An efficient algorithm for temporal financial information monitoring

The web contains a huge amount of real-time financial information related to currency exchange, interest rates, commodity prices, and stock markets in addition to more information regarding relevant information such as organizations´ balance sheets, market shares, and history of their performance. Temporal financial monitoring basically help observe/store financial information to be processed based on pre-defined temporal conditions. Specific actions are performed whenever these conditions are met. An example of temporal conditions is online monitoring for a financial value´s increase or decrease by a certain amount within a specified time period. This financial value could be the price of a particular stock, oil price, gold price, or any other real-time financial value. Such approach requires storing large amounts of data over some extended period of time until the conditions are met. This paper develops an efficient storage algorithm for temporal financial monitoring. The algorithm preprocesses retrieved data based on the specified condition and stores only the data relevant to the condition. This reduces the amount of storage needed for this kind of monitoring and it provides fast financial monitoring.