Master Stock Price Analysis: Creating MACD Chart in Power BI

Master Stock Price Analysis: Creating MACD Chart in Power BI

Table of Contents

1. Introduction
2. What is the Moving Average Convergence Divergence (MACD)?
3. How is the MACD calculated?
4. Steps to calculate the MACD
   1. Calculate the Short-Term EMA
   2. Calculate the Long-Term EMA
   3. Calculate the MACD Line
   4. Calculate the Signal Line
   5. Calculate the MACD Histogram
5. Embedding R Scripts in Power BI Power Query
6. Creating the MACD Chart in Power BI Desktop
7. Interpreting the MACD Chart
   1. Price Trend
   2. Momentum
   3. Price Divergence
   4. Overbought/Oversold
8. Using MACD for Investment Decisions
9. Conclusion
10. FAQ

📈 What is the Moving Average Convergence Divergence (MACD)?

The Moving Average Convergence Divergence (MACD) is a popular technical analysis tool used by traders and investors to make informed decisions about buying, selling, or holding stocks based on trend direction, momentum, divergence, and overbought/oversold conditions. It consists of two Exponential Moving Averages (EMAs) of a stock's price - a shorter-term EMA (usually 12 periods) and a longer-term EMA (usually 26 periods). The MACD line is the difference between these two EMAs, and it is further smoothed by a 9-day EMA to generate a signal line. The MACD histogram represents the difference between the MACD line and the signal line.

📊 How is the MACD calculated?

The MACD is calculated using the following steps:

1. Calculate the Short-Term EMA: This involves using the closing prices of a stock over a specific period (usually 12 days) to calculate the shorter-term EMA, known as the "fast" EMA.
2. Calculate the Long-Term EMA: This involves using the closing prices of a stock over a longer period (usually 26 days) to calculate the longer-term EMA, known as the "slow" EMA.
3. Calculate the MACD Line: The MACD line is obtained by subtracting the long-term EMA from the short-term EMA.
4. Calculate the Signal Line: A 9-day EMA of the MACD line is calculated to generate a signal line, which helps to smooth out the MACD line.
5. Calculate the MACD Histogram: The MACD histogram is the difference between the MACD line and the signal line. It represents the visual representation of the MACD indicator.

📊 Steps to calculate the MACD

Step 1: Calculate the Short-Term EMA

The short-term EMA is calculated using the closing prices of a stock over a specific period, often 12 days. This EMA is referred to as the "fast" EMA. The calculation formula is as follows:

EMA_12_today = (Close_today - EMA_12_yesterday) * (2 / (1 + 12)) + EMA_12_yesterday

Step 2: Calculate the Long-Term EMA

Similarly, the long-term EMA is calculated using the closing prices of the stock over a longer period, often 26 days. This EMA is referred to as the "slow" EMA. The calculation formula is as follows:

EMA_26_today = (Close_today - EMA_26_yesterday) * (2 / (1 + 26)) + EMA_26_yesterday

Step 3: Calculate the MACD Line

The MACD line is obtained by subtracting the long-term EMA from the short-term EMA. The formula is as follows:

MACD = EMA_12_today - EMA_26_today

Step 4: Calculate the Signal Line (9-day EMA of MACD)

A 9-day EMA of the MACD line is then calculated to smooth out the MACD line and generate a signal line. The formula is as follows:

SignalLine_Today = (MACD - SignalLine_yesterday) * (2 / (1 + 9)) + SignalLine_yesterday

Step 5: Calculate the MACD Histogram

The MACD histogram represents the difference between the MACD line and the signal line. It is calculated as follows:

MACD Histogram = MACD - SignalLine

The resulting MACD chart typically consists of the MACD line, the signal line, and the MACD histogram.

📊 Embedding R Scripts in Power BI Power Query

To calculate the MACD in Power BI, you can embed R scripts in Power Query. This allows you to leverage the power of R programming language for the calculation. By using the ready-made EMA function in the R Package "TTR" and the "dplyr" package for data manipulation, you can group the stock data by StockCode, calculate the MACD indicators for each stock, and update the dataset with the MACD values.

📊 Creating the MACD Chart in Power BI Desktop

Once you have calculated the MACD indicators using Power Query and R script, you can create a MACD chart in Power BI Desktop. This involves placing line charts for the closing price and the MACD lines, as well as a slicer for stock code selection and year filtering. You can format the visuals and add dynamic titles to enhance the presentation of the MACD chart.

📊 Interpreting the MACD Chart

The MACD chart provides valuable insights into the price movements of stocks. Here's how to interpret the different aspects of the MACD chart:

Price Trend

The MACD chart allows you to analyze price trends. By observing the closing price line, you can identify upward or downward trends. However, it's important to consider the timeframe and other factors to determine the overall trend.

Momentum

The MACD histogram indicates the momentum of a stock. Positive values above the zero line indicate upward momentum, while negative values below the zero line indicate downward momentum. Small fluctuations suggest moderate momentum.

Price Divergence

Price divergence refers to the relationship between the price and the MACD. If the price and MACD are moving in the same direction, there is no significant divergence. Divergence may suggest discrepancies between price action and momentum.

Overbought/Oversold

The MACD indicator provides insights into whether a stock is overbought or oversold. When the MACD stays within the middle range and does not reach the upper or lower extremes, it suggests a balanced market without extreme conditions.

📊 Using MACD for Investment Decisions

The MACD is a useful tool for traders and investors to make informed decisions. However, it should not be used as the sole factor for investment choices. It's important to consider other factors such as fundamentals and broader market conditions before making any investment decisions.

📊 Conclusion

The Moving Average Convergence Divergence (MACD) is a powerful technical analysis tool that helps traders and investors identify trends, momentum, price divergence, and overbought/oversold conditions. By understanding how to calculate and interpret the MACD chart, you can make more informed decisions in the stock market.

📊 FAQ

Q: What is the purpose of the MACD chart? A: The MACD chart is used to analyze stock price trends, momentum, price divergence, and overbought/oversold conditions.

Q: How is the MACD calculated? A: The MACD is calculated using Exponential Moving Averages (EMAs) of a stock's price.

Q: Can the MACD be used alone for investment decisions? A: No, the MACD should be used in conjunction with other indicators and analysis methods.

Q: How can I create a MACD chart in Power BI? A: You can calculate the MACD using R scripts in Power Query and then create a chart in Power BI Desktop.

Q: What factors should I consider besides the MACD for investment decisions? A: It's important to consider fundamentals and broader market conditions before making investment choices.