WO2019095569A1 - Procédé d'analyse financière basé sur un événement financier et économique sur un microblogue, serveur d'applications, et support de stockage lisible par ordinateur - Google Patents

Procédé d'analyse financière basé sur un événement financier et économique sur un microblogue, serveur d'applications, et support de stockage lisible par ordinateur Download PDF

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Publication number
WO2019095569A1
WO2019095569A1 PCT/CN2018/076130 CN2018076130W WO2019095569A1 WO 2019095569 A1 WO2019095569 A1 WO 2019095569A1 CN 2018076130 W CN2018076130 W CN 2018076130W WO 2019095569 A1 WO2019095569 A1 WO 2019095569A1
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financial
microblog
event
hotspot
data stream
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PCT/CN2018/076130
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English (en)
Chinese (zh)
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王健宗
吴天博
黄章成
肖京
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平安科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/06—Asset management; Financial planning or analysis

Definitions

  • the present application relates to the field of financial data, and in particular, to a financial analysis method, an application server, and a computer readable storage medium based on a microblog financial event.
  • the financial sector As far as the financial sector is concerned, it mainly includes two aspects: on the one hand, asset prices are not affected by small factors as they were 30 years ago, but are affected by a combination of factors. On the other hand, when there are more and more relevant factors affecting assets, how to identify the correlation and causality behind the incident becomes more difficult.
  • the judgment of the general investors on financial investment is mainly based on personal investment experience and a perceptual judgment on various current financial events, but this method requires long-term investment experience and certain professional knowledge. For ordinary investors, there are still great difficulties and uncertainties in judging valuable information from a large number of financial events.
  • the present application proposes a financial analysis method, an application server and a computer readable storage medium based on the microblog financial event, which can conveniently, quickly and intuitively find current stock market data and finance in the hot and hot financial events.
  • Transaction data affects large financial and hot events, which in turn provides direct and effective reference for investors.
  • the present application provides an application server, where the application server includes a memory and a processor, where the memory stores a financial analysis program based on a Weibo financial event that can be run on the processor.
  • the financial analysis program based on the Weibo financial event is executed by the processor, the following steps are implemented:
  • the impact index is visualized.
  • the present application further provides a financial analysis method based on a microblog financial event, the method is applied to an application server, and the method includes:
  • the impact index is visualized.
  • the present application further provides a computer readable storage medium storing a financial analysis program based on a microblogging financial event, the financial analysis program based on a microblog financial event
  • the step of performing, by the at least one processor, the financial analysis method based on the Weibo financial event as described above may be performed by at least one processor.
  • the application server, the financial analysis method based on the microblog financial event, and the computer readable storage medium proposed by the present application first establish a financial microblog account pool, according to the financial microblog account pool. Obtaining a microblog data stream; secondly, obtaining a financial hotspot event according to the microblog data stream; then, constructing a model of the impact of the financial hotspot event on the stock market and the financial; and then, according to the obtained financial hotspot event and the impact The model analyzes the impact index of the financial hotspot event on the stock market and finance; finally, the impact index is visualized.
  • 1 is a schematic diagram of an optional hardware architecture of an application server of the present application
  • FIG. 2 is a program module diagram of a first embodiment of a financial analysis program based on a Weibo financial event according to the present application
  • FIG. 3 is a flowchart of a microblog hot topic discovery algorithm based on “acceleration” in a preferred embodiment of the present application
  • FIG. 4 is a flow chart of a first embodiment of a financial analysis method based on a microblogging financial event according to the present application.
  • FIG. 1 it is a schematic diagram of an optional hardware architecture of the application server 1.
  • the application server 1 may be a computing device such as a rack server, a blade server, a tower server, or a rack server.
  • the application server 1 may be a stand-alone server or a server cluster composed of multiple servers.
  • the application server 1 may include, but is not limited to, the memory 11, the processor 12, and the network interface 13 being communicably connected to each other through a system bus.
  • the application server 1 connects to the network through the network interface 13 to obtain information.
  • the network may be an intranet, an Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, or a 5G network.
  • Wireless or wired networks such as networks, Bluetooth, Wi-Fi, and call networks.
  • Figure 1 only shows the application server 1 with components 11-13, but it should be understood that not all illustrated components may be implemented, and more or fewer components may be implemented instead.
  • the memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), and a random access memory (RAM). , static random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like.
  • the memory 11 may be an internal storage unit of the application server 1, such as a hard disk or memory of the application server 1.
  • the memory 11 may also be an external storage device of the application server 1, such as a plug-in hard disk equipped with the application server 1, a smart memory card (SMC), and a secure digital ( Secure Digital, SD) cards, flash cards, etc.
  • the memory 11 can also include both the internal storage unit of the application server 1 and its external storage device.
  • the memory 11 is generally used to store an operating system installed in the application server 1 and various types of application software, such as program code of the financial analysis program 200 based on the Weibo financial event. Further, the memory 11 can also be used to temporarily store various types of data that have been output or are to be output.
  • the processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments.
  • the processor 12 is typically used to control the overall operation of the application server 1, such as performing data interaction or communication related control and processing, and the like.
  • the processor 12 is configured to run program code or process data stored in the memory 11, such as running the financial analysis program 200 based on the microblog financial event.
  • the network interface 13 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the application server 1 and other electronic devices.
  • the application server 1 installs and runs a financial analysis program 200 based on the microblog financial event, and when the financial analysis program 200 based on the microblog financial event runs, the application server 1 establishes a financial class. a microblog account pool, obtaining a microblog data stream according to the financial microblog account pool; obtaining a financial hotspot event according to the microblog data stream; constructing an impact model of the financial hotspot event on the stock market and the financial; The financial hotspot event and the impact model analyze the impact index of the financial hotspot event on the stock market and the financial; and visualize the impact index.
  • the present application proposes a financial analysis program 200 based on Weibo financial events.
  • FIG. 2 it is a program module diagram of the first embodiment of the financial analysis program 200 based on the Weibo financial event.
  • the financial analysis program 200 based on the Weibo financial event includes a series of computer program instructions stored in the memory 11, and when the computer program instructions are executed by the processor 12, the implementation of the present application can be implemented.
  • the financial analysis program 200 based on the Weibo financial event may be divided into one or more modules based on the particular operations implemented by the various portions of the computer program instructions.
  • the financial analysis program 200 based on the microblog financial event may be divided into an establishing module 201, an obtaining module 202, a model building module 203, an analyzing module 204, and a display module 205. among them:
  • the establishing module 201 is configured to establish a financial microblog account pool. Specifically, the establishing module 201 is configured to extract a predetermined number of target accounts from a full amount of microblog accounts to establish the financial microblog account pool according to a preset extraction policy, where the full amount of microblog accounts refer to the application. All the microblog accounts monitored by the server 1, for example, the application server 1 monitors about 200,000 microblog accounts, and then extracts the full amount of microblog accounts according to the account extraction conditions and the extraction policy, wherein the so-called account extraction conditions and extraction
  • the policy may be a keyword policy, which refers to a preset financial keyword.
  • the establishing module 201 determines, according to the brief description of the microblog account, whether there is a preset financial keyword, and if so, the microblog account is included in the financial microblog account pool. In addition, the establishing module 201 can also search by using a preset microblog account list, for example, a person related to the financial industry, that is, directly inserting the microblog account of the relevant financial person into the financial microblog account pool.
  • a preset microblog account list for example, a person related to the financial industry, that is, directly inserting the microblog account of the relevant financial person into the financial microblog account pool.
  • the establishing module 202 is further configured to preset the update time of the financial microblog account pool. Then, the full amount of microblog accounts are extracted again according to the update time to update the financial class microblog account pool. For example, the establishing module 202 presets the financial microblog account pool to be updated once every 10 minutes.
  • the specific update time is set by the administrator according to the needs, and the application is not limited. In this embodiment, due to the real-time changing characteristics of the financial information, the accuracy and timeliness of the data transmitted by the established financial microblog account pool can be ensured by periodically updating the above-mentioned financial microblog account pool.
  • the obtaining module 202 is configured to obtain a microblog data stream according to the financial microblog account pool established by the establishing module 201, and obtain a financial hotspot event according to the microblog data stream.
  • the obtaining module 202 acquires a financial hotspot event from the microblog data stream based on a preset microblog hot topic discovery algorithm. For example, the "acceleration" of the microblog hot topic discovery algorithm.
  • FIG. 3 is a flowchart of a microblog hot topic discovery algorithm based on “acceleration”.
  • S"(t) is used as an indicator to measure the acceleration of the total microblog data stream, that is, the acceleration of the overall microblog stream;
  • X"(t) is used as an indicator to measure the acceleration of the first-order word frequency microblog data stream.
  • the first-order word frequency refers to the frequency of occurrence of a single word; Y"(t) is used as an index to measure the acceleration of the second-order word frequency microblog data stream, the second-order word frequency refers to the frequency at which two words appear simultaneously; the "gray box” is a sparse matrix non- The part of zero value, that is, the non-zero value part after word vectorization; the first-order word frequency of X"(t) is a vector, and the second-order word frequency of Y"(t) is a matrix.
  • Step (1) is to collect the microblog data and vectorize the representation to obtain S"(t).
  • Step (2) is to calculate the acceleration X"(t) of the first-order word frequency and the acceleration Y"(t) of the second-order word frequency.
  • Step (3) is to monitor and update the data stream in real time based on the results of the previous operation.
  • Step (4) is the notification and the summation is performed.
  • Step (5) is to output the result of the discovered hot event stream.
  • the topic of the word with the highest X"(t) and Y"(t) is a hot topic.
  • the model building module 203 is configured to construct an impact model of the financial hotspot event on the stock market and the financial.
  • model building module 203 constructs an impact model of the financial hotspot event on the stock market and the finance by:
  • the model building module 203 firstly acquires a large number of historical financial hotspot events, simultaneously acquires stock market data and financial transaction data at the same time as the historical financial hotspot event, and then compares the historical financial hotspot events with the stock market data and financial transactions.
  • the data is trained to obtain a functional relationship between the historical financial hotspot event and the stock market data and financial transaction data, and finally the impact model is constructed according to the function relationship.
  • the analyzing module 204 is configured to analyze an impact index of the financial hotspot event on the stock market and the financial according to the financial hotspot event acquired by the obtaining module 202 and the impact model constructed by the model building module 203.
  • the impact model has been determined through the above steps, and the financial hotspot event is imported into the impact model, thereby outputting an intuitive impact index.
  • the current financial hotspot event is that the central bank has lowered the deposit reserve ratio.
  • the hotspots are introduced into the above-mentioned impact model.
  • the deposit reserve ratio is lowered, the funds in the market are relatively more substantial, and investment activities are more accessible.
  • the impact model will output an estimated stock market upside index, such as how many points are expected to go up.
  • the display module 205 is configured to visualize the impact index obtained by the analysis module 204. Specifically, the impact index is visualized in the terminal device.
  • the terminal device may be a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, and a vehicle.
  • a mobile device such as a device, and a fixed terminal such as a digital TV, a desktop computer, a notebook, a server, and the like.
  • the financial analysis program 200 based on the microblog financial event proposed by the present application firstly establishes a financial microblog account pool, and obtains a microblog data stream according to the financial microblog account pool; Obtaining a financial hotspot event according to the microblog data stream; then, constructing an impact model of the financial hotspot event on the stock market and the financial; and then analyzing the financial hotspot event according to the obtained financial hotspot event and the impact model The impact index on the stock market and finance; finally, the impact index is visualized.
  • the present application also proposes a financial analysis method based on Weibo financial events.
  • FIG. 4 it is a flowchart of the first embodiment of the financial analysis method based on the Weibo financial event of the present application.
  • the order of execution of the steps in the flowchart shown in FIG. 4 may be changed according to different requirements, and some steps may be omitted.
  • Step S401 establishing a financial microblog account pool.
  • the financial account type microblog account pool is established by extracting a preset number of target accounts from the full amount of microblog accounts according to a preset extraction policy, where the full amount of microblog accounts refers to all monitored by the application server 1
  • the microblog account for example, the application server 1 monitors about 200,000 microblog accounts, and then extracts the full amount of microblog accounts according to the account extraction conditions and the extraction policy, wherein the so-called account extraction conditions and extraction policies may be keywords.
  • Policy the keyword policy refers to a preset financial keyword.
  • the application server 1 determines whether there is a preset financial keyword according to the brief description of the microblog account, and if so, the microblog account is included in the financial microblog account pool.
  • the application server 1 can also search through a preset microblog account list, for example, a person related to the financial industry, that is, directly insert the microblog account of the relevant financial person into the financial microblog account pool.
  • the application server 1 is further configured to preset the update time of the financial microblog account pool. Then, the full amount of microblog accounts are extracted again according to the update time to update the financial class microblog account pool. For example, the application server 1 presets the financial class microblog account pool to be updated once every 10 minutes.
  • the specific update time is set by the administrator according to the needs, and the application is not limited.
  • the accuracy and timeliness of the data transmitted by the established financial microblog account pool can be ensured by periodically updating the above-mentioned financial microblog account pool.
  • Step S402 Acquire a microblog data stream according to the financial microblog account pool, and obtain a financial hotspot event according to the microblog data stream.
  • the application server 1 acquires a financial hotspot event from the microblog data stream based on a preset microblog hot topic discovery algorithm. For example, the "acceleration" of the microblog hot topic discovery algorithm.
  • FIG. 3 is a flowchart of a microblog hot topic discovery algorithm based on “acceleration”.
  • S"(t) is used as an indicator to measure the acceleration of the total microblog data stream, that is, the acceleration of the overall microblog stream;
  • X"(t) is used as an indicator to measure the acceleration of the first-order word frequency microblog data stream.
  • the first-order word frequency refers to the frequency of occurrence of a single word; Y"(t) is used as an index to measure the acceleration of the second-order word frequency microblog data stream, the second-order word frequency refers to the frequency at which two words appear simultaneously; the "gray box” is a sparse matrix non- The part of zero value, that is, the non-zero value part after word vectorization; the first-order word frequency of X"(t) is a vector, and the second-order word frequency of Y"(t) is a matrix.
  • Step (1) is to collect the microblog data and vectorize the representation to obtain S"(t).
  • Step (2) is to calculate the acceleration X"(t) of the first-order word frequency and the acceleration Y"(t) of the second-order word frequency.
  • Step (3) is to monitor and update the data stream in real time based on the results of the previous operation.
  • Step (4) is the notification and the summation is performed.
  • Step (5) is to output the result of the discovered hot event stream.
  • the topic of the word with the highest X"(t) and Y"(t) is a hot topic.
  • Step S403 constructing an impact model of the financial hotspot event on the stock market and the financial.
  • the application server 1 constructs an impact model of the financial hotspot event on the stock market and the finance by:
  • the application server 1 firstly acquires a large number of historical financial hotspot events, and simultaneously acquires stock market data and financial transaction data at the same time as the historical financial hotspot event, and then the historical financial hotspot event and the stock market data and financial transaction data. Performing training to obtain a functional relationship between the historical financial hotspot event and the stock market data and financial transaction data, and finally constructing the impact model according to the function relationship.
  • Step S404 Analyze an impact index of the financial hotspot event on the stock market and the finance according to the obtained financial hot spot event and the impact model.
  • the impact model has been determined through the above steps, and the financial hotspot event is imported into the impact model, thereby outputting an intuitive impact index.
  • the current financial hotspot event is that the central bank has lowered the deposit reserve ratio.
  • the hotspots are introduced into the above-mentioned impact model.
  • the deposit reserve ratio is lowered, the funds in the market are relatively more substantial, and investment activities are more accessible.
  • the impact model will output an estimated stock market upside index, such as how many points are expected to go up.
  • Step S405 visualizing the impact index.
  • the impact index is visualized in the terminal device.
  • the terminal device may be a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, and a vehicle.
  • a mobile device such as a device, and a fixed terminal such as a digital TV, a desktop computer, a notebook, a server, and the like.
  • the financial analysis method based on the microblog financial event proposed by the present application firstly establishes a financial microblog account pool, and obtains a microblog data stream according to the financial microblog account pool; secondly, according to The microblog data stream obtains a financial hotspot event; then, constructs a model of the impact of the financial hotspot event on the stock market and the financial; and then analyzes the financial hotspot event against the stock market according to the obtained financial hotspot event and the impact model And the financial impact index; finally, the impact index is visualized.
  • the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better.
  • Implementation Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

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Abstract

La présente invention concerne un procédé d'analyse financière basé sur un événement financier et économique sur un microblogue. Le procédé comporte les étapes consistant à: explorer des données corrélées d'une société financière cible au moyen d'un collecteur; prétraiter les données corrélées; effectuer une segmentation de texte sur les données corrélées prétraitées pour obtenir un ensemble de textes; analyser l'ensemble de textes pour obtenir un ensemble de thèmes; calculer un ensemble de mots-clés de l'ensemble de textes; sélectionner un mot-clé concordant avec l'ensemble de thèmes à partir de l'ensemble de mots-clés; sélectionner un mot indiquant une anticipation du public concernant la société financière cible, et calculer le degré d'occurrence conjointe du mot d'anticipation et du mot-clé au moyen d'un modèle préétabli; et délivrer une conclusion d'évaluation concernant la société financière cible selon le degré d'occurrence conjointe. La présente invention concerne également un serveur d'applications et un support de stockage lisible par ordinateur. Au moyen du procédé d'analyse de données financières, du serveur d'applications et du support de stockage lisible par ordinateur selon la présente invention, des données d'attitudes fournies par le public à propos de politiques mises en œuvre par la société financière cible peuvent être obtenues rapidement, et le développement d'entreprises apparentées est favorisé.
PCT/CN2018/076130 2017-11-17 2018-02-10 Procédé d'analyse financière basé sur un événement financier et économique sur un microblogue, serveur d'applications, et support de stockage lisible par ordinateur WO2019095569A1 (fr)

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CN110750622A (zh) * 2019-09-17 2020-02-04 南京理工大学 基于大数据的金融事件发现方法
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