JP2002183465A - Method of graphing activity in financial market - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a computer execution method for displaying an individual quantity element of activity of time/volume distribution corresponding to different prices in the market by superposing it on a conventional OHLC price-time chart. SOLUTION: Plural bars on the price-time chart are plotted and one of the bars is taken out of the chart in order to make a frequency distribution diagram. The frequency distribution diagram divides the highest prices and the lowest prices of the bars into plural individual estimated price sections. The frequency distribution diagram records a quantity of dealing activity generated in a time period displayed by the bar in the respective individual price sections, and a set of individual market inside elements is obtained from the frequency distribution diagram. The set of the individual market inside elements contains a continuous price range having considerably high dealing activity, a price section having maximum dealing activity, and a continuous price range having considerably low dealing activity. A geometrical diagram is overlapped on the bars and the price-time chart overlapped with the geometrical diagram is displayed to the user.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of creating a chart by executing a computer, that is, using time and volume distribution as quantitative factors, respectively, and analyzing traded instruments (instruments) in a financial market. The present invention relates to a method used for graphing a motion and overlaying the graph on a conventional price-time table.

[0002]

2. Description of the Related Art In financial chart plotting, a bar chart, a Japanese candlestick chart (Ja
The two price-time chart formats of the panese Candlestick Chart are the most widely used by traders and analyzers to predict future price movements. In these two types of charts, each bar is a time frame
In a specific time section called (Time frame), the opening, high, low and closing prices (hereinafter, OHLC) of financial instruments (for example, stocks, indices, currencies) are shown. These O
Since the time-series analysis of prices based on HLC has already evolved into thousands of methods and technologies, all of them can be said to be technical analysis in general.

However, for various financial products, between the start and end of the market, and between high and low prices,
Many movements and phenomena occur, which are useful information to monitor and control the overall market conditions. For example, information such as the cumulative range of the market dynamics, the transaction price of the maximum trading volume, and the change trend of the market when the price reaches near a certain high or low price can be cited. As is well known, such market internal information, although not found in conventional charts, is widely used as a trading tactic between traders and analyzers.

Conventional OHLC charts, which only display such OHLC prices, obviously cannot provide a complete chart including potential market conditions. This is because an intermediate price change process from the start to the end of the transaction is ignored. Usually, if a trader wants to have a track of these changes in market inside information,
They have to rely on manual processes by redundant and tedious humans. For example, they observe price fluctuations from an electronic bulletin board and record the information in a diary.

As described above, for a particular bar, it is not possible to obtain delicate market inside information from the price of a simple OHLC, but by analyzing the trading volume and time spent on the price at that bar. This information can be obtained by inferring and deducing. For example, by making a frequency distribution chart and recording the unit time / volume at each price in the bar, it is possible to easily obtain information including price ranges of high price movement, low price movement and maximum volume movement. Can be identified. Also, different statistical parameters can be calculated based on this distribution. If this child set of information is graphed and superimposed on a conventional OHLC chart using simple geometric figures, for example, colored points or rectangles, one new type of chart is formed. You.

[0006] By making the new chart formed by the present invention as similar as possible to the conventional chart, traders who are familiar with the conventional chart feel unfamiliar with the new chart. Without doing so, more information can be obtained.

[0007]

SUMMARY OF THE INVENTION One object of the present invention, which has been made in view of the above background, is to separate the individual quantification factors of market internal activity with respect to the time / volume distribution corresponding to different prices into the conventional method. It is to enlarge the conventional OHLC price-time chart by displaying it over the OHLC price-time chart.

[0008] Thus, one of the objects of the present invention is to identify at least one corresponding price level. For each bar in the price-time chart, the level indicates a large amount of trading activity, which is called a modal point. The trading activity may be volume, or the time a transaction has spent on one price in the market, or both.

Another object of the present invention is to provide at least one
To confirm two consecutive price ranges. In the price-time chart, within each corresponding bar, the range includes significant trading activity, which is referred to as a Dence Area. Another object of the present invention is to identify a contiguous price range that most trading activities correspond to, thereby identifying a reasonable market value for the bar, and refer to this range as the Active Range.

It is a further object of the present invention to ascertain a range of continuous prices at both ends of the bar that includes minimal trading activity (called Extreme Tails). Those skilled in the art will recognize that those whose prices are close to the high or low neighborhood of the bar have minimal trading activity in terms of time or volume, and the relative repulsion displayed in the neighborhood ( I understand that resistance) or support is substantial. It is another object of the present invention to display at least one of the above information over a corresponding bar of the OHLC chart in a manner convenient for visual observation.

[0011]

SUMMARY OF THE INVENTION To identify the individual values of the above market internal elements, for each bar in the price-time chart, the corresponding price and trading volume in the sub-timeframe are collected. Then, a frequency distribution chart is created based on the chart, and the numerical values of the elements directly obtained from the chart are superimposed on the price-time chart.

FIG. 1A shows one bar of a conventional bar chart, and FIG. 1B shows one bar of a conventional Japanese candlestick chart. FIG. 1B (I) shows that the closing price 25 of the bar is higher than the opening price 10, and at the same time, FIG.
(II) shows that the closing price 25 of the bar is lower than the opening price 10. As shown in FIG. 1B, the open price of the bar is 10
And the rectangle surrounded by the closing price 25 is called the “substance” of the bar. According to the conventional standard, when the closing price 25 is higher than the opening price 10, the entity is hollow as shown in FIG. 1B (I). When the closing price 25 is lower than the opening price 10, the bar is filled with black as shown in FIG. 1B (II).

In one preferred embodiment of the present invention,
Where the underlying price-time chart is a bar chart, the appearance of the bar of the present invention is as shown in FIG. 2A. FIG. 2A (I) shows a case where the closing price 25 is higher than the opening price 10, and FIG. 2A (II) shows a case where the closing price 25 is lower than the opening price 10. In both charts, the modal point 35 is marked as a smaller colored point on the center axis of the bar. In FIG. 2A, only the activity area 30 is shown, but the tight area 45 is not shown. The illustrated activity range 30 is rectangular and is surrounded by a colored graphic symmetrically about the center axis of the bar (a line connecting the high and low prices), and the colored graphic starts at a closing price 25. Used to identify whether it is higher or lower than the value 10. In one preferred embodiment of the present invention, if the closing price 25 is higher than the opening price 10, FIG.
The rectangle is hollow, as shown in (I); otherwise, the color is added, as shown in FIG. 2A (II). Since the figure with such a color is similar to the entity in the Japanese candlestick chart, the bar made according to the present invention is apparently familiar to a user who is familiar with the Japanese candlestick chart. There will be something. In the preferred embodiment, the extremum tail 40 is superimposed over the central axis of the bar in a thick, clear line. However, the activity area 30 or the close area 45
Only can be displayed, and both cannot be displayed at the same time. This is to avoid obscuring the original bar due to displaying too much information with a similar appearance.

In the preferred embodiment, if the underlying price-time chart is a Japanese candlestick chart, the appearance of the bar according to the present invention is as shown in FIG. 2B. FIG. 2B (I) shows a case where the closing price 25 is higher than the opening price 10. At the same time, FIG.
It shows the case where it is lower than 0. As shown in both charts, the modal point 35 is marked as one point on the corresponding bar vertical axis (a virtual line connecting the high and low prices). The extreme tail 40 is superimposed on the actual axis by a line with a distinct color. In FIG. 2B, only the activity area 30 is displayed, and the tight area 45 is not displayed. The activity area 30 is displayed as a rectangle symmetrically surrounding one vertical axis. This rectangle has a striped pattern to distinguish it from the actual substance of the original candlestick chart. Activity area 30 or close area 45
Only can be displayed, and both cannot be displayed at the same time.

Alternate embodiments include displaying different information by utilizing different geometric shapes, sizes, colored graphics and materials. One of ordinary skill in the art of the present invention can come up with combining different graphics by overlaying some or all of this element on a bar. The spirit of the present invention is to overlay elements inside the market on the OHLC bar in a visually observable manner, thereby comparing to the traditional bar chart or Japanese candlestick chart familiar to the user, The goal is to avoid unfamiliarity.

One of the features of the present invention is that the conventional OHLC at a specific time frame per bar above the chart
An application software program that displays a chart, calculates a component inside the market, and displays the value over the conventional OHLC chart. The program allows the user to select the components and to select in what format (geometric shape, color, large or small, etc.). Also, the internal setting values (default settings) that are possessed are the same as in the above-described embodiment.

Prior to the present invention, traders seeking to keep track of volume and time distribution information must do so in a redundant, manual fashion. It also had no fixed quantitative standard and had to rely on rough estimates. According to the present invention, by superimposing quantitative market internal information on the figure, the trader no longer needs to independently observe and take notes, but can immediately know from the chart. In addition, information on the time series analysis and the relationship between the analysis and the ordinary OHLC can be easily obtained. New trade insights related to the present invention can be easily formed and new technical analysis theories can be developed.

[0018]

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings are provided for a further understanding of the invention, and are incorporated in and constitute a part of this specification. BRIEF DESCRIPTION OF THE DRAWINGS Preferred embodiments of the present invention are illustrated and used in conjunction with the detailed description to interpret the principles of the invention.

Hereinafter, the present invention will be described in detail with reference to the drawings. Terminology For the purposes of the following discussion, the term "volume" refers to the volume of a stock or monetary quantity. This is a futures or commodity transaction
(open interest) also applies. The term "bar" (bar)
Can be used for all price-time charts,
Regardless of a bar chart or a Japanese candlestick chart, it means a graphed entity in a section of a designated time.

The term "OHLC" means open, high, low,
Means the closing price, which means the first, highest, lowest and last transaction price, respectively, in the time interval. The term "OHLC chart" means a special type of chart that is a bar chart, Japanese candlestick chart, or an apparent bar chart, but has no opening or closing price, or both.

In the bar of the bar chart, the center vertical line connecting the highest and lowest prices is called a center axis. As for the Japanese candlestick chart, a rectangle surrounding the open price and the close price is called an “entity”. The imaginary vertical line connecting the highest price and the lowest price on the stick is called a "virtual axis".
The term “bar interval” means the period of time indicated by the bar. The term "bar range" means the distance between the bar's high and low prices.

"Preferred time frame" means the selected time frame of the displayed price-time chart. “Basic time frame” means a time frame of price and volume data, and is used to calculate the numerical value of the market internal element. The base time frame is smaller than the preferred time frame. For one particular example, assuming the preferred time frame is daily, and if the system is set to utilize the five minute data to calculate the market internal factor, the base time frame is five minutes. is there. “Basic bar” means one bar of the basic time frame. In one specific example of the above, the base bar is a five-minute bar for the specified date.

FIG. 3 shows an embodiment of the present invention. Specifically, the apparatus of the present invention comprises a central processing unit 100 for executing a computer readable chart program 110, a database 115, an end user interface 130, and an external data vendor 125 in accordance with one embodiment of the present invention. A data interface 120 for retrieving value data in real time or ex post.
Via this device, the user 105 can specify a chart request 140 and receive a chart retrieved according to the present invention.

The above operation is performed by the central processing unit 100 executing the chart program 110 according to an embodiment of the present invention, which will be described below. The computer-readable software can be created in the form of a computer-executable program (hereinafter, referred to as a "chart program"). For example, C language, Visual C ++, JAVA (registered trademark), Vi
It can also be created in languages such as sual Basic. The central processing unit 100 includes, for example, UNIX (registered trademark), OS
Use multiple tasking operating systems like / 2, NT, or VMS. The chart program includes PC, MAC, Power PC, workstation (w
know that it can run on widely changing platforms such as laptops, laptops, palms, cable set-top boxes, video game hardware, information devices, televisions, PDAs, etc. And these belong to the technical scope of the present invention.

The central processing unit 100 is a conventional computer device including a CPU, a memory, and a storage device. Conventional computers and workstations with sufficient memory and program processing power can be the central processing unit 100. In another embodiment, the central processing unit 100 functions as a server and receives multiple chart requests 140 from multiple client systems connected to a network (eg, a local network, the Internet, or a wireless digital network). Then, the extracted chart is transmitted to the system of each client.

For a variety of different financial instruments and respective historical market internal elements, database 115 stores historical O
Used to store HLC price and volume data. Parameter settings defined by different users or systems are stored here and stored in the parameter file 18.
5 is also stored inside. Oracle Corp.
Ion) can be used to build and manage these databases. The settings of the stored internal parameter file 185 can be defined by the system or the user via the end user interface 130. In another embodiment, some or all data stored in the database 115 is stored in the central processing unit 100, for example, a storage device such as a RAM.

The data interface 120 is used as a gateway for the central processing unit 100,
It is used to obtain real-time or past price and transaction data from external data vendors 125, such as ridge or Bloomberg. Central processing unit 10
If 0 resides on a client workstation supported by this type of data vendor, the chart program will receive live and historical data via the DDE protocol (DDE protocol) or API (Application Program Interface), It can be easily configured. A hot link or a warm link can be established. In the hot link, the chart program 110 transmits the data request 1
A financial product for which live data is to be obtained is designated via the link 45. Then, the data vendor 125 continuously sends live fetched data 150 of the specified product to the chart program 110. In these two types of links, the chart program 110 specifies the name of the financial instrument and the format of the data via the data request 145. Data vendor 125 then
The requested acquisition data 150 is stored in the chart program 11
Send to 0. In hot link, data vendor 12
5 keeps sending the chart program 110 to update the live data, but does not perform the warm link in this manner. Past data requests use warm links. Alternatively, if the central processing unit 100 is not resident at the client workstation of the data vendor 125, the data interface 120
0 can use a public switched telephone network of a local or regional telephone company to connect to the data vendor 125 via an Internet connection, thereby obtaining data from the vendor. Dedicated data lines, wireless telephones, personal communication systems PCS
(Personal Communication System), microwave, or satellite can provide this type of connection.
After the vendor retrieves the data, the chart program 110 stores the data in the database 115,
In this way, some data need not be retrieved again in the future.

It should be noted that in one embodiment, the data interface 120 can be omitted if the device does not support real-time data. End user interface 130
Comprises a display device and a user input device. The display device may be a computer monitor, a TV screen, or a display screen of a mobile phone. The user input device may be a keyboard, a mouse pad, a remote channel, a pointing device, a voice recognition system, or
It may be a keypad of a mobile phone.

Utilizing the above arrangement, the present invention provides a method and apparatus used to display a more detailed price-time chart. To do this, sub-timeframe price-volume data is used to quantify market internal factors,
Including graphing the elements and overlaying them on a conventional OHLC chart. The market internal factors correlate through the price time / volume distribution at the bar.

Once the user makes the chart request 140 shown in FIG. 3, the system is executed according to the flow shown in FIG. The chart request 140 is one request executed by the user 105 under the chart program 110 and is used to request that the price-time chart of the present invention be displayed on the end user interface 130. The user 105 submits a chart request 140 via the end user interface 130. The request is configured by entering the name or symbol of the requested financial instrument and the time frame of the requested chart (eg, daily, weekly, or hourly). As shown in FIG. 4, a chart request is received at step 155 and at step 160 the associated OHLC
It is used to take data and create a traditional chart, such as an underlying bar chart or Japanese candlestick chart. In addition, O
HLC and volume data are also acquired and used to calculate correlated market internal factors. Data can be obtained from the database 115 or from an external data vendor 125 through the data interface 120. By way of example, a warm link is established using the DDE protocol, a DDE data request 145 is sent to the data vendor 125, and the specified acquisition data 150 is returned via a handshaking mechanism. You. Thereafter, in step 165, the chart program 110 calculates the relevant market internal element using the acquired data 150. Alternatively, at step 160, if the element has already been calculated and previously stored in the chart request, the element can be obtained from a database. In step 170 after data extraction and element calculation, the chart program 110
A conventional chart (bar chart or Japanese candlestick chart) of the required time frame is displayed, and in step 175 the corresponding market internal element is graphed and overlaid on the conventional chart. The removal chart 135 is then displayed through the end user interface 130 for viewing by the user 105. The calculated market internal element is stored in the database 115,
Prepare for later use. The above calculations are typically completed within one second. It should be noted that steps 170 and 175 can be executed and completed with chart program 110.

When the user or the system modifies the settings for the calculation step 165 in the parameter file 185, the internal market element of the stored bar needs to be updated.

In the real-time setting, the chart program 110 transmits live acquired data 1 from the data vendor 125 through the data interface 120.
50, the chart program 110
Need to recalculate the market internal factors and update the display of the corresponding chart. This is completed by the real-time update process 180 of FIG. 4, which will be described in detail when a real-time embodiment described later is disclosed.

FIG. 5 shows an example of the step 165 for calculating the market internal element. During the base timeframe, the corresponding price-to calculate the bar inside market element of one particular preferred bar-
The time and volume data is retrieved in step 160 of FIG. The different parameter settings are read by the parameter file 185 at step 190. A parameter file 185 resides in the database 115. After that, a frequency distribution chart is created. Here, there are provided two types of methods for creating a frequency distribution chart: a time-based method and a volume-based method. In this preferred embodiment, the user 105 cannot see the histogram. A distribution chart is created in the chart program and used in step 200 to obtain market internal elements. In this preferred embodiment, the market internal elements are all activity ranges 30, modal points 35, extreme tails 40,
And a tight zone 45. In an alternative embodiment,
Market internal elements include only one set of said elements.

FIG. 6 shows an example of an embodiment in which a frequency distribution chart is created for a specific day using the time method based on price data corresponding to every 30 minutes of the day. Thus, the preferred time frame is daily, while the base time frame is 30 minutes. FIG. 6A shows the highest price and the lowest price in a section every 30 minutes of the day. According to FIG. 6A, that day the market starts at 9:30,
It ends at 13:30. A frequency distribution chart can be obtained based on these data, and is shown in FIG. 6B. As shown in the figure, the Y-axis of the figure shows individual price levels, each of which is divided into 0.5 increments, while the X-axis shows frequency. The numerical value of the increment unit is read from the parameter file 185.

Next, the steps for creating a frequency distribution diagram will be described. As shown in the table of FIG. 6A, the first foundation bar is:
9: 30-10: 00, 121 high and 1 low
20. One mark "X" is marked at each of the positions 120, 120.5, and 121 on the chart. Next, the second base bar corresponding to 10: 00-10: 30 is checked. The second bar has a high 122 and a low 120.
5, one "X" is marked at each of the positions 120.5, 121, 121.5 and 122. The plots of the other data in FIG. 6A repeat the same process, and for brevity, redundant detailed steps will not be described here.

FIG. 6B also shows that the resulting price distribution is close to the normal distribution in general circumstances. In FIG. 6B, each mark “X” is referred to as a basic time unit (hereinafter abbreviated as BTU). Thus, each individual price level on the Y-axis has a certain number of BTUs associated with it, which is the quantitative quantity of trading time spent in the market at that price level throughout the day.

FIG. 7 shows an example of one embodiment, which is a method used to create a frequency distribution chart by the volume method. The preferred time frame is daily and the price increment is 0.5. 7A through the volume traded by individual price throughout the day. The volume data is obtained from the volume of each price change.
Display in the item of stock quantity. In other embodiments, the volume data is displayed in terms of stock trading value, or
If the security is a commodity or a future contract, it can be indicated by the number of contracts concluded. FIG. 7B shows the resulting frequency distribution diagram. On the Y axis,
The individual price levels are plotted, while the X-axis plots the volume traded at each price on its Y-axis. FIG.
In B, assume that one "X" mark indicates 1000 shares. According to the table of FIG.
When trading a stock, the corresponding price 124 in the distribution diagram of FIG.
One "X" is marked on the top. Similarly, when 2,000 shares are traded at the price 123, the price 123
Are marked with two "X" above. Others in this table are plotted on the diagram in a similar manner. Here, for brevity, redundant discussion regarding the remaining plots is omitted.

For the sake of simplicity, in the following description, the frequency distribution diagram will be described with reference to each "X" obtained by the volume method.
Is also called "BTU". It should be noted that in FIG. 7B, the distribution map was carefully created and, for subsequent discussion, was made to be exactly the same as that shown in FIG. 6B. The user can choose to use the time method or the volume method for the internal acquisition of the distribution map in the chart program. One of ordinary skill in the art will recognize that a perfect liquid security, such as a currency or index future, would be
It is understood that the charts obtained by the different methods are highly correlated. Since all conditions are the same, the more time the market spends on one price, the naturally the higher the trading volume. However, small caps (small-cap stoc
For illiquid securities like k), this situation is not always true. Inactive stocks trade at low or zero volume during most of the day,
It may stagnate at the same price. In this case, a distorted result may be obtained according to the time method. On the other hand, the time method is more appropriate for liquid securities,
For active trading securities, real-time trading volume is not accurate. The user needs to decide which method to use for different securities.

Regardless of whether the modal point calculation method is based on the time method or the volume method, refer to the frequency distribution diagram of FIG. 6B. As shown in FIG. 6B, price 120.5 has the most BTUs, which may be in units of time (if using the time method) or volume units (if using the volume method). It may be. Thus, the price is the most time spent in the market or the most price level in the volume traded, with 120.5 being the modal point.

Sometimes, the price level of the largest quantity of BTU is 1
More than one may appear. When this phenomenon occurs, the chart program 110 displays the point closest to the middle point of the optimum bar by default. It is called the central modal point. Alternatively, the chart program 110 can be configured to display all modal points on a single bar to the user.

Since there are two methods for obtaining the frequency distribution chart (time and volume), each method produces a set of modal points, which are not identical. The user determines whether the displayed modal points are calculated by the time method or the volume method. It should be noted that under standard circumstances, modal points calculated by the time method must be close to similar modal points calculated by the volume method. This is because the more time spent on a given price in that market, the more naturally the volume traded at that price.

Activity Range FIG. 8 shows the mean deviation method used by the present invention. As an example, the activity range is calculated using the frequency distribution chart of FIG. The method will now be described in detail. It should be noted that each BTU is one frequency unit (time or volume) of a particular price. Thus, the histogram can be a population of the total number of BTUs that have individually individual prices. Then, the present invention calculates the average value and the standard deviation of the population of the BTU price. The activity range is defined as “mean ± standard deviation (constant)”, wherein the constant is defined as a default value 1 in advance. This indicates that the activity range, by default, is time-based or volume-based, indicating a price range on the bar, which includes about 68% (one standard deviation) of trading activity. . The system uses parameter file 1
Read the value of the constant from 85. In FIG. 8, it is assumed that the constant is 1. Therefore, its activity range is μ ± δ, that is,
(121.79, 118.21). The activity range includes 68% of the trading activity, so that it can be a reasonable equilibrium value of the market, such as the price range of the trading agreed by the participants gathered in the whole bar section. .

In another embodiment, the range of activity is calculated by replacing the average price with the mode or median price. In the present invention, another method of calculating the activity range, a method called an active ratio method, can be used. FIG. 9 shows the steps of the activity proportional method. In step 300, the chart program 11
In the case of 0, first, the numerical value of the percentage is read from the parameter file 185. This percentage is called activity proportion. In order not to lose generality, assume that the value is 70%. Here, the step of acquiring the activity range in FIG. 6B will be described. Further, referring to FIG. 6B, in the frequency distribution chart, the total number of BTUs is 42, and the integer closest to 70% of 42 is 29.
Therefore, according to this embodiment, in step 300, the value of "X" is 29. Next, the sampling process is started. At step 310, the sample is
Starting from the central modal point 120.5 with U. Initially, the specimen contains only 120.5. Then, in step 320, it is confirmed that the price is closest to the upper and lower boundary prices 121 and 120 of the sample, and in step 330, it is compared whether the BTU price is high or not. Since step 121 has more than 120 BTUs (5 to 4), step 340 results in placing price 121 in the sample. This specimen currently includes 120.5 and 121. Next, at step 360, 11 BTs are added to the sample.
Since only U is included and smaller than 29, the sampling process continues. Thus, step 320
The price 1 closest to the upper and lower boundary prices of the sample
Check 21 and 120. Price 120 is price 121.
Since there are more than five BTUs (4 to 3), at step 340, price 120 will be sampled. This process continues in the same manner and for the sake of brevity, similar steps will not be shown here. Once the sample contains at least more than 29 BTUs,
When it shows 70% of the total number of BTUs,
The sampling process stops. The resulting range of activity is 119-1
22.5.

In short, the activity range can be defined by the time method or the volume method, and the time method or the volume method has two types (mean-standard deviation method and activity proportional method), respectively. Acquire the activity range by individual frequency distribution chart. Thus, the activity range of the system has four sets of values that may be different from each other, but those values are likely to be highly correlated. Whether the activity range is calculated by the time method or the volume method, or by one of two methods under the selected method, the determination of both is read from the parameter file 185.

Tight Zones Tight zones are defined as discrete price ranges with a significant amount of activity. However, unlike the situation of the activity range, it is not required that the activity is the maximum activity. Therefore, on the same bar 1
It has more than one tight zone.

FIG. 10 shows a frequency distribution diagram, in which the amount of price activity is not similar to the standard distribution shown in FIG. 6B. Rather, the pattern of FIG. 10 is a pair of distribution patterns. In appearance, two price ranges can be ascertained, and the trading activity contained therein is approximately higher than the rest, namely approximately 124.5-125.5 and 121.5-122.5. Thus, in such a case, utilizing a single range of activity to show its distribution is too simplistic, instead using two tight zones to show each zone one of its distributions. Should be so.

Here, a method for quantifying the tight area will be described with reference to the distribution diagram of FIG. 10 as an example. In one scheme,
If the number of BTUs included in the frequency distribution diagram is larger than a predetermined arbitrary number, it indicates that the price section has a considerable amount of activity, and the arbitrary number is called a close number. The choice of this number is fairly subjective. One way to rate the appropriate close number is to calculate the average number of BTUs (called density) for each price in the histogram. By way of example, according to FIG. 10, it has a total of 16 price levels and 33 BTUs.
Therefore, the density is 33/16 = 2, taking the nearest integer. Thus, if one price has more than one BTU, the price can be considered to include a significant amount of activity. A more accurate selection is based on recent, eg 1
It can be based on the average density of 00 bars. The long-term average is a better estimate, and the density value is not affected by daily fluctuations.

FIG. 11 shows the close number method, which is used to estimate the close area. The predetermined close number is determined in step 400
To take out from the parameter file 185. The number is 2
(Hence, X = 2). Chart program 1
10 then uses this number to calculate the close area. The calculation confirms the individual price levels and is based on the fact that the number of BTUs is greater than the close number of its individual contiguous price range. At step 410, a sample A is created, which includes all price intervals in the histogram. Therefore, FIG.
According to 0, the sample A is {120, 120.5, 121,
121.5,... 127, 127.5}. In the next step 430, the specimen B is confirmed. Sample B contains the central modal point in Sample A, which is exactly 1
25. B also includes successive price sections, and each price section includes two or more BTUs. Thus, according to FIG. 10, sample B is 124.5-125.5, the range being the largest set of consecutive price sections, of which each price section contains more than one BTU. Then, in step 440, the price interval of sample B is excluded from sample A, so sample A now has $ 120,120.
5, 121, 121.5, ... 124, 126, 12
6.5, 127, 127.5}. Step 4
At 50, the content 124.5-125.5 of B is output as the first tight zone, stored in memory or database 115, and prepared for further processing. Step 420
Detects that sample A is not an empty sample, and thereby attempts an operation to identify other tight areas. From step 430, the second tight zone is 121.5-
Confirm that it is 122.5, store it in specimen B,
The output is made in step 450. In step 440, after deleting B from A, the sample A is now $ 12
0,123,123.5,124,126.5,12
7, 127.5%. As shown in FIG. 10, there is no one in the remaining price section of sample A that has two or more BTUs in the remaining price section, so step 420
Terminates the operation.

FIG. 12 shows another method used by the present invention. This is used to identify tight areas and is called the boundary density method. This method does not use a tight number, but reads the boundary density X from the parameter file at step 500. Under this scheme, the tight zone defines the largest continuous price range, which contains a density greater than X.

FIG. 12 shows an outline of the deduction of the boundary density method.
Here, the deduction method will be described using the frequency distribution diagram of FIG. 10 as an example. Assuming a selected multiple value of 1.5 and a moving average density of 2 over a long period of time, the scheme has no close area of overlap and the density at the boundary is greater than 3 (1.5
× 2) can be confirmed. According to step 510 of FIG. 12, the scheme starts at 125, which is the central modal point. Specimen A now contains 125 and has a density of 4 and price 125 has 4 BTUs. Then, in step 530, sample B is identified and has a maximum set containing 125 consecutive price intervals,
And have a density greater than 3. If we go a step further and include neighboring price sections, the density will be less than 3.
Thus, according to FIG. 10, B is 124.5-12.
5.5. If you would like to know the cause in this case, please refer to the price range 124.5-125.5. It includes 10 BTUs and 3 price segments, so the average is 33.3 (10/3), which is greater than 3. B
Are price sections 126 and 124, respectively. If 126 is included in B, the density is 3 = ((10+
2) / 4) and is no longer greater than 3. Therefore,
126 cannot be included in B. If 124 is included in B, the density changes to 3 = ((10 + 2) / 4), which is not larger than 3. Therefore, 124 cannot be included in B. Therefore, the maximum continuous price range where the density obtained is greater than 3 at the boundary is 124.5
−125.5. In step 550, sample B
Output as the first tight zone, and in step 540, the price section of B is deleted from A. Step 540
After that, A is then $ 120, 120.5, ... 12
4, 126, 126.5,..., 127.5}.
Then repeat this step. For brevity, a detailed description of the detailed steps is omitted here. Those skilled in the art can understand based on these deductions that the second tight zone is 121.5-122.5.

In short, the tight zone is obtained by the time or volume method. For each time method or volume method, there are two types (close number and boundary density), and the close area can be obtained from individual frequency distribution diagrams. Thus, the system can have four distinct sets of tight zones, although these values are likely to have a high degree of correlation. The close area is calculated by the time method or the volume method, and is calculated by either of the two methods under the selected method, and both the determinations are read from the parameter file 185.

It should be noted that in the above example, only two tight zones were obtained, but it would be understood by a person skilled in the art that two or more tight zones could be identified in the frequency distribution diagram. Should.

Extreme Value Tail Referring again to FIG. Continuous price range starting from bar highs 123-124 and bar lows 116-11
It should be noted that the contiguous price range starting at 8.5 contains only one or two BTUs. It is called an extreme tail, and although the trading activity is displayed by time or volume, the price range is 1-2 B
It has only TUs, indicating that the market has the least amount of trading activity within this range. A further limitation on the extreme tail is on trades where the market does not occur during the last scheduled section of the bar. Accordingly, the last scheduled section is the last trading time, and the second section of 123 in FIG.
Assuming that "X" occurs within the interval of that time, its extreme tail does not include price 123. The upper extreme tail is simply 123.5-124, not 123-124. It should be noted that not all bars have extreme tails due to the limitations described above. Also, the price included in the extreme tail can have the largest number of BTUs, which can be any number, and also need to be equal to the number -2 used in the above description. Absent. The system obtains the numerical value and the scheduled section from the parameter file 185.

Referring again to FIG. Even if the price is 12
Even though 3.5 has only one BTU,
It should be noted that it is not an extremum because it occurs in the middle part. Extremum is a continuous price range starting at the bar high or low. If the high value of the bar itself is not an extremum (a section that exceeds two BTUs or occurs in the final scheduled interval), the extremum is not plotted with an extremum tail. Similarly, if the low of the bar itself is not an extreme, the low will not be plotted with an extreme tail.

Preferred Embodiment of the Stacking Method Referring again to FIG. 2, it shows the appearance of a bar formed according to the present invention. In FIG. 2A, the underlying price-
The time chart is a bar chart. The activity range 3
Numerical values of 0, modal point 35, and tail extremum 40 are overlaid on the chart. The active area 30 shows a rectangle and is plotted symmetrically around the center axis of the bar. As shown in the figure, if the closing price 25 is higher than the opening price 10, the activity range 30 is hollow (FIG. 2A (I)). Otherwise, the color is painted (FIG. 2A (I)). How to color
Similar to the method used to color the bar entity in the Japanese candlestick chart (FIG. 1B). The central modal point 35 is shown as a colored point and is located on the center axis of the bar. The extreme tail 40 is represented by a bold colored line and is plotted at the top of the bar's central axis.
This is because the close area 45 is not superimposed in FIG. 2A, and when the close area 45 is superimposed, the appearance of the bar is confused.

Alternatively, FIG. 13 shows that the system or user can choose to display any of the tight zones 45, thereby replacing the activity area 30. FIG.
In 3A, the closing price 25 is higher than the opening price 10, so that the tight zone 45 is hollow. In FIG. 13B, the opening price 10 is higher than the closing price 25, so the tight area 45 is filled. The expression format of the close area 45 is similar to the expression of the activity range 30. It should be noted that the bars formed in accordance with the present invention are shown in FIGS. 2A and 13A, the appearance of which is similar to the appearance of a Japanese candlestick chart. Thereby, a user who is accustomed to using the bar chart or the Japanese candlestick chart does not feel unfamiliar with the bar of the present invention. In addition, it should be noted that in FIG. 13, each bar contains only two tight zones. The bar can include many tight zones, each tight zone showing its own individual rectangle.

Referring to FIG. 2B, FIG. 2B shows the appearance of a bar formed according to one preferred embodiment of the present invention, and the underlying price-time chart is a Japanese candlestick chart. The closing price is 25 in (I) of FIG. 2B.
Is higher than the opening price 10, and the opposite case is shown in FIG. 2B (II). The activity range 30 can be shown as a rectangle and is plotted so as to enclose the actual axis symmetry of the bar. The rectangle has a diagonal pattern and is used to distinguish it from the conventional rectangle of a candlestick entity. The central modal point 35 is plotted on the virtual axis of the bar at the colored point. The extreme tail 40 is a bold colored line, shown at the top of the imaginary axis at both ends of the bar. FIG. 2B does not show the close area 45 in an overlapping manner. This is because the appearance of the bar is mixed in the overlapping display. Or Figure 1
In FIG. 4, the system or the user sets the activity range 30 (FIG. 1)
4A indicates that the close area 45 can be selected to be displayed instead of the close price 25 being higher than the open price 10 and vice versa (as shown in FIG. 14B). In FIG. 14, forty-five stripes in the tight area are shown as the active area 3 in FIG.
It should be noted that this is slightly different from the zero stripes.
This is to distinguish between the two. It should be noted that in FIG. 14 each bar includes only two tight zones 45. However, the bar can also include any number of tight zones. Each tight zone has one individual rectangle representing itself.

Other Embodiments of the Overlap Method Other embodiments may use alternative overlay methods.
FIG. 15 shows the appearance of an alternative bar of the present invention, which includes only a subset, does not include all market elements, and the underlying price-time chart is a bar chart. 15A and 15E, the modal point is not shown. 15B and 15F do not show the activity range. 15C and FIG.
G shows no extreme tail. 15D and 15H, only the central modal point is shown.

FIG. 16 shows the appearance of a bar formed according to another embodiment of the present invention, wherein the underlying price-time chart is a mixed bar chart. 16A and 16
In D, the underlying bar does not show an open price. 16B and 16E, the underlying bar does not indicate the closing price. In FIGS. 16C and 16F, the underlying bars do not show the open and close prices. One skilled in the art will appreciate that other combinations are possible.

[0060] Of the other embodiments, alternative overlay methods can be used. FIG. 19 shows an alternative appearance of a bar according to the invention, which contains only a subset,
The price-time chart, which does not include all market elements and is underlying, is a Japanese candlestick chart. 17A and 17D, only the modal points are shown. 17B and 17E, only the modal points are shown. 17C and 17F, the extreme tail is not shown. One skilled in the art will appreciate that other combinations are possible.

FIG. 18 shows another embodiment, in which one or more modal points are shown. FIG. 18A shows the bar, and the underlying price-time chart is a bar chart. For FIG. 18B, the underlying price-time chart is a Japanese candlestick chart. In other alternative embodiments described above, the user may select which market internal elements to overlay on the underlying price-time chart,
It is possible to select a geometric figure, a size, a colored figure, and a material for displaying the element. User-defined settings are stored in the parameter file 185.

Those skilled in the art will appreciate that the internal elements of the market can be represented by a combination of various geometric forms, and that it is not possible to plot all existing possible forms for the present invention. . The spirit of the invention lies in the way in which the elements are superimposed, i.e., when the user compares the bars in a traditional bar chart or a Japanese candlestick chart,
The purpose is to make the bar created look less unfamiliar.

Embodiment of Real-Time Update FIG. 19 shows one embodiment, in which the chart program operates in a real-time environment. In FIG. 19, it is assumed that the user is currently observing a graphic in a specific time frame of a product and a graphic in which bar internal elements are overlapped according to the present invention. The real-time price data packet 590 reaches the chart program via the data interface 120 of FIG. The price data packet is secured (seurit
y), price, date and time, time, volume, and other relevant information codes. In step 610, this information is retrieved from data packet 590.
In step 620, a check is made by comparing the code of the data packet 590 with the code of the chart currently being executed. If the security of the corresponding price data packet is not the security of the chart under observation, there is no need to update the display of the chart. At step 680, the data of data packet 590 is stored in database 115 for later retrieval. On the other hand, if the security of the corresponding price data packet 590 is the same as the security of the chart under observation, an update will need to be made. First, in step 630,
Check the corresponding timestamp for that security,
If the timestamp is within the time interval in which the closest bar is shown, then in step 660 the chart program need only update the display of the closest bar in the figure. As an example, assuming that the chart is an hourly chart, the time interval corresponding to the most recent bar is 11: 00-12: 00. If the time stamp is 11:45, the chart program only needs to update the display of the recent bar. For a recent bar update, at step 640, the bar interior elements of the recent bar are recalculated according to the price of the additional data packet.
The new value of the OHLC and the bar internal element are displayed. The recalculated numerical value is updated to the database 115. Conversely, if the timestamp exceeds the time interval represented by the most recent bar in the chart, then at step 670 the entire chart moves one time unit to the left and forms a new bar. All OH on new bar
The LCs are all equal to the price of the data packet. The internal elements of the market corresponding to this new bar are also calculated in step 640. At this point, the chart program does not display market internal elements. The reason is that the bar contains only one price, which makes the element virtually meaningless. Overlaying will give the appearance an unnecessary blur.

While only a few exemplary embodiments of the present invention have been described in detail, those skilled in the art will appreciate that the present invention is substantially different from the illustrated embodiments. It can be easily understood that modifications can be made without departing from the techniques and advantages. By way of example, in another embodiment, the chart program may not create a histogram. Conversely, it only records having the highest volume or time price traded within the entire time period, makes it a modal point, and overlays it on the bar. Also, in other embodiments, the area of activity and the close area are:
Other similar statistical parameter calculations, eg semi-variance
(semi-variance) or third moment
(Not the standard deviation used in the present invention). Accordingly, any such modifications fall within the scope of the invention as defined in all claims.

[Brief description of the drawings]

FIG. 1 is a diagram showing bars of a conventional bar chart and a Japanese candlestick chart.

FIG. 2 is a diagram showing an appearance of a bar according to one embodiment of the present invention.

FIG. 3 is a diagram showing an apparatus according to the first embodiment of the present invention.

FIG. 4 is a diagram showing a flowchart as an example when a user executes a chart creation request.

Fig. 5 After receiving the chart request of the end user,
It is the figure which showed the flowchart which calculates a market internal element.

FIG. 6 is a diagram showing creation of a frequency distribution diagram based on time using price data of a basic time frame.

FIG. 7 is a diagram showing creation of a frequency distribution diagram based on trading volume using price-volume data of a unit variable price.

FIG. 8 is a diagram showing an example of obtaining an activity range by using an average deviation method.

FIG. 9 is a diagram showing a flowchart of calculating an activity range using the close proportional method calculation.

FIG. 10 is a diagram showing an example of a frequency distribution diagram showing a pair of distribution patterns.

FIG. 11 is a diagram showing calculation of a close area using a close number method.

FIG. 12 is a diagram illustrating calculation of a tight area using the boundary density method.

FIG. 13 illustrates an embodiment of the appearance of a bar formed in accordance with the present invention, showing a tight area, a modal point, and an extreme tail superimposed on a price-time chart of a bar chart. .

FIG. 14 shows an appearance 1 of a bar formed according to the present invention.
FIG. 3 is a diagram showing a tight area, a modal point, and an extreme tail portion superimposed on a price-time chart of a Japanese candlestick chart.

FIG. 15 shows another embodiment of the appearance of a bar formed according to the present invention, and shows a bar chart price-
FIG. 7 shows a subset of tight zones, modal points and extreme tails overlaid on a time chart.

FIG. 16 illustrates another embodiment of the appearance of a bar formed in accordance with the present invention, showing a tight zone, a modal point and an extreme tail, and being synthesized with a price-time chart in a superimposed Barchard format. It is a figure, in which the opening price or closing price is not shown, or neither is shown.

FIG. 17 illustrates another embodiment of the appearance of a bar formed in accordance with the present invention, showing a tight area, a modal point and a subset of extreme tails, and a superimposed price-time chart in Japanese style. It is a candlestick chart.

FIG. 18 illustrates another embodiment of the appearance of a bar formed according to the present invention, showing one or more modal points.

FIG. 19 is a diagram showing an embodiment illustrating one process of updating a chart in real time.

[Explanation of symbols]

 10 opening price 15 high price 20 low price 25 closing price 30 activity range 35 modal point 40 extreme value tail 100 central processing unit 105 user 110 chart program 115 database 120 data interface 125 data vendor 130 end user interface 135 extraction chart 140 chart request 145 data request 150 Acquisition data

Claims (42)

[Claims] 1. A computer-implemented method for monitoring, for a user, the price activity of a financial instrument traded in a financial market within a predetermined time frame, comprising: (a) displaying multiple bars on a single price-time chart; Plot; this price-time chart is a two-dimensional figure;
The Y coordinate represents the price, the X coordinate represents the time, the X axis is divided into a number of predetermined individual sections, each section having a bar correlated thereto, and the amount of time represented by each section is specified. Equal to the amount of time in the time frame, each bar includes at least the highest and lowest prices traded in a time interval correlated to the bar in the market, and each bar is displayed vertically on the chart. (B) taking one bar from the chart and creating a frequency distribution chart, which divides the highest and lowest prices of the bar into a number of individual predetermined price segments; And the frequency map records, during each of the individual price intervals, an amount of trading activity occurring within a time period represented by the bar; (c) a set of individual activities from the frequency map. Market internal key Wherein the individual market internal elements of the set include a continuous price range having at least one significant trading activity, a price segment having one highest trading activity, and a continuous price range having one significant trading activity. (D) graphically representing each element in the set of market internal elements by a symmetrical geometrical figure, and overlaying the geometrical figure on a bar; (e) overlaying the geometrical figure Displaying a price-time chart to the user; a computer-implemented method for monitoring the price activity of a financial instrument for the user. 2. The method of claim 1, wherein in step (b), trading activity on a price interval is defined by the total volume in the price interval over the time period represented by the bar. The method described in. 3. In the step (b), the trading activity on the price section is such that, during the time period in the price section indicated by the bar, the market has at least one predetermined number of fixed time units. The method of claim 1, wherein the time interval represented by each predetermined fixed time unit therein is defined as being significantly less than the time interval represented by the bar. . 4. The method of claim 1, wherein in step (a), the price-time chart is a bar chart. 5. The method of claim 1, wherein in step (a), the price-time chart is a Japanese candlestick chart. 6. The method of claim 1, wherein in step (a), the price-time chart is a bar chart, and the open or close price does not indicate at least one. 7. The step (d) graphically represents the price interval having the largest trading activity by a point, wherein the point is the actual value of the time interval on the X-axis of the price-time chart. And the center of the point is colinear with the highest and lowest prices of the bar, and the center of the Y coordinate of the point is The method of claim 1, further comprising being located at a midpoint of the interval. 8. In the step (c), the continuous price range having the considerably lower trading activity is one continuous price range, the top end of which is the highest price of the bar, and the continuous price range is Enclosing the set of price sections on the frequency distribution diagram, and having a transaction activity included in each price section of the set of price sections lower than a predetermined amount; and in the step (d), The method of claim 1, further comprising: graphically representing the continuous price range by a geometric figure. 9. In the step (c), the geometric figure is a vertical line having a predetermined width and color connecting the high price and the low price of the price range, and the vertical line is:
The method of claim 1, wherein the highest price and the lowest price of the bar are overlaid on an imaginary line connecting the bars. 10. In the step (c), the continuous price range having the considerably lower trading activity is one continuous price range, the bottom end of which is the lowest price of the bar, and the continuous price range is Enclosing the set of price sections on the frequency distribution diagram, and wherein the trading activity included in each price section of the set of price sections is lower than a predetermined amount; and the step (d) includes: , By geometric shapes,
The method of claim 1, further comprising graphically representing a continuous price range having significantly lower trading activity on the bar. 11. The geometrical figure is a vertical line having a predetermined width and color connecting high and low prices of the price range, and the vertical line is a virtual line connecting a highest price and a lowest price of the bar. 2. The method according to claim 1, wherein the superimposition is on a line.
The method according to 0. 12. The step (d) comprises graphically representing, by means of a geometrical figure, a continuous price range having at least one considerably higher trading activity, and overlaying said geometrical figure on said bar; The geometric figure is a rectangle having a predetermined width and length, wherein the rectangle has a vertex surrounding a Y coordinate and a continuous price range having the considerably high trading activity, and the center of the rectangle has: The method of claim 1, further comprising being collinear with a highest price and a lowest price of the bar. 13. The method according to claim 1, further comprising: setting the rectangle to be hollow if the closing price of the bar is higher than the opening price; and coloring the rectangle if the closing price of the bar is lower than the opening price. 13. The method of claim 12, wherein the method comprises: 14. The price-time chart is a Japanese candlestick chart, wherein the rectangle has the same width as a bar entity, and the rectangle includes a pattern to be distinguished from the bar entity. 13. The method of claim 12, wherein the method comprises: 15. The method according to claim 14, wherein the pattern is a diagonal pattern. 16. The step of obtaining a continuous price range including the considerably high trading activity includes the steps of: (a) calculating an average price of the price distribution on the frequency distribution diagram, and labeling the result as X; ) Calculating the standard deviation of the prices of the price distribution on the frequency distribution diagram and labeling the result as Y; (c) defining the continuous price range as a numerical value X ± (Y) (b), wherein b The method of claim 1, wherein is a predetermined constant. 17. The step of obtaining the continuous price range including the fairly high trading activity includes: (a) obtaining a predetermined constant, summing up the total amount of trading activity in the frequency distribution chart, Multiplying the total amount by a predetermined constant and labeling the result as X; (b) the continuous price range including the substantial trading activity is the narrowest price where the total trading activity included in the frequency distribution chart is larger than X; The method of claim 1, comprising including a range. 18. The method of claim 1, wherein in step (c), the step of the continuous price range including the fairly high trading activity comprises a set of individual price intervals, including at least one price interval, The method of claim 1, wherein the average trading activity included in a set of individual price segments includes being greater than a predetermined amount. 19. In step (c), the step of the continuous price range including the fairly high trading activity comprises a set of individual price intervals, including at least one price interval, The method of claim 1, wherein within the set of individual price segments, trading activity included in each price segment is greater than a predetermined amount. 20. The step (b) further comprises: taking each of the bars from the chart and plotting a histogram for each bar; and performing the step (c). Obtaining, for each of the bars, a set of market internal elements from the corresponding histogram, wherein the set of market internal elements includes at least one market internal element; and In step (d), a geometrical figure
The method of claim 1, further comprising: graphically representing each market interior element in the set of market interior elements and overlaying the geometric figure on the bar. 21. The frequency distribution chart is created by a computer therein and is not displayed to the user, but at the same time comprises the price-time chart with market internal elements superimposed and displayed to the user. The method of claim 1, comprising: 22. The method of claim 1, wherein a user can select a set of market internal elements to overlay on the price-time chart. 23. The method of claim 1, wherein a user can define the geometrical shape to display market internal elements. 24. An apparatus for plotting price movement based on a designated time frame in a financial market, comprising: a storage device; and a processor connected to the storage device, wherein the storage device includes the processor The processor functions in conjunction with the program to: (a) receive a chart display request from a user; and (b) display a price-time chart, the chart comprising:
Bar chart, or Japanese candlestick chart, the chart does not show the bar chart of the opening price,
(C) extracting at least one bar from the price-time chart and collecting a set of data pairs; The set of data pairs includes at least one data pair, wherein the data pair is comprised of a price interval and trading activity occurring within the price interval within the time period correlated to the bar. (D) obtaining a set of market internal elements based on said data pair, comprising: a price range having at least one significantly higher trading activity, a price range having one significantly lower trading activity; (E) graphically representing each market internal element in the set of market internal elements by a geometric figure, and expressing the geometric figure in the price-time Overlaid on the bar of the chart;
And (f) displaying to the user a price-time chart superimposed with said geometrical figure; an apparatus for plotting price movements based on a specified time frame in a financial market. 25. The method according to claim 25, wherein in step (d), the trading activity defined on a price section is a total volume traded through the time period in which the bar is displayed in the price section. An apparatus according to claim 24. 26. In the step (d), the trading activity defined on a price section includes:
Throughout the time period in which the bars are represented, a predetermined number of fixed time units are traded at least once in the market, and the time interval in which each of the fixed time units is represented is generally represented by the bar. 26. The apparatus of claim 24, wherein the time interval is less than the time interval. 27. In the step (d), a step of extracting a set of market internal elements includes creating a frequency distribution chart, wherein the frequency distribution chart calculates a maximum price and a minimum price of the bar by a plurality of individual prices. 25. The method according to claim 24, wherein segmenting is performed, and the frequency distribution diagram includes recording, during each of the individual price sections, an amount of trading activity occurring within a time period represented by the bar. Equipment. 28. In the step (e), the price section having the maximum trading activity calculated in the step (d) is represented by a point, and the point is represented on the X-axis of the price-time chart. The point has a diameter substantially smaller than the actual length of the time interval, the center of the point is collinear with the highest and lowest prices of the bar, and the Y coordinate center of the point is The apparatus of claim 24, further comprising being located on a midpoint. 29. In step (d), the continuous price range with the significantly lower trading activity is a continuous range, the top end of which is the highest price of the bar and each within the price range. And the transaction activity included in the price range is lower than a predetermined amount; and the step (e) includes:
The apparatus of claim 24, further comprising graphically representing the continuous price range and overlaying the geometric figure on the bar of the price-time chart. 30. The geometric figure is a vertical line having a predetermined width and color of the high and low prices of the price range, and the vertical line is superimposed on an imaginary line connecting the highest price and the lowest price of the bar. 30. The method of claim 29, further comprising:
An apparatus according to claim 1. 31. In the step (d), the continuous price range having the considerably lower trading activity is a continuous price range, the bottom end of which is the lowest price of the bar;
And the trading activity included in each price within the continuous price range is lower than a predetermined amount; and the step (e) includes:
25. The method of claim 24, further comprising graphically representing a continuous price range having substantially lower trading activity on the bar, and overlaying the geometric shape on a bar of a price-time chart. Equipment. 32. The geometric figure is a vertical line having a predetermined width and color connecting a high price and a low price in the price range, and the vertical line connects a highest price and a lowest price of the bar. The apparatus of claim 31, comprising superimposing on a virtual line. 33. In the step (e), the geometric figure graphically represents a continuous price range having at least one significantly higher trading activity, and the geometric figure is overlaid on the bar, The geometric figure is a rectangle having a predetermined width and length, the rectangle has a Y coordinate and a vertex surrounding the continuous price range having the considerably high trading activity, and the center of the rectangle is 25. The apparatus of claim 24, further comprising: the bar's highest and lowest prices being collinear. 34. The method according to claim 24, wherein the step (e) further includes a method of adding a color used to identify whether the closing price of the bar is higher than the opening price. apparatus. 35. The price-time chart is a Japanese candlestick chart, wherein the rectangle has the same width as the substance of the bar, and the rectangle includes a pattern to be distinguished from the substance of the bar. 34. The device of claim 33, wherein the device. 36. The apparatus according to claim 35, wherein the pattern is a diagonal pattern. 37. In the step (d), obtaining the continuous price range having a fairly high trading activity comprises: (a) for the set of prices and through a time period correlated to the bar; (B) Calculate a first price X based on the price activity distribution of the sampling step, and make it the average, median or mode of the distribution. (C) calculating a second price Y and taking it as the standard deviation of the distribution; and (d) denoting the continuous price range including the fairly high trading activity as X ±
27. The apparatus of claim 24, wherein (Y) is defined as (b), wherein b is a predetermined constant. 38. In the step (d), the step of obtaining the continuous price range having the considerably high trading activity includes the step of determining that the trading activity having the narrowest continuous price range on the bar has a total price within the bar. 25. The apparatus of claim 24, comprising confirming that a predetermined ratio of trading activity is greater than a predetermined ratio. 39. In the step (d), the continuous price range having substantially higher trading activity surrounds a set of price ranges, and the set of price ranges includes at least one price range, Each of the price sections in the price section of the set is traded at least once in the market during the time period correlated to the bar, and the set of price sections has an average trading activity greater than a predetermined amount. The apparatus of claim 24, comprising: 40. In the step (d), the continuous price range having substantially higher trading activity surrounds a set of price segments, and the set of price segments includes at least one price segment, Each of the price sections within a set of price sections is traded at least once in the market within the time period correlated to the bar, and the trading activity of each price section of the set. 25. The apparatus of claim 24, wherein the is greater than a predetermined amount. 41. For each of the bars in the price-time chart, obtain a set of market internal elements, including a price range with at least fairly high trading activity and a price interval with the highest trading activity. 3. The method of claim 2, further comprising: graphically representing each of said sets of market internal elements by a geometrical figure and superimposing on said correlated bar in said price-time chart.
An apparatus according to claim 4. 42. The apparatus of claim 24, further comprising equipment for updating said price-time chart in a real-time environment.