line. The height or depth of the histogram, as well as the speed of change, all interact to generate a variety of useful market data.

SPY shows four notable MACD signals over a 5-month period. The first signal flags waning momentum, while the second captures a directional thrust that unfolds right after the signal goes off. The third signal looks like a false reading but accurately predicts the end of the February–March buying impulse. The fourth triggers a whipsaw that’s evident when the histogram fails to penetrate the zero line. 

Volume Indicators

On-Balance-Volume (OBV)

Image by Sabrina Jiang © Investopedia 2020

Keep volume histograms under your price bars to examine current levels of interest in a particular security or market. The slope of participation over time reveals new trends—often before price patterns complete breakouts or breakdowns. You can also place a 50-day average of volume across the indicator to see how the current session compares with historic activity.

Now add on-balance volume (OBV), an accumulation-distribution indicator, to complete your snapshot of transaction flow. The indicator adds up buying and selling activity, establishing whether bulls or bears are winning the battle for higher or lower prices. You can draw trendlines on OBV, as well as track the sequence of highs and lows. It works extremely well as a convergence-divergence tool. For example, between January and April, Bank of America (BAC) proved this when prices hit a higher high while OBV hit a lower high, signaling a bearish divergence preceding a steep decline.

The Bottom Line

Choosing the right technical indicators is daunting but can be managed if novice traders focus the effects into five categories of market research: trend, mean reversion, relative strength, momentum, and volume. Once they’ve added effective indicators for each category, they can begin the long but satisfying process of tweaking inputs to match their trading styles and risk tolerance.

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How to Apply Technical Indicators to Mutual Funds

Written by admin. Posted in Technical Analysis

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Most investors evaluate mutual funds using the principles of fundamental rather than technical analysis. Mutual funds tend to be long-term, buy-and-hold investments, and technical analysis is better suited to shorter-term trading.

That said, investors should not overlook the value of some common technical indicators to provide trading insights for almost any kind of investment or financial instrument, including mutual funds. Below are five common technical indicators that can be applied to mutual funds.

Key Takeaways

  • Mutual funds are most often evaluated using fundamental analysis as opposed to technical analysis, which is more commonly used for shorter-term trading.
  • Technical analysis, however, can provide a significant amount of insight into most investments and financial assets, including mutual funds.
  • Common technical indicators that can help evaluate a mutual fund as a good or bad investment include trendlines, moving averages, the relative strength index (RSI), support and resistance levels, and chart formations.

1. Trendlines

Most technical analysis starts with trendlines, which are lines that connect multiple price points and extend into the future to identify price trends and areas of support/resistance. For mutual funds, look at a long-term price chart in order to determine its trend.

A trendline can be plotted by drawing a line that connects multiple lows of a mutual fund over time. The fund may have tested this trendline on numerous occasions over the years. If the fund price breaks conclusively through a well-established, long-term trendline, it is a bearish signal. An investor in such a fund should consider selling their fund holdings if this occurs.

Conversely, a breakout above a well-defined trendline may be a bullish signal, indicating the investor should stay in the fund. 

2. Moving Averages

Moving averages are averages of time-series data, such as prices. Investors can use these to identify price trends of a mutual fund. A rising moving average suggests that the fund is in an uptrend, while a declining moving average would indicate that it is in a downtrend.

A second major application arises from the crossover of two moving averages, for example, a short-term, 20-day moving average and a long-term, 200-day moving average.

If the 20-day moving average breaks above the 200-day moving average, this would be considered a bullish signal for the mutual fund. Conversely, if the 20-day moving average breaks below the 200-day moving average, this would be a bearish signal.

The 200-day moving average is considered a key technical indicator, with breaks above or below that regarded as important trading signals. It is especially suited for mutual fund technical analysis because of its longer-term nature.

3. Relative Strength Index (RSI)

The Relative Strength Index (RSI) is a momentum indicator that compares the magnitude of recent gains to recent losses in order to evaluate whether the mutual fund is overbought or oversold.

An RSI above 70 would suggest that the mutual fund is overbought and its value is overpriced and poised to retreat. An RSI below 30 indicates an oversold state that may trigger a bounce, which may bolster a value investor’s buy decision.

4. Support and Resistance

A support level is formed when a mutual fund trades down to a certain level and then bounces back up. Over time, this level becomes an area of strong support for the mutual fund. Conversely, a resistance area is formed when the fund is unable to break above a certain price level.

Support and resistance levels highlight the direction of the market and help determine entry and exit points.

The further apart these tests of support and resistance, and the more frequent that the fund trades down or up to the support or resistance level, the more formidable they become. A break of long-term support is very bearish and may signal a substantial downside for the mutual fund. A move above long-term resistance is very bullish and signals significant upside.

5. Chart Formations

There are a number of different chart types used in technical analysis, with the most common being line charts and bar charts.

Advanced users may prefer candlestick charts to point-and-figure charts. Chart formations for a mutual fund can be interpreted like stocks. The head-and-shoulders pattern, for instance, is interpreted as being quite bearish for the fund, while the reverse head-and-shoulders pattern is viewed as a bullish signal.

A chart pattern that is easy to identify and that has a high degree of reliability is the double or triple top or bottom. A double top or triple top is typically formed after a long period and signals an imminent trend reversal; if a mutual fund that has been trending higher is unable to break through this formation, it may be headed lower. Conversely, a fund that has formed a double or triple bottom may be poised to move higher.

The Bottom Line

While mutual funds do not readily lend themselves to technical analysis, investors can apply some common technical indicators to predict mutual fund movements. Technical indicators like trendlines, moving averages, RSIs, and chart formations are widely used in mutual fund analysis as they provide reliable signals that are easy to interpret.

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