Moving averages method is used in statistics to analyze data points, which are calculated by averaging several subsets of a larger dataset. A moving average is a measure of how well a piece of work is doing over a given period of time. The moving average method is a popular stock indicator in technical analysis (MA). In order to smooth out price data, the calculation of a stock’s moving average is carried out in order to create an average price that is continuously updated.
A moving average method can be used to safeguard the price of a stock from the short-term volatility that is unavoidable in the financial markets.
Moving average Method
In technical analysis, the moving average is a simple but useful instrument. A stock’s support and resistance levels and trend direction can both be predicted using moving averages. Trend-following or trailing is because it uses previous prices as its basis.
The larger the lag, the longer the moving average period. That’s why you’ll see more lag when using the 200-day moving average because it’s based on prices for the prior 200 days. These two moving averages, the 50-day and 200-day moving averages are frequently monitored by investors and traders.
Investors have complete control over the time span used to calculate moving averages, making them a highly flexible tool. There are six most frequent moving average time periods: 15, 20, 30, 50, and 200 days. The more sensitive the average is to price movements, the shorter the time period employed to produce it is. The average is less sensitive over a longer time period.
Moving averages can be calculated using multiple time periods of differing lengths, depending on the trading intentions of the investor. The usage of short-term moving averages is more common in trading, while long-term investors prefer longer-term moving averages. As far as moving averages are concerned, there is no such thing as a “perfect” time frame. Experimenting with a variety of time periods until you find one that works best for your plan is the greatest method to discover which one works best for you.
Types of moving average method
Simple moving average
Simple moving averages (SMAs) are derived by taking the arithmetic mean of a set of values over a specific period of time and dividing it by the number of periods. To put it another way, a set of numbers, or financial instrument prices, are combined and then divided by the number of prices in the set.
Exponential moving average
To make it more responsive to changes in the market, the exponential moving average weighs recent prices more heavily. A simple moving average (SMA) must be calculated first in order to generate an exponential moving average (EMA). Next, you must determine the “smoothing factor,” which is commonly calculated using the following formula: [2/(selected time period + 1)/(smoothing factor). As a result, the multiplier for a 20-day moving average is [2/(20+1)]= 0.0952. To get the current value, you add the smoothing factor to the previous EMA. This means that the EMA places a greater emphasis on recent prices, whereas the SMA places an equal emphasis on all values.
Moving average Method example
To better understand the moving average, let’s look at the price of a company’s shares. A look at the last 12 trading sessions:
Day | Stock Price |
1 | 30.5 |
2 | 30.6 |
3 | 30.35 |
4 | 29.7 |
5 | 28.1 |
6 | 29.25 |
7 | 30.25 |
8 | 30.9 |
9 | 31.05 |
10 | 32.15 |
11 | 32 |
12 | 31.5 |
In order to predict the stock price on the 13th day, we’ll use a basic 4-day moving average.
Moving Average is calculated using the formula given below
Simple Moving Average = (A1 + A2 + …… + An) / n
Periodicity = 4
On the 13th day, the stock price is anticipated to be $31.68 based on a simple moving average of the last four days.
Calculation of trend by moving Average method
Temperature records have been smashed in a number of cities and countries during the past few days, according to the news. A new standard has been set by the amount of rainfall in a certain area. How could they have been aware of it? What evidence do they have to back up their claims? These are the data that have been collected over a period of time. By now, I’m sure you’re all familiar with time-series data and all of its numerous components. Moving averages will be used to determine the trend of a set of data in this section.
The moving average method in a time series
Three basic types of moving average method in time series fluctuations exist: long-term swings, short-term or periodic swings, and random changes. The general propensity of the data to increase or decrease over a lengthy period of time is shown by a long-term variation or trend. The change may be gradual, but it will always be there.
The study of moving average method in time series:
Think of a time series as an example. Do you have any plans for it? Is there a formula for figuring out how changes in one component affect the other? In time series analysis, the most common issues are:
To figure out what factors are at play and what their combined effect is on the way a time series moves and
To isolate, examine, analyze, and measure each component separately while keeping the rest of the system constant.
Conclusion
Using a moving average method to get a sense of the overall trends in a dataset is the most effective method of doing so. The moving average makes it much easier to foresee long-term trends than it otherwise would be. Calculations can be performed for any duration of time. Consider the sales data collected over a twenty-year period. Using that information, you can construct a 5-year moving average, a 4-year moving average, and so on and so forth. Market analysts may employ a 50-day or 200-day moving average to assist them in analyzing market trends and (hopefully) predicting where the stock market will go in the near future.
