Order flow footprint chart generation method and system based on market snapshot, computer device and storage medium

Abstract

This application relates to the field of computers and provides a method, system, computer device, and storage medium for generating an order flow footprint based on market snapshots. The method includes: acquiring real-time market snapshot data; performing transaction direction judgment processing based on the real-time market snapshot data to obtain the transaction direction judgment result corresponding to the real-time market snapshot data; performing volume allocation processing based on the transaction direction judgment result to determine volume allocation data, thereby obtaining an initial order flow footprint; performing bullish / bearish force analysis processing based on the volume allocation data to determine the indicator analysis result of the bullish / bearish force analysis indicator; and displaying the indicator analysis result in the initial order flow footprint to generate a target order flow footprint. The implementation of this method improves the computational efficiency and real-time performance of the data, and enhances the effectiveness of data analysis.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, system, computer device, and storage medium for generating order flow footprint graphs based on market data snapshots. Background Technology

[0002] In the process of analyzing market data, it is necessary to have a deeper understanding of the microstructure of the data. Traditional candlestick charts can only display basic information and cannot intuitively reflect micro information such as the balance of power between buyers and sellers in the market.

[0003] In existing technologies, transaction-by-transaction data is analyzed manually to reveal its microstructure. However, current analytical methods typically require processing large amounts of transaction data, resulting in low computational efficiency and real-time performance, leading to poor performance in market data analysis. Summary of the Invention

[0004] This application provides a method, system, computer device, and storage medium for generating order flow footprints based on market data snapshots. More specifically, this application provides a method, system, computer device, computer storage medium, and computer program product for generating order flow footprints based on market data snapshots, which improves the efficiency and real-time performance of data computation and enhances the effectiveness of data analysis.

[0005] In a first aspect, embodiments of this application provide a method for generating an order flow footprint graph based on market data snapshots, including:

[0006] Get real-time market snapshot data;

[0007] The trading direction is determined based on the real-time market snapshot data to obtain the trading direction determination result corresponding to the real-time market snapshot data.

[0008] Based on the transaction direction judgment result, the transaction volume is allocated to determine the transaction volume allocation data in order to obtain the initial order flow footprint map;

[0009] Based on the transaction volume distribution data, a bullish-bearish force analysis is performed to determine the indicator analysis results of the bullish-bearish force analysis indicators.

[0010] The results of the indicator analysis are displayed in the initial order flow footprint map to generate the target order flow footprint map.

[0011] Optionally, in some embodiments of this application, obtaining real-time market snapshot data includes:

[0012] Obtain preset interface connection data and update cycle data for real-time updates;

[0013] Based on the update rules represented by the update cycle data, the data is updated in real time through the interface representing the data in the data to obtain the real-time market snapshot data.

[0014] Optionally, in some embodiments of this application, the step of performing transaction volume allocation processing based on the transaction direction determination result to determine transaction volume allocation data in order to obtain an initial order flow footprint map includes:

[0015] If the transaction direction determination result is the first direction, the first transaction volume data is generated on the first display side;

[0016] If the transaction direction determination result is the second direction, second transaction volume data is generated on the second display side;

[0017] The initial order flow footprint is determined based on the first transaction volume data on the first display side and the second transaction volume data on the second display side.

[0018] Optionally, in some embodiments of this application, the step of performing bullish / bearish force analysis processing based on the trading volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes:

[0019] The net trading volume is calculated based on the trading volume allocation data.

[0020] The analysis results of the indicator are determined based on the net trading volume value.

[0021] Optionally, in some embodiments of this application, the step of performing bullish / bearish force analysis processing based on the trading volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes:

[0022] Based on the transaction volume allocation data, adjacent transaction identification processing is performed to obtain adjacent transaction identification results;

[0023] The indicator analysis results are determined based on the adjacent transaction identification results.

[0024] Optionally, in some embodiments of this application, the step of performing bullish / bearish force analysis processing based on the trading volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes:

[0025] Based on the results of adjacent transaction identification, a short-selling imbalance judgment is performed to obtain the short-selling imbalance judgment result;

[0026] Based on the results of adjacent transaction identification, a multi-party imbalance judgment is performed to obtain the multi-party imbalance judgment result;

[0027] The index analysis results are determined based on the results of the short-side imbalance judgment and the results of the long-side imbalance judgment.

[0028] Optionally, in some embodiments of this application, the step of performing bullish / bearish force analysis processing based on the trading volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes:

[0029] Based on the short-side imbalance judgment result, short-side accumulation zone identification processing is performed to obtain the short-side accumulation zone identification result;

[0030] Based on the results of the multi-party imbalance judgment, multi-head accumulation zone identification processing is performed to obtain the multi-head accumulation zone identification result.

[0031] The index analysis results are determined based on the identification results of the empty accumulation zone and the identification results of the multi-head accumulation zone.

[0032] Secondly, embodiments of this application provide an order flow footprint generation system based on market data snapshots, which has the functionality to implement the order flow footprint generation method based on market data snapshots provided in the first aspect above. This functionality can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described functionality, and these modules can be software and / or hardware.

[0033] In one possible design, the system includes:

[0034] The data acquisition module is used to acquire real-time market snapshot data;

[0035] The trading direction determination module is used to perform trading direction determination processing based on the real-time market snapshot data, and obtain the trading direction determination result corresponding to the real-time market snapshot data.

[0036] The initial order flow footprint generation module is used to perform transaction volume allocation processing based on the transaction direction judgment result, determine the transaction volume allocation data, and obtain the initial order flow footprint.

[0037] The bullish and bearish force analysis module is used to perform bullish and bearish force analysis processing based on the trading volume allocation data, and determine the indicator analysis results of the bullish and bearish force analysis indicators.

[0038] The results display module is used to display the indicator analysis results in the initial order flow footprint map to generate the target order flow footprint map.

[0039] In another aspect, this application provides a computer device including at least one connected processor and a memory, wherein the memory is used to store program code, and the processor is used to call the program code in the memory to execute the methods described in the above aspects.

[0040] In another aspect, this application provides a computer storage medium including instructions that, when executed on a computer, cause the computer to perform the methods described in the above aspects.

[0041] In another aspect, this application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the methods described in the above aspects.

[0042] Compared to traditional technologies, the technical solution of this application embodiment does not require processing a large amount of transaction data, has high computational efficiency, and can generate order flow footprints in real time; based on a visualization method, it intuitively displays the microstructure of the market, and can identify important information such as the balance of power between bulls and bears, bullish accumulation zones and bearish accumulation zones, providing strong support for users' decision-making, thereby improving the overall computational efficiency and real-time performance of the data, and improving the effect of data analysis. Attached Figure Description

[0043] Figure 1 This is an application environment diagram for one embodiment.

[0044] Figure 2 This is a flowchart of one embodiment.

[0045] Figure 3 This is a flowchart of a method in one embodiment.

[0046] Figure 4 This is an interactive flowchart in one embodiment.

[0047] Figure 5 This is a diagram illustrating the order flow in one embodiment.

[0048] Figure 6 This is a structural block diagram of a system in one embodiment.

[0049] Figure 7 This is a system flowchart of one embodiment.

[0050] Figure 8 This is a system block diagram of one embodiment.

[0051] Figure 9 This is an internal structural diagram of a computer device in one embodiment.

[0052] Figure 10 This is a diagram of the internal structure of a computer device in another embodiment. Detailed Implementation

[0053] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. The division of modules appearing in the embodiments of this application is only a logical division. In actual applications, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interface, and the indirect coupling or communication connection between modules may be electrical or other similar forms. None of these are limited in the embodiments of this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed among multiple circuit modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of this application.

[0054] Figure 1 As an application environment diagram in one embodiment, this application provides a method for generating an order flow footprint diagram based on market data snapshots, which can be applied to, for example... Figure 1 In the application scenario shown, terminal 102 communicates with server 104 via a network.

[0055] The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0056] It should be noted that the terminal 102 involved in the embodiments of this application can be a wired terminal or a wireless terminal, and can be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connectivity, or other processing devices connected to a wireless modem. The wireless terminal can communicate with one or more core networks via a wireless access network, and the wireless terminal can be a mobile terminal, such as a mobile phone or a computer with a mobile terminal.

[0057] Figure 2 This is a flowchart illustrating one embodiment, such as... Figure 2As shown in the embodiment of this application, the method for generating an order flow footprint based on market data snapshots includes:

[0058] S1000: Obtain real-time market snapshot data.

[0059] Real-time market snapshot data refers to market quotes and transaction information at a specific moment. For example, real-time market snapshot data includes transaction information such as the latest price, the last best bid price, the last best ask price, and the transaction volume.

[0060] S2000 performs trading direction determination based on real-time market snapshot data, and obtains the trading direction determination result corresponding to the real-time market snapshot data.

[0061] Among them, the trading direction refers to the main buying and selling direction, and the trading direction judgment and processing refers to the analysis process of determining whether the transaction is mainly buying or mainly selling; the trading direction judgment result includes the judgment conclusion of main buying, main selling, or equal distribution.

[0062] For example, step S2000 can also be described as: determining the current main buy and main sell direction based on the main buy and main sell direction rules.

[0063] S3000 performs transaction volume allocation processing based on the transaction direction judgment result, determines the transaction volume allocation data, and obtains the initial order flow footprint map.

[0064] Among them, the transaction volume allocation process refers to the operation of allocating transaction volume to the corresponding display side according to direction.

[0065] Among them, the volume allocation data refers to the volume information on the left and right sides after the direction is divided. For example, the main buying volume is allocated to the right half of the candlestick chart, and the main selling volume is allocated to the left half of the candlestick chart.

[0066] The initial order flow footprint map refers to a basic visualization map without superimposed analysis indicators, which can be composed of transaction volume allocation data.

[0067] For example, step S3000 can also be described as: based on the judgment result of the main buying and main selling directions, the main buying volume is allocated to the right half of the K-line chart, and the main selling volume is allocated to the left half of the K-line chart, forming an initial order flow footprint chart.

[0068] S4000, based on the trading volume distribution data, performs bullish and bearish force analysis to determine the indicator analysis results of the bullish and bearish force analysis.

[0069] Among them, the analysis of bullish and bearish forces refers to the analytical operation of calculating and identifying the strength of bullish and bearish forces; the indicators of bullish and bearish forces refer to the various indicators used to characterize the strength of bullish and bearish forces; and the results of the indicator analysis refer to the conclusions drawn from the analysis of bullish and bearish forces.

[0070] For example, step S4000 can also be described as: calculating the delta value, identifying adjacent transactions, determining short-side imbalance, long-side imbalance, long-side accumulation zone, and short-side accumulation zone.

[0071] S5000 displays the results of indicator analysis in the initial order flow footprint map to generate the target order flow footprint map.

[0072] Among them, the target order flow footprint map refers to the final visualization map after overlaying all indicators.

[0073] For example, step S4000 can also be described as: displaying the analysis results in the form of an order flow footprint diagram.

[0074] Compared to traditional technologies, this embodiment first acquires real-time market snapshot data, then performs trading direction judgment processing to obtain the trading direction judgment result corresponding to the real-time market snapshot data, and then performs volume allocation processing to obtain an initial order flow footprint map. Next, it performs bullish / bearish strength analysis processing to determine the indicator analysis results, and finally displays the indicator analysis results in the initial order flow footprint map to generate a target order flow footprint map. The technical solution of this embodiment does not require processing large amounts of individual transaction data, has high computational efficiency, and can generate order flow footprint maps in real time. Based on a visual approach, it intuitively displays the market microstructure, can identify important information such as the comparison of bullish and bearish forces, bullish accumulation zones, and bearish accumulation zones, providing strong support for user decision-making, thereby improving the overall computational efficiency and real-time performance of the data and enhancing the effectiveness of data analysis.

[0075] Optionally, in some embodiments of this application, obtaining real-time market snapshot data includes: obtaining preset interface connection data and update cycle data for real-time updates; and performing real-time updates through the data interfaces represented in the interface connection data based on the update rules represented by the update cycle data to obtain real-time market snapshot data.

[0076] The preset interface connection data refers to the configuration information used to connect to market data sources, and the data interface it represents is the API connection interface.

[0077] The update cycle data refers to the set data refresh interval. The data refresh interval represented by the update cycle data can be the data period of the K-line, including commonly used periods such as 1 minute, 5 minutes, 30 minutes, 1 hour, and 1 day.

[0078] Among them, the update rules for the updated periodic data representation refer to the execution specifications for automatically refreshing data on a periodic basis.

[0079] In this embodiment, the real-time nature of data is ensured, the stability of system operation is improved, and the data acquisition delay is reduced by using a preset interface and periodic updates.

[0080] In another embodiment, in step S2000, the rules for determining the main buy and main sell directions corresponding to the transaction direction determination process include: if the latest price is less than or equal to the previous best bid price, the transaction direction determination result is a main sell direction; if the latest price is greater than or equal to the previous best ask price, the transaction direction determination result is a main buy direction; if the above situations do not apply (for example, the latest price is greater than the previous best bid price and the latest price is less than the previous best ask price), the transaction direction determination result is that the transaction volume of the main buy and main sell directions is equally divided.

[0081] Optionally, in some embodiments of this application, the transaction volume allocation process is performed based on the transaction direction judgment result to determine the transaction volume allocation data in order to obtain an initial order flow footprint map, including: generating first transaction volume data on the first display side when the transaction direction judgment result is a first direction; generating second transaction volume data on the second display side when the transaction direction judgment result is a second direction; and determining the initial order flow footprint map based on the first transaction volume data on the first display side and the second transaction volume data on the second display side.

[0082] Among them, the first direction is the main buying direction; the first display side refers to the position where the trading volume is displayed corresponding to the main buying direction, such as the right side, which is the right half of the K-line chart; the first trading volume data refers to the main buying trading volume.

[0083] Among them, the second direction is the main selling direction; the second display side refers to the position where the transaction volume is displayed corresponding to the main selling direction, such as the left side, that is, the left half of the K-line chart; the second transaction volume data refers to the main selling transaction volume.

[0084] In addition, the first direction can also be the main selling direction, in which case the second direction is the main buying direction; the first direction and the second direction, the first display side and the second display side, the first transaction volume data and the second transaction volume data can be flexibly adjusted according to the actual situation of the scheme, as long as the data correspondence is clear, and the example in this embodiment should not be construed as a limitation on the technical solution of this application.

[0085] For example, the main buying volume is allocated to the right half of the candlestick chart, and the main selling volume is allocated to the left half of the candlestick chart, forming an initial order flow footprint chart.

[0086] In this embodiment, transaction volume data is generated separately for each direction and side, which simplifies the drawing logic, improves the efficiency of visualization generation, and enhances the display effect.

[0087] In another embodiment, in step S3000, the trading volume allocation is performed based on the trading direction judgment result to determine the trading volume allocation data and obtain the initial order flow footprint diagram. Specifically, this includes: arranging the real-time market snapshot data in chronological order to obtain a time axis; dividing the transaction prices in the real-time market snapshot data into price ranges to form a price axis; determining the trading volume allocation data for each point in time based on the trading direction judgment result, the trading volume allocation data including the main buying volume and the main selling volume; allocating the main buying volume to the right half of the K-line chart of the corresponding price in the trading data, and allocating the main selling volume to the left half of the K-line chart of the corresponding price in the trading data; and displaying the allocated trading volume allocation data in different colors or shapes according to the price-time coordinate system formed by the time axis and the price axis to form the initial order flow footprint diagram.

[0088] Optionally, in some embodiments of this application, the analysis of bullish and bearish forces is performed based on the trading volume allocation data to determine the indicator analysis results of the bullish and bearish forces analysis indicators, including: calculating the net trading volume value based on the trading volume allocation data; and determining the indicator analysis results based on the net trading volume value.

[0089] The net trading volume, also known as the delta value, refers to the difference between the total volume of main buy orders and the total volume of main sell orders, which is the sum of the main buy volume and the sum of the main sell volume in the K-line chart.

[0090] In this embodiment, the net trading volume is calculated to intuitively reflect the strength of the bulls and bears, improving analysis efficiency and enhancing the accuracy of trend judgment.

[0091] Optionally, in some embodiments of this application, the analysis of bullish and bearish forces is performed based on the trading volume allocation data to determine the indicator analysis results of the bullish and bearish forces analysis indicators, including: performing adjacent transaction identification processing based on the trading volume allocation data to obtain adjacent transaction identification results; and determining the indicator analysis results based on the adjacent transaction identification results.

[0092] Among them, the adjacent transaction identification process refers to the operation of identifying the corresponding transaction positions diagonally opposite each other; the adjacent transaction identification result refers to the position data of the adjacent transactions obtained.

[0093] For example, adjacent transactions mean the adjacent transactions formed by the main seller position on the left and the main buyer position on the right diagonally opposite the K-line of the order flow footprint chart.

[0094] In this embodiment, by identifying adjacent transactions, a basis for subsequent analysis is provided, which improves the accuracy of the analysis and enhances the ability to analyze microstructures.

[0095] Optionally, in some embodiments of this application, the analysis of long and short forces is performed based on the transaction volume allocation data to determine the indicator analysis results of the long and short force analysis indicators, including: performing short-side imbalance judgment processing based on the adjacent transaction identification results to obtain the short-side imbalance judgment result; performing long-side imbalance judgment processing based on the adjacent transaction identification results to obtain the long-side imbalance judgment result; and determining the indicator analysis results based on the short-side imbalance judgment results and the long-side imbalance judgment results.

[0096] Among them, the judgment and processing of short-selling imbalance refers to the analysis that the short-selling volume is significantly greater than the long-selling volume; the judgment result of short-selling imbalance refers to the conclusion of whether short-selling imbalance has occurred.

[0097] For example, if the volume of transactions by the main seller is more than three times the volume of transactions by the main buyer, the result of the short-selling imbalance judgment is "judged as short-selling imbalance".

[0098] Among them, the judgment and processing of multi-party imbalance refers to the analysis that judges the multi-party quantity to be significantly greater than the short-party quantity; the judgment result of multi-party imbalance refers to the conclusion of whether multi-party imbalance has occurred.

[0099] For example, if the volume of transactions by the main buyer is more than three times the volume of transactions by the main seller, the result of the judgment of imbalance of the multiple parties is "judged as imbalance of the multiple parties".

[0100] In this embodiment, the imbalance between buyers and sellers is determined by adjacent transactions, which improves the reliability of the signal and enhances the effectiveness of the analysis.

[0101] Optionally, in some embodiments of this application, the analysis of bullish and bearish forces is performed based on the trading volume allocation data to determine the indicator analysis results of the bullish and bearish forces analysis indicators, including: based on the bearish imbalance judgment result, the bearish accumulation band identification process is performed to obtain the bearish accumulation band identification result; based on the bullish imbalance judgment result, the bullish accumulation band identification process is performed to obtain the bullish accumulation band identification result; and the indicator analysis results are determined based on the bearish accumulation band identification result and the bullish accumulation band identification result.

[0102] Among them, the short accumulation zone identification process refers to the operation of identifying continuous short-side imbalance areas; the short accumulation zone identification result refers to the conclusion of whether a short accumulation zone has been formed.

[0103] For example, the number of consecutive short-selling imbalances is counted based on the short-selling imbalance judgment results. If the number of consecutive short-selling imbalances is greater than or equal to 3, the short-selling accumulation zone identification result is "formation of short-selling accumulation zone".

[0104] Among them, the multi-head accumulation zone identification process refers to the operation of identifying continuous multi-head imbalance areas; the multi-head accumulation zone identification result refers to the conclusion of whether a multi-head accumulation zone has been formed.

[0105] For example, the number of consecutive imbalances is obtained by statistically analyzing the results of the multi-party imbalance judgment. If the number of consecutive imbalances is greater than or equal to 3, the result of the multi-head accumulation zone identification is "multi-head accumulation zone is formed".

[0106] In this embodiment, key areas are accurately located by identifying multi-hole accumulation zones through continuous imbalance.

[0107] As can be seen from the above embodiments, the analysis results of the bullish and bearish forces analysis indicators include: net trading volume (delta value), adjacent trading identification results, bearish imbalance judgment results, bullish imbalance judgment results, bearish accumulation zone identification results (bearish accumulation zone), and bullish accumulation zone identification results (bullish accumulation zone).

[0108] Accordingly, in step S5000, displaying the indicator analysis results in the initial order flow footprint map to generate the target order flow footprint map includes: adjusting the image of the initial order flow footprint map based on the displayed indicator analysis results to generate the target order flow footprint map. Image adjustment refers to using different colors or shapes to identify different data and displaying different data in specific locations. Specific image adjustment methods can be found in the following embodiments, aiming to clearly display each data item.

[0109] In another embodiment, the method further includes generating trading signals based on the indicator analysis results of the order flow footprint chart. Specifically, this includes: determining a bullish trading signal when a bullish accumulation zone forms or when the price retraces to the bullish accumulation zone; determining a bearish trading signal when a bearish accumulation zone forms or when the price rises to the bearish accumulation zone; determining a bullish trading signal when the price breaks above the bearish accumulation zone; determining a bearish trading signal when the price breaks below the bullish accumulation zone; determining a bullish trading signal when the net trading volume of three consecutive candlesticks is positive; and determining a bearish trading signal when the net trading volume of three consecutive candlesticks is negative.

[0110] In another embodiment, the method further includes: generating transaction suggestion display information based on transaction signals; and updating the target order flow footprint map in real time.

[0111] Among them, the trading advice display information is used to provide users with trading suggestions; the target order flow footprint map is updated in real time to reflect the latest market changes.

[0112] The technical research process and other technical details of this application are described below with reference to a specific embodiment.

[0113] In modern financial markets, investors need a deeper understanding of market microstructures to make more accurate trading decisions. Traditional candlestick charts can only display basic information about price and volume, failing to intuitively reflect micro-level information such as the balance of power between buyers and sellers and the distribution of trading volume.

[0114] To address this challenge, order flow analysis methods have emerged in existing technologies, revealing the microstructure of the market by analyzing individual transaction data. However, existing order flow analysis methods typically require processing large amounts of individual transaction data, are computationally complex, and have poor real-time performance, making it difficult to meet investors' needs for real-time market analysis.

[0115] Furthermore, existing order flow analysis methods lack intuitive visualization methods, making it difficult for investors to quickly understand and apply the analysis results. Therefore, how to quickly and accurately generate intuitive order flow footprint charts based on market snapshot data has become an important research direction in the field of financial market data analysis.

[0116] Based on this, this application provides a method for generating an order flow footprint based on market snapshots, also known as a method for calculating an order flow footprint based on market snapshots, which can be applied to the field of data analysis in financial markets.

[0117] Figure 3 Here is a flowchart of a method in one embodiment. Figure 4 Here is an interaction flowchart for one embodiment, see reference. Figure 3 and Figure 4 The method for generating order flow footprints based on market data snapshots provided in this application specifically includes the following steps.

[0118] Step S1000: Obtain real-time market snapshot data.

[0119] Step S2000: Determine the current main buy and main sell direction based on the main buy and main sell direction rules.

[0120] Step S3000: Based on the results of the main buy and sell direction judgment, allocate the main buy volume to the right half of the K-line chart and the main sell volume to the left half of the K-line chart to form the initial order flow footprint chart.

[0121] Step S4000: Calculate the delta value, identify adjacent transactions, determine short-side imbalance, long-side imbalance, long accumulation zone, and short accumulation zone.

[0122] Step S5000: Display the analysis results in the form of an order flow footprint diagram.

[0123] Step S1000 involves data acquisition, specifically including: connecting via API (such as the Dalian Commodity Exchange's market data API), enabling the system to update data in real time, including market quotes, and candlestick charts for commonly used timeframes such as 1-minute, 5-minute, 30-minute, 1-hour, and daily charts. This ensures the analysis results are always up-to-date and provides multi-period data to promptly reflect market changes.

[0124] In step S2000, the rules for determining the main buying and selling directions include: (1) Selling direction: latest price ≤ last bid price; (2) Buying direction: latest price ≥ last ask price; (3) If the above conditions are not met, the trading volume of the main buying and selling directions is equally distributed.

[0125] By using the rules for determining the primary buy and sell directions, the system can accurately identify the primary buy and sell directions for each transaction, providing a foundation for generating subsequent order flow graphs.

[0126] Step S3000 is the step of generating the order flow footprint diagram. The order flow footprint diagram can intuitively show the balance of power between bulls and bears in the market and help users understand the microstructure of the market.

[0127] In one embodiment, in step S3000, the process of generating the order flow footprint is as follows: (1) Arrange the real-time market snapshot data in chronological order to form a time axis. (2) Divide the transaction prices into price ranges to form a price axis. (3) For each price range at each time point, based on the judgment result of the main buying and selling directions, display the main buying volume on the right side of the corresponding price range and the main selling volume on the left side of the corresponding price range; wherein, the left and right sides can also be interchanged, but usually the main buying is on the right side and the main selling is on the left side. (4) Represent the size of the transaction volume by the color depth or area size to form an intuitive order flow footprint. Wherein, the darker the color and the larger the number, the larger the transaction volume.

[0128] In another embodiment, in step S3000, the process of generating the order flow footprint can also be as follows: (1) Arrange the real-time market snapshot data in chronological order; (2) For the transaction data at each time point, according to the judgment result of the main buying and main selling direction, allocate the main buying transaction volume to the right half of the K-line chart of the corresponding price, and allocate the main selling transaction volume to the left half of the K-line chart of the corresponding price; (3) According to the price-time coordinate system, display the allocated transaction volume in different colors or shapes to form the order flow footprint.

[0129] Step S4000 specifically includes:

[0130] Step S4100: Calculate the delta value, which is the sum of the main buying volume and the sum of the main selling volume of the K-line.

[0131] Step S4100 can reflect the balance of power between buyers and sellers within the K-line period; specifically, calculate the delta value: for each K-line period, calculate the sum of the main buying volume minus the sum of the main selling volume to obtain the delta value.

[0132] Step S4200: Identify adjacent transactions (adjacent transaction identification), which refers to adjacent transactions formed by the main seller's position on the left and the main buyer's position diagonally opposite on the right of the order flow footprint chart K-line.

[0133] In step S4200, identifying adjacent transactions refers to identifying adjacent transactions formed by the left main seller position and the right main buyer diagonally opposite position in the order flow footprint graph.

[0134] Step S4300: Determine whether there is a short-selling imbalance or a long-selling imbalance.

[0135] Step S4300 specifically includes: for each adjacent transaction, comparing the transaction volume of the main seller and the transaction volume of the main buyer. If the transaction volume of the main seller is much greater than the transaction volume of the main buyer (usually greater than or equal to 3 times), it is judged that the short side is unbalanced; if the transaction volume of the main buyer is much greater than the transaction volume of the main seller (usually greater than or equal to 3 times), it is judged that the long side is unbalanced.

[0136] Judgment of short-selling imbalance: The trading volume of the main seller in adjacent transactions is much greater than the trading volume of the main buyer, usually greater than or equal to 3 times;

[0137] Judgment of imbalance among multiple parties: The transaction volume of the main buyer in adjacent transactions is much greater than the transaction volume of the main seller, usually greater than or equal to 3 times;

[0138] Step S4400: Identify short-selling and long-selling bands.

[0139] Step S4400 requires determining short-side and long-side imbalances to identify long and short accumulation zones. Specifically, it includes: (1) counting the number of consecutive short-side imbalances. If the number of consecutive imbalances is greater than or equal to 3, a short accumulation zone is formed. (2) counting the number of consecutive long-side imbalances. If the number of consecutive imbalances is greater than or equal to 3, a long accumulation zone is formed.

[0140] The identification rules in step S4400 include: (1) Short accumulation zone identification: multiple consecutive short imbalances, usually greater than or equal to 3 times; (2) Long accumulation zone identification: multiple consecutive long imbalances, usually greater than or equal to 3 times.

[0141] Through the analytical indicators in step S4400, the system can conduct in-depth analysis of the balance of power between buyers and sellers in the market, providing strong support for users' trading decisions.

[0142] Step S5000 presents the results, including information such as the balance of power between buyers and sellers, and price-time relationships. Through intuitive visualization, Step S5000 allows users to quickly understand and apply the analysis results, improving the efficiency and accuracy of their trading decisions.

[0143] In step S5000, the content displayed in the order flow footprint diagram includes: (1) the distribution of transaction volume under the price-time coordinate system; (2) the comparison of the main buying volume and the main selling volume; (3) the trend of delta value; (4) the position and quantity of adjacent transactions; (5) the areas of short-side imbalance and long-side imbalance; and (6) the distribution of long-side accumulation zones and short-side accumulation zones.

[0144] The technical features of the order flow footprint generation method based on market snapshot provided in this application are: (1) Based on market snapshot data, it does not require processing a large amount of transaction data, the calculation is simple and the real-time performance is strong; (2) The intuitive visualization display method helps users quickly understand the micro structure of the market; (3) It can identify important market information such as the comparison of bullish and bearish forces, the distribution of trading volume inside the K-line, bullish accumulation zone and bearish accumulation zone; (4) The system architecture is clear, the functional modules are complete, and it is easy to implement and expand.

[0145] This application utilizes market snapshot data and a simple, efficient algorithm to quickly generate order flow footprints, providing a clear view of the market's microstructure and helping users identify market trends, the balance of power between buyers and sellers, and trading opportunities. The system boasts advantages such as high real-time performance, simple calculations, and excellent visualization, meeting investors' needs for real-time market analysis.

[0146] The advantages of the order flow footprint generation method based on market snapshot provided in this application are: (1) strong real-time performance: based on market snapshot data, there is no need to process a large amount of transaction data, the calculation is simple, and the order flow footprint can be generated in real time; (2) good visualization effect: intuitively display the micro structure of the market, including the comparison of bullish and bearish forces, price-time relationship and other information, to help users quickly understand market dynamics; (3) strong analytical capability: able to identify important market information such as the comparison of bullish and bearish forces, bullish accumulation zone and bearish accumulation zone, to provide strong support for users' trading decisions; (4) easy to expand: the system architecture is clear, the functional modules are complete, it is easy to implement and expand, and more analytical functions can be added according to user needs.

[0147] This application effectively solves the problems existing in the prior art, providing investors with an efficient and intuitive market analysis tool with broad application prospects. The system can be applied to real-time analysis of financial markets such as stocks, futures, and foreign exchange, helping investors better understand market microstructures and make more accurate trading decisions.

[0148] Figure 5 This is an order flow effect diagram in one embodiment. The order flow effect diagram is the target order flow footprint diagram calculated in this application. The target order flow footprint diagram includes the following parts:

[0149] Basic candlestick data: includes candlestick time, opening price, highest price, lowest price, closing price, and the chart contains 5 candlesticks.

[0150] Volume distribution within a candlestick chart: The numbers inside the candlestick chart represent the main buying volume (located on the left side of the candlestick chart) and the main selling volume (located on the right side of the candlestick chart) within the corresponding price range. For example, the data 293|642 of the first candlestick chart indicates that within the range of 3059~3060, the main buying volume was 293 and the main selling volume was 642.

[0151] K-line buying volume: The sum of all buying volumes on the left side of the K-line.

[0152] K-line main selling volume: the sum of all main selling volumes on the right side of the K-line.

[0153] Delta value: K-line main buying volume - K-line main selling volume, i.e. Figure 5 The number at the top of each candlestick indicates that buyers are in control, while a negative number indicates that sellers are in control.

[0154] Adjacent transaction positions: The position one cell above the main buy transaction on the left and the main sell transaction on the right are considered adjacent transaction positions. Taking the data at the bottom of the first candlestick as an example, 760 and 642 are adjacent transaction positions, 293 and 654 are adjacent transaction positions, and so on.

[0155] Short-selling imbalance: The volume of the main seller in adjacent transactions is greater than the volume of the main buyer by x times, where x can be configured. In the chart, it is 2 times. The green number inside the K-line indicates short-selling imbalance.

[0156] Multiple imbalances: The trading volume of the main buyer in adjacent transactions is greater than the trading volume of the main seller by x times, where x can be configured. In the chart, it is 2 times. The red numbers inside the K-line indicate multiple imbalances.

[0157] Bullish accumulation zone: Multiple consecutive bullish imbalances, usually more than or equal to 3 times, as shown in the red band formed by the first K-line in the figure, which contains the bullish imbalance data of 654, 391, 342, 818.

[0158] Short position accumulation zone: Multiple consecutive short position imbalances, usually more than or equal to 3 times, as shown in the green band formed by the last hard palate K line in the figure, which contains the short position imbalance data of 447, 753, 1049.

[0159] This application provides a method and system for calculating order flow footprints based on market snapshots. This system, based on market snapshot data, quickly generates order flow footprints using a simple and efficient algorithm. It can intuitively display the market's microstructure, helping users identify market trends, the balance of power between buyers and sellers, and trading opportunities. The system has advantages such as strong real-time performance, simple calculation, and good visualization effects, meeting investors' needs for real-time market analysis and possessing broad application prospects.

[0160] This application discloses a method and system for calculating order flow footprints based on market snapshots. The system automatically generates order flow footprints based on market snapshot data, using algorithms such as determining the main buy and sell directions, volume distribution, and delta calculation. This provides a clear view of the market's microstructure, helping users identify market trends, the balance of power between buyers and sellers, and trading opportunities. The system includes a data acquisition module, a main buy and sell direction determination module, an order flow footprint generation module, a buy / sell power analysis module, and a results display module. It can process market data in real time and generate accurate order flow footprints, providing strong support for users' trading decisions.

[0161] It should be noted that any technical feature in any of the above embodiments provided in this application is also applicable to any of the following embodiments provided in this application, and similar details will not be repeated hereafter.

[0162] Figure 6 Here is a structural block diagram of the system in one embodiment, with reference to Figure 6 The order flow footprint generation system based on market snapshots includes:

[0163] Data acquisition module 601 is used to acquire real-time market snapshot data;

[0164] The trading direction determination module 602 is used to perform trading direction determination processing based on real-time market snapshot data, and obtain the trading direction determination result corresponding to the real-time market snapshot data.

[0165] The initial order flow footprint generation module 603 is used to process the transaction volume allocation based on the transaction direction judgment result, determine the transaction volume allocation data, and obtain the initial order flow footprint.

[0166] The bullish and bearish force analysis module 604 is used to perform bullish and bearish force analysis based on the trading volume allocation data, and to determine the indicator analysis results of the bullish and bearish force analysis indicators.

[0167] The results display module 605 is used to display the indicator analysis results in the initial order flow footprint map to generate the target order flow footprint map.

[0168] In this embodiment of the application, based on, as follows Figure 6The connections between the modules or units shown in the diagram improve the efficiency and real-time performance of data computation and enhance the effectiveness of data analysis through their cooperation.

[0169] Figure 7 Here is a system flowchart of one embodiment. Figure 8 Here is a system block diagram from one embodiment, with reference to Figure 7 and Figure 8 The order flow footprint generation system based on market snapshots, also known as the system for calculating order flow footprints based on market snapshots, includes: a data acquisition module, used to acquire real-time market snapshot data, including the latest price, the last bid price, the last ask price, and trading volume; a primary buy / sell judgment module (also known as a trading direction judgment module), used to determine the primary buy / sell direction of the current transactions based on the comparison between the latest price and the last bid and ask prices; an order flow footprint generation module (also known as an initial order flow footprint generation module), used to allocate the primary buy volume to the right half of the candlestick chart and the primary sell volume to the left half of the candlestick chart based on the primary buy / sell direction judgment results, forming the order flow footprint; a bullish / bearish strength analysis module, used to calculate the delta value, identify adjacent transactions, and determine bearish imbalance, bullish imbalance, bullish accumulation zones, and bearish accumulation zones; and a results display module, used to display the market microstructure in the form of an order flow footprint, including information such as the comparison of bullish and bearish strength and price-time relationships.

[0170] In another embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, it includes a processor, memory, input / output interfaces, and a communication interface. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface is connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores relevant data. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. The computer program can be executed by the processor to implement the various methods described in the above embodiments.

[0171] In yet another embodiment, a computer device is provided, such as a terminal, whose internal structure diagram may be as follows: Figure 10As shown, it includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. The computer program can be executed by the processor to implement the various methods described in the above embodiments.

[0172] Those skilled in the art will understand that Figure 9 and Figure 10 The structure shown is only a block diagram of a part of the structure related to the present application and does not constitute a limitation on the computer device on which the present application is applied. It may also include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, in order to realize the function of the computer device.

[0173] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0174] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the systems, devices, equipment, modules or units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0175] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, devices, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0176] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0177] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0178] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0179] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium, or a semiconductor medium (e.g., a solid-state drive), etc.

[0180] The technical solutions provided by the embodiments of this application have been described in detail above. Specific examples have been used in the embodiments of this application to illustrate the principles and implementation methods of the embodiments of this application. The description of the above embodiments is only for the purpose of helping to understand the methods and core ideas of the embodiments of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments of this application. Therefore, the content of this specification should not be construed as a limitation on the embodiments of this application.

Claims

1. A method for generating an order flow footprint graph based on market data snapshots, characterized in that, The method includes: Get real-time market snapshot data; The trading direction is determined based on the real-time market snapshot data to obtain the trading direction determination result corresponding to the real-time market snapshot data. Based on the transaction direction judgment result, the transaction volume is allocated to determine the transaction volume allocation data in order to obtain the initial order flow footprint map; Based on the transaction volume distribution data, a bullish-bearish force analysis is performed to determine the indicator analysis results of the bullish-bearish force analysis indicators. The results of the indicator analysis are displayed in the initial order flow footprint map to generate the target order flow footprint map.

2. The method according to claim 1, characterized in that, The acquisition of real-time market snapshot data includes: Obtain preset interface connection data and update cycle data for real-time updates; Based on the update rules represented by the update cycle data, the data is updated in real time through the interface representing the data in the data to obtain the real-time market snapshot data.

3. The method according to claim 1, characterized in that, The step of allocating transaction volume based on the transaction direction determination result to determine transaction volume allocation data and obtain an initial order flow footprint map includes: If the transaction direction determination result is the first direction, the first transaction volume data is generated on the first display side; If the transaction direction determination result is the second direction, second transaction volume data is generated on the second display side; The initial order flow footprint is determined based on the first transaction volume data on the first display side and the second transaction volume data on the second display side.

4. The method according to claim 1, characterized in that, The step of performing bullish / bearish force analysis based on the transaction volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes: The net trading volume is calculated based on the trading volume allocation data. The analysis results of the indicator are determined based on the net trading volume value.

5. The method according to claim 1, characterized in that, The step of performing bullish / bearish force analysis based on the transaction volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes: Based on the transaction volume allocation data, adjacent transaction identification processing is performed to obtain adjacent transaction identification results; The indicator analysis results are determined based on the adjacent transaction identification results.

6. The method according to claim 5, characterized in that, The step of performing bullish / bearish force analysis based on the transaction volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes: Based on the results of adjacent transaction identification, a short-selling imbalance judgment is performed to obtain the short-selling imbalance judgment result; Based on the results of adjacent transaction identification, a multi-party imbalance judgment is performed to obtain the multi-party imbalance judgment result; The index analysis results are determined based on the results of the short-side imbalance judgment and the results of the long-side imbalance judgment.

7. The method according to claim 6, characterized in that, The step of performing bullish / bearish force analysis based on the transaction volume allocation data to determine the indicator analysis results of the bullish / bearish force analysis indicators includes: Based on the short-side imbalance judgment result, short-side accumulation zone identification processing is performed to obtain the short-side accumulation zone identification result; Based on the results of the multi-party imbalance judgment, multi-head accumulation zone identification processing is performed to obtain the multi-head accumulation zone identification result. The index analysis results are determined based on the identification results of the empty accumulation zone and the identification results of the multi-head accumulation zone.

8. A system for generating order flow footprint graphs based on market data snapshots, characterized in that, The system includes: The data acquisition module is used to acquire real-time market snapshot data; The trading direction determination module is used to perform trading direction determination processing based on the real-time market snapshot data, and obtain the trading direction determination result corresponding to the real-time market snapshot data. The initial order flow footprint generation module is used to perform transaction volume allocation processing based on the transaction direction judgment result, determine the transaction volume allocation data, and obtain the initial order flow footprint. The bullish and bearish force analysis module is used to perform bullish and bearish force analysis processing based on the trading volume allocation data, and determine the indicator analysis results of the bullish and bearish force analysis indicators. The results display module is used to display the indicator analysis results in the initial order flow footprint map to generate the target order flow footprint map.

9. A computer device, characterized in that, The computer device includes: At least one processor and memory; The memory is used to store program code, and the processor is used to call the program code stored in the memory to execute the method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, It includes instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 7.

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