Technical Trading Indicators in XAUUSD Trading (Part I)

Whether you’re curious about forex trading, things trading, or claim trading, it can be valuable to utilize technical analysis as part of your procedure, including learning various trading indicators. Trading indicators are mathematical estimates plotted as lines on a cost chart and can assist traders in determining specific signals and trends within the demand.

Using trading indicators is characteristic of any technical trader’s approach. Paired with the right risk control tools, it could aid you in gaining more understanding of price trends.

Technical Trading Indicators in XAUUSD Trading (Part I)

Relative Strength Index (RSI)

The Relative Strength Index (RSI) is a velocity arrow that calculates the rate and change of cost movements. It is categorized as a leading indicator, meaning signals are usually shown before the price. The RSI is considered one of the most suitable indicators for traders to know if the currency they purchased is overbought or oversold. The Relative Strength Index (RSI) fluctuates among 0 and 100. An overbought (RSI above 70) will show an uptrend in the market. Thus traders will buy the currency for a long time.

On the other hand, an oversold (RSI under 30) will show a downtrend in the market, and traders will sell a currency for a long time, and now the market will change its direction. Furthermore, there is also a trend called centerline crossovers in the Relative Strength Index, which traders also tend to look for as a confirmation for trend formations. A downtrend is likely to occur when the RSI is below 50, and a possible uptrend is when the RSI is above 50. The Relative Strength (RSI) indicator will be explained in more detail in the next chapter.

The equation for calculating the RSI: 

𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑆𝑡𝑟𝑒𝑛𝑔𝑡ℎ 𝐼𝑛𝑑𝑒𝑥 =

100 – [100 /(1 + (𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑜𝑓 𝑈𝑝𝑤𝑎𝑟𝑑 𝑃𝑟𝑖𝑐𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 / 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑜𝑓 𝐷𝑜𝑤𝑛𝑤𝑎𝑟𝑑 𝑃𝑟𝑖𝑐𝑒 𝐶ℎ𝑎𝑛𝑔𝑒))]

Bollinger Bands

The Bollinger band is another well-known technical indicator defined by a set of trend lines. The function of Bollinger bands is to help determine whether the trading prices are high or low relative. To calculate the Bollinger band indicator, the first step is to enumerate a simple moving average. A 2-day SMA (Standard Moving Average) is commonly used, which would average the closing prices for the first 20 days as the first data point and so on for the following data. By using the formula, the upper and lower bands will be produced. Even though the Relative Strength Index (RSI) is an effective technical indicator, combining the tool with other technical indicators in making decisions for opening a position would be much more effective. This is because the RSI is considered a leading indicator, which typically means that it sends signals before the prices on the chart, which can result in the signs being false or too early.

Formula:

• The second line (upper Bollinger band) = Moving Average of the Close + the Standard Deviations
• The third line (lower Bollinger band) = Moving Average of the Close – the Standard Deviations

Moving Average Convergence Divergence (MACD)

The Moving Average Convergence Divergence (MACD) is an indicator that uses the trading style momentum and shows the relationship between two moving averages of a security’s price. It consists of two exponential moving averages, the signal line (red) and the MACD line (blue). In addition, the MACD indicator also includes a histogram located behind the lines. The histogram illustrates the distinction between the signal line and the MACD line. As the difference becomes more extensive, the histogram or bar chart length will become longer. The technical signals will be triggered when it crosses its signal line above (to buy) or below (to sell). The value of MACD will be positive if the 12-period EMA (blue MACD line) is above the 26-period WMA (red signal line) and vice versa.

The equation for Moving Average Convergence Divergence:

𝑀𝐴𝐶𝐷 = 12 𝑃𝑒𝑟𝑖𝑜𝑑 𝐸𝑀𝐴 − 26 𝑃𝑒𝑟𝑖𝑜𝑑 𝐸𝑀𝐴

Moving Average (MA)

The Moving Average (MA) is an indicator for stocks but is often used in technical analysis for trading in the foreign exchange market. Usually, in statistics, the function of the moving average is in calculating the data standards. In technical analysis, the part of the moving average is similar in that the moving average of the prices is estimated to create an updated average price where traders can pin down the direction of the trend to find out the resistance level and support. The moving averages are customizable depending on the trader’s trading objectives. However, the most common periods are 15, 20, 30, 50, 100, and 200 days. The traders can choose from no right and wrong time frame, but it is essential to test out many different time frames to find out which period works best for you. Traders can decide the periods based on their trading objectives, whether they conduct short-term or long-term trading.

If the moving average rises, an uptrend signal is presented with an uptrend, and a downtrend signal is given if the moving average declines. Likewise, upward momentum is established if the moving average with the shorter period crosses above the moving average with the more extended period (bullish crossover). Contrarily, a downward momentum is set if the moving average with the shorter period crosses below the moving average with the more extended period (bearish crossover).

There are two types of moving averages:

• Simple Moving Average (SMA)

The simple moving average (SMA) is one of the simplest indicators used in technical analysis as it is easier to set. In statistics, a given set of values is calculated using the arithmetic mean. In the foreign exchange (FOREX) market, the simple moving average (SMA) is defined as a currency pair’s average closing price over a specific period. Since the prices change continuously, the moving average will change accordingly. This explains the reason why the average is named “moving.”

The equation for estimating the straightforward moving average (SMA):

𝑆𝑀𝐴 = (𝑃1 + 𝑃2 + 𝑃3 … + 𝑃𝑛) / 𝑛

• Exponential Moving Average (EMA)

The exponential moving average (EMA) is similar to the simple moving average (SMA) in a way that it observes price trends over time; however, the difference is that the EMA is a type of weighted moving average (WMA). This means that the EMA is a much more improved version of the SMA that gives more weight to the most up-to-date data of the prices, thus reacting more quickly to price changes.