Stock Screener (‘Sentiment’) – Example 23: Define a time frame and classify daily, monthly and quarterly % fluctuations in closing prices within that timeframe into several distinct categories

This is an example of a (sentiment-based) scan that uses the newly introduced market aggregate functions in the Advanced Scanner that ships with ChartAlert

1 minute

ATTN: This scan is an extension of an earlier scan (refer to Example 22: Define a time frame and classify the daily % fluctuations in closing prices within that timeframe into ‘n’ distinct categories), with the exception of extracting a few more data points in this scan.

List data from "01-Sep-2023"

Add col MARKET_COUNT(chg%<=-4) as Chg <-4% format 0
Add col MARKET_COUNT(chg%<0 and chg%>-4) as Chg 0 To -4% format 0
Add col MARKET_COUNT(chg%>0 and chg%<4) as Chg 0 to 4% format 0
Add col MARKET_COUNT(chg%>=4) as Chg >4% format 0

Add col MARKET_COUNT(chg%(cl, cl a month ago) >= 25) as MChg >25% format 0
Add col MARKET_COUNT(chg%(cl, cl a month ago)<= -25) as MChg <-25% format 0

Add col MARKET_COUNT(chg%(cl, cl a month ago) >= 50) as MChg >50% format 0
Add col MARKET_COUNT(chg%(cl, cl a month ago)<= -50) as MChg <-50% format 0

Add col MARKET_COUNT(chg%(cl, cl 34 bars ago) >= 13) as 34BChg >13% format 0
Add col MARKET_COUNT(chg%(cl, cl 34 bars ago)<= -13) as 34BChg <-13% format 0

Add col MARKET_COUNT(chg%(cl, cl a quarter ago) >= 25) as QChg >25% format 0
Add col MARKET_COUNT(chg%(cl, cl a quarter ago)<= -25) as QChg <-25% format 0

Add Column chg%
Add Column chg%(cl, cl a month ago) as MChg
Add Column chg%(cl, cl 34 bars ago) as 34BChg
Add Column chg%(cl, cl a quarter ago) as QChg

Apply to niftymic250

Set report type to SUMMARY-DATEWISE

Below is a breakdown of the scan presented in a step-by-step manner.


Continue reading “Stock Screener (‘Sentiment’) – Example 23: Define a time frame and classify daily, monthly and quarterly % fluctuations in closing prices within that timeframe into several distinct categories”

Stock Screener (‘Sentiment’) – Example 22: Define a time frame and classify the daily % fluctuations in closing prices within that timeframe into ‘n’ distinct categories

This is an example of a (sentiment-based) scan that uses the newly introduced market aggregate functions in the Advanced Scanner that ships with ChartAlert

1 minute

This functionality was introduced in October 2023 (Version 23.10.1)

List data from "01-Sep-2023" 

Add col MARKET_COUNT(chg%<=-4) as Chg <=-4% format 0
Add col MARKET_COUNT(chg%<0 and chg%>-4) as Chg 0 To -4% format 0

Add col MARKET_COUNT(chg%>0 and chg%<4) as Chg 0 to 4% format 0
Add col MARKET_COUNT(chg%>=4) as Chg >=4% format 0

Add Column chg%

Apply to nifty500

Set report type to SUMMARY-DATEWISE

Below is a breakdown of the scan presented in a step-by-step manner.


Continue reading “Stock Screener (‘Sentiment’) – Example 22: Define a time frame and classify the daily % fluctuations in closing prices within that timeframe into ‘n’ distinct categories”

Stock Screener (‘Sentiment’) – Example 21: Count and display the number and % of stocks that are currently trading above/below their respective n-bar Moving Average

This is an example of a (sentiment-based) scan that uses the newly introduced market aggregate functions in the Advanced Scanner that ships with ChartAlert

1 minute

This functionality was introduced in October 2023 (Version 23.10.1)

List symbols

Add Column Close
Add Column Volume format 0,000

Add Column IIF(cl > ema(50),1,0) as IsAbvEMA
 Group rows by IsAbvEMA

Add Column CHG%(cl,ema(50)) as Diff%
 Sort on Column Diff% desc

Add Column MARKET_COUNT(cl > ema(50)) as AbvEMA
Add Column MARKET_COUNT (cl < ema(50)) as BlwEMA
Add col MARKET_PERCENT(cl > ema(50)) as AbvEMA%
Add col MARKET_PERCENT(cl < ema(50)) as BlwEMA%

Apply to NIFTY500

plot ema(50)

Below is a breakdown of the scan presented in a step-by-step manner.


Continue reading “Stock Screener (‘Sentiment’) – Example 21: Count and display the number and % of stocks that are currently trading above/below their respective n-bar Moving Average”