CN109166041A

CN109166041A - Stock market's forward prediction method and system, computer system and readable storage medium storing program for executing

Info

Publication number: CN109166041A
Application number: CN201810999121.XA
Authority: CN
Inventors: 房磊
Original assignee: Beijing Jingdong Financial Technology Holding Co Ltd
Current assignee: Beijing Jingdong Financial Technology Holding Co Ltd
Priority date: 2018-08-29
Filing date: 2018-08-29
Publication date: 2019-01-08

Abstract

Present disclose provides a kind of stock market's forward prediction methods, the exponent data including obtaining the object time node of target stock market within a preset period of time, wherein include multiple timing nodes in preset time period；Corresponding first exponent data of each timing node in other time node is determined in preset time period according to the first weight based on the exponent data of object time node；Corresponding second exponent data of each timing node in other time node is determined in preset time period according to the second weight based on the exponent data of object time node；The corresponding deviation of each timing node is determined according to corresponding first exponent data of each timing node and the second exponent data；Hot value corresponding with each timing node is converted by the corresponding deviation of each timing node, wherein the corresponding hot value of each timing node is used to predict the trend characteristic of target stock market entirety market.The disclosure additionally provides a kind of stock market's forward prediction system, computer system and computer readable storage medium storing program for executing.

Description

Stock market's forward prediction method and system, computer system and readable storage medium storing program for executing

Technical field

This disclosure relates to which Internet technical field, more particularly, to a kind of stock market's forward prediction method and system, calculates Machine system and computer readable storage medium.

Background technique

In internet finance correlative technology field, some way can use in a manner of when quantifying to select to judge stock market Tendency situation, for example, tendency situation include but is not limited to go up or drop either shake.If it is determined that being to go up, then It buys in and holds；If it is determined that being drop, then sells and bring down stocks；If it is determined that being concussion, then cast high low suck, to be more than The earning rate of Holding strategy is simply bought in, so transaction is a kind of relatively high mode of doing business of earning rate when selecting.But it is intended to Accurate judgement stock market tendency has comparable difficulty.

Most of the implementation of tool is ex-post analysis when most of quantization is selected at present, i.e., after stock market information disclosure, It is maintained into database by the way of artificial operation or mechanical reptile crawl, shows historical data to investor, lean on experience Decision recommendation etc. before making Stock Market Forecasting with subjective judgement and throw.This mode relies on the update feelings of crawl data source to a certain extent Condition, the space that can optimize be it is continuous shorten the stock market that will be monitored disclose information update to associated databases time.But due to Time-lag effect, although stock market's ex-post analysis can obtain accurate data to a certain extent, lack it is perspective and predictive, and And subjective consciousness is stronger, it is difficult to avoid the weakness of human nature, such as greedy, frightened, idea of leaving things to chance, it is also difficult to overcome cognitive Bias etc.. Meanwhile it is higher to investor's competency profiling, need investor to have relevant financial knowledge etc..

Therefore, during realizing disclosure design, at least there are the following problems in the related technology for inventor's discovery:

Judge that the trend of stock market causes the investment decision of user at high cost using the relevant technologies.

Summary of the invention

In view of this, can present disclose provides a kind of stock market's forward prediction method and system, computer system and computer Read storage medium.

An aspect of this disclosure provides a kind of stock market's forward prediction method, including obtains target stock market in preset time The exponent data of object time node in section, wherein include multiple timing nodes in above-mentioned preset time period；Based on above-mentioned mesh The segmentum intercalaris when exponent data of mark timing node determines each in other time node in above-mentioned preset time period according to the first weight Corresponding first exponent data of point；When determining above-mentioned default according to the second weight based on the exponent data of above-mentioned object time node Between corresponding second exponent data of each timing node in other time node in section；It is corresponding according to above-mentioned each timing node First exponent data and the second exponent data determine the corresponding deviation of above-mentioned each timing node；And segmentum intercalaris when will be above-mentioned each The corresponding deviation of point is converted into hot value corresponding with above-mentioned each timing node, wherein above-mentioned each timing node is corresponding Hot value is used to predict the trend characteristic of above-mentioned target stock market entirety market.

In accordance with an embodiment of the present disclosure, the above method further includes determining above-mentioned first weight and above-mentioned second weight, including Obtain the exponent data of multiple first time nodes of the above-mentioned target stock market in first time period；When according to above-mentioned multiple first The exponent data of intermediate node is fitted to obtain above-mentioned first weight；Obtain multiple second of above-mentioned target stock market in second time period The exponent data of timing node, wherein the time span of above-mentioned second time period is shorter than the time span of above-mentioned first time period； And it is fitted to obtain above-mentioned second weight according to the exponent data of above-mentioned multiple second timing nodes.

In accordance with an embodiment of the present disclosure, the above method further includes when obtaining above-mentioned first using distributed task dispatching mode Between multiple first time nodes in section exponent data and above-mentioned second time period in multiple second timing nodes index Data.

In accordance with an embodiment of the present disclosure, by the corresponding deviation of above-mentioned each timing node be converted into it is above-mentioned each when segmentum intercalaris The corresponding hot value of point include will the corresponding deviation of above-mentioned each timing node according to the progress deviation amendment of default correction formula, obtain To deviation correction value corresponding with above-mentioned each timing node；Whether judge the corresponding deviation correction value of above-mentioned each timing node In targets threshold section；Judging the corresponding deviation correction value of the timing node not situation in above-mentioned targets threshold section Under, the hot value of corresponding timing node is determined as fixed hot value corresponding with the timing node；And judging the time In the case that the corresponding deviation correction value of node is in above-mentioned targets threshold section, the corresponding deviation of corresponding timing node is repaired Positive value calculates hot value corresponding with the timing node according to temperature conversion proportion.

In accordance with an embodiment of the present disclosure, it is converted into and above-mentioned each time by the corresponding deviation of above-mentioned each timing node After the corresponding hot value of node, the above method further includes visualizing one or more times in above-mentioned multiple timing nodes The hot value of node.

In accordance with an embodiment of the present disclosure, it is converted into and above-mentioned each time by the corresponding deviation of above-mentioned each timing node After the corresponding hot value of node, the above method further includes when determining each according to the corresponding hot value of above-mentioned each timing node First amount of increase and amount of decrease of intermediate node；The second of each timing node is determined according to the corresponding exponent data of above-mentioned each timing node Amount of increase and amount of decrease；And by the first amount of increase and amount of decrease of above-mentioned each timing node and above-mentioned second amount of increase and amount of decrease in a manner of tendency chart It is visualized.

Another aspect of the disclosure provides a kind of stock market's forward prediction system, including obtains module, the first determining mould Block, the second determining module, third determining module and conversion module.Module is obtained for obtaining target stock market within a preset period of time Object time node exponent data, wherein include multiple timing nodes in above-mentioned preset time period；First determining module is used Other time node in above-mentioned preset time period is determined according to the first weight in the exponent data based on above-mentioned object time node In corresponding first exponent data of each timing node；Second determining module is used for the index number based on above-mentioned object time node The corresponding second index number of each timing node in other time node is determined in above-mentioned preset time period according to according to the second weight According to；Third determining module is used to be determined according to corresponding first exponent data of above-mentioned each timing node and the second exponent data State the corresponding deviation of each timing node；And conversion module be used to convert the corresponding deviation of above-mentioned each timing node to The corresponding hot value of above-mentioned each timing node, wherein the corresponding hot value of above-mentioned each timing node is for predicting above-mentioned mesh Mark the trend characteristic of stock market's entirety market.

In accordance with an embodiment of the present disclosure, above system further includes the 4th determining module, for determine above-mentioned first weight and Above-mentioned second weight, above-mentioned 4th determining module include first acquisition unit, the first fitting unit, second acquisition unit and second Fitting unit.First acquisition unit is used to obtain the finger of multiple first time nodes of the above-mentioned target stock market in first time period Number data；First fitting unit is used to be fitted to obtain according to the exponent data of above-mentioned multiple first time nodes above-mentioned first power Weight；Second acquisition unit is used to obtain the index number of multiple second timing nodes of the above-mentioned target stock market in second time period According to, wherein the time span of above-mentioned second time period is shorter than the time span of above-mentioned first time period；And second fitting unit For being fitted to obtain above-mentioned second weight according to the exponent data of above-mentioned multiple second timing nodes.

In accordance with an embodiment of the present disclosure, above-mentioned first acquisition unit obtains above-mentioned first using distributed task dispatching mode The exponent data and above-mentioned second acquisition unit of multiple first time nodes in period use distributed task dispatching mode Obtain the exponent data of multiple second timing nodes in above-mentioned second time period.

In accordance with an embodiment of the present disclosure, above-mentioned conversion module includes amending unit, judging unit, determination unit and calculates single Member.Amending unit be used for will the corresponding deviation of above-mentioned each timing node according to the progress deviation amendment of default correction formula, obtain Deviation correction value corresponding with above-mentioned each timing node；Judging unit is for judging the corresponding deviation of above-mentioned each timing node Whether correction value is in targets threshold section；Determination unit is for judging the corresponding deviation correction value of timing node not above-mentioned In the case where in targets threshold section, the hot value of corresponding timing node is determined as fixed heat corresponding with the timing node Angle value；And computing unit is for judging situation of the corresponding deviation correction value of timing node in above-mentioned targets threshold section Under, the corresponding deviation correction value of corresponding timing node is calculated into temperature corresponding with the timing node according to temperature conversion proportion Value.

In accordance with an embodiment of the present disclosure, above system further includes the first display module.First display module be used for by It states the corresponding deviation of each timing node to be converted into after hot value corresponding with above-mentioned each timing node, on visual presentation State the hot value of one or more timing nodes in multiple timing nodes.

In accordance with an embodiment of the present disclosure, above system further includes the 5th determining module, the 6th determining module and the second displaying Module.5th determining module is used to be converted into and above-mentioned each timing node pair by the corresponding deviation of above-mentioned each timing node After the hot value answered, the first amount of increase and amount of decrease of each timing node is determined according to the corresponding hot value of above-mentioned each timing node Degree；6th determining module is used to determine that the second of each timing node rises according to the corresponding exponent data of above-mentioned each timing node Drop range degree；And second display module be used for the first amount of increase and amount of decrease of above-mentioned each timing node and above-mentioned second amount of increase and amount of decrease It is visualized in a manner of tendency chart.

Another aspect of the disclosure provides a kind of computer system, including one or more processors；Memory is used In the one or more programs of storage, wherein when said one or multiple programs are executed by said one or multiple processors, make It obtains said one or multiple processors realizes forward prediction method in stock market's as described above.

Another aspect of the disclosure provides a kind of computer readable storage medium, is stored thereon with executable instruction, The instruction makes processor realize forward prediction method in stock market's as described above when being executed by processor.

Another aspect of the present disclosure provides a kind of computer program, and the computer program, which includes that computer is executable, to be referred to It enables, described instruction is when executed for realizing forward prediction method in stock market's as described above.

In accordance with an embodiment of the present disclosure, because using the exponent data based on object time node according to different weights It determines in preset time period the corresponding exponent data of each timing node in other time node, and calculates each timing node pair The deviation answered converts the corresponding deviation of each timing node to the technological means of hot value corresponding with each timing node, Allow user that can understand views on broad market movements according to hot value, user need not comprehend financial term and empty forms hard to understand The theory analysis of elaborate section judges that the trend of stock market causes the investment of user to be determined using the relevant technologies so at least partially overcoming Plan technical problem at high cost, and then reached the time cost technical effect for decision of reducing investment outlay.

Detailed description of the invention

By referring to the drawings to the description of the embodiment of the present disclosure, the above-mentioned and other purposes of the disclosure, feature and Advantage will be apparent from, in the accompanying drawings:

Fig. 1 diagrammatically illustrates the example that can apply stock market's forward prediction method and system according to the embodiment of the present disclosure Property system architecture；

Fig. 2 diagrammatically illustrates the flow chart of stock market's forward prediction method according to the embodiment of the present disclosure；

Fig. 3 diagrammatically illustrates the flow chart of determination the first weight and the second weight according to the embodiment of the present disclosure；

Fig. 4 diagrammatically illustrates the schematic diagram of the distributed scheduling framework according to the embodiment of the present disclosure；

Fig. 5 diagrammatically illustrate according to the embodiment of the present disclosure convert the corresponding deviation of each timing node to each The flow chart of the corresponding hot value of timing node；

Fig. 6 diagrammatically illustrates the signal of the hot value of one timing node of visual presentation according to the embodiment of the present disclosure Figure；

Fig. 7 diagrammatically illustrates the flow chart of stock market's forward prediction method according to another embodiment of the disclosure；

Fig. 8 diagrammatically illustrates the schematic diagram of the visual presentation tendency chart according to the embodiment of the present disclosure；

Fig. 9 diagrammatically illustrates the block diagram of stock market's forward prediction system according to the embodiment of the present disclosure；

Figure 10 diagrammatically illustrates the block diagram of stock market's forward prediction system according to another embodiment of the disclosure；

Figure 11 diagrammatically illustrates the block diagram of the 4th determining module according to the embodiment of the present disclosure；

Figure 12 diagrammatically illustrates the block diagram of the conversion module according to the embodiment of the present disclosure；And

Figure 13 diagrammatically illustrates the computer system for being adapted for carrying out method as described above according to the embodiment of the present disclosure Block diagram.

Specific embodiment

Hereinafter, will be described with reference to the accompanying drawings embodiment of the disclosure.However, it should be understood that these descriptions are only exemplary , and it is not intended to limit the scope of the present disclosure.In the following detailed description, to elaborate many specific thin convenient for explaining Section is to provide the comprehensive understanding to the embodiment of the present disclosure.It may be evident, however, that one or more embodiments are not having these specific thin It can also be carried out in the case where section.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid Unnecessarily obscure the concept of the disclosure.

Term as used herein is not intended to limit the disclosure just for the sake of description specific embodiment.It uses herein The terms "include", "comprise" etc. show the presence of the feature, step, operation and/or component, but it is not excluded that in the presence of Or add other one or more features, step, operation or component.

There are all terms (including technical and scientific term) as used herein those skilled in the art to be generally understood Meaning, unless otherwise defined.It should be noted that term used herein should be interpreted that with consistent with the context of this specification Meaning, without that should be explained with idealization or excessively mechanical mode.

It, in general should be according to this using statement as " at least one in A, B and C etc. " is similar to Field technical staff is generally understood the meaning of the statement to make an explanation (for example, " system at least one in A, B and C " Should include but is not limited to individually with A, individually with B, individually with C, with A and B, with A and C, have B and C, and/or System etc. with A, B, C).Using statement as " at least one in A, B or C etc. " is similar to, generally come Saying be generally understood the meaning of the statement according to those skilled in the art to make an explanation (for example, " having in A, B or C at least One system " should include but is not limited to individually with A, individually with B, individually with C, with A and B, have A and C, have B and C, and/or the system with A, B, C etc.).It should also be understood by those skilled in the art that substantially arbitrarily indicating two or more The adversative conjunction and/or phrase of optional project shall be construed as either in specification, claims or attached drawing A possibility that giving including one of these projects, either one or two projects of these projects.For example, phrase " A or B " should A possibility that being understood to include " A " or " B " or " A and B ".

Embodiment of the disclosure provides a kind of stock market's forward prediction method, stock market's forward prediction system, computer system And computer readable storage medium.This method includes the index for obtaining the object time node of target stock market within a preset period of time Data, wherein include multiple timing nodes in preset time period；Exponent data based on object time node is according to the first weight Determine in preset time period corresponding first exponent data of each timing node in other time node；Based on object time node Exponent data determine in preset time period that each timing node corresponding second refers in other time node according to the second weight Number data；Determine that each timing node is corresponding according to corresponding first exponent data of each timing node and the second exponent data Deviation；Hot value corresponding with each timing node is converted by the corresponding deviation of each timing node, wherein segmentum intercalaris when each The corresponding hot value of point is used to predict the trend characteristic of target stock market entirety market.

Fig. 1 diagrammatically illustrates the example that can apply stock market's forward prediction method and system according to the embodiment of the present disclosure Property system architecture.It should be noted that being only the example that can apply the system architecture of the embodiment of the present disclosure shown in Fig. 1, with side The technology contents those skilled in the art understand that disclosure are helped, but are not meant to that the embodiment of the present disclosure may not be usable for other and set Standby, system, environment or scene.

As shown in Figure 1, system architecture 100 may include terminal device 101,102,103, network according to this embodiment 104 and server 105.Network 104 between terminal device 101,102,103 and server 105 to provide communication link Medium.Network 104 may include various connection types, such as wired and or wireless communications link etc..

User can be used terminal device 101,102,103 and be interacted by network 104 with server 105, to receive or send out Send message etc..Various telecommunication customer end applications, such as the application of shopping class, net can be installed on terminal device 101,102,103 (merely illustrative) such as the application of page browsing device, searching class application, instant messaging tools, mailbox client and/or social platform softwares.

Terminal device 101,102,103 can be the various electronic equipments with display screen and supported web page browsing, packet Include but be not limited to smart phone, tablet computer, pocket computer on knee and desktop computer etc..

Server 105 can be to provide the server of various services, such as utilize terminal device 101,102,103 to user The website browsed provides the back-stage management server (merely illustrative) supported.Back-stage management server can be to the use received The data such as family request analyze etc. processing, and by processing result (such as according to user's request or the webpage of generation, believe Breath or data etc.) feed back to terminal device.

It should be noted that forward prediction method in stock market's provided by the embodiment of the present disclosure generally can be by server 105 It executes.Correspondingly, forward prediction system in stock market's provided by the embodiment of the present disclosure generally can be set in server 105.This Stock market's forward prediction method provided by open embodiment can also by be different from server 105 and can with terminal device 101, 102,103 and/or server 105 communicate server or server cluster execute.Correspondingly, provided by the embodiment of the present disclosure Stock market's forward prediction system also can be set in be different from server 105 and can with terminal device 101,102,103 and/or clothes It is engaged in the server or server cluster that device 105 communicates.Alternatively, forward prediction method in stock market's provided by the embodiment of the present disclosure Can be executed by terminal device 101,102 or 103, or can also by be different from terminal device 101,102 or 103 other Terminal device executes.Correspondingly, forward prediction system in stock market's provided by the embodiment of the present disclosure also can be set in terminal device 101, it in 102 or 103, or is set in other terminal devices different from terminal device 101,102 or 103.

It should be understood that the number of terminal device, network and server in Fig. 1 is only schematical.According to realization need It wants, can have any number of terminal device, network and server.

Fig. 2 diagrammatically illustrates the flow chart of stock market's forward prediction method according to the embodiment of the present disclosure.

As shown in Fig. 2, this method includes operation S201~S205.

In operation S201, the exponent data of the object time node of target stock market within a preset period of time is obtained, wherein pre- If in the period including multiple timing nodes.

In accordance with an embodiment of the present disclosure, the type of target stock market without limitation, such as can be current A-share, H-share etc.. Target stock market is also possible to Shanghai and Shenzhen 300 or mark general 500 etc., and Shanghai and Shenzhen 300 refers to by the anti-of Shanghai and Shenzhen stock exchange joint publication The financial indicator of Hu-Shen 300 index establishment target and operation conditions is reflected, and can be index as the evaluation criterion of investment performance Change investment and index derivative product innovation provides basic condition.

By taking target stock market is A-share as an example, during preset time period can be on August on August 21st, 22,1 2017, Timing node can be each day of trade, and object time node can be the first day of trade of preset time period, such as in August, 2017 22, exponent data can be deep bid index, for example, on August 22nd, 2017 deep bid indexes are 3200 points.

In operation S202, determined based on the exponent data of object time node according to the first weight other in preset time period Corresponding first exponent data of each timing node in timing node.

In operation S203, determined based on the exponent data of object time node according to the second weight other in preset time period Corresponding second exponent data of each timing node in timing node.

In accordance with an embodiment of the present disclosure, the recent observed value of the observation period in preset time period has larger shadow to predicted value It ringing, it can more reflect the trend of recent market variation, greater weight value can be given for the observed value close to time span of forecast, for The range prediction phase, farther away observed value then accordingly gave lesser weighted value, adjusted each observed value to prediction with different weighted values It is worth role, predicted value is enable more approximately to reflect that the development trend in market future, the first weight can be used as close The weight of the observed value of time span of forecast, the second weight can be used as the weight of range prediction phase farther away observed value.

For example, 1, F_n: calculate long-term weighted moving average (such as the weighted moving average in 1 year of 300 closing price of Shanghai and Shenzhen Value)

F₁=close；

F₂=(2*close+199* (F₁))/201；

……

F_n=(2*close+199* (F_n-1)))/201。

Wherein, F₁=close is the exponent data of object time node, F_n=(2*close+199* (F_n-1)))/201 in Number can be used as the first weight.

2、E_n: calculate the short-term weighted moving average (such as a month weighted moving average) of 300 closing price of Shanghai and Shenzhen

E₁=close；

E₂=(2*close+29* (E₁))/31；

……

E_n=(2*close+29* (E_n-1))/31。

Wherein, E₁=close is the exponent data of object time node, E_n=(2*close+29* (E_n-1))/31 in number Word can be used as the second weight.

The number used in formula calculating can be the empirical value obtained by observing measuring and calculating for a long time, pass through these numbers The calculating of this method is participated in as weight, can allow predicted value more accurately close to overall trend situation.

In operation S204, when determining each according to corresponding first exponent data of each timing node and the second exponent data The corresponding deviation of intermediate node.

In accordance with an embodiment of the present disclosure, the corresponding deviation A of each timing node_nIt can be and counted in the following way It calculates:

A₁=0；

A₂=E₂-F₂；

……

A_n=E_n-F_n。

In accordance with an embodiment of the present disclosure, by introducing deviation, it can reflect the first weight and the second weight calculation obtain The degree of constituent parts value of statistical indicant difference size or the finger of deviation situation in data distribution dispersion degree, or reflection statistics for entire group Mark can enable predicted value closer to market true value by constantly reducing this deviation.

In operation S205, hot value corresponding with each timing node is converted by the corresponding deviation of each timing node, Wherein, the corresponding hot value of each timing node is used to predict the trend characteristic of target stock market entirety market.

In accordance with an embodiment of the present disclosure, the corresponding hot value of each timing node can predict target stock market to a certain extent Trend characteristic allows investor that can shift to an earlier date maximum probability before deep bid information announcing and judges tendency situation.For example, temperature rise 50 with On, start to buy in, hold entire rise section, enjoys bull market income.Temperature falls to 50 hereinafter, start only to be full of to sell, pocket for Peace, evades bear market Downside Risk.

In accordance with an embodiment of the present disclosure, customer investment is reduced by way of behavior finance and Financial Engineering buy stock Or the cost of decision making of fund, the investment tool when quantization of current quotations tendency is selected is shown by way of hot value.Mainly It is modeled by multiple-factor weight model, by analyzing domestic macroeconomic data index, capital market valuation data target, stock market The trading activity in market former years, and momentum model is combined, it carries out fraction re-computation and statistical analysis obtains investment hot value index.

By embodiment of the disclosure, because using the exponent data based on object time node according to different weights It determines in preset time period the corresponding exponent data of each timing node in other time node, and calculates each timing node pair The deviation answered converts the corresponding deviation of each timing node to the technological means of hot value corresponding with each timing node, Allow user that can understand views on broad market movements according to hot value, user need not comprehend financial term and empty forms hard to understand The theory analysis of elaborate section judges that the trend of stock market causes the investment of user to be determined using the relevant technologies so at least partially overcoming Plan technical problem at high cost, and then reached the time cost technical effect for decision of reducing investment outlay.

Below with reference to Fig. 3~Fig. 8, method shown in Fig. 2 is described further in conjunction with specific embodiments.

Fig. 3 diagrammatically illustrates the flow chart of determination the first weight and the second weight according to the embodiment of the present disclosure.

As shown in figure 3, determining that the first weight and the second weight include operation S206~S209.

In operation S206, the exponent data of multiple first time nodes of the target stock market in first time period is obtained.

In accordance with an embodiment of the present disclosure, first time period can be 2 years, 3 years or longer period.

In operation S207, it is fitted to obtain the first weight according to the exponent data of multiple first time nodes.

In operation S208, the exponent data of multiple second timing nodes of the target stock market in second time period is obtained, In, the time span of second time period is shorter than the time span of first time period.

In accordance with an embodiment of the present disclosure, the time span of second time period is shorter than the time span of first time period.For example, The time span of first time period is 2 years, and the time span of second time period can be 1 month.Under normal circumstances, the second time Section can be recent a period of time when fitting.

In operation S209, it is fitted to obtain the second weight according to the exponent data of multiple second timing nodes.

By embodiment of the disclosure, the time span of second time period is shorter than the time span of first time period, with not Same weighted value adjusts each index value to predicted value role, and predicted value is enable more approximately to reflect the hair in market future Exhibition trend.

According to an embodiment of the invention, multiple the in first time period can be obtained using distributed task dispatching mode The exponent data of multiple second timing nodes in the exponent data and second time period of one timing node.

According to an embodiment of the invention, distributed scheduling can use quartz framework, uses and provided by boundary of database The scheduling strategy in source.By T-1 days stock market datas of distributed task dispatching timing acquisition, investor can drape over one's shoulders in deep bid information Maximum probability judges tendency situation in advance before dew.Operation distributed task dispatching core algorithm module calculates daily deep bid hot value And ups and downs situation is prejudged out with this, database and redis caching are stored data into, is carried out finally by UI display module visual Change and shows.

Fig. 4 diagrammatically illustrates the schematic diagram of the distributed scheduling framework according to the embodiment of the present disclosure.

As shown in figure 4, the operation that each server is all based on the same Database lock can by taking 300 data source of Shanghai and Shenzhen as an example To guarantee data uniqueness, the asynchronous operation of multiple databases at the same time ensure that the High Availabitity row of service, distributed task scheduling The utilization of scheduler module ensure that and largely dispatch the case where data are not in repetitive schedule in initialization data, can also protect Card is used for core calculations in stipulated time punctual errorless 300 data of scheduling Shanghai and Shenzhen in the future, ensure that the high availability of system.

Fig. 5 diagrammatically illustrate according to the embodiment of the present disclosure convert the corresponding deviation of each timing node to each The flow chart of the corresponding hot value of timing node.

As shown in figure 5, converting hot value packet corresponding with each timing node for the corresponding deviation of each timing node Include operation S2051~S2054.

In operation S2051, the corresponding deviation of each timing node is subjected to deviation amendment according to default correction formula, is obtained Deviation correction value corresponding with each timing node.

In accordance with an embodiment of the present disclosure, the corresponding deviation of each timing node deviation is carried out according to default correction formula to repair It just can be and calculated in the following way:

4、B_n: the index short-term averaging of deviation

B₁=E₁；

B₂=(2*A₂+ 8* (B_2-1))/10；

……

B_n=(2*A_n+ 8* (B_n-₁))/10。

5、D_n: short-term deviation

D₁=A₁-B₁；

D₂=A₂-B₂；

……

D_n=A_n-B_n。

6, RD: the deviation for amplifying radix is corrected

RD₁=D₁*3+3；

……

RD_n=D_n*3+3。

In operation S2052, judge the corresponding deviation correction value of each timing node whether in targets threshold section.

In accordance with an embodiment of the present disclosure, targets threshold section can be by obtaining after testing for a long time, for example, target Threshold interval is (- 200,200).After obtaining deviation correction value corresponding with each timing node, if deviation correction value (RD) it is greater than 200, hot value can be 90；If deviation correction value (RD) is less than -200, hot value can be 10.

In operation S2053, in the case where judging the corresponding deviation correction value of timing node not in targets threshold section, The hot value of corresponding timing node is determined as fixed hot value corresponding with the timing node.

It, will in the case where judging that the corresponding deviation correction value of timing node is in targets threshold section in operation S2054 The corresponding corresponding deviation correction value of timing node calculates hot value corresponding with the timing node according to temperature conversion proportion.

In accordance with an embodiment of the present disclosure, when deviation correction value (RD) is in (- 200,200) section, temperature conversion proportion can To calculate by 10+0.2* (RD+200), the hot value after conversion can be integer.

Embodiment through the invention, deviation correction value can be used for amplifying radix, improve the accuracy of hot value, reach Effectively determine the development trend in market future.

According to an embodiment of the invention, corresponding with each timing node converting the corresponding deviation of each timing node to Hot value after, visualize in multiple timing nodes the hot value of one or more timing nodes.

According to an embodiment of the invention, if value is 1 between hot spot, and multirow feelings are seen in expression when hot value is more than or equal to 50, It can be prompted when visualizing with red background, be that value is 0 between hot spot less than 50, indicate to see null feelings, visualize It can be prompted when displaying with blue background.That is, the background colour in tactful tendency section is blue, when more null values when more null values are 0 When being 1, the background colour in tactful tendency section is red.

Fig. 6 diagrammatically illustrates the signal of the hot value of one timing node of visual presentation according to the embodiment of the present disclosure Figure.

As shown in fig. 6, hot value is equal to 49, it is believed that be that stock market continues wavy market.

According to an embodiment of the invention, according to can from the point of view of the trend characteristic subdivision of hot value prediction target stock market entirety market To be following quantification manner:

(1) 50 or more market temperature represent market and are likely to enter new ascendant trend, and deep bid systematicness investment opportunity can Can occur.

(2) temperature is prime investment section between 50-55: market temperature returns to 50 or more, represents deep bid in future one Section time trend direction, temperature indicate that market just enters rebound between 50-55 degree, and market does not start also to rise sharply at this time, city Field tendency is more flat, is preferably to buy in section.

(3) temperature is more than 65 viewpoints: temperature is more than 65 degree, represents market and initially enters very surging rise state, can To represent a kind of performance of short-term market overheat.If this performance does not adjust, market will rise steadily, and hit new peak repeatly.So " the big bull market " often said will be constituted.Another angle, if market future is not bull market, more than 65 degree, it is possible to Occur facing the performance of short-term market readjustment.

(4) 0-40 degree, which represents market and is in, accelerates drop process, illustrates that whole market is in systematic risk, Suo Youhang Industry is all fallen killing, and is preferably not involved in.

(5) 40-50 degree represents market off trend and slows down, into the concussion section of limited rise.This section, surging neck The industry that rises will show one's promises, and the following new market will rise industry expansion in these necks, how to track and be detailed in theme temperature.

(6) 50 degree of lines of demarcation.Market returns to 50 degree or more, and representing market will close to an end from concussion sideways movement, opens Begin new up-trend.Therefore the section of most preferably buying in of single fund or equity investment is exactly that will go up in market, and do not have also Before rising sharply (being best purchase section between 50-55).

According to an embodiment of the invention, the front-end technology of html+div+css, auxiliary can be used by visualizing module It using the asynchronous loading technique of ajax, is exchanged by carrying out low volume data with server on backstage, it is different that ajax can be such that webpage realizes Step updates.This means that can be updated, enhance to certain part of webpage in the case where not reloading entire webpage The ease for use that data are shown.Html is a kind of hypertext markup language, and it is non-to may include picture, link or even music, program etc. Text element.Div is the location technology in a kind of cascading style sheets, is usually used in combination block grade element, will pass through style sheet These elements are formatted.Css is a kind of computer language for showing the files pattern such as html, can be in webpage The typesetting of element position carries out Pixel-level and accurately controls, and supports almost all of font size pattern, possess to web object and The ability of model pattern editor.Ajax is a kind of in the case where being not necessarily to reload entire webpage, being capable of update section subnetting page Technology.

Embodiment through the invention clearly shows the complicated data elements such as simple page number and figure Out, it appears that it is more intuitive, vivider, data experience property can be enhanced.

Fig. 7 diagrammatically illustrates the flow chart of stock market's forward prediction method according to another embodiment of the disclosure.

After converting hot value corresponding with each timing node for the corresponding deviation of each timing node, such as Fig. 7 Shown, this method includes operation S210~S212.

In operation S210, the first amount of increase and amount of decrease of each timing node is determined according to the corresponding hot value of each timing node Degree.

In operation S211, the second amount of increase and amount of decrease of each timing node is determined according to the corresponding exponent data of each timing node Degree.

Operation S212, by the first amount of increase and amount of decrease of each timing node and the second amount of increase and amount of decrease in a manner of tendency chart into Row visualizes.

According to an embodiment of the invention, the history of obtained temperature Value Data and target stock market that temperature strategy prejudges is referred to The data visualization of number data tendency charts is shown, can a daily point, and clearly indicate ups and downs section, overall trend It is very clear.

Fig. 8 diagrammatically illustrates the schematic diagram of the visual presentation tendency chart according to the embodiment of the present disclosure.As shown in figure 8, Ordinate indicates that amount of increase and amount of decrease, abscissa indicate the time, and the Trendline in figure respectively indicates the ups and downs being calculated with hot value Trend and the ups and downs trend being calculated with stock market's history index data.

Embodiment through the invention, according to the follow-up inspection of temperature signal backtracking and firm offer exponent data, by mostly empty The form visualization in section shows temperature signal strategy tendency chart.It is accumulative ups and downs letter occur by long-term follow observation in recent years Numbers 33 times, wherein be expected to rise signal 16 times, successfully issue 14 times of being expected to rise；It sees spacing wave 17 times, sees empty success 16 times, through the invention Success judges 30 ups and downs, and temperature signal accuracy rate is 90.1% or so.

Fig. 9 diagrammatically illustrates the block diagram of stock market's forward prediction system according to the embodiment of the present disclosure.

As shown in figure 9, stock market's forward prediction system 300 is including obtaining module 301, the first determining module 302, second determines Module 303, third determining module 304 and conversion module 305.

The exponent data that module 301 is used to obtain the object time node of target stock market within a preset period of time is obtained, In, it include multiple timing nodes in preset time period.

First determining module 302 is used to determine preset time according to the first weight based on the exponent data of object time node Corresponding first exponent data of each timing node in other time node in section.

Second determining module 303 is used to determine preset time according to the second weight based on the exponent data of object time node Corresponding second exponent data of each timing node in other time node in section.

Third determining module 304 is used for true according to corresponding first exponent data of each timing node and the second exponent data Determine the corresponding deviation of each timing node.

Conversion module 305 is used to convert temperature corresponding with each timing node for the corresponding deviation of each timing node Value, wherein the corresponding hot value of each timing node is used to predict the trend characteristic of target stock market entirety market.

Figure 10 diagrammatically illustrates the block diagram of stock market's forward prediction system according to another embodiment of the disclosure.

As shown in Figure 10, stock market's forward prediction system 300 further includes the 4th determining module 306, for determining the first weight With the second weight.

Figure 11 diagrammatically illustrates the block diagram of the 4th determining module according to the embodiment of the present disclosure.

As shown in figure 11, the 4th determining module 306 includes first acquisition unit 3061, the first fitting unit 3062, second Acquiring unit 3063 and the second fitting unit 3064.

First acquisition unit 3061 is used to obtain the finger of multiple first time nodes of the target stock market in first time period Number data.

First fitting unit 3062 according to the exponent data of multiple first time nodes for being fitted to obtain the first weight.

Second acquisition unit 3063 is used to obtain the finger of multiple second timing nodes of the target stock market in second time period Number data, wherein the time span of second time period is shorter than the time span of first time period.

Second fitting unit 3064 according to the exponent data of multiple second timing nodes for being fitted to obtain the second weight.

In accordance with an embodiment of the present disclosure, first acquisition unit 3061 is obtained at the first time using distributed task dispatching mode The exponent data and second acquisition unit 3063 of multiple first time nodes in section are obtained using distributed task dispatching mode The exponent data of multiple second timing nodes in second time period.

By embodiment of the disclosure, the utilization of distributed task dispatching module be ensure that a large amount of in initialization data The case where data are not in repetitive schedule is dispatched, electricity can guarantee in the future in the stipulated time punctual errorless number of scheduling Shanghai and Shenzhen 300 According to core calculations are used for, the high availability of system ensure that.

Figure 12 diagrammatically illustrates the block diagram of the conversion module according to the embodiment of the present disclosure.

As shown in figure 12, conversion module 305 includes amending unit 3051, judging unit 3052, determination unit 3053 and meter Calculate unit 3054.

Amending unit 3051 is used to the corresponding deviation of each timing node carrying out deviation amendment according to default correction formula, Obtain deviation correction value corresponding with each timing node.

Whether judging unit 3052 is for judging the corresponding deviation correction value of each timing node in targets threshold section.

Determination unit 3053 is for judging the corresponding deviation correction value of the timing node not feelings in targets threshold section Under condition, the hot value of corresponding timing node is determined as fixed hot value corresponding with the timing node.

Computing unit 3054 is for judging situation of the corresponding deviation correction value of timing node in targets threshold section Under, the corresponding deviation correction value of corresponding timing node is calculated into temperature corresponding with the timing node according to temperature conversion proportion Value.

In accordance with an embodiment of the present disclosure, stock market's forward prediction system 300 further includes the first display module 307.First shows Module 307 is used for after converting hot value corresponding with each timing node for the corresponding deviation of each timing node, can The hot value of one or more timing nodes in multiple timing nodes is shown depending on changing.

In accordance with an embodiment of the present disclosure, stock market's forward prediction system 300 further includes that the 5th determining module the 308, the 6th determines Module 309, the second display module 310.

5th determining module 308 be used for convert the corresponding deviation of each timing node to it is corresponding with each timing node Hot value after, the first amount of increase and amount of decrease of each timing node is determined according to the corresponding hot value of each timing node.

6th determining module 309 is used to determine the of each timing node according to the corresponding exponent data of each timing node Two amounts of increase and amount of decrease.

Second display module 310 is used for the first amount of increase and amount of decrease of each timing node and the second amount of increase and amount of decrease with tendency chart Mode visualized.

It is module according to an embodiment of the present disclosure, submodule, unit, any number of or in which any more in subelement A at least partly function can be realized in a module.It is single according to the module of the embodiment of the present disclosure, submodule, unit, son Any one or more in member can be split into multiple modules to realize.According to the module of the embodiment of the present disclosure, submodule, Any one or more in unit, subelement can at least be implemented partly as hardware circuit, such as field programmable gate Array (FPGA), programmable logic array (PLA), system on chip, the system on substrate, the system in encapsulation, dedicated integrated electricity Road (ASIC), or can be by the hardware or firmware for any other rational method for integrate or encapsulate to circuit come real Show, or with any one in three kinds of software, hardware and firmware implementations or with wherein any several appropriately combined next reality It is existing.Alternatively, can be at least by part according to one or more of the module of the embodiment of the present disclosure, submodule, unit, subelement Ground is embodied as computer program module, when the computer program module is run, can execute corresponding function.

For example, obtaining module 301, the first determining module 302, the second determining module 303, third determining module 304 and turning Change module 305 in it is any number of may be incorporated in a module/unit/subelement realize or it is therein any one Module/unit/subelement can be split into multiple module/unit/subelements.Alternatively, in these module/unit/subelements One or more modules/unit/subelement at least partly function can be with other modules/unit/subelement at least portion Point function combines, and realizes in a module/unit/subelement.In accordance with an embodiment of the present disclosure, module 301, the are obtained At least one of one determining module 302, the second determining module 303, third determining module 304 and conversion module 305 can be down to It is implemented partly as hardware circuit, such as field programmable gate array (FPGA), programmable logic array (PLA), on piece less The system in system, encapsulation, specific integrated circuit (ASIC) in system, substrate, or can by circuit carry out it is integrated or The hardware such as any other rational method or firmware of encapsulation realize, or with three kinds of software, hardware and firmware implementations In any one or several appropriately combined realized with wherein any.Alternatively, obtain module 301, the first determining module 302, At least one of second determining module 303, third determining module 304 and conversion module 305 can be at least at least partially implemented Corresponding function can be executed when the computer program module is run for computer program module.

Figure 13 diagrammatically illustrates the computer system for being adapted for carrying out method as described above according to the embodiment of the present disclosure Block diagram.Computer system shown in Figure 13 is only an example, should not function and use scope to the embodiment of the present disclosure Bring any restrictions.

It as shown in figure 13, include processor 501 according to the computer system of the embodiment of the present disclosure 500, it can be according to depositing Storage is loaded into random access storage device (RAM) 503 in the program in read-only memory (ROM) 502 or from storage section 508 Program and execute various movements appropriate and processing.Processor 501 for example may include general purpose microprocessor (such as CPU), Instruction set processor and/or related chip group and/or special microprocessor (for example, specific integrated circuit (ASIC)), etc..Place Reason device 501 can also include the onboard storage device for caching purposes.Processor 501 may include for executing according to the disclosure Single treatment unit either multiple processing units of the different movements of the method flow of embodiment.

In RAM 503, it is stored with system 500 and operates required various programs and data.Processor 501, ROM 502 with And RAM 503 is connected with each other by bus 504.Processor 501 is held by executing the program in ROM 502 and/or RAM 503 The various operations gone according to the method flow of the embodiment of the present disclosure.It is noted that described program also can store except ROM 502 In one or more memories other than RAM 503.Processor 501 can also be stored in one or more of by execution Program in memory executes the various operations of the method flow according to the embodiment of the present disclosure.

In accordance with an embodiment of the present disclosure, system 500 can also include input/output (I/O) interface 505, input/output (I/O) interface 505 is also connected to bus 504.System 500 can also include be connected to I/O interface 505 with one in lower component Item is multinomial: the importation 506 including keyboard, mouse etc.；Including such as cathode-ray tube (CRT), liquid crystal display (LCD) Deng and loudspeaker etc. output par, c 507；Storage section 508 including hard disk etc.；And including such as LAN card, modulatedemodulate Adjust the communications portion 509 of the network interface card of device etc..Communications portion 509 executes communication process via the network of such as internet. Driver 510 is also connected to I/O interface 505 as needed.Detachable media 511, such as disk, CD, magneto-optic disk, semiconductor Memory etc. is mounted on as needed on driver 510, in order to be pacified as needed from the computer program read thereon It is packed into storage section 508.

In accordance with an embodiment of the present disclosure, computer software journey may be implemented as according to the method flow of the embodiment of the present disclosure Sequence.For example, embodiment of the disclosure includes a kind of computer program product comprising be carried on computer readable storage medium Computer program, which includes the program code for method shown in execution flow chart.In such implementation In example, which can be downloaded and installed from network by communications portion 509, and/or from detachable media 511 It is mounted.When the computer program is executed by processor 501, the above-mentioned function limited in the system of the embodiment of the present disclosure is executed Energy.In accordance with an embodiment of the present disclosure, system as described above, unit, module, unit etc. can pass through computer program Module is realized.

The disclosure additionally provides a kind of computer readable storage medium, which can be above-mentioned reality It applies included in equipment/device/system described in example；Be also possible to individualism, and without be incorporated the equipment/device/ In system.Above-mentioned computer-readable medium carries one or more program, when said one or multiple programs are performed When, realize the method according to the embodiment of the present disclosure.

In accordance with an embodiment of the present disclosure, computer readable storage medium can be computer-readable signal media or calculating Machine readable storage medium storing program for executing either the two any combination.Computer readable storage medium for example can be --- but it is unlimited In system, device or the device of --- electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor, or any above combination.It calculates The more specific example of machine readable storage medium storing program for executing can include but is not limited to: have the electrical connection, portable of one or more conducting wires Formula computer disk, hard disk, random access storage device (RAM), read-only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory device or The above-mentioned any appropriate combination of person.In the disclosure, computer readable storage medium can be it is any include or storage program Tangible medium, which can be commanded execution system, device or device use or in connection.And in this public affairs In opening, computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal, In carry computer-readable program code.The data-signal of this propagation can take various forms, including but not limited to Electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer-readable Any computer readable storage medium other than storage medium, the computer readable storage medium can send, propagate or pass It is defeated to be used for by the use of instruction execution system, device or device or program in connection.Computer-readable storage medium The program code for including in matter can transmit with any suitable medium, including but not limited to: wireless, wired, optical cable, radio frequency letter Number etc. or above-mentioned any appropriate combination.

For example, in accordance with an embodiment of the present disclosure, computer readable storage medium may include above-described ROM 502 And/or one or more memories other than RAM 503 and/or ROM 502 and RAM 503.

Flow chart and block diagram in attached drawing are illustrated according to the system of the various embodiments of the disclosure, method and computer journey The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation A part of one module, program segment or code of table, a part of above-mentioned module, program segment or code include one or more Executable instruction for implementing the specified logical function.It should also be noted that in some implementations as replacements, institute in box The function of mark can also occur in a different order than that indicated in the drawings.For example, two boxes succeedingly indicated are practical On can be basically executed in parallel, they can also be executed in the opposite order sometimes, and this depends on the function involved.Also it wants It is noted that the combination of each box in block diagram or flow chart and the box in block diagram or flow chart, can use and execute rule The dedicated hardware based systems of fixed functions or operations is realized, or can use the group of specialized hardware and computer instruction It closes to realize.

It will be understood by those skilled in the art that the feature recorded in each embodiment and/or claim of the disclosure can To carry out multiple combinations or/or combination, even if such combination or combination are not expressly recited in the disclosure.Particularly, exist In the case where not departing from disclosure spirit or teaching, the feature recorded in each embodiment and/or claim of the disclosure can To carry out multiple combinations and/or combination.All these combinations and/or combination each fall within the scope of the present disclosure.

Embodiment of the disclosure is described above.But the purpose that these embodiments are merely to illustrate that, and It is not intended to limit the scope of the present disclosure.Although respectively describing each embodiment above, but it is not intended that each reality Use cannot be advantageously combined by applying the measure in example.The scope of the present disclosure is defined by the appended claims and the equivalents thereof.It does not take off From the scope of the present disclosure, those skilled in the art can make a variety of alternatives and modifications, these alternatives and modifications should all fall in this Within scope of disclosure.

Claims

1. a kind of stock market's forward prediction method, comprising:

Obtain the exponent data of the object time node of target stock market within a preset period of time, wherein in the preset time period Including multiple timing nodes；

Other time in the preset time period is determined according to the first weight based on the exponent data of the object time node Corresponding first exponent data of each timing node in point；

Other time in the preset time period is determined according to the second weight based on the exponent data of the object time node Corresponding second exponent data of each timing node in point；

Each timing node is determined according to corresponding first exponent data of each timing node and the second exponent data Corresponding deviation；And

Hot value corresponding with each timing node is converted by the corresponding deviation of each timing node, wherein institute The corresponding hot value of each timing node is stated for predicting the trend characteristic of the target stock market entirety market.

2. according to the method described in claim 1, wherein, the method also includes determination first weights and second power Weight, comprising:

Obtain the exponent data of multiple first time nodes of the target stock market in first time period；

It is fitted to obtain first weight according to the exponent data of the multiple first time node；

Obtain the exponent data of multiple second timing nodes of the target stock market in second time period, wherein described second The time span of period is shorter than the time span of the first time period；And

It is fitted to obtain second weight according to the exponent data of the multiple second timing node.

3. according to the method described in claim 2, wherein, the method also includes:

Obtained using distributed task dispatching mode multiple first time nodes in the first time period exponent data and The exponent data of multiple second timing nodes in the second time period.

4. according to the method described in claim 1, wherein, by the corresponding deviation of each timing node be converted into it is described every The corresponding hot value of a timing node includes:

The corresponding deviation of each timing node is subjected to deviation amendment according to default correction formula, obtain with it is described each when The corresponding deviation correction value of intermediate node；

Judge the corresponding deviation correction value of each timing node whether in targets threshold section；

In the case where judging the corresponding deviation correction value of timing node not in the targets threshold section, by the corresponding time The hot value of node is determined as fixed hot value corresponding with the timing node；And

In the case where judging that the corresponding deviation correction value of timing node is in the targets threshold section, segmentum intercalaris when will be corresponding The corresponding deviation correction value of point calculates hot value corresponding with the timing node according to temperature conversion proportion.

5. according to the method described in claim 1, wherein, by the corresponding deviation of each timing node be converted into it is described After the corresponding hot value of each timing node, the method also includes:

Visualize the hot value of one or more timing nodes in the multiple timing node.

6. according to the method described in claim 1, wherein, by the corresponding deviation of each timing node be converted into it is described After the corresponding hot value of each timing node, the method also includes:

The first amount of increase and amount of decrease of each timing node is determined according to the corresponding hot value of each timing node；

The second amount of increase and amount of decrease of each timing node is determined according to the corresponding exponent data of each timing node；And

First amount of increase and amount of decrease of each timing node and second amount of increase and amount of decrease are carried out visually in a manner of tendency chart Change and shows.

7. a kind of stock market's forward prediction system, comprising:

Module is obtained, for obtaining the exponent data of the object time node of target stock market within a preset period of time, wherein described It include multiple timing nodes in preset time period；

First determining module, when for determining described default according to the first weight based on the exponent data of the object time node Between corresponding first exponent data of each timing node in other time node in section；

Second determining module, when for determining described default according to the second weight based on the exponent data of the object time node Between corresponding second exponent data of each timing node in other time node in section；

Third determining module, for being determined according to corresponding first exponent data of each timing node and the second exponent data The corresponding deviation of each timing node；And

Conversion module, for converting heat corresponding with each timing node for the corresponding deviation of each timing node Angle value, wherein the corresponding hot value of each timing node is used to predict the trend characteristic of the target stock market entirety market.

8. system according to claim 7, wherein the system also includes the 4th determining modules, for determining described One weight and second weight, the 4th determining module include:

First acquisition unit, for obtaining the index number of multiple first time nodes of the target stock market in first time period According to；

First fitting unit obtains first weight for being fitted according to the exponent data of the multiple first time node；

Second acquisition unit, for obtaining the index number of multiple second timing nodes of the target stock market in second time period According to, wherein the time span of the second time period is shorter than the time span of the first time period；And

Second fitting unit obtains second weight for being fitted according to the exponent data of the multiple second timing node.

9. system according to claim 8, wherein the first acquisition unit is obtained using distributed task dispatching mode The exponent data and the second acquisition unit of multiple first time nodes in the first time period use distributed task scheduling Scheduling mode obtains the exponent data of multiple second timing nodes in the second time period.

10. system according to claim 7, wherein the conversion module includes:

Amending unit, for will the corresponding deviation of each timing node according to the progress deviation amendment of default correction formula, obtain To deviation correction value corresponding with each timing node；

Judging unit, for judging the corresponding deviation correction value of each timing node whether in targets threshold section；

Determination unit, for judging the corresponding deviation correction value of the timing node not situation in the targets threshold section Under, the hot value of corresponding timing node is determined as fixed hot value corresponding with the timing node；And

Computing unit is used in the case where judging that the corresponding deviation correction value of timing node is in the targets threshold section, The corresponding deviation correction value of corresponding timing node is calculated into hot value corresponding with the timing node according to temperature conversion proportion.

11. system according to claim 7, wherein the system also includes:

First display module, for being converted into and each timing node pair by the corresponding deviation of each timing node After the hot value answered, the hot value of one or more timing nodes in the multiple timing node is visualized.

12. system according to claim 7, wherein the system also includes:

5th determining module, for being converted into and each timing node pair by the corresponding deviation of each timing node After the hot value answered, the first amount of increase and amount of decrease of each timing node is determined according to the corresponding hot value of each timing node Degree；

6th determining module, for determining the second of each timing node according to the corresponding exponent data of each timing node Amount of increase and amount of decrease；And

Second display module, for by the first amount of increase and amount of decrease of each timing node and second amount of increase and amount of decrease with trend The mode of figure is visualized.

13. a kind of computer system, comprising:

One or more processors；

Memory, for storing one or more programs,

Wherein, when one or more of programs are executed by one or more of processors, so that one or more of Processor realizes forward prediction method in stock market's described in any one of claims 1 to 6.

14. a kind of computer readable storage medium, is stored thereon with executable instruction, which makes to handle when being executed by processor Device realizes forward prediction method in stock market's described in any one of claims 1 to 6.