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Using PowerBI to Analyze Stock Markets: Building a Technical Indicators Dashboard from Scratch


In today’s fast-paced financial markets, data-driven decisions have become an essential part of successful investing. PowerBI is a powerful tool that allows users to visualize data, extract insights, and create customized dashboards to analyze market trends. At Lucky Mario, we are dedicated to empowering investors with tools and knowledge to make well-informed decisions. In this blog, we will guide you step-by-step through the process of using PowerBI to create a technical indicators dashboard for stock market analysis, including popular metrics like Moving Averages (MA), Relative Strength Index (RSI), and more.


1. Introduction to Technical Indicators and PowerBI

Before diving into building the dashboard, it’s important to understand what technical indicators are and why they are important for market analysis. Technical indicators are mathematical calculations based on historical price, volume, or open interest data, used to predict future price movements. Investors rely on these indicators to help them determine market trends and identify optimal points for buying or selling securities.

PowerBI, a data visualization and business intelligence tool by Microsoft, provides the perfect platform for integrating financial data, performing complex calculations, and creating visually appealing dashboards to represent stock market data. The tool’s flexibility makes it ideal for building custom dashboards for both novice and advanced users.

At Lucky Mario, we understand the importance of integrating analytical tools to make the stock market data more comprehensible for retail and institutional investors alike. This step-by-step tutorial will help you build a dashboard that includes technical indicators such as Moving Averages (MA), Relative Strength Index (RSI), and other visualizations to help with trend identification.


2. Setting Up the Data Sources

The first step in building a PowerBI stock market dashboard is obtaining the right data sources. You will need reliable and real-time stock data to create meaningful visualizations.


2.1 Acquiring Stock Market Data

There are several options for acquiring stock market data:

  • Yahoo Finance API or Alpha Vantage API are popular APIs that offer historical and real-time stock data for free. These APIs can be used to pull stock prices, volumes, and other relevant metrics.

  • CSV Files: Alternatively, you can download stock data from Yahoo Finance or Google Finance as CSV files and import them into PowerBI.

  • Excel Spreadsheets: If you have a subscription to a market data service, you can export stock prices directly into Excel spreadsheets.


2.2 Importing Data into PowerBI

Once you have your data source ready, the next step is to import the data into PowerBI:

  1. Open PowerBI Desktop.

  2. Click on Get Data and select the appropriate source (e.g., Web for API, CSV for downloaded files, or Excel).

  3. Provide the necessary URL or file path and click Load to bring the data into PowerBI.

After importing the data, it’s essential to ensure that it is clean and properly formatted. Use the Power Query Editor to remove any missing or irrelevant data points that could interfere with your analysis.


3. Data Transformation and Preparation

For accurate technical analysis, it’s crucial that the data is correctly formatted and transformed to derive meaningful insights. In this stage, you will perform a series of data transformations.


3.1 Adding Date Column and Sorting

Stock market data usually includes columns such as Date, Open, High, Low, Close, and Volume. The Date column is particularly important because it allows you to sort and analyze data in a chronological order. Ensure that your data is sorted correctly based on date.


3.2 Calculating Moving Averages (MA)

Moving Averages (MA) are one of the most common technical indicators. A Moving Average smoothens out price data to help identify trends. We will calculate the Simple Moving Average (SMA) and Exponential Moving Average (EMA) using DAX (Data Analysis Expressions) in PowerBI.

To calculate a 10-day SMA:

  1. Go to Modeling > New Measure.

  2. Enter the following DAX formula:

    10-Day SMA = AVERAGEX(FILTER(StockData, StockData[Date] >= MAX(StockData[Date]) - 9), StockData[Close])

    This formula calculates the average closing price over the last 10 days, which helps to indicate the short-term trend.

For an EMA, which gives more weight to recent data, you can use:

10-Day EMA = CALCULATE([10-Day SMA], ALLEXCEPT(StockData, StockData[Date]))

Moving averages help investors identify trends by smoothing out fluctuations. A rising moving average generally indicates an upward trend, while a falling average indicates a downward trend.


4. Calculating Relative Strength Index (RSI)

The Relative Strength Index (RSI) is a momentum indicator that measures the speed and change of price movements. The RSI oscillates between 0 and 100, providing an indication of whether an asset is overbought or oversold.

To calculate RSI in PowerBI:

  1. New Measure: Create a new measure for average gains and average losses over a 14-day period.

    Avg Gain = AVERAGEX(FILTER(StockData, StockData[Date] <= MAX(StockData[Date]) && StockData[Date] > MAX(StockData[Date]) - 14 && StockData[Close] > StockData[PreviousClose]), StockData[Close] - StockData[PreviousClose])

  2. Next, create a measure for RSI:

    RSI = 100 - (100 / (1 + ([Avg Gain] / [Avg Loss])))

  3. Plot this RSI value on your dashboard, adding conditional formatting to indicate overbought (RSI > 70) and oversold (RSI < 30) conditions.


5. Building the Dashboard

Once the calculations are complete, it’s time to create the visualizations and build the PowerBI dashboard.


5.1 Adding Charts for Visualization

PowerBI allows you to create various types of charts that are ideal for visualizing stock data and technical indicators.

  • Line Chart for Stock Prices: Create a line chart to display the historical price of the stock. Use Date on the x-axis and Close Price on the y-axis.

  • Overlay Moving Averages: Overlay the SMA and EMA lines on top of the line chart to help visualize trends more clearly.

  • RSI Visualization: Use a line chart to visualize RSI. Add threshold lines at 30 and 70 to visually indicate overbought and oversold levels.


5.2 Adding Data Cards and KPIs

To make your dashboard more informative, add Data Cards and KPIs to show the latest stock price, RSI value, and trend direction.

  • Data Cards for Close Price and Volume provide an instant summary of the key metrics.

  • KPI Visualization for RSI helps investors know whether the stock is overbought or oversold at a glance.


5.3 Customizing the Dashboard

Make sure to customize the dashboard for a professional appearance:

  • Add titles and legends to explain the visuals.

  • Use conditional formatting to highlight important trends, such as positive or negative price movements.

  • Make the dashboard interactive by allowing users to filter data by date ranges or specific stocks.

At Lucky Mario, we recommend customizing the visuals in such a way that complex financial data becomes accessible and actionable for investors of all experience levels.


6. Publishing and Sharing the Dashboard

Once your dashboard is complete, it’s time to share it with your team or clients.

  1. Publish: Click on the Publish button in PowerBI Desktop to upload the dashboard to the PowerBI Service. Ensure you have a PowerBI Pro account to enable sharing features.

  2. Set Up Scheduled Refresh: If you are using a live data source such as an API or SQL database, make sure to set up a scheduled refresh so that your dashboard always reflects the most up-to-date data.

  3. Share the Dashboard: You can share your PowerBI dashboard with others by creating a shareable link or adding user permissions via the PowerBI Service.

At Lucky Mario, we believe in fostering a collaborative environment. Sharing dashboards enables stakeholders to stay updated and make decisions based on real-time data insights.


7. Conclusion

Building a stock market technical indicators dashboard using PowerBI is a powerful way to visualize market trends and make data-driven investment decisions. This tutorial has shown you how to set up your data sources, calculate important technical indicators like Moving Averages (MA) and Relative Strength Index (RSI), and create an informative and interactive PowerBI dashboard.

The key to a successful financial analysis dashboard is ensuring that the information is accessible, actionable, and accurate. PowerBI provides the tools needed to turn raw financial data into meaningful insights, and at Lucky Mario, we are committed to helping you make the most of these capabilities to enhance your investment strategy.

Whether you are an individual investor or part of an organization, a well-designed technical indicators dashboard can make a huge difference in your decision-making process. Feel free to reach out to Lucky Mario for further guidance, and stay tuned for more tutorials on using technology for smarter investing.

 
 
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