On-Balance Volume Indicator (OBV) – Complete Guide for Traders

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The scope of technical indicators has expanded rapidly, with new ones in development every day. However, the Exponential Moving Average is one of the first ones to be developed. It’s among the most commonly used indicators and is fairly easy to understand. If you’re looking to make the most of your futures trading portfolio and want to utilize this technical indicator, look no further. This article will focus on what Exponential Moving Average (EMA) is and what are the strategies traders use to make successful trades.

**Table of Contents:**

- What is The Exponential Moving Average?
- Exponential Moving Average Calculation
- How Does The EMA Work?
- How to Use The Exponential Moving Average
- What is The Difference Between Simple and Exponential Moving Average
- EMA Strategies
- Pros and Cons of The Exponential Moving Average
- F.A.Qs

Exponential Moving Average or EMA is an advanced version of the simple average that puts greater weight on the most recent data points, while calculating the average for a particular day. By focusing more on the latest data points, the EMA ensures that the old and redundant data points do not have the same influence on the indicator as the latest data point. This is different from calculating the simple average, where all data points have the same weight.

The disadvantage of a simple average is that it might not give you a number weighted to heavily on old data. In many cases that’s not the most accurate figure. For example, if a company’s earnings result shows that it beat Street estimates, that may lead to a surge in price. A simple average indicator would not capture that momentume adequately. One would have to wait for a few days before it would actually reflect this information.

The EMA, on the other hand, would be more responsive to such changes by placing more weight to the latest developments in price. A trader can customize the weight the indicator needs to assign to the latest data point based on the importance they attach to the latest figure. It is this particular feature that makes EMA a more effective tool than the simple average.

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EMA_{t} = Closing Price_{t} * multiplier + EMA_{t-1} *(1 – multiplier)

Here “t” denotes the instant for which the EMA needs to be calculated and “t-1” is the previous instant.

The formula for the multiplier is the following:

Multiplier = Smoothing Factor / (1 + number of days)

So, if you want to put more weight on the latest data point, you can do it by increasing the smoothing factor and decreasing the number of days. The next section will tell you how the exponential moving average formula can be used to calculate an actual EMA using different inputs namely the closing price, smoothing factor, and the number of days.

Let us develop the EMA profile of an asset from scratch. Some of the parameters we need to define at the beginning are the smoothing factor and the number of days. If we need to calculate the 50-day EMA, we would require 51 data points. The simple average of the first 50 data points would be the EMA_{t-1} in our first iteration, since we do not have a history for the EMA. We would process it by using a smoothing factor of 2. First, we need to find the multiplier based on these two inputs.

Multiplier = 2 / (1 + 50) = 0.0392

Now, if the simple average of the past 50 days was 100 and the closing stock price today is 125, the EMA would be calculated as:

EMA = 125 * 0.0392 + 100 * (1 – 0.0392) = 100.98

Now we have an EMA to work with and will no longer have to rely on the simple average to determine the subsequent EMAs. On the 52^{nd} day we assume the price to be 130 and the EMA would be calculated as:

EMA_{52} = Price_{52} * 0.0392 + EMA_{51} * (1 – 0.0392)

EMA_{52 }= 130* 0.0392 + 100.98 * (1 – 0.0392) = 102.12

It should be noted though that a weight of 0.0392 may seem somewhat small for calculating the exponential moving average, however, it is higher than the weight a simple average calculation would put on it. In our case, in which we are considering a span of 50 days, the weight for a simple average for all the data points would be 1/50 or 0.02.

As we have highlighted earlier, the EMA focuses more on the current price point. An investor can adjust the two variables, smoothing factor and number of days to change the multiplier. We will illustrate the impact of changing these two parameters on our assumptions in the previous section.

Multiplier = 1.5/51 = 0.0294

EMA_{51 }= 125 * 0.0294 + 100 * (1 – 0.0294) = 100.74

EMA_{52 }= 130* 0.0294 + 100.74 * (1 – 0.0294) = 101.60

Compared to our base scenario in which EMA_{51} and EMA_{52} were 100.98 and 102.12, we can observe that reducing the smoothing factor underestimates the EMA when the price is constantly rising.

Multiplier = 2/26 = 0.0769

EMA_{51 }= 125 * 0.0769 + 100 * (1 – 0.0769) = 101.92

EMA_{52 }= 130* 0.0769 + 101.92 * (1 – 0.0769) = 104.08

Compared to our base scenario we’ll see that reducing the days improves the accuracy when the price is constantly rising.

Multiplier = 1.5/26 = 0.0577

EMA_{51 }= 125 * 0.0577+ 100 * (1 – 0.0577) = 101.44

EMA_{52 }= 130* 0.0577 + 101.92 * (1 – 0.0577) = 103.09

Compared to our base scenario we observe this is more responsive since reducing the count of days has a higher impact than reducing the scaling factor.

So, in short, we have to reduce the number of days or increase the scaling factor to ensure that maximum weight is placed on the latest data points. These adjustments can be made, especially when we are observing a breakout and old data points would have less predictive capabilities. Traders who are into short term trading can reduce the time considerably in order to detect trends faster.

A moving average trend is plotted alongside price to determine the trend. Normally a set of EMA trends is used in order to enhance the efficiency of a technical indicator. These sets of EMA trends are called the ribbon. The shorter the period, the more responsive the ribbon is to the current price. For example, ribbons using 10, 20, 30, 40, and 50 days would be more responsive than ribbons using 150, 160, 170, 180, and 190 days. The chart below shows the 10-day (blue line), 20-day (orange line), and 30-day (pink line) EMAs for the S&P 500 E-Mini.

We see that the 10-day EMA seems to track the latest price more accurately and is more responsive to any significant changes in trends. Some of the ways in which traders can use the EMA ribbons include:

- When ribbons converge to a single point, it could indicate a reversal in trend
- When the shorter EMA crosses below the longer moving averages we can expect a downtrend. Likewise, when the shorter EMA crosses above longer EMAs we can expect an uptrend.
- When the ribbons are spread far apart we can expect a trend being developed. This can be an uptrend or a downtrend

All of the signal types mentioned above have been marked on the chart above. For example, the point marked “a” shows the 10-day, 20-day, and 30-day EMAs converging and we see a reversal in trend. The price that was rising is now in a downtrend, at that point.

The fundamental difference between the two is that the weight it attaches to the latest data points. You can find a table on a few additional difference below:

Simple Moving Average (SMA) | Exponential Moving Average(EMA) |

The SMA treats each data point equally with weight for each data point being 1/n, where n is the number of days | The EMA puts more weightage on the recent data point by replacing the weight used in the SMA by a multiplier |

Only the number of days can be changed to alter the sensitiveness of the SMA | Scaling factor and number of days can be adjusted to change the multiplier |

Less responsive to the latest price point | More responsive to the latest price |

Slower in detecting a trend or reversal of a trend | Faster in detecting a trend or reversal of a trend |

For calculating n-day SMA, a history of n price points are required | For calculating n-day EMA, a history of n+1 price points is required. The first EMA, however, would be based on an SMA since a historical EMA is unavailable after the completion of n+1 days |

Investors generally favor EMA over SMA due to the features that have been discussed. Many of them still use the as a reference in many cases, since it is a simple tool that is easy to aunderstand.

Like we said before, the ability to fine-tune the parameters in the multiplier makes EMA an effective tool. There are numerous strategies that have been developed in order to perform technical analysis. The basic idea is to compare the trend of a short EMA with that of a short EMA. These strategies have been used in different asset classes namely equity, commodities, foreign exchange, and even cryptocurrency. We will discuss two of the common trading strategies that traders use to determine the price movement and how traders can interpret the interplay between a short EMA and a long EMA.

The EMA 12 and EMA 26 trading strategy is one of the most common and simple strategies that is used by traders. While we have demonstrated our previous example using days as our unit of time, the period can be more granular. For example, in this case, we could use 12 minutes and 26 minutes as our frames of reference.

We can take a live example using the S&P 500 E-Mini once again. The blue line is the EMA 12 and the orange line is EMA 26.

We have labeled two points as “A” and two points as “B” on the chart above. You can interpret them as the following:

- In the first “A” we see the two lines converging and the EMA 12 fall below the EMA 26 which should have signaled a downtrend. The opposite happens in the second “A” as the EMA 12 crossed above EMA 26 and an uptrend follows
- The two “B” marks illustrate a phase in which there is a continuation in the trend. The first one demonstrates a continuing downtrend while the second one shows a strong uptrend. Wider lines should indicate a stronger trend in the asset that we’re tracking.

While such technical indicators serve as a useful tool, it should not be used in isolation. For instance, the actual result may vary from what these tools indicate. In addition, it’s imperative to establish a stop loss as well.

Another common strategy that traders use in especially dynamic markets is the 5 EMA and 8 EMA crossover strategy. Since we are using the 5 EMA and 8 EMA, you can expect this strategy to be highly responsive. That can make it an effective tool in volatile markets. Using the same S&P 500 E-Mini market we will explain how to use this strategy to enter or exit a position.

The purple line is the EMA 5 and the orange line is EMA 8. We have highlighted two crossovers in the above chart. We should note that these lines are very close to each other since the time interval is relatively small when you compare it to the example we had illustrated earlier.

- The EMA 5 is above the EMA 8
- This could be a signal to enter so you should also keep a close eye on the price
- If price is above the EMAs that makes the signal stronger
- An uptrend follows

- The EMA 5 falls below the EMA 8
- This could be an indication to short, but price should also be taken into account
- If the price is below these EMAs that makes the signal stronger
- A downtrend follows

Since the time intervals are very small, these trades can be very risky and one should establish a stop loss in order to execute a trade. The chart also illustrates numerous instances of crossovers during which the rate is range-bound. In these cases it may be essential that we also rely on price action for confirmation.

Out of the many technical indicators available, the EMA is one of the simplest. It is a favorite of many successful traders. The flexibility it offers in terms of adjusting the smoothing factor or time period makes it a versatile tool. Traders can use it for long term trades by adjusting the EMA for a longer period. In markets like FX where the indicator needs to be reactive to the latest price, traders can simply reduce the time interval. The indicator works particularly well in a trending market. If used well it can lead to a substantial profit for the trader. You can also customize and apply it to a wide range of asset classes as well.

There are some disadvantages to it as well that a trader should be wary of. Since it attaches more importance to the latest price points, the indicator could send out false signals in a market that is range-bound. Like most indicators, the dependence on stale data points may be high for the EMA as well. In some cases this can hamper the predictive ability. The trader might only catch a change in trends with a significant delay. This could lead to them missing out on a good opportunity. It is necessary to enhance the analysis using other indicators and price action. Establishing a stop loss is also a must in trading since the loss could be significant when leverage is used. There is also no way to decide which EMAs should be used in determining an optimum crossover strategy.

Today the EMA is still a useful tool for traders It continues to see common use even though many more sophisticated technical indicators have cropped up since. The flexibility it offers along with the simple computational requirements makes it a handy tool in conducting analysis at a fast pace.

The 50-day average gives us a picture of the price in the last 50 days. Traders can compare this with the latest price and estimate the future direction based on this.

The exponential moving average is typically preferable in a trending market, where the latest price should be given more weight in establishing the average. In such a case, simple moving averages tend to underestimate or overestimate the price. When the price is range bound, both the averages tend to perform in a similar manner.

Swing trading involves trades for the medium term. One could use three EMAs like EMA 9, EMA 13, and EMA 50. To get a clear indication of an uptrend, the current price that was below these three lines should rise above these EMAs. Moreover, EMA 9 should be higher than the EMA 13 which in turn should be above EMA 50.