Systems and methods for corporate share buyback

Abstract

Systems, methods and computer program products enable companies to consistently repurchase corporate stock at a price below the industry-standard Volume Weighted Average Pricing (VWAP). Historical trade data is analyzed to identify prior prime purchasing opportunities that are used in determining a baseline. During each trading period, as a favorable purchasing opportunity arises, the amount of corporate stock to be purchased is adjusted based upon the strength of the current pricing when compared to the baseline. That is, when the current pricing is identified as being highly favorable, more shares of corporate stock are purchased. Accordingly, this dynamic purchasing scheme allows companies to consistently repurchase corporate stock at favorable prices.

1 . A method, comprising:
 determining that a current Volume Weighted Average Price (VWAP) of a current trading period for a stock is greater than a last closing price of the current trading period for the stock;   calculating a purchase strength factor by dividing a mathematical difference between the current VWAP and the last closing price by a weighting factor, wherein the weighting factor is determined by averaging a number of largest historical gap values identified from a plurality of historical trading periods for the stock, wherein each of the number of historical gap values represents a respective mathematical difference between a respective average stock price and a respective last closing price for a respective historical trading period for the stock;   multiplying the purchase strength factor and a predetermined number of shares to determine a buyback number of shares of the stock; and   generating a buy indication based upon the buyback number of shares of the stock,   wherein the prior steps are performed by a computer associated with an electronic trading system.   
   
   
       2 . The method of  claim 1 , wherein the respective average stock price is a respective volume weighted average price. 
   
   
       3 . The method of  claim 1 , wherein the number of largest historical gap values are identified based upon a comparison of historical gap values for all historical trading periods within a historical trading window of time. 
   
   
       4 . The method of  claim 3 , wherein the historical trading window of time ranges between 20 and 60 days. 
   
   
       5 . The method of  claim 3 , wherein the historical trading window of time ends prior to a beginning of the current trading period. 
   
   
       6 . The method of  claim 1 , wherein the predetermined number of shares is a pro-rated number of the total number of shares to be purchased. 
   
   
       7 . The method of  claim 6 , wherein the pro-rated number of shares is determined by dividing the total number of shares to be purchased by an available number of trading periods during which the total number of shares can be purchased. 
   
   
       8 . The method of  claim 1 , wherein the current trading period is less than a single day. 
   
   
       9 . The method of  claim 1 , wherein the current trading period and each of the plurality of historical trading periods have a same duration. 
   
   
       10 . The method of  claim 1 , wherein generating the buy indication comprises automatically directing a buy order for purchasing the buyback number of shares. 
   
   
       11 . A system, comprising:
 a memory for storing computer-program instructions;   a processor in communications with the memory, wherein the processor is configured to execute the computer-program instructions to:
 determine that a current Volume Weighted Average Price (VWAP) of a current trading period for a stock is greater than a last closing price of the current trading period for the stock; 
 calculate a purchase strength factor by dividing a mathematical difference between the current VWAP and the last closing price by a weighting factor, wherein the weighting factor is determined by averaging a number of largest historical gap values identified from a plurality of historical trading periods for the stock, wherein each of the number of historical gap values represents a respective mathematical difference between a respective average stock price and a respective last closing price for a respective historical trading period for the stock; 
 multiply the purchase strength factor and a predetermined number of shares to determine a buyback number of shares of the stock; and 
 generate a buy indication based upon the buyback number of shares of the stock. 
   
   
   
       12 . The system of  claim 11 , wherein the respective average stock price is a respective volume weighted average price. 
   
   
       13 . The system of  claim 11 , wherein the number of largest historical gap values are identified based upon a comparison of historical gap values for all historical trading periods within a historical trading window of time. 
   
   
       14 . The system of  claim 13 , wherein the historical trading window of time ranges between 20 and 60 days. 
   
   
       15 . The system of  claim 13 , wherein the historical trading window of time ends prior to a beginning of the current trading period. 
   
   
       16 . The system of  claim 11 , wherein the predetermined number of shares is a pro-rated number of the total number of shares to be purchased. 
   
   
       17 . The system of  claim 16 , wherein the pro-rated number of shares is determined by dividing the total number of shares to be purchased by an available number of trading periods during which the total number of shares can be purchased. 
   
   
       18 . The system of  claim 11 , wherein the current trading period is less than a single day. 
   
   
       19 . The system of  claim 11 , wherein the current trading period and each of the plurality of historical trading periods have a same duration. 
   
   
       20 . The system of  claim 11 , wherein the processor is configured to generate the buy indication by automatically directing a buy order for purchasing the buyback number of shares.