Quantitative transaction risk control method and device, equipment and medium

Abstract

The invention provides a risk control method for a unified risk control platform and a quantitative transaction system, and relates to the field of information security and the field of finance. The risk control method for the unified risk control platform comprises the following steps: acquiring all undetermined transaction instructions in a quantitative transaction system; determining a current transaction stage of each to-be-determined transaction instruction; processing each undetermined transaction instruction based on N risk control index rules in the current transaction stage to obtain N risk control index results; and for each to-be-determined transaction instruction, if M risk control index results do not conform to a first constraint condition exist, a risk prompt is sent to the quantitative transaction system, and the quantitative transaction system is configured to respond to the risk prompt and refuse to deal with the to-be-determined transaction instruction.

Description

Technical Field

[0001] The present disclosure relates to the fields of information security and finance, and more specifically, to a risk control method, device, equipment, medium and program product for quantitative trading. Background Art

[0002] "Quantitative trading" refers to the process of replacing human subjective judgment with mathematical models, using computer technology to select a variety of "high-probability" events that can bring excess returns from a large amount of historical data to formulate quantitative trading strategies, and then implement strategies to achieve high-frequency trading. In related technologies, it is usually a scattered, single-point risk management process for each quantitative trading strategy.

[0003] In the process of realizing the disclosed invention concept, the inventors found that with the increase, update and iteration of quantitative trading strategies, the corresponding risk control rules increase accordingly, resulting in redundant risk control rule data, which occupies storage space. In addition, redundant risk control rule data such as elimination and duplication may form noise, affecting the reading speed of effective risk control rule data in the database, resulting in increased resource loss, slow calculation speed of risk control value and inability to trade in time. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a risk control method, apparatus, device, medium and program product for quantitative trading.

[0005] One aspect of the disclosed embodiments provides a risk control method for quantitative trading, which is used for a unified risk control middle platform, including:

[0006] Obtain all pending trading instructions in the quantitative trading system, where the pending trading instructions are in a pending transaction state;

[0007] Determine the current transaction stage of each pending transaction instruction, wherein at least one risk control indicator rule is pre-configured for each transaction stage in the pending transaction state;

[0008] Processing each pending transaction instruction based on the N risk control indicator rules in the current transaction stage to obtain N risk control indicator results;

[0009] For each pending transaction instruction, if there are M risk control indicator results that do not meet the first constraint condition, a risk warning is sent to the quantitative trading system, and the quantitative trading system is configured to refuse to execute the pending transaction instruction in response to the risk warning, where N and M are both integers greater than or equal to 1, and M is less than or equal to N.

[0010] According to an embodiment of the present disclosure, the quantitative trading system is configured to process all pending trading instructions in a real-time environment based on real-time market data, and to perform all simulated trading in a simulation environment based on the real-time market data, wherein the simulation environment runs in parallel with the real-time environment;

[0011] After processing each pending transaction instruction to obtain N risk control indicator results, the method further includes:

[0012] The N risk control indicator results are sent to the quantitative trading system, and the quantitative trading system is configured to perform risk control on each simulated transaction in the simulation environment based on the N risk control indicator results and a second constraint condition, wherein the first constraint condition is different from the second constraint condition.

[0013] According to an embodiment of the present disclosure, after sending the N risk control indicator results to the quantitative trading system, the method further includes:

[0014] Receiving the second constraint condition sent by the quantitative trading system, the quantitative trading system being configured to send the second constraint condition if the simulated trading result in the simulation environment meets the preset condition;

[0015] The second constraint condition is used as a new first constraint condition to perform risk control on all the pending transaction instructions.

[0016] According to an embodiment of the present disclosure, each quantitative trading instruction has a pre-trading stage and an in-process trading stage, wherein the pre-trading stage includes a stage in which any pending trading instruction of the transaction is not placed in the market, and the in-process trading stage includes a stage in which any pending trading instruction of the transaction is already placed in the market;

[0017] For each transaction stage in the pending transaction state, at least one risk control indicator rule is pre-configured, including:

[0018] At least one corresponding risk control indicator rule is configured for the pre-transaction stage and the in-transaction stage respectively.

[0019] According to an embodiment of the present disclosure, the quantitative trading system is configured to run S quantitative trading strategies to process all the pending trading instructions, where S is an integer greater than or equal to 1;

[0020] The configuration of at least one corresponding risk control indicator rule for the pre-transaction stage and the in-transaction stage respectively includes:

[0021] In the pre-trading stage or the in-trading stage, each configured risk control indicator rule is applicable to at least one quantitative trading strategy.

[0022] According to an embodiment of the present disclosure, the current transaction stage includes the pre-transaction stage or the in-transaction stage, and before processing each pending transaction instruction to obtain N risk control indicator results, the method further includes:

[0023] Determine the quantitative trading strategy to which each pending trading instruction belongs;

[0024] Based on the quantitative trading strategy to which each pending trading instruction belongs, the N risk control indicator rules are selected from at least one risk control indicator rule corresponding to the current trading stage.

[0025] According to an embodiment of the present disclosure, if there are M risk control indicator results that do not meet the first constraint condition, refusing to execute the pending transaction instruction includes:

[0026] Stop running the quantitative trading strategy to which the pending trading instruction belongs.

[0027] Another aspect of the disclosed embodiment provides a risk control method for quantitative trading, which is used in a quantitative trading system, including:

[0028] Send all pending transaction instructions in a pending transaction state to a unified risk control center, which is configured to perform risk control using any of the above methods applicable thereto;

[0029] For each pending transaction instruction, if a risk warning sent by the unified risk control center is received, the pending transaction instruction will be rejected.

[0030] According to an embodiment of the present disclosure, the method further includes:

[0031] Process all pending trading instructions in a live trading environment based on real-time market data;

[0032] Perform all simulated transactions in a simulation environment based on the real-time market data, wherein the simulation environment runs in parallel with the real-time environment;

[0033] Receive N risk control indicator results sent by the unified risk control platform, and perform risk control on each simulated transaction in the simulation environment based on the N risk control indicator results and a second constraint condition, where the second constraint condition is different from the first constraint condition in the unified risk control platform.

[0034] According to an embodiment of the present disclosure, the method further includes:

[0035] If the simulated transaction result in the simulation environment meets the preset conditions, the second constraint condition is sent to the unified risk control center;

[0036] The unified risk control center is configured to use the second constraint condition as a new first constraint condition to perform risk control on all the pending transaction instructions.

[0037] According to an embodiment of the present disclosure, after sending the second constraint condition to the unified risk control center, the method further includes:

[0038] The constraint condition is updated based on the real-time market data to obtain an updated second constraint condition, and the second constraint condition before and after the update is different;

[0039] In the simulation environment, risk control is performed on each simulated transaction based on the N risk control indicator results and the updated second constraint condition.

[0040] According to an embodiment of the present disclosure, the quantitative trading system includes an automatic quotation engine and a strategy configuration terminal, wherein the strategy configuration terminal is configured to run S quantitative trading strategies to process all the pending trading instructions, where S is an integer greater than or equal to 1;

[0041] The method further comprises:

[0042] Using the strategy configuration terminal to periodically send S heartbeat information to the automatic quotation engine, wherein the S heartbeat information corresponds to the S quantitative trading strategies one by one;

[0043] When the automatic quotation engine does not receive any of the S heartbeat information within a predetermined time, an exception is processed for the corresponding quantitative trading strategy.

[0044] According to an embodiment of the present disclosure, the abnormal processing of the corresponding quantitative trading strategy includes:

[0045] A cancellation order instruction is sent for the corresponding quantitative trading strategy, and the cancellation order instruction is used to cancel at least part of the pending trading instructions under the corresponding quantitative trading strategy.

[0046] Another aspect of the present disclosure provides a risk control system for quantitative trading, including:

[0047] A unified risk control platform is configured to execute the method as described in any of the above items applicable thereto, and to perform risk control on all pending trading instructions in the quantitative trading system that are in a pending transaction state;

[0048] The quantitative trading system is configured to execute any of the above methods applicable thereto, and conduct quantitative trading based on the risk control results of the unified risk control center.

[0049] Another aspect of the disclosed embodiment provides a risk control device for quantitative trading, which is used for a unified risk control middle platform, including:

[0050] An instruction acquisition module is used to acquire all pending transaction instructions in the quantitative trading system, wherein the pending transaction instructions are in a pending transaction state;

[0051] A stage determination module, used to determine the current transaction stage of each pending transaction instruction, wherein at least one risk control indicator rule is pre-configured for each transaction stage in the pending transaction state;

[0052] An indicator calculation module, used to process each pending transaction instruction based on the N risk control indicator rules in the current transaction stage to obtain N risk control indicator results;

[0053] A risk warning module is used for sending a risk warning to the quantitative trading system for each pending transaction instruction if there are M risk control indicator results that do not meet the first constraint condition. The quantitative trading system is configured to refuse to execute the pending transaction instruction in response to the risk warning, where N and M are both integers greater than or equal to 1, and M is less than or equal to N.

[0054] Another aspect of the disclosed embodiment provides a risk control device for quantitative trading, which is used in a quantitative trading system, including:

[0055] An instruction sending module, used for sending all pending transaction instructions in a pending transaction state to a unified risk control center, wherein the unified risk control center is configured to execute the method according to any one of claims 1 to 7 for risk control;

[0056] The risk control module is used to refuse to execute each pending transaction instruction if a risk warning sent by the unified risk control center is received.

[0057] Another aspect of an embodiment of the present disclosure provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the method as described above.

[0058] Another aspect of the embodiments of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method as described above.

[0059] Another aspect of the embodiments of the present disclosure further provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0060] One or more of the above embodiments have the following beneficial effects: forming a unified risk control system for each quantitative trading strategy, supporting the connection of the quantitative trading system with the unified risk control middle platform to realize high-frequency and high-speed data interaction, monitoring all pending trading instructions in the quantitative trading system as a whole through the unified risk control middle platform, and being able to select N risk control indicator rules according to the current trading stage of each pending trading instruction, and then sending a risk warning under the condition that the risk control indicator result does not meet the first constraint condition. It realizes real-time dynamic risk control management at the overall level, institutional level, and across strategies, overcoming the problems existing in the scattered and single-point risk control methods for each quantitative trading strategy in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0062] Figure 1A The full flow chart of implementing quantitative trading according to an embodiment of the present disclosure is schematically shown;

[0063] Figure 1B A diagram schematically illustrates an application scenario of a risk control method for quantitative trading according to an embodiment of the present disclosure;

[0064] Figure 2 A flowchart schematically shows a risk control method for quantitative trading according to an embodiment of the present disclosure;

[0065] Figure 3 A flowchart of cross-strategy risk control according to an embodiment of the present disclosure is schematically shown;

[0066] Figure 4A A flow chart of risk control in a simulation environment according to an embodiment of the present disclosure is schematically shown;

[0067] Figure 4B A scene diagram of a simulation according to an embodiment of the present disclosure is schematically shown;

[0068] Figure 5 A flowchart of updating real disk environment constraint conditions according to an embodiment of the present disclosure is schematically shown;

[0069] Figure 6 A flowchart of updating the constraints of the simulation environment according to an embodiment of the present disclosure is schematically shown;

[0070] Figure 7 A flowchart of exception handling according to an embodiment of the present disclosure is schematically shown;

[0071] Figure 8 A structural block diagram of a risk control device for quantitative trading in a unified risk control center according to an embodiment of the present disclosure is schematically shown;

[0072] Fig. 9 A block diagram schematically shows a structure of a risk control device for quantitative trading in a quantitative trading system according to an embodiment of the present disclosure; and

[0073] Fig.10 A block diagram of an electronic device suitable for implementing a risk control method for quantitative trading according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0074] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0075] Quantitative trading is usually executed at high speed and high frequency, using computer algorithms and fast trading execution systems to achieve rapid entry and exit of the market and take advantage of instantaneous price changes. Due to the characteristics of high speed, high frequency and instantaneousness, a large number of trading instructions and records will also be generated. The risk control methods of ordinary transactions are not applicable to quantitative trading, for example, there will usually be problems such as risk control mismatch or untimely transactions.

[0076] As the number of programmed quantitative trading strategies and trading volume gradually increase, the requirements for programmed quantitative trading risk management are increasing. The scattered, single-point risk control methods for each quantitative trading strategy in related technologies are no longer applicable. It is necessary to upgrade the original scattered, single-point risk control methods, build a unified risk management system for programmed trading, and add cross-platform data and risk control centralized management.

[0077] In some embodiments of the present disclosure, a risk control method for quantitative trading is provided, which forms a unified risk control system for each quantitative trading strategy, supports the connection of the quantitative trading system with the unified risk control middle platform to realize high-frequency and high-speed data interaction, monitors all pending trading instructions in the quantitative trading system as a whole through the unified risk control middle platform, and can select N risk control indicator rules according to the current trading stage of each pending trading instruction, and then sends a risk prompt under the condition that the risk control indicator result does not meet the first constraint condition. It realizes real-time dynamic risk control management at the overall level, institutional level, and across strategies, and overcomes the problems existing in the scattered and single-point risk control methods for each quantitative trading strategy in the related technology.

[0078] It should be noted that the risk control method for quantitative trading provided in the present disclosure can be used in relevant aspects of quantitative trading in the financial field, and can be used in any field outside the financial field. The present disclosure does not limit the application field.

[0079] Figure 1A The full flow chart of implementing quantitative trading according to an embodiment of the present disclosure is schematically shown.

[0080] Reference Figure 1A In the process of implementing quantitative trading, you can first set risk control parameters in the trading order system, such as risk control indicators, risk control indicator rules and risk control strategies. The risk control strategy can be obtained by combining one or more risk control indicators. The risk control indicator rules include specific conditions for calculating the values ​​of each risk control indicator. Then, perform quantitative analysis, strategy editing, strategy backtesting, backtesting approval and other operations on the quantitative platform (such as the strategy configuration end). After the backtesting approval is passed, simulation release can be carried out, simulation operation can be carried out in the simulation environment, and simulation approval can be carried out based on the simulation operation results. After the simulation approval is passed, the real market will be released, the quantitative trading strategy will be run in the real market environment, the strategy deployment and operation will be carried out in the trading order system, and automatic quotation / trading will be triggered, and real market trading will be triggered on the trading platform. In this process, unified risk control is carried out.

[0081] Figure 1B The following schematically shows an application scenario diagram of the risk control method for quantitative trading according to an embodiment of the present disclosure. It should be noted that: Figure 1B The examples shown are merely examples to which the embodiments of the present disclosure can be applied, so as to help those skilled in the art understand the technical content of the present disclosure, but do not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0082] like Figure 1B As shown, the application scenario 100 of the transaction data processing method is applied to a risk control system that interacts with a foreign exchange trading center 110 for quantitative trading. The system includes a unified risk control center and a quantitative trading system. The unified risk control center performs risk control on all pending transaction instructions in the quantitative trading system that are in a pending transaction state; the quantitative trading system performs quantitative trading based on the risk control results of the unified risk control center.

[0083] In some embodiments, the unified risk control center is set in the financial market transaction management system (FMBM) 120. The quantitative trading system includes the ComStar quotation engine 130 and the strategy configuration end, which includes the quantitative investment and trading platform (F-QIT) strategy node 150 and the F-QIT monitoring node 160. The risk control system can also include the Financial Markets Data Service (FMDS) 140 and the Big Data Platform (BDP) 170.

[0084] The foreign exchange trading center 110 can provide a local currency trading system and a local currency client. Our traders can initiate quotes in the ComStar quotation engine 130 or the automatic quotation engine can automatically quote. The counterparty trader can initiate quotes in the local currency client. The foreign exchange trading center 110 can also provide the current market data to the ComStar quotation engine 130.

[0085] The foreign exchange trading center 110 can provide transactions in the "inter-bank foreign exchange market", and domestic financial institutions that can engage in foreign exchange business (including Chinese and foreign banks and non-bank financial institutions) can conduct transactions between RMB and foreign exchange through the local currency trading system of the foreign exchange trading center.

[0086] It can be understood that the foreign exchange trading center 110 is only one of the optional "inter-bank markets", and the "inter-bank market" can also include the interbank lending market, bill market, bond market and gold market, etc.

[0087] The financial market transaction management system 120 can set up a unified risk control center, which can perform functions such as risk control, transaction approval, batch bookkeeping and data center management.

[0088] The unified risk control center can configure one or more risk control indicators and risk control strategies, carry out unified risk control system construction and implementation, support the collection and call of risk control information such as exposure, profit and loss, flow, etc. of the quantitative system across strategies or platforms, build a hierarchical risk control system for the quantitative system, support docking with the risk control center to achieve high-speed data information interaction, and support risk control factor-driven strategies based on exposure, flow, profit and loss, etc.

[0089] ComStar quotation engine 130 is also called automatic quotation engine, which can handle other quotation methods such as spot bond trading (dialogue quotation, request quotation, bilateral quotation, anonymous quotation) and interest rate swap (anonymous quotation). For example, in response to a transaction initiated by a trader based on one or more quotation methods, the automatic quotation engine can access one or more quotation sources in real time, use its own processing mechanism or quotation strategy to process the quotation, and then publish the comprehensive quotation to the trader, and then trade at this price. The automatic quotation engine can also be configured with one or more quotation strategies, risk control indicators and risk control strategies to achieve the purpose of pre-transaction risk control. ComStar quotation engine 130 is only an optional method of quotation engine, and the embodiments of the present disclosure are not limited to this.

[0090] The financial market shared data service 140 is built based on Kafka (a high-throughput distributed publish-subscribe messaging system) message middleware, and is used to store messages to increase the rate of information interaction between applications.

[0091] F-QIT strategy node 150 is also called the real-time strategy node. Traders with corresponding permissions can select the corresponding trading strategy, configure the strategy parameters, start the strategy to automatically execute and continuously monitor. During the operation of the strategy, traders continuously monitor the operation status and operation indicators of the strategy in the system and operate as needed according to factors such as the market environment. The node automatically performs data cleaning, transaction execution, pending orders, price release and other steps according to the strategy logic, completes the entire process of market making and order trading, and conducts market making transactions in a systematic and intelligent manner.

[0092] It supports traders to easily complete strategy selection, strategy parameter configuration and startup, strategy monitoring and disposal; supports traders to set strategy-level and system-level risk control limits according to the requirements of the risk management department; supports trading supervisors to effectively manage systems and permissions; supports traders or quantitative analysts to easily use tools for strategy development; and supports traders to conduct comprehensive and complete evaluations of the effectiveness of trading strategies.

[0093] The F-QIT monitoring node 160 can obtain the operation log of the F-QIT strategy node 150, and decide to start or stop the F-QIT strategy node 150 or the transaction strategy therein according to the monitoring situation.

[0094] Data Lake 170 is used to store transaction data and is quickly integrated into financial market operations by combining technologies such as big data, artificial intelligence, and blockchain. It relies on massive financial market transaction data to discover and analyze financial market rules.

[0095] The foreign exchange trading center 110, the financial market transaction management system 120, the ComStar quotation engine 130, the financial market shared data service 140, the F-QIT strategy node 150, the F-QIT monitoring node 160 and the data lake 170 can be as follows Figure 1B Data interaction is performed as shown by the arrows to complete transaction data processing.

[0096] According to the embodiments of the present disclosure, on the basis of launching the ComStar quotation engine 130, the actual docking of the quantitative trading platform (QIT) with the financial market transaction management system (FMBM), the ComStar quotation engine and the foreign exchange trading center transaction strategy interface is further supported, and a management framework for overall risk management and risk control for programmed quantitative trading is established. The overall control variables such as overall flow, exposure, profit and loss are monitored through a unified risk control middle platform, and the quantitative trading system is linked with the risk control middle platform to achieve cross-strategy and cross-instance control; a process-oriented risk control management model is constructed, so that the overall and strategy-level risk control can be applied to all aspects of quantitative trading strategy development and actual application; risk control simulation is included in the backtesting and simulation platform to further improve the versatility of the strategy program in all aspects.

[0097] The following will be based on Figure 1B The scene described by Figure 2 to Figure 7 The risk control method of quantitative trading in an embodiment of the present disclosure is described in detail.

[0098] Figure 2 The flowchart of the risk control method of quantitative trading according to the embodiment of the present disclosure is schematically shown.

[0099] like Figure 2 As shown, the risk control of quantitative trading in this embodiment includes:

[0100] In operation S210, the quantitative trading system sends all pending trading instructions in a pending transaction state to the unified risk control center;

[0101] The unified risk control center is independent of the quantitative trading system. The pending transaction status may include the status when the internal initiation has not yet been sent to the foreign exchange trading center 110, when the order has been sent to the foreign exchange trading center 110 and successfully placed, but not traded, when the quotation information of the counterparty in the market is received but the acceptance of the transaction instruction has not been sent to the foreign exchange trading center 110, etc.

[0102] The transaction instruction includes one or more transaction attributes, and the value of each attribute serves as the basis for the transaction. The transaction attribute includes the transaction type attribute and the transaction elements related to the transaction form attribute involved in the transaction instruction. The transaction type attribute includes at least one of the transaction types such as spot bond trading, interest rate swap, pledged repo, buyout repo, interbank lending, spot bond trading, interest rate swap and bond lending. The transaction form attribute may include at least one of the quotation methods such as dialogue quotation, request quotation, bilateral quotation and anonymous quotation.

[0103] Taking the dialogue quotation as an example, the specific fields of the transaction elements include: message sending time, message ID, transaction record number, quotation number, quotation deadline mark, market, quotation direction, quotation method, dialogue quotation source, quotation participant information, quotation participant type mark, institution code, trader code, transaction account code, clearing speed, clearing type, etc. The transaction elements can be extracted from the transaction data according to actual needs, and the embodiments of the present disclosure do not limit this.

[0104] In operation S220, the unified risk control center obtains all pending transaction instructions in the quantitative trading system;

[0105] For example, the unified risk control center can interact with the ComStar quotation engine 130 and the F-QIT strategy node 150 for data.

[0106] In operation S230, the unified risk control center determines the current transaction stage of each pending transaction instruction, wherein at least one risk control indicator rule is pre-configured for each transaction stage in the pending transaction state;

[0107] In operation S240, the unified risk control center processes each pending transaction instruction based on the N risk control indicator rules in the current transaction stage to obtain N risk control indicator results;

[0108] There may be some or all of the same risk control indicator rules between different transaction stages, or the risk control indicator rules between different transaction stages may be completely different. N is a variable, and the N risk control indicator rules may be some or all of the pre-configured rules in the current transaction stage, and the N value between different transaction stages may be the same or different.

[0109] In some embodiments, each risk control indicator rule includes the conditions and methods for calculating its corresponding indicator value. Each risk control indicator result is the corresponding indicator value. In other embodiments, the risk control indicator rule may also include at least one of a risk control strategy rule and a risk control model rule, and the risk control strategy rule may be a rule for calculating a combination of multiple indicators. The risk control model rule may be executed by a machine learning model obtained by pre-training a machine learning algorithm, for example, each pending transaction instruction is input into a risk control model, and the prediction result is the risk control indicator result.

[0110] In operation S250, for each pending transaction instruction, if there are M risk control indicator results that do not meet the first constraint condition, the unified risk control center sends a risk warning to the quantitative trading system, and the quantitative trading system is configured to refuse to execute the pending transaction instruction in response to the risk warning, where N and M are both integers greater than or equal to 1, and M is less than or equal to N.

[0111] The first constraint condition may include a condition threshold, for example, an exposure limit indicator is set with an exposure limit threshold. If the risk control indicator rule of the exposure limit indicator calculates that the exposure limit is greater than the exposure limit threshold, the first constraint condition is not met. In one embodiment, when the first constraint condition is met, the risk control passes and the transaction instruction continues to be executed. When the first constraint condition is not met, the risk control fails, and a risk warning can be generated and sent. The risk warning may include a message sent to the quantitative trading system and / or an alarm message sent to a manual.

[0112] In operation S260, for each pending transaction instruction, if the quantitative trading system receives a risk warning sent by the unified risk control center, it will refuse to execute the pending transaction instruction.

[0113] For example, the quantitative trading system stops sending the pending transaction instruction or the order cancellation request to the foreign exchange trading center 110.

[0114] In some embodiments, if there are M risk control indicator results that do not meet the first constraint condition, refusing to execute the pending transaction instruction includes: stopping the execution of the quantitative trading strategy to which the pending transaction instruction belongs.

[0115] You can stop only one pending transaction instruction with risk warning, or stop the strategy to which the pending transaction instruction with risk warning belongs. The function of stopping strategy is to prevent the running strategy from being unsuitable for the current market situation and stop loss in time.

[0116] According to the embodiments of the present disclosure, real-time dynamic risk control management at the overall level, institutional level, and across strategies can be achieved, overcoming the problems existing in the related art of performing scattered, single-point risk control for each quantitative trading strategy.

[0117] In some embodiments, each quantitative trading instruction has a pre-trading stage and an in-process trading stage, the pre-trading stage includes the stage when any pending trading instruction of the transaction is not placed in the market, and the in-process trading stage includes the stage when any pending trading instruction of the transaction is already placed in the market; for each trading stage in the pending transaction state, at least one risk control indicator rule is pre-configured, including: configuring at least one corresponding risk control indicator rule for the pre-trading stage and the in-process trading stage respectively. Configuring risk control indicator rules according to the characteristics of different trading stages is flexible and comprehensive.

[0118] For example, the pre-trading stage includes the stage when the initial quotation trading instruction of a transaction has not been sent to the foreign exchange trading center 110. The in-process trading stage includes the stage when the order has been placed in the market but not executed, and the order has been sent to the foreign exchange trading center 110 but not placed or executed successfully. The pre-trading stage and the in-process trading stage can have the same risk control indicator rules, and of course the risk control indicator rules between the two can also be completely different.

[0119] Taking the pre-trading stage as an example, multiple cumulative and non-cumulative risk control indicators and corresponding risk control indicator rules can be set;

[0120] If any risk control indicator exceeds the limit during the operation of the strategy, the strategy will be automatically stopped without the approval process, and the detailed information of the limit will be recorded in the strategy log. All the limit exceeding logs triggered in the system can be checked historically. The prompt information of the risk control indicator with specific values ​​is: "This quotation XXX (quotation number) XX indicator (a certain indicator, such as a single authorization) exceeds the limit, the current value is XX, and the authority value is XX."; The prompt information of the risk control indicator with no number of values ​​is: "This quotation XXX (quotation number) XX indicator (a certain indicator, such as a single authorization) exceeds the limit".

[0121] For example, the cumulative institutional-level risk control indicators include exposure limit information; when using QIT to issue instructions, the FMBM risk control center will read the real-time value of the actual cumulative indicators by default, and calculate the risk control indicator value based on the QIT's new and historical orders within T days to obtain the corresponding result (over-limit or not), and the risk control center will return the corresponding result to QIT, and release if it is not over-limited, and stop the strategy if it is over-limited. Over-limit means that the first constraint condition is not met.

[0122] In the same trading stage, different transaction types may have different risk control indicator rules. For example, the risk control indicator rules for bilateral bond quotations are as follows: for transactions initiated by us, after the order is issued, the difference between the buy and sell is checked. If the trader's exposure limit exceeds the limit, the system will hard control and stop the strategy. The system will prompt the detailed reason to the trader; for transactions initiated by the counterparty, after the order is issued, the transaction is checked one by one. If the trader's exposure limit exceeds the limit, the system will hard control and stop the strategy. The system will prompt the detailed reason to the trader; and the risk control indicator rules for anonymous bond quotations are as follows: for transactions initiated by us, after the order is issued, the transaction is checked one by one. If the trader's exposure limit exceeds the limit, the strategy will be stopped. The system will prompt the detailed reason to the trader. Transactions initiated by the counterparty are the same as the bilateral quotations mentioned above.

[0123] For example, non-cumulative institutional-level risk control indicators include price comparison information, single authorization information, anti-money laundering information, external fraud information, money laundering risk level information, restricted peer institution list control, peer specialized business access list, etc. Refer to the risk control settings shown in Table 1.

[0124] Table 1

[0125]

[0126]

[0127] In some embodiments, the quantitative trading system is configured to run S quantitative trading strategies to process all pending trading instructions, where S is an integer greater than or equal to 1;

[0128] The S quantitative trading strategies include, for example, grid trading strategy, conditional order strategy, quick order splitting strategy, pegging strategy and volume-weighted average price strategy (VWAP strategy).

[0129] The strategy configuration terminal can determine whether the market pattern is oscillating with high volatility, oscillating with low volatility, unilateral trend, bilateral trend, etc. according to the current market data and / or historical market data, and trigger the corresponding trading strategy. The strategy configuration terminal can input the current market data into S quantitative trading strategies to trigger the execution strategy.

[0130] The market data may be the price, stock, etc. of the transaction target product in the transaction market. For example, the market data may include the current price of the interest rate business (taking the spot bond trading business as an example), the current quotes of each trading party, and the trading party includes a quoter or a financial institution. It should be noted that in some embodiments of the present disclosure, the interest rate transaction of the spot bond trading business is taken as an example, but the embodiments of the present disclosure are not limited to this.

[0131] Each quantitative trading strategy includes at least one trading rule, which controls each quantitative trading strategy to execute its own trading rule to process the trading information in the current market data and obtain trading instructions. The trading rules include rules and conditions for processing the input market data and inputting the transaction content.

[0132] In some embodiments, configuring at least one corresponding risk control indicator rule for the pre-transaction stage and the in-transaction stage respectively includes:

[0133] In the pre-trading stage or the in-trading stage, each configured risk control indicator rule is applicable to at least one quantitative trading strategy.

[0134] According to the embodiments of the present disclosure, the risk control indicator rules have a one-to-one or one-to-many relationship with the quantitative trading strategy, and through all investment channels involved in risk control, the risk control indicator system can be improved and rigid control of all channels can be uniformly implemented to effectively prevent the occurrence of operational risks.

[0135] Figure 3 A flowchart of cross-strategy risk control according to an embodiment of the present disclosure is schematically shown.

[0136] The current transaction stage includes the pre-transaction stage or the in-transaction stage. Before processing each pending transaction instruction and obtaining N risk control indicator results, such as Figure 3 As shown, this embodiment includes:

[0137] In operation S310, determining the quantitative trading strategy to which each pending trading instruction belongs;

[0138] In operation S320, based on the quantitative trading strategy to which each pending trading instruction belongs, N risk control indicator rules are selected from at least one risk control indicator rule corresponding to the current trading stage.

[0139] For example, by running a grid trading strategy to initiate at least one pending trading instruction, combined with the current market data, some or all of the pre-configured risk control indicator rules of the current trading stage can be selected. The conditional order strategy is also selected from all pre-configured risk control indicator rules of the current trading stage. Even if multiple quantitative trading strategies are running on different platforms, risk control is also based on all pre-configured risk control indicator rules of the current trading stage.

[0140] According to the embodiments of the present disclosure, cross-strategy and cross-platform overall risk control is implemented for all pending trading instructions, reducing redundant data of the original decentralized risk control method for each quantitative trading strategy and improving risk control efficiency.

[0141] In some embodiments, the simulation environment and the real-time market data can be processed synchronously and in parallel by the real-time environment. The simulation environment involved in the present disclosure can be a high-simulation environment, which refers to an environment that is completely consistent with at least one of the hardware resources, software programs, input data, quantitative trading strategies, risk control indicator rules, and quantitative trading processes of the real-time environment, so that simulation trading that conforms to the actual situation can be realized in the field of quantitative trading. The following will further introduce an embodiment of using the simulation environment to realize dynamic management of constraints in the real-time environment for risk control.

[0142] Figure 4A The flowchart of risk control in a simulation environment according to an embodiment of the present disclosure is schematically shown. Figure 4B The diagram schematically shows a scene diagram of a simulation according to an embodiment of the present disclosure.

[0143] like Figure 4A As shown, this embodiment includes:

[0144] In operation S410, the quantitative trading system processes all pending trading instructions in a real-time trading environment based on real-time market data;

[0145] In operation S420, the quantitative trading system performs all simulated transactions in a simulation environment based on real-time market data, and the simulation environment and the real trading environment run in parallel;

[0146] For example, the QIT side reuses the existing simulation framework, and the simulation strategy part is physically isolated from the real strategy part. The operation of the simulation part strategy will not affect the real strategy. The running time of the simulation disk is consistent with the running time of the real disk, such as parallel synchronous operation.

[0147] In operation S430, the unified risk control center sends N risk control indicator results to the quantitative trading system.

[0148] In operation S440, the quantitative trading system receives N risk control indicator results sent by the unified risk control platform, and performs risk control on each simulated transaction in a simulation environment based on the N risk control indicator results and a second constraint condition, where the second constraint condition is different from the first constraint condition in the unified risk control platform.

[0149] One or more simulated quantitative trading strategies are configured in the simulation environment, and one or more simulated risk control indicator rules can also be configured, which can be the same as the quantitative trading strategies and risk control indicator rules in the real environment. In other words, the various steps of the unified risk control center can be reproduced in the simulation environment, such as operation S220 to operation S250. By controlling the quantitative trading strategy to perform simulated trading operations, the simulated trading results are obtained, and the simulated trading results are monitored to see whether they meet the second constraint condition. The second constraint condition is different from the first constraint condition and may include at least one of: different threshold values, different risk control coverage, different risk control emphasis, or different rule content.

[0150] Reference Figure 4B , the application scenario 400 includes a foreign exchange trading center 110, an X-Bond engine 131, a financial market shared data service 140, a data lake 170, an F-QIT simulation strategy node 410, an F-QIT simulation monitoring node 420, and an F-QIT simulation simulator node 430. The functions of the foreign exchange trading center 110, the X-Bond engine 131, the financial market shared data service 140, and the data lake 170 are respectively the same as those in the application scenario 100, and the F-QIT simulation strategy node 410 and the F-QIT simulation monitoring node 420 are respectively the same as the F-QIT strategy node 150 and the F-QIT monitoring node 160. The F-QIT simulation simulator node 430 can be used to execute the simulation transaction instructions sent by the F-QIT simulation strategy node 410 to obtain backtesting results or simulated transaction results.

[0151] Quantitative trading processes and analyzes real-time market data quickly and trades at high frequencies. However, the market changes rapidly, and the constraints of risk control may need to be adjusted dynamically. Therefore, the simulation environment is configured with the same hardware, software and other resources as the real environment, and has the same input data during parallel operation. The second constraint can be dynamically configured based on the real-time market data and / or trading situation to consider the risks in the future. In this way, the second constraint cooperates with the first constraint to form a risk control mechanism with higher risk control capabilities and efficiency.

[0152] Figure 5 The flowchart of updating the real disk environment constraint conditions according to the embodiment of the present disclosure is schematically shown.

[0153] like Figure 5 As shown, this embodiment includes:

[0154] In operation S510, if the simulated transaction result in the simulation environment meets the preset conditions, the quantitative trading system sends the second constraint condition to the unified risk control center;

[0155] The preset conditions include that all simulated transaction results are normal. Specifically, each risk control indicator result meets the second constraint condition and / or the simulated transaction result meets the profit expectation.

[0156] In some embodiments, if some risk control indicator results do not meet the second constraint condition, the corresponding value in the second constraint condition can be updated.

[0157] In operation S520, after sending the N risk control indicator results to the quantitative trading system, the unified risk control center receives the second constraint condition sent by the quantitative trading system.

[0158] In operation S530, the unified risk control center uses the second constraint condition as the new first constraint condition to perform risk control on all pending transaction instructions.

[0159] For example, when using QIT to issue a quotation, QIT defaults to reading the current risk control indicator values ​​of the FMBM system risk control center and obtaining the corresponding results, whether it exceeds the limit or not; all pre-risk control indicators implemented in the simulation environment only control simulated transactions and cannot affect real transactions. In some embodiments, when the first constraint is updated, the quantitative trading system is always running. For example, the original first constraint is used between 9:00 and 9:30 in the morning, and the second constraint is used as the new first constraint between 9:30 and 10:00 in the morning. Whether to continue updating after 10 o'clock depends on the simulated transaction results in the simulation environment. The update method can be a regular update, or the data can be updated by conditional triggering.

[0160] According to the embodiments of the present disclosure, during the quantitative trading process, risks may change according to real-time market conditions and / or trading situations. Therefore, the second constraint condition may be verified through risk control of simulated transactions in a simulation environment (the simulated transaction results meet the preset conditions), thereby achieving dynamic management of risk control and improving risk control capabilities when the verification is passed.

[0161] Figure 6 The flowchart of updating the constraint conditions of the simulation environment according to the embodiment of the present disclosure is schematically shown.

[0162] After sending the second constraint to the unified risk control center, Figure 6 As shown, this embodiment includes:

[0163] In operation S610, the constraint condition is updated based on the real-time market data to obtain an updated second constraint condition, and the second constraint condition before and after the update is different;

[0164] Updating the constraint conditions may include updating the thresholds of one or more risk control indicators, thereby achieving refined risk control scale adjustment.

[0165] In operation S620, risk control is performed on each simulated transaction based on the N risk control indicator results and the updated second constraint condition in the simulation environment.

[0166] If the simulated transaction results meet the expected conditions, the updated second constraint can continue to be sent to the unified risk control center to replace the current first constraint.

[0167] In some embodiments, the simulation environment can add risk control indicator rules at any trading stage, or delete risk control indicator rules in the real trading environment, and update the original second constraint condition accordingly. For example, simulation environment parameters are added for traders to maintain, including: "Simulation environment parameter limit value", "Simulation environment parameter warning value", the value is an absolute value; "Effective start date", "Effective end date", define the parameter activation and deadline, "Effective start date" and "Effective end date" default to the current day, support modification; (For all fields, please refer to Figure 2 ). If the simulation environment open limit parameter value is modified through QIT, the value modified by QIT shall prevail. If it is not modified, the FMBM production environment parameter value shall prevail.

[0168] If the simulated transaction result meets the expected conditions, the risk control indicator rule set and the updated second constraint condition are sent to the unified risk control middle station, and the original risk control indicator rule set and the first constraint condition are replaced in the corresponding transaction stage. It can be understood that the first constraint condition or the second constraint condition includes the threshold value of at least one risk control indicator rule corresponding to each transaction stage.

[0169] According to the embodiments of the present disclosure, the constraints can be adjusted dynamically and flexibly, which can not only perform risk control on all pending transaction instructions as a whole, but also have high flexibility.

[0170] For example, the F-QIT strategy node 150 can automatically perform steps such as data cleaning, transaction execution, pending orders, price release, etc. according to the strategy logic, run S quantitative trading strategies, and complete the entire process of market making and order trading. The ComStar quotation engine 130 can obtain the current market data from the foreign exchange trading center 110, and the strategy configuration end receives the current market data sent by the ComStar quotation engine 130. Based on the current market data, the strategy configuration end triggers S quantitative trading strategies to generate at least one pending transaction instruction and sends it to the ComStar quotation engine 130. The ComStar quotation engine 130 is used to execute the pending transaction instruction to complete at least one financial transaction. It can be understood that the ComStar quotation engine 130 can also store one or more automatic quotation strategies locally, or use remote databases or cloud services for storage to automatically trigger or close some locally running quantitative trading strategies, which are also subject to risk control through a unified risk control platform. The following is through Figure 7 Describes how to perform strategy stability checks based on the strategy configuration side and the automatic quotation engine.

[0171] Figure 7 The flowchart of exception handling according to the embodiment of the present disclosure is schematically shown.

[0172] like Figure 7 As shown, this embodiment includes:

[0173] In operation S710, the strategy configuration terminal periodically sends S heartbeat information to the automatic quotation engine, and the S heartbeat information corresponds to the S quantitative trading strategies one by one;

[0174] In operation S720, when the automatic quotation engine does not receive any of the S heartbeat information within a predetermined time, an exception process is performed on the corresponding quantitative trading strategy.

[0175] In some embodiments, performing exception handling on the corresponding quantitative trading strategy includes: sending an order cancellation instruction for the corresponding quantitative trading strategy, where the order cancellation instruction is used to cancel at least part of the pending trading instructions under the corresponding quantitative trading strategy.

[0176] Taking the in-process transaction stage of the spot bond market quotation scenario as an example, the following steps are included:

[0177] (1) QIT can send heartbeats normally according to the policy instance number dimension, with a heartbeat interval of 30 seconds. ComStar can receive and monitor the heartbeats normally;

[0178] (2) When ComStar does not receive a heartbeat from a certain policy instance number for more than 120 seconds, it can mark the corresponding policy instance number from the heartbeat queue;

[0179] (3) When ComStar does not receive a heartbeat from a certain policy instance number for more than 120 seconds, it can send a heartbeat exception report to QIT to verify that the report message fields meet the message standard requirements of both parties;

[0180] (4) When ComStar does not receive a heartbeat from a certain strategy instance number for more than 120 seconds, it can issue a cancellation command for the order number under the strategy instance number through the trading interface, verify whether the quotation status to be cancelled in the quotation source of "external system" on the ComStar market quotation main interface is "cancel", and after receiving the feedback from the local currency trading system, return the feedback message to QIT according to the original process.

[0181] According to an embodiment of the present disclosure, the strategy instance number is the number of the quantitative trading strategy. It is possible to monitor the stability of the strategy through heartbeat information at the granularity of a single quantitative trading strategy and realize automatic cancellation of abnormal orders.

[0182] Refer to above Figure 2 to Figure 7 In terms of ex ante risk control, through all investment channels involved in risk control, we will improve the ex ante risk control indicator system and achieve rigid control of all channels at the system level, effectively prevent the occurrence of operational risks, and achieve risk control at the institutional level and institutional indicators. In terms of in-process risk control, we will establish an intelligent risk monitoring and early warning mechanism to grasp the latest investment and transaction conditions in real time, accurately identify and push reminders at the first time, and actively withdraw orders for in-process strategies through "heartbeat" monitoring that supports the operation of trading strategies, so as to achieve independent control of the operation risks of trading strategies. In terms of post-risk control, by establishing a unified view of business management monitoring, we will strengthen the monitoring, analysis, early warning, and control of the execution of investment limits to effectively prevent business risks. We will enhance the means of identifying and monitoring abnormal transaction risks, and achieve full-process online management of overdue transactions.

[0183] Therefore, we should build a risk control system for each trading stage (such as the pre-stage of RMB interest rate quantitative trading), expand the scope of market data access, further enrich the types of market-making and active trading strategies, improve strategy operation, real-time monitoring and post-trading analysis reports, and gradually realize the real operation of quantitative trading on the basis of stable simulation operation. We can realize the risk control management of the whole process before, during and after the quantitative trading (such as bonds), improve the level of refined transaction management and intelligent risk control, and achieve the risk control effect of the whole process before, during and after the transaction.

[0184] Based on the above-mentioned risk control method of quantitative trading, the present disclosure also provides a risk control device for quantitative trading. Figure 8 and Fig. 9 Describe in detail.

[0185] Figure 8 The structural block diagram of the risk control device for quantitative trading of the unified risk control center according to the embodiment of the present disclosure is schematically shown.

[0186] like Figure 8 As shown, the risk control device 800 of this embodiment includes an instruction acquisition module 810 , a stage determination module 820 , an indicator calculation module 830 , and a risk warning module 840 .

[0187] The instruction acquisition module 810 may perform operation S220 to acquire all pending transaction instructions in the quantitative trading system, where the pending transaction instructions are in a pending transaction state;

[0188] The stage determination module 820 may perform operation S230 for determining the current transaction stage of each pending transaction instruction, wherein at least one risk control indicator rule is pre-configured for each transaction stage in the pending transaction state;

[0189] The indicator calculation module 830 may perform operation S240 to process each pending transaction instruction based on the N risk control indicator rules in the current transaction stage to obtain N risk control indicator results;

[0190] The risk warning module 840 can execute operation S250, which is used to send a risk warning to the quantitative trading system for each pending transaction instruction if there are M risk control indicator results that do not meet the first constraint condition. The quantitative trading system is configured to refuse to execute the pending transaction instruction in response to the risk warning, where N and M are both integers greater than or equal to 1, and M is less than or equal to N.

[0191] The risk control device 800 includes modules for respectively executing the various steps of any method embodiment applicable to the unified risk control center described above.

[0192] Fig. 9 The structural block diagram of the risk control device for quantitative trading in a quantitative trading system according to an embodiment of the present disclosure is schematically shown.

[0193] like Fig. 9 As shown, the risk control device 900 of this embodiment includes an instruction sending module 910 and a risk control module 920 .

[0194] The instruction sending module 910 may perform operation S210 for sending all pending transaction instructions in a pending transaction state to a unified risk control center, where the unified risk control center is configured to execute a risk control method for the same;

[0195] The risk control module 920 may execute operation S260 to refuse to execute each pending transaction instruction if a risk warning sent by the unified risk control center is received.

[0196] The risk control device 800 or the risk control device 900 includes modules for respectively executing the steps of any one of the method embodiments applicable to the quantitative trading system as described above.

[0197] It should be noted that the implementation methods, technical problems solved, functions realized, and technical effects achieved of each module / unit / sub-unit in the device part embodiment are the same or similar to the implementation methods, technical problems solved, functions realized, and technical effects achieved of each corresponding step in the method part embodiment, and will not be repeated here.

[0198] According to an embodiment of the present disclosure, any multiple modules in the risk control device 800 or the risk control device 900 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0199] According to an embodiment of the present disclosure, at least one of the risk control device 800 or the risk control device 900 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or may be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the risk control device 800 or the risk control device 900 may be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function may be executed.

[0200] Fig.10 A block diagram of an electronic device suitable for implementing a risk control method for quantitative trading according to an embodiment of the present disclosure is schematically shown.

[0201] like Fig.10As shown, the electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage part 1008 into a random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0202] In RAM 1003, various programs and data required for the operation of electronic device 1000 are stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other via bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1002 and / or RAM 1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0203] According to an embodiment of the present disclosure, the electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to the bus 1004. The electronic device 1000 may further include one or more of the following components connected to the I / O interface 1005: an input portion 1006 including a keyboard, a mouse, etc.; an output portion 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1008 including a hard disk, etc.; and a communication portion 1009 including a network interface card such as a LAN card, a modem, etc. The communication portion 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage portion 1008 as needed.

[0204] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0205] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0206] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method provided by the embodiment of the present disclosure.

[0207] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 1001. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0208] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1009, and / or installed from the removable medium 1011. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0209] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0210] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0211] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0212] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A risk control method for quantitative trading, used for a unified risk control platform, including: Obtain all pending trading instructions in the quantitative trading system, where the pending trading instructions are in a pending transaction state; Determine the current transaction stage of each pending transaction instruction, wherein at least one risk control indicator rule is pre-configured for each transaction stage in the pending transaction state; Processing each pending transaction instruction based on the N risk control indicator rules in the current transaction stage to obtain N risk control indicator results; For each pending transaction instruction, if there are M risk control indicator results that do not meet the first constraint condition, a risk warning is sent to the quantitative trading system, and the quantitative trading system is configured to refuse to execute the pending transaction instruction in response to the risk warning, where N and M are both integers greater than or equal to 1, and M is less than or equal to N.

2. The method according to claim 1, wherein: The quantitative trading system is configured to process all pending trading instructions in a real-time trading environment based on real-time market data, and to perform all simulated trading in a simulation environment based on the real-time market data, wherein the simulation environment and the real-time trading environment are run in parallel; After processing each pending transaction instruction to obtain N risk control indicator results, the method further includes: The N risk control indicator results are sent to the quantitative trading system, and the quantitative trading system is configured to perform risk control on each simulated transaction in the simulation environment based on the N risk control indicator results and a second constraint condition, wherein the first constraint condition is different from the second constraint condition.

3. The method according to claim 2, wherein: After sending the N risk control indicator results to the quantitative trading system, the method further includes: Receiving the second constraint condition sent by the quantitative trading system, the quantitative trading system being configured to send the second constraint condition if the simulated trading result in the simulation environment meets the preset condition; The second constraint condition is used as a new first constraint condition to perform risk control on all the pending transaction instructions.

4. The method according to claim 1, wherein: Each quantitative trading instruction has a pre-trading stage and an in-process trading stage. The pre-trading stage includes the stage when any pending trading instruction of the transaction has not been placed in the market, and the in-process trading stage includes the stage when any pending trading instruction of the transaction has been placed in the market; The at least one risk control indicator rule pre-configured for each transaction stage in the pending transaction state includes: At least one corresponding risk control indicator rule is configured for the pre-transaction stage and the in-transaction stage respectively.

5. The method according to claim 4, wherein: The quantitative trading system is configured to run S quantitative trading strategies to process all pending trading instructions, where S is an integer greater than or equal to 1; The configuration of at least one corresponding risk control indicator rule for the pre-transaction stage and the in-transaction stage respectively includes: In the pre-trading stage or the in-trading stage, each configured risk control indicator rule is applicable to at least one quantitative trading strategy.

6. The method according to claim 5, wherein: The current transaction stage includes the pre-transaction stage or the in-transaction stage. Before processing each pending transaction instruction to obtain N risk control indicator results, the method further includes: Determine the quantitative trading strategy to which each pending trading instruction belongs; Based on the quantitative trading strategy to which each pending trading instruction belongs, the N risk control indicator rules are selected from at least one risk control indicator rule corresponding to the current trading stage.

7. The method according to claim 6, wherein: If there are M risk control indicator results that do not meet the first constraint condition, the pending transaction instruction is rejected, including: Stop running the quantitative trading strategy to which the pending trading instruction belongs.

8. A quantitative trading risk control method for a quantitative trading system, comprising: Sending all pending transaction instructions in a pending transaction state to a unified risk control center, wherein the unified risk control center is configured to execute the method according to any one of claims 1 to 7 for risk control; For each pending transaction instruction, if a risk warning sent by the unified risk control center is received, the pending transaction instruction will be rejected.

9. The method according to claim 8, wherein: The method further comprises: Process all pending trading instructions in a live trading environment based on real-time market data; Perform all simulated transactions in a simulation environment based on the real-time market data, wherein the simulation environment runs in parallel with the real-time environment; Receive N risk control indicator results sent by the unified risk control platform, and perform risk control on each simulated transaction in the simulation environment based on the N risk control indicator results and a second constraint condition, where the second constraint condition is different from the first constraint condition in the unified risk control platform.

10. The method according to claim 9, wherein: The method further comprises: If the simulated transaction result in the simulation environment meets the preset conditions, the second constraint condition is sent to the unified risk control center; The unified risk control center is configured to use the second constraint condition as a new first constraint condition to perform risk control on all the pending transaction instructions.

11. The method according to claim 10, wherein: After sending the second constraint condition to the unified risk control center, the method further includes: The constraint condition is updated based on the real-time market data to obtain an updated second constraint condition, and the second constraint condition before and after the update is different; In the simulation environment, risk control is performed on each simulated transaction based on the N risk control indicator results and the updated second constraint condition.

12. The method according to claim 8, wherein: The quantitative trading system includes an automatic quotation engine and a strategy configuration terminal, wherein the strategy configuration terminal is configured to run S quantitative trading strategies to process all the pending trading instructions, where S is an integer greater than or equal to 1; The method further comprises: Using the strategy configuration terminal to periodically send S heartbeat information to the automatic quotation engine, wherein the S heartbeat information corresponds to the S quantitative trading strategies one by one; When the automatic quotation engine does not receive any of the S heartbeat information within a predetermined time, an exception is processed for the corresponding quantitative trading strategy.

13. The method according to claim 12, wherein: The abnormal processing of the corresponding quantitative trading strategy includes: A cancellation order instruction is sent for the corresponding quantitative trading strategy, and the cancellation order instruction is used to cancel at least part of the pending trading instructions under the corresponding quantitative trading strategy.

14. A risk control system for quantitative trading, comprising: A unified risk control middle platform, configured to execute the method according to any one of claims 1 to 7, and to perform risk control on all pending transaction instructions in a pending transaction state in a quantitative trading system; The quantitative trading system is configured to execute the method according to any one of claims 8 to 13, and perform quantitative trading based on the risk control results of the unified risk control center.

15. A risk control device for quantitative trading, used for a unified risk control platform, comprising: An instruction acquisition module is used to acquire all pending transaction instructions in the quantitative trading system, wherein the pending transaction instructions are in a pending transaction state; A stage determination module, used to determine the current transaction stage of each pending transaction instruction, wherein at least one risk control indicator rule is pre-configured for each transaction stage in the pending transaction state; An indicator calculation module, used to process each pending transaction instruction based on the N risk control indicator rules in the current transaction stage to obtain N risk control indicator results; A risk warning module is used for sending a risk warning to the quantitative trading system for each pending transaction instruction if there are M risk control indicator results that do not meet the first constraint condition. The quantitative trading system is configured to refuse to execute the pending transaction instruction in response to the risk warning, where N and M are both integers greater than or equal to 1, and M is less than or equal to N.

16. A risk control device for quantitative trading, used in a quantitative trading system, comprising: An instruction sending module, used for sending all pending transaction instructions in a pending transaction state to a unified risk control center, wherein the unified risk control center is configured to execute the method according to any one of claims 1 to 7 for risk control; The risk control module is used to refuse to execute each pending transaction instruction if a risk warning sent by the unified risk control center is received.

17. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 10.

18. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 10.

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