Careful analysis of price and security wise delivery position data can help investors in predicting future price movements. Hence, investors are advised to use security wise deliverable percentage as a confirmatory parameter to validate their investment decisions. Let's say you have identified stock A for investment at a price P based on fundamental and technical analysis. To be doubly sure of your decision, just have a look at the history of security wise deliverable percentage of the particular stock. Why? Hear this:

A low deliverable quantity or delivery percentage over a period of time (few days to a month) is indicative of a high intraday activity (Buying in the morning and selling in the evening or vice versa). This means that the current price trend (either up or down) is dubious and will be short lived.

Similarly, a high deliverable quantity or delivery percentage over a period of time (few days to a month) is indicative of positional or long term activity i.e. buying and holding for long term (bullish) or selling and getting out of the stock completely (bearish). This means that the current price trend (either up or down) is going to sustain for relatively longer period.

While analyzing the security wise delivery percentage data, try to map your finding with following decision table a.k.a. thumb rules:

Price Delivery Percentage Price Prediction Investment Decision
Rising Rising Price uptrend is likely to sustain Buy
Rising Falling Price uptrend might not sustain Sell
Falling Rising Price downtrend is likely to sustain Sell
Falling Falling Price Downtrend might not sustain Buy

Enough of theory. Let's get real and have a look at all the stocks (FnO and non FnO) falling into above categories. We have done this categorization based on approximately last 3 months (60 trading days) price and delivery data. However, you can visualize data for other time frames too below. You can click on individual rows in tables below to get the detail view of price, security wise delivery position, volume (total traded quantity) and total number of trades. Before you start playing around, one common sense pointer about total traded quantity (volume) and total number of trades data:

High volume with low total number of trades indicates activity by institutional players, whereas low volume with high total number of trades indicates activity by retail players

A comparative analysis of daily and average figures will give you a fair idea about who the players are. The detail view has the average figures for price, delivery percentage, volume and total number of trades. You are all set to go now:

Price and Security Wise Delivery Trends of FnO Stocks



Price and Security Wise Delivery Trends of Non FnO Stocks


Hungry for more? If you do not find the stock of your interest above, the drop down below enables you to plot price, security wise delivery percentage, total traded quantity and total number of trades data of individual NSE stocks for past 1 week, 1 month, 3 months and 1 year period. For people who have deep interest in trading and who wants to do a correlation analysis on security wise delivery trend and combined open interest of future contracts (to validate whats being observed in cash market is also getting reflected in futures market), we have also included a plot of price and future contracts combined open interest (this will load with data only for stocks which trade in FnO). With the visual chart, you can very well interpret the underlying trend and spot the anomalies in price movements. So please help yourself.

Plot Security Wise Delivery Position





 

Where to go from here?

Security Wise Delivery Percentage analysis to separate good stocks from risky once

More insights on Security Wise Delivery Position

 

Disclaimer* - The data on this page comes from what we have in our database and is not complete plus there might be inaccuracy in the numbers shown in the tables and charts above. So use this data for analysis purpose only and do not treat it as any recommendation to invest. Also do a second level check for data accuracy from direct sources like NSE and BSE.

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