Stop Loss Orders

Stop loss orders ("stops") are limits set by traders at which they will automatically enter or exit trades - an order to buy or sell is placed in the market if price reaches a specified limit.

The first discipline that any trader should master is to always limit your losses.

A stop loss order is set to limit a trader's potential loss. The stop loss is placed below the current price (to protect a long position) or above the current price (to protect a short position).

      Example: If you purchase 1,000 IBM at $90.00 you may decide to place a stop loss as follows:
                      SELL 1,000 IBM IF price is less than or equal to $87.00
                      If price falls to $87.00 your order will be activated.
                      Your loss is limited to $3.00 per share (plus brokerage).

 As a rule: avoid markets with low liquidity where extreme price fluctuations are possible.

Stop Loss Order Types

• Market Stop Orders
  This is a conventional stop loss order - the stop activates a market order to sell (or buy) at the prevailing market price.
• Limit Stop Orders
  The limit stop activates an order to sell at the prevailing market price but not below a specified limit (or buy at the prevailing price up to a specified limit).
• Fixed Price Stop Orders
  The stop loss activates an order at a fixed price. Some exchanges refer to these as limit stop orders so check that you are using the correct stop loss order.

Limit stop orders are recommended for entering a trade: they have a greater chance of success than fixed price orders but are not as open-ended as market orders (where your order will be executed no matter what the market price is).

Market stop orders should be used to exit trades: to ensure that the order has the best possible chance of execution. Never hold on to securities if price falls sharply - in the hope that they will recover. Edwin Lefevre sums up the predicament in Reminiscences of a Stock Operator :

It was the same with all. They would not take a small loss at first but had held on, in the hope of a recovery that would "let them out even." And prices had sunk and sunk until the loss was so great it seemed only proper to hold on, if need be a year, for sooner or later prices must come back. But the break "shook them out," and prices just went so much lower because so many people had to sell, whether they would or not.

Evaluation of Stop Losses

Stop loss orders do not always work perfectly. If a major support level is breached, a large number of stops may be activated at the same time. Sellers will far exceed buyers, causing price to fall sharply and leaving sell orders unfilled. In extreme cases there may be no buyers at all for a security -- not at any price.

Imperfect as they are, stops are still an effective mechanism for limiting risk and protecting capital.

If stops are not accepted in a market, set your own limits and place buy or sell orders when the price is reached. Use SMS alerts if they are available from an online broker. Self-discipline is required to execute stops without hesitation.

Steps Required

1. First, determine your maximum acceptable loss;
2. Set stop loss order levels based on sound technical levels;
3. Adjust your stop loss levels over time to lock in profits;
4. Use trailing stops to time your entry and exit from the market.

Setting Stop Loss Orders

Stop loss order levels need to be technically consistent, otherwise they will cost you money. Arbitrary levels are likely to be activated by the normal cycle.

Base your stop losses on technical levels, such as:

• Support/ resistance levels,
• Above/below the most recent peak/trough,
• Above or below reversal signals; or
• At the crossing of moving averages.

Example

This example illustrates the use of 2 different technical levels for stop losses:

1. The first stop loss is placed just below the level of the most recent trough.
2. The second stop loss is placed below the support line (on a reversal signal above the support line).

Support and Resistance Levels

Avoid placing your stop loss exactly at the support or resistance level for two reasons:

1. Trends often reverse at these levels and you may be stopped out unnecessarily;
2. A large number of stops may be set at the support or resistance level, especially where it has formed at a round number.

Rather set your stop loss one or two ticks below a support level or one or two ticks above a resistance level. For example: If a support level has formed at $20.00, set the stop loss at $19.90 so that you are only stopped out if the support level is penetrated.

Adjusting Stop Loss Orders

Adjust your stop loss orders, over time, in the direction of the trend being traded:

    In an up-trend move your stop loss up to below the Low of the most recent trough.
    In a down-trend move your stop loss down to above the High of the last peak.

Only a break in the trend (or large correction) will stop you out.
Using Moving Averages

An alternative approach, that may prevent you from being shaken out of a trend too early, is to use a long-term moving average in conjunction with the above. Stan Weinstein (Secrets for Profiting in Bull and Bear Markets) suggests using a 30 week moving average. This is suitable for investors following the primary trend, adjust the length of the moving average if trading in a shorter time frame.

In an up-trend move your stop loss to below:

•     the Low of the most recent trough, or

•     the moving average, whichever is lower.

In a down-trend move your stop loss to above:

•     the High of the most recent peak, or

•     the moving average, whichever is higher.

Example

Johnson & Johnson is charted with a 63 day exponential moving average. Stop loss order levels are depicted by horizontal trendlines.

1. Go long [L]. The signal is taken when price respects the moving average. A stop loss order is placed at [S1], below the Low of the most recent trough or below the moving average, whichever is lower (shown by the start of the trend line).
2. At [S2] move the stop loss up to below the moving average at the next trough.
3. At [S3] move the stop loss to below the Low at the next trough (this is lower than the moving average).
4. At [S4] move the stop loss to below the moving average at the next trough.
5. The stop loss order is activated [X] when the next correction falls below the previous trough.

Ranging Market

In a ranging market adjust your stop loss based on the cycle in one time frame shorter than the cycle being traded. For instance, if trading an intermediate cycle (in a ranging market), move your stop loss orders up or down in accordance with the short cycle.

Maximum Acceptable Loss

Set the maximum loss that you are prepared to accept on any single trade. This is usually expressed as a percentage. Avoid trades where the difference between your entry level and the stop-loss exceeds the maximum acceptable loss.

Consider the following factors when determining your maximum acceptable loss:

• Whether you are investing or trading;
• The time frame that you are trading in;
• Whether you are trading on margin;
• Your overall risk profile; and
• Your level of diversification.

A long-term investor/trader with reasonable risk diversification may find 6%, or even 10%, an acceptable limit. A short-term trader may set a limit of only 2%.

Trailing Stop Loss Orders

Trailing stop loss orders have three uses:

• To limit your losses,
• To protect your profits, or
• To prevent you from entering (or exiting) a trade too early or on a false signal.

Stops can be based on the high/low of the daily trading range or on a trailing percentage. Welles Wilder's Parabolic SAR is a further form of trailing stop.

The rules below are based on Screen 3 of the Triple Screen trading system, described by Alexander Elder in Trading for a Living.

Buy-Stop

When you get a signal to go long - place a buy order one tick above the High on the signal day. If price rallies, you will be stopped in on the next day. If price falls, the buy order will remain untouched. Move the buy order down to one tick above the High on the second day. Continue to lower the buy order on each subsequent day until price rallies and you are stopped in.

When you are stopped in, place a stop loss below the Low of the recent down-trend (the lowest Low since the signal day).

Sell-Stop

When you get a signal to go short - place an order to sell short one tick below the Low on the signal day. If price falls, you will be stopped in on the next day. If price rallies, the buy order will remain untouched. Move the sell-stop up to one tick below the Low on the second day. Continue to raise the sell-stop on each subsequent day until there is a correction and you are stopped in.

When your sell-stop is executed, place a stop loss above the High of the recent up-trend (the highest High since the signal day).

* Day 4 makes a new High and a new Low. If the High was made before the sell-stop is reached, the stop-loss will be placed as shown. If the sell-stop was activated before the new High was made, then the stop-loss would have been placed above the High of Day 3 and the trade would have been stropped out on making the new High.

Example

Intel Corporation is shown with a  21 day exponential moving average and 7-day Stochastic  %K and  %D.

1. %K falls below 20. Place a trailing buy-stop just above the day's High of $33 1/2.
2. Move the buy-stop down to $33, above the High of day 2.
3. Move the stop down to above the High of day 3.
4. Move the stop down to $32 1/2 - one tick above the High on day 4.
5. The day opens with a new Low of $31 3/8 and then rises until we are stopped in at $32 1/2. Place a stop-loss below the Low (i.e.. the lowest Low since day [1]). Thereafter, price falls back to the day's Low, but fails to activate the stop-loss one tick below.

Inside Days

The rules for sell and buy stops are sometimes varied by excluding inside days:

• no adjustment is made to a buy-stop if the day does not make a new low;
• no adjustment is made to a sell-stop on days that do not make a new high.

Trailing Percentage Stops

Trailing percentage stop orders are offered by some online brokers. The stop order works with a ratchet effect - it trails price movements by a set percentage, but only in the direction of the trend. If price reverses direction, the stop remains at its previous level and will be activated if price reverses by more than the trailing percentage.

Buy-Stop

Buy-stops are used to enter long positions or to close short positions.

In the example below, the trailing stop is set at 6%. The trader will be stopped in if price rises 6% above the lowest Low.

The buy-stop ratchets down on each day that price forms a new low. The stop loss for each day is set at 6% above the lowest Low since the signal (Day 1).

Note that the stop loss remains unchanged if the previous day does not form a new Low.

Sell-Stop

Sell-stops are used to exit long positions or to enter short positions.

Compare the 10% trailing stop, in the example below, to a 6% trailing stop. With a 6% sell-stop the trade would have been exited at 48.9 on Day 3 (52.0 - 10%).

Setting the Trailing Percentage Stop

When setting the trailing percentage, consider the following factors:

• If the stop losses are being used to limit your losses, decide on your maximum acceptable loss beforehand.
• Determine the magnitude of the intra-day cycle - you do not want your stop loss to be activated by normal intra-day fluctuations. Use intra-day charts or in-depth information from an online broker.

A Word of Caution

Check how your broker calculates trailing stops!

Many brokers calculate trailing stops on the last close and do not adjust on an intra-day basis. If price runs up from $20.00 to $28.00 during a single session and then falls back to close at $21.00, you will not be stopped out with a 5% trailing stop calculated on this basis, because price is still above yesterday's high, even though it has fallen 25% intra-day!

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Stop Loss Research

Stop-Loss Orders: 

Introduction

Many traders and investors place Stop Loss orders as part of their day-to-day investment activity. Virtually all trading books recommend the use of stops, with many making statements like "Trading without stops is like driving without a seatbelt". The argument for the use of stop-loss rules seems inherently sound, yet there appears to be no real evidence that stops are providing the safety benefits that many traders expect.

With regard to medium to longer term equity trading systems (which appears to cover the majority of investors and traders), it may well be that stops are causing more harm than good!

As traders, we are used to having an initial stop loss on a trade, and congratulating ourselves when the stop saves us money as the trade goes south very quickly. Although a stop-loss rule may save us from damage on specific trades, it seems doubtful whether this beneficial effect actually holds when we measure it at a portfolio level. There are a number of specific reasons why this may be the case, which I will touch on later in this series.

As traders, we shouldn't really focus on the return of each individual trade; rather we should focus on the overall return of our portfolio. A large amount of my empirical testing appears to show a mismatch between stop performance at an individual trade level, and stop performance at a portfolio level.

In this series of articles, I would like to demonstrate the mismatch that stops appear to introduce, and show you a way to be able to test this for yourself. This article is part 1 of a 3-part series. In this article, I will introduce an example system, and demonstrate how to benchmark the system with and without a variety of stops, and statistically analyse the results.

You can then use this same process to benchmark the effect stops are having on your own individual trading system, to determine if you are actually benefiting from using stops.

Measuring the impact of Stops

To measure the impact of stops on a trading system, it is necessary to consider the effect that stops have on both individual trades, and on specific portfolios constructed from those trades.

To assess the effect that stops have on individual trades, we can benchmark and measure changes in:

• Trade daily mean return ($) – average return per day
• Average number of days trades are open

To benchmark the raw trades signalled by the entry and exit rules, we initially assume unlimited equity, and a nominal investment of $10,000 per trade.

To assess the effect that stops have on specific portfolios, we can benchmark and measure changes in:

• APR% (Annual Percentage Return) – a portfolio's return
• Max DD% (Maximum % Drawdown) – which shows the worst case drawdown (peak to valley) that the portfolio equity curve has suffered.
• Sharpe Ratio - which shows the amount of risk taken per unit of return. Ignoring the risk-free rate adjustment, the Sharpe Ratio is a measure of how volatile portfolio returns have been. (As an example, two different traders may both have achieved a return of 20% over time. The Sharpe Ratio will be highest for the trader who has achieved this result with the least volatility.)

When benchmarking a portfolio, it is important to take account of the amount of equity used. In this case, a relatively simple 'percentage of equity' model is used. We allocate 2% of available equity to each trade, from an initial starting capital of $1,000,000.

By monitoring the variables above, we can benchmark the metrics that are obtained from a set of trading rules. We can then add stops to the trading rules and repeat this process. This will allow us to empirically measure the effects that the stops have on those key metrics. We can then statistically determine whether the portfolio outcome has been improved by the addition of the stop rules.

Case Study

The majority of traders would be best described as medium to longer-term equity investors. In essence, this means that they trade ordinary shares, and aim to hold each share from several months to several years. Typically, this group of investors name themselves 'trend traders', and their aim is to identify and ride a trend for as long as possible. Often one or more simple (or exponential) moving averages provide entry and exit setups. Typically, this group also only trades the long side.

For this reason, I have chosen a 60-day ema crossover system as the example case study system . A 60-day ema crossover system buys when the price crosses above a 60-day ema, and sells when the price crosses below a 60-day ema.

An example trade is shown below in Figure 1. The pink line represents the value of the EMA(60).

The data chosen for the case study is the constituents of the ASX200 (since inception April 2000) until the end of 2009. Where possible, I have adjusted this data for delistings and code changes, and trading results include an allowance for transaction costs. To address survivorship bias, buy signals are only issued on stocks which were constituents of the ASX200 on the day the signal was generated.

Remember the objective is not to determine whether these are desirable rules for trading; it is to allow us to select and emulate the basic characteristics of the kind of stocks that the majority of traders and investors in the ASX200 are focused on.

No stops

Initially, we need to benchmark the buy and sell rules without any stops. This gives us a baseline against which to compare the performance of the stops we will introduce.

Raw Trades

The key characteristics of the raw trades generated by buying/selling $10,000 worth of stock every time the buy/sell conditions occur are:

Daily Mean Return = $ 0.61, Average Number of days trades are open = 21.44

Later, when we introduce a variety of stop combinations to the buy/sell rules, we can measure the effects they have using this baseline.

Portfolio

The key characteristics of the portfolio generated by these trades are:

APR = 2.63 %, MAX DD = -34.63 %, Sharpe Ratio = 0.31

Now we know how much potential return there is in the rules (APR%), how risky those rules are (DD%), and a measure of the overall risk for that specific return (Sharpe ratio). Later, when we introduce a variety of stop combinations to the buy/sell rules, we can measure the effects they have using this baseline.

Initial Percentage Stops

Many traders simply use a fixed percentage to determine their stop level price. As an example, a trader might say, "I will set a stop loss 5% below my entry price". Here, we test every initial stop loss percentage threshold from 1% - 10% in steps of 1, for all the trades generated by the ema crossover rules.

The impact that these initial stops have on both return and risk is presented next.

Raw Trades

From the table presented, it is clear that none of the stop methods tested improved the 'NO STOP LOSS' portfolio's daily mean return. This is as expected, given that, by definition, an initial stop loss rule entails selling at a loss. To determine whether this approach has decreased our risk, we next test within a portfolio setting.

Portfolio

From this table, we can see that none of the stop methods have improved the 'NO STOP LOSS' portfolio's APR. Further, none of the stop loss settings was able to improve the Sharpe Ratio. Some of the higher percentage stops achieve similar Maximum Drawdown%, but none of the stop loss settings was able to improve the Sharpe Ratio. In essence, all combinations of stop loss tested achieved less return, and were riskier.

Trailing Percentage Stops

Many traders and brokers use an initial percentage stop and a trailing percentage stop to manage their positions. As an example, a trader might say, "I will set a stop loss 5% below my entry price, and then trail it 5% below the previous days closing price as the trade progresses". Here, we test this method using percentage thresholds from 1% - 10% in steps of 1, for all the trades generated by the ema crossover rules.

An example is shown in Figure 2. The green dots show the position of the percentage-based trailing stop, and the pink line shows the value of the EMA(60).

The impact that these percentage trailing stops have on both return and risk is presented next.

Raw Trades

From the table presented, it is clear that none of the stop methods tested improved the 'NO STOP LOSS' portfolio's daily mean return. This is as expected, given that, by definition, an initial stop loss rule entails selling at a loss. To determine whether this approach has decreased our risk, we next test within a portfolio setting.

Portfolio

From this table, we can see that none of the stop methods have improved the 'NO STOP LOSS' portfolio's APR. Further, none of the stop loss settings was able to improve the Sharpe Ratio. Again, all combinations of stop loss tested achieved less return, and were riskier.

Implications

To statistically compare the portfolio results, we can use the ANOVA procedure, which allows us to simultaneously compare all the trades generated under the 'NO STOP LOSS' condition, with all the sets of trade possibilities from the 10 stop loss combinations. This allows us to determine whether there is any statistical significance in our findings.

ATR-based Stops

Many traders simply use a multiple of the ATR (Average True Range) to determine their stop level price. As an example, a trader might say, "I will set a stop loss 2 times the 5-day ATR below my entry price". To demonstrate the versatility of this technique, I have implemented this as both an initial ATR stop, and then allowed it to become a trailing stop as the trade moves into profit. This is typical of the way many retail traders manage their ATR based stops.

An example is shown in Figure 3. The green dots show the position of the ATR-based trailing stop, and the pink line shows the value of the EMA(60).

The impact that these initial stops have on both return and risk is presented next.

Raw Trades

From the table presented, it is clear that none of the stop methods tested improved the portfolio's return. This is as expected, given that, by definition, an initial stop loss rule entails selling at a loss. To determine whether this approach has decreased our risk, we next test within a portfolio setting.

Portfolio

From this table, we can see that none of the stop methods have improved the 'NO STOP LOSS' portfolio's APR. Further, none of the stop loss settings was able to improve the Sharpe Ratio. Again, all combinations of stop loss tested achieved less return, and were riskier.

Implications

Again we can use the ANOVA procedure to determine the statistical significance of these results. The results indicate that no benefit has been obtained from any of the stop combinations tested.

Monte-Carlo Analysis

By definition a portfolio is a subset of the raw trades signalled by the entry and exit rules. The most common reason that a portfolio usually has less trades than the total possible relates to the way the trader/investor manages money, and that is why it is important to test a portfolio with a specific amount of capital. Different amounts of capital (and money management approaches) can give rise to different possible portfolios.

Consider a trader/investor who invests his/her money in multiples of $10,000 according to the above buy/sell rules. What will the trader/investor do if 2 stocks are signalled on the same day, yet the trader/investor only has $10,000 left? Clearly, only 1 trade can be taken, but which one?

It may well be that over time the two trades have very different outcomes. For example, one goes up, and one goes down!

When running a portfolio, the issue of having more trading opportunities than money can occur reasonably frequently, particularly in a trend-trading approach. Again, in the above example, what will the trader/investor do on the next day, when yet another trade is signalled, and there is no money left to take it. Of course, it must be skipped from the portfolio.

To fully understand the implications of taking and skipping certain trades, quantitative analysts may resort to Monte-Carlo modeling, which allows us to build a probability outcome of all the possible portfolios which could have been built dependent on the decisions the trader/investor took.

As an example, in an earlier paragraph we wondered how to model the portfolio outcome when there were two possible trading candidates but only enough money to take 1 trade. The solution using computational mathematical methods is that from this point forward, there are now two theoretical portfolios � one with each possible stock in it. Following on from this logic, you can see that over a period of time, there could actually be a great number of possible portfolios, all dependent on the decisions taken by the individual trader/investor. All of these portfolios would be real possible outcomes, totally dependent on the choices made by the trader/investor on a day to day basis!

To assess the impact of stops completely, we need to consider not just one simulated portfolio outcome (as we did earlier), but a large number of the possible theoretical outcomes. We can approach this using the Monte-Carlo methodology, and determine the probability of various return and drawdown outcomes.

The following figures show the probability distributions for the Raw Return (aka Net Profit) and the Maximum Drawdown metrics for 1000 of the possible 'NO STOP LOSS' portfolios. These provide the benchmark for this final piece of analysis. Under each figure, I have also included the smallest, average and largest values obtained from the 1000 simulations.

 Smallest =-17.32%, Average = 11.66%, Largest = 43.82%

Smallest = -30.00%, Average = -44.44%, Largest = -53.21%

Outcomes

The following table shows the average values for both the Net Profit % (not the APR%), and the Maximum Drawdown % for 1000 possible portfolios for each of the 25 stop combinations tested.

Implications

From inspection of this table, we can see that there was no set of 1000 possible portfolios more profitable than the 'NO STOP LOSS' combinations. We can also see the ATR based stop methods have performed quite poorly compared to nearly all of the simple percentage based stop methods. In summary, no combination of stops was able to improve on the basic strategy without stops.

Conclusion

Some traders appear to use stops to provide a level of comfort about the risk they take with their trading. If you feel you absolutely cannot live without stops, even after performing similar tests to these on your own system, you must, of course, continue using them. Perhaps you could even consider simply making them wider.

However, many traders and investors appear to view the stop loss order as a panacea. These empirical results show that the stop loss order may actually be contributing to the poor performance of some traders, and may even be the cause of their lower than expected returns.

One of the reasons that this behavior may be occurring is that many stops are being hit at the same time. This is more likely due to changes in the overall market rather than having any specific relationship to changes in some particular company share price.

By Dr. Bruce Vanstone.

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Basics Setup for Trading

Trading Basics




The market has 4 basic phases and no trading system is suited to all of them. Some systems are suited to Phases 1 and 3, when the market is ranging, while others are designed to trade the trends in Phases 2 and 4. Trend-trading systems are more popular as they require less time and normally generate larger returns.
SGX Stocks 20-minute delayed
 
Trading Trends

The object of trend-trading is to go long at the transition from Phase 1 to Phase 2 and to exit before Phase 4. Some models also short the market during Phase 4, but this should be left to experienced traders .

Successful systems are built around the following principles:
 
Selecting securities.

    Use the Stock Screener to identify potential Market Leaders.
    
Market direction.

    (a) Decide on the Time Frame that you are trading.
    (b) Confirm the Market Direction using a suitable trend indicator.
 
Trend direction.

    Using the same indicator, check the Trend Direction of each security.
    Entry signals.

    (a) Take Entry Signals from a suitable momentum oscillator.
    (b) Use Trailing Stops to time entry and exit points.
    
Stop losses.

    (a) Set Stop Loss Orders as soon as your trade is confirmed.
    (b) Do not exceed the Maximum Acceptable Loss.
    (c) Be technically consistent when Setting Stop Levels.
    (d) Adjust Stop Levels over time to protect your profits.
    
Exit signals.

    Take Exit Signals from a suitable trend indicator.

A Word Of Caution

These are typical steps that a trader will follow in deciding what stocks to buy, when to buy them and when to sell. It is not a magic formula, but consistent use should enhance your investment performance.

Trading methods can be compared to a carpenter's tools: Skilled use can produce outstanding results but unskilled use may lead to injury. Learn to use your trading tools properly before committing any capital. Study the behavior of the indicators over several years, learn their strengths and weaknesses and how they interact with each other and with the market. Start with a small amount of capital and only increase this when you are confident that you have a winning strategy.
   

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All About MACD from a deferent angle

 

Talking Points:

• While no indicator is perfect, they can help traders address probabilities in a market
• Moving Averages can be helpful, but often lack an active signaling mechanism
• MACD takes trading with moving averages one step further

The journey for most traders starts in a similar way…

Traders are drawn to markets because of the potential. And like anything else in life, most people understand that training and education are vitally necessary parts of success. Most will then act on this understanding, and will begin learning the ‘tools of the trade.’

And that is where the quest will begin…

In the FX markets, Technical Analysis often receives a heavier portion of this focus and there are a couple of different reasons for that. This journey of learning technical analysis can be a short couple of days or might take years or even decades. Regardless of how the trader approaches learning Technical Analysis, one thing that is fairly uniform is that the ‘common’ indicators are learned first before more advanced studies like price action or Elliot Wave.

These are the indicators like RSI, or Stochastics, or Pivot Points. And what will often happen is that after a trader learns how to use the indicator, they also learn that the indicator isn’t a panacea, and is from time-to-time, incorrect.

Does this mean that the indicator is worthless and can’t be used?

Absolutely not! It merely reiterates what all of us should know about markets going in… which is that markets are unpredictable no matter how you approach them.

Rather, trading is but a series of probabilities; and indicators can be helpful tools to look to trade with those probabilities.

In this article, we’re going to examine one of the more versatile indicators that is also one of the first discarded by new traders in their initial trading education: MACD.

The MACD Line

MACD is an acronym that is short for Moving Average Convergence Divergence, which is really just a long and drawn out way of saying it measures the relationship of moving averages.

The moving average is, in-and-of-itself, a very formidable indicator. It’s easy and simple and it just averages the last X periods worth of closing prices. The moving average is often the very first indicator learned because of how simple it is to teach and understand. And the benefits of trading with a moving average can be very clear and apparent, especially if the indicator is being used for trend analysis.

But, trading with a moving average doesn’t always work; and so traders will then learn the benefit of the moving average crossover. By adding a second moving average, we stand the chance to be able to ‘slow down’ the indicator signals. Whereas trading with one moving average entailed buying or selling when price crossed over, the crossover waits for one moving average to cross another before triggering a signal.

But, once again – this doesn’t always work. And this is where MACD comes into play. Traders wanted a way to try to enter the position at the early stage of a move… far before a moving average crossover might take place.

So, rather than watching moving averages, these traders plotted the difference between the averages as an oscillator (shown below).

MACD measures the spatial relationship of exponential moving averages

Created with Marketscope/Trading Station II

In this example, a 13 (in green) and 34 period (in blue) EMA is shown on the price chart. Notice when the two moving averages cross (highlighted with the red circle), MACD correspondingly crosses the ‘0’ line.

As the distance between the moving averages grows larger (or diverges), MACD moves lower to illustrate the growing difference that’s being seen in the EMAs.

On the flip side, when prices move higher, MACD will begin moving higher to reflect the convergence of the Exponential Moving Averages. If price moves high enough, MACD will eventually go up and over the ‘0’ line, and if prices can continue moving higher, the distance between the 13 and 34 period EMAs will also grow, and MACD will again show that divergence (this time to the up-side with an increasingly large MACD value).

This is the MACD line, and it’s the heart-and-soul of the indicator. But, at this point, there is no difference between the MACD line and a simple moving average crossover.

The Signal Line

The MACD line can bring a lot of value, in-and-of-itself, but it’s far from a panacea. After all, MACD is just the spatial relationship between those two EMAs, and if that’s what one wants to trade for, why not just follow a couple of moving averages?

The next part of the indicator is a key element to trading with MACD, and this is called ‘the signal line.’ The signal line is a moving average applied to MACD. By default, the signal line is usually a 9 period EMA; but this is really up to each individual trader. So, the signal line is a moving average based on the difference between two other moving averages. While this may sound confusing, do not worry – most charting packages can do this for you fairly easily and you don’t have to perform the mathematical computations for each.

By applying the signal line, the trader opens up the possibility of entering the trend far before a crossover of the 13 and 34 period moving averages would usually allow.

As an example, take a look at the previous setup we had investigated when MACD crossed down and under the ‘0’ line (and when the 13 and 34 period EMAs had crossed); but this time we’re going to apply the signal line to MACD.

MACD crossover with signal line will takes place far sooner than the crossover of Moving Averages

Created with Marketscope/Trading Station II

This is the benefit of MACD: The fact that it may allow for an earlier entry into a trend is what makes this such a phenomenal indicator. Sure, it won’t work all-of-the-time, but this is trading and there is nothing that works all-of-the-time.

MACD can make for a fantastic indicator in strategies because of just this feature; and if often functions best as a ‘trigger’ into positions in trend-based strategies.

The Histogram

The last part of the indicator is a further extension of the mathematical relationship between all of these moving averages.

The histogram measures the difference between the MACD line, and the signal line. When MACD crosses the signal line, the histogram goes to a value of ‘0.’

The Histogram measures the difference between MACD and Signal lines

Created with Marketscope/Trading Station II

As you can see in the above image, as the MACD and the signal lines converge or diverge; the histogram will reflect this properly. As MACD falls further underneath the signal line, the histogram will print lower to reflect this growing difference.

As MACD crosses over the signal line, the histogram will crossover ‘0’ and will continue to move higher as long as MACD continues moving higher above the signal line.

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