What’s the role of moving averages in tech analysis?

[ad_1]

Moving averages in technical analysis help securities traders and others in the financial management industry to identify trends related to price changes of stocks and commodities on the open market. There are three types of moving averages in technical analysis: Simple Moving Average (SMA), Linear Weighted Average (LWA), and Exponential Moving Average (EMA). Moving averages are some of the most commonly used technical indicators in security analysis: Technical indicators are statistics derived from market data used to predict changes in financial assets or economies. Each average is calculated based on the closing price of a security or other financial instrument over a certain period of time. Financial analysts then plot the averages on a chart or graph and look for price trends based on fluctuations in the plot points.

The SMA is calculated based on the average price of a stock or commodity over a given period of time. It is constantly “on the move” because as new closing prices become available, the oldest closing price falls. For example, the first day of a five-day moving average is based on the last five closing prices for the security. Each day, a new closing value is added, the oldest closing price is lowered, and a new five-day average is calculated. Moving averages in technical analysis of this type give an overview of how a stock or commodity is trading relative to the time period used.

One criticism of the SMA is the fact that each closing price is equally weighted in determining the moving average. Actually, the most recent prices should have a higher weight because they are the most indicative of future trends. LWA and EMA are two moving averages that were developed to offset this discrepancy.

The linear weighted average is calculated to reflect the importance of recent prices. Each closing price is multiplied based on its position in the data field. For example, when calculating a five-day average, the most recent closing price would be multiplied by five, the second most recent would be multiplied by four, and so on. Those values ​​would be added and divided by the sum of the multipliers. In this case, the sum of the multipliers would be 15 (5 + 4 + 3 + 2 + 1 = 15).

The exponential moving average is the most complicated of the moving averages in technical analysis. It is based on a convoluted equation involving SMA, the security’s current price, an adjustment factor to account for price fluctuations, and the number of time periods. Fortunately, most quantitative analysis software packages and spreadsheets have the ability to calculate this average for traders. EMA is sensitive to new data input and consequently provides a more accurate forecast of price changes than SMA.

Once these moving averages are calculated in technical analysis, they are plotted on charts. A chart showing an upward sloping moving average along with a price that is above the moving average indicates an upward trend for a stock or commodity. Alternatively, a downward sloping moving average combined with a price below the moving average indicates a downtrend and generally prompts traders to sell.

Traders can also plot short-term moving averages and long-term moving averages on the same chart, for example, a chart containing a stock’s five-day moving average and 10-day moving average. If the points of the short-term moving average chart are higher than those of the long-term moving average, stock prices show an upward trend. Conversely, a short-term moving average that is lower than the long-term moving average may indicate a downtrend.

Smart Asset.

[ad_2]