the-daily-trading-coach-101-lessons-for-becoming-your-own-trading-psychologist-brett-steenbarger-_2009_-a23

Looking for the Edge 333For this investigation, we’ll examine half-hourly data for the S&P 500emini contract. I obtain my intraday data from my quote platforms; in thecurrent example, I’ll use e-Signal. To do this, we create a 30-minute chartof the ES futures contract; click on the chart and scroll to the right to movethe chart backward in time. When we’ve covered the last 20 days or so,we click on the menu item Tools; select Data Export; then uncheck theboxes for the data that we won’t need. In this case, all we’ll need is Date,Time, and Volume. We click the button for Copy to Clipboard and open afresh sheet in Excel. Once we click on the Excel menu item for Edit andselect Paste, with the cursor at cell A2, we’ll populate the sheet with theintraday data. We can then enter names for the columns in row 1: Date;Time; and Volume. (If you’re downloading from e-Signal, those names willaccompany the data and you can download the data with the cursor at A1).Our next step is to highlight the entire data set that we want to cover.We click on the Excel menu item for Data; select Filter; and select AutoFilter.A set of small arrows will appear beside the column names. Click thearrow next to Time and, from the drop down menu, select the time that representsthe start of the trading day. In my case, living in the Chicago area inCentral Time, that would be 8:30 A.M. You’ll then see all the volume figuresfor the half-hour 8:30 A.M. to9:00A.M. Click on Edit; select Copy; open ablank sheet; click on Edit; and select Paste. This will put the 8:30 A.M. dataon a separate sheet. If you have 20 values (the past 20 days), you can enterthe formula “=average(c2:c21)” and you’ll see the average trading volumefor the first half-hour of trading. Of course, you can filter for any time ofday and see that half-hour’s average volume as well.When you know the average trading volume for a particulartime period, you can assess institutional participation in realtime—particularly with respect to whether this volume picks upor slows down as a function of market direction.The filter function is helpful when you want to pull out data selectivelyfrom a data set. Let’s say, for instance, that you had a column in which youcoded Mondays as 1; Tuesday’s as 2; etc. You could then filter out the 1sin the historical data set and see how the market behaved specifically onMondays. Similarly, you could code the first or last days of the month andfilter the data to observe the returns associated with those.In general, I find filtering most helpful for intraday analyses, when Iwant to see how markets behave at a particular time of day under particularconditions. Frankly, however, this is not where I find the greatest edgestypically, and it’s not where I’d recommend that a beginner start withhistorical investigations. Should you become serious about investigating