5 results about "Price fluctuation" patented technology

The invention belongs to a price determination method, and provides a method for determining upper and lower limits of contract price fluctuation of a power market and a related device, aiming at the technical problems that a price limit mechanism for setting fixed upper and lower limits of prices is adopted in the current power transaction, a price discovery suppression function exists, and violent price swing within a day cannot be effectively coped with. Calculating a positive excess sample and / or a negative excess sample, then taking the positive excess sample and / or the negative excess sample as input, and obtaining a morphological parameter and a scale parameter when a log-likelihood value of the positive excess sample and / or a log-likelihood value of the negative excess sample converges through generalized Pareto distribution iterative calculation; and finally, positive tail risk measurement index expected loss and / or negative tail risk measurement index expected loss are / is obtained through calculation and serve as an upper limit and a lower limit of contract price fluctuation of the electricity market. And the technical problem of violent price swing within the day can be effectively solved.

The system according to this embodiment aims to maximize sales and profits by responding to fluctuations in demand and price changes by competitors. [Solution] The system according to the embodiment comprises a data collection unit, an analysis unit, a pricing unit, a monitoring unit, and an adjustment unit. The data collection unit collects sales data, competitor data, and market trends. The analysis unit analyzes the data collected by the data collection unit. The pricing unit sets prices based on the analysis results obtained by the analysis unit. The monitoring unit adjusts the prices set by the pricing unit in accordance with price fluctuations of competitors. The adjustment unit further adjusts the prices adjusted by the monitoring unit based on market seasonality and trends.

We provide the system. [Solution] Means of obtaining market information, A means of analyzing acquired market information to predict price fluctuations, Based on the analysis results, a means to automate the buying and selling of assets, A means of generating personalized suggestions through interaction with the user, A means of regularly reporting on the user's investment performance, A means of proposing ways to optimize consumer behavior based on feedback on investment results, A system that includes this.

We provide the system. [Solution] Information gathering means for acquiring energy consumption information, An anomaly detection means that analyzes consumption patterns based on acquired information and detects abnormalities, A pricing plan optimization method that proposes the most suitable pricing plan to the user, A price fluctuation prediction method that predicts future price fluctuations based on market price information, A user terminal that displays the user's energy consumption status in real time and notifies them when an anomaly occurs, A system that includes this.

The invention discloses a bulk commodity price fluctuation prediction system and method based on multi-source heterogeneous data fusion, and belongs to the technical field of data analysis and prediction, and the system comprises a multi-source data collection module which is used for collecting related data corresponding to a target commodity, the related data comprises unstructured data, related information is obtained from the unstructured data, and the unstructured data is stored in a database; the related information comprises the transaction information and the transaction party associated with the transaction information. According to the method, multi-source heterogeneous data is comprehensively collected, the influence range of transaction information is finely distinguished, key features such as inventory, production planning and sales plans of a transaction party are deeply extracted, and data fusion and dynamic prediction analysis are combined, so that the accuracy, timeliness and practicability of price fluctuation prediction of bulk commodities are improved, and the method is suitable for popularization and application. Therefore, decision making of enterprises is effectively supported, market adaptability is enhanced, and market risks are reduced.