Analyzing market data through graphs and looking for trends is difficult because the data points sometimes change drastically from month to month. For example, if a brand new condo building was built in September 2018, home sales may have seen a large spike that month, when September is usually a slow sales month. Thankfully, when creating charts in ShowingTime’s InfoSparks market analysis tool, there is an option to use a “rolling” data view to smooth short-term fluctuations and highlight longer-term trends you are looking for. Learn how to utilize this option in this sample scenario.
When setting up your chart options, you want to first decide on a timeline. The timeline selection determines the amount of data being reported on; 1 year, 3 years, 5 years, etc. up to the maximum data available. This selection will change the timeline along the bottom of your chart.
In the graph below, a monthly timeline is shown for the median sales price of an entire MLS, so the line is very jagged as this data varies quite a bit according to the month. Seasonal peaks and valleys are often a factor, demonstrated below by the annual dips in January and peaks each summer. The data point for April will show you the median sales price for all transactions that took place only in the month of April 2019.
Next, you will see the same information, but in the Rolling 12 Months data view. This view is determined by taking data from a certain month and rolling it together with the data from the past 3, 6 or 12 months.
In this case, each point on the line is actually showing the median sales price for 12 months of data at each point (April 2019 plus the previous eleven months). When looking at April 2019, the median sales price changes because it is factoring in not only sales prices from April 2019, but also those from the previous 11 months going back to May 2018. By using this approach, you lessen the seasonal peaks and valleys, smoothing out the line to show a trend.
InfoSparks makes it easy to analyze data and get an accurate picture of trends. Whether you are looking over a few months or a year, the rolling data view can help give you a clearer picture of what you are evaluating.
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