CA2555967A1 - Mcisaac method for charting financial instrument price and volume activities - Google Patents
Mcisaac method for charting financial instrument price and volume activities Download PDFInfo
- Publication number
- CA2555967A1 CA2555967A1 CA 2555967 CA2555967A CA2555967A1 CA 2555967 A1 CA2555967 A1 CA 2555967A1 CA 2555967 CA2555967 CA 2555967 CA 2555967 A CA2555967 A CA 2555967A CA 2555967 A1 CA2555967 A1 CA 2555967A1
- Authority
- CA
- Canada
- Prior art keywords
- price
- volume
- chart
- bar
- transaction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Engineering & Computer Science (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The following is in two distinct parts. The first part describes a method of processing raw transaction data for stocks or other financial instruments. The second part describes a series of new charts/graphs using the processed data. The charts described herein will allow the user to accurately view the degree of volume or transactions at specific price points or narrow price ranges by indications on daily, weekly or monthly price bars. These provide an alternative to conventional 'open/close' price indicators and allow volume to play a more important part in technical analysis.
Description
Canada Patent Aupiication Subiect Matter:
- Processing Stock market or financial instrument transaction data - Producing charts with processed data Contents: Page Abstract: 2 Specifications: 2 - Subject Matter 2 - Broad Description: 2 - Clear & Complete Description 3 o The transaction ranking method. 3 o The charts produced with the ranked data. 4 = Summary of chart types 4 ~ Detailed descriptions of the chart types. 5 ~ Notes on the above charting methods 13 Preferred Practice 14 Other Relevant Patents 15 Applicant's name, address and citizenship 19 Statement that a patent is sought 19 Short descriptions of the attached figures. 20 Applicant:
Jason Mcisaac 47 St. Andrew's Ave Mt. Pearl, NL
Patent Agent: NONE
August 10,2006 The Abstract The following is in two distinct parts. The first part describes a method of processing raw transaction data for stocks or other financial instruments. The second part describes a series of new charts/graphs using the processed data. The charts described herein will allow the user to accurately view the degree of volume or transactions at specific price points or narrow price ranges by indications on daily, weekly or monthly price bars. These provide an alternative to conventional 'open/dose' price indicators and allow volume to play a more important part in technical analysis.
The saecifications:
Subiect Matter:
1- Processing Stock market or financial instrument transaction data via a transaction ranking system.
- Processing Stock market or financial instrument transaction data - Producing charts with processed data Contents: Page Abstract: 2 Specifications: 2 - Subject Matter 2 - Broad Description: 2 - Clear & Complete Description 3 o The transaction ranking method. 3 o The charts produced with the ranked data. 4 = Summary of chart types 4 ~ Detailed descriptions of the chart types. 5 ~ Notes on the above charting methods 13 Preferred Practice 14 Other Relevant Patents 15 Applicant's name, address and citizenship 19 Statement that a patent is sought 19 Short descriptions of the attached figures. 20 Applicant:
Jason Mcisaac 47 St. Andrew's Ave Mt. Pearl, NL
Patent Agent: NONE
August 10,2006 The Abstract The following is in two distinct parts. The first part describes a method of processing raw transaction data for stocks or other financial instruments. The second part describes a series of new charts/graphs using the processed data. The charts described herein will allow the user to accurately view the degree of volume or transactions at specific price points or narrow price ranges by indications on daily, weekly or monthly price bars. These provide an alternative to conventional 'open/dose' price indicators and allow volume to play a more important part in technical analysis.
The saecifications:
Subiect Matter:
1- Processing Stock market or financial instrument transaction data via a transaction ranking system.
2- Producing charts with processed data.
A Broad description of the invention:
A computerized system will take the raw transaction data [number of units and arice for each transaction] within a day and rank the transactions byprice within that day with no regard to the time within that day.
The ranked data is then used to produce 5 new stock charting methods.
A clear and complete description of the invention and its usefulness:
l: The Transaction Ranking method:
Raw transaction data for a day [week or month can also be used] is taken for any financial instrument involving price per transaction and volume per transaction.
The raw data is fed into a spreadsheet with 'sorting' capabilities and all of the transactions are ranked by the 'price' column. See table below.
Table 1: Raw Transaction Data for Financial Instrument XYZ in chronological order. Then shown after ranking by price.
Chronological Order After Ranking by Price Transaction Price Volume Transaction Price Volume 1 19.92 750 4 19.81 300 2 19.94 100 9 19.86 1000 3 20.07 500 1 19.92 750 4 19.81 300 2 19.94 100 20.06 400 6 20.02 400 6 20.02 400 5 20.06 400 7 20.09 800 3 20.07 500 8 20.13 600 7 20.09 800 9 19.86 1000 8 20.13 600 20.14 600 10 20.14 600 11 20.23 1000 14 20.18 100 12 20.21 2000 12 20.21 2000 13 20.29 500 11 20.23 1000 14 20.18 100 13 20.29 500 20.31 2000 15 20.31 2000 16 20.32 1000 16 20.32 1000 17 20.35 1000 17 20.35 1000 18 20.38 3000 20 20.36 2000 19 20.41 2000 18 20.38 3000 20.36 2000 19 20.41 2000 Total: Total:
Price range: $ 0.60 20050 Price range: $ 0.60 20050 II: Charts Produced by using the Sorted Data:
The sorted data in the sorted/ranked table can then be processed to produce any of the charts/graphs below. [this section composes the remainder of the specifications section of the present application.] The chart types are:
A- The 'Equal Segments by Price' chart B- The 'Equal Segments by Volume' chart C- The 'Median Transaction Indicator' chart D- The 'Average/mean Volume Indicator chart E- The 'Cropped off Price Bar' chart.
Summary of chart types:
A- The 'Eaual Seaments by Price' chart: divides the price bar into egual price segments.
Then segments are shaded or colour coded to show relative volume in segment.
B- The'Eaual Seaments by Volume' chart: divides the price bar into equal segments by volume. This will usually show varying segment sizes with vary prices ranges, indicating unequal volume distribution.
C- The 'Median Transaction Indicator' chart: indicates on price bar the point at which half of the transactions are below the indicated price and half above.
D- The 'Average/mean Volume Indicator' chart: indicates on price bar the point at which half of the volume is below the indicated price and half above.
E- The 'CroDoed off Price Bar' chart: crops off a selected % of the highest and/or lowest priced volume. This eliminates high priced and low priced low-volume spikes which are not true indicators of demand.
A Detailed Descrigtion of the Chart types:
A- Eciual Segments by Price (see Fig 1, attached):
What is it? - A conventional intra-day higMow price bar will be augmented by dividing it into several equal price segments.
- For example, if the price range for the day is 60 cents, the user can choose to divide the bar into 4 equal 15 cent segments. The relative volume, the % vs the total, within each price segment will be indicated by different degrees of shading, colour or width on the price bar itself. The higher the volume density, the darker the shading.
- The user chooses the number of segments he wishes to use and chooses the time range for each price bar (ie. day, week or month). So a user would choose parameters to build the chart such as: 'daily chart', '4 segments per day', '6 week range'.
- dividing the price range into 2 to 5 segments would probably be the most practical unless one is using weekly or monthly indicators with larger price ranges; then 6-10 segments may be useful.
- As the user chooses a varying number of segments, a key is produced indicating the % of the total volume that each shade represents. In other words, if dividing into 5 segments, the 'even distribution' would show 20% of the volume in each segment. The 'even distribution' would be indicated by a neutral shade. A 5 segment bar would indicate a neutral shade for volume in the range of 15-25%, lighter shades for 5-14% and the lightest shading for <5%. Conversely, slightly darker than neutral shading would be used to indicate 26-40% of the volume and the darkest shading to indicate >40% volume within that segment. However, if the user chooses a 2 segment bar, then 'neutral' would be in the 40-60% range, lighter shades would be required for <40% volume and darker shades for >60% volume. A total of 4-6 different shades should suffice for any situation.
How is it calculated? - The segments are generated by dividing the ranked transaction list into equal parts by price; total price range divided by the number of segments desired. The volume [number of shares] of all the transactions within each price segment are added up and then compared to the total volume to generate the % of the total. The volume within each segment will almost always vary, indicating that volume is not evenly distributed.
Table 2: Ranked Data Showing $0.15 segments.
For price bar showing 4 Equal Segments by Price. Indicated by colour. 4 Segments of $0.15 each.
Volume Volume Transaction Price Volume Running Total Segment Total:
4 19.81 300 9 19.8f3 4000 130O
1 19.92 760 2O0 2 19.94 100 2150 Segment 1: 2150 6 20.02 400 2550 20.06 400 2950 3 20.07 500 3450 7 20.09 800 4250 Segment 2: 2100 8 20.13 600 4850 20.14 B00 5450 14 20.18 100 5560 12 20.21 2000 7550 11 20.23 1000 8550 Sogmertt 3: 4300 13 20.29 500 9050 20.31 2000 11050 16 20.32 1000 12050 17 20.35 1000 13050 20.36 2000 15050 18 20.38 3000 18050 19 20.41 2000 20050 Segment 4:11500 Range $ 0.60 20050 25% of Range: $ 0.15 Low 25% 19.81-19.96 =2150 med lovw 2590 19.97-20.11 =2100 med high 25% 20.12-20.26 =4300 high 25% 20.27-20.41 =11500 [See next page for notes on this table.]
Eaual Seaments by Price lcontinuedl In the example above [Table 2], to find the volume in the lowest 25% of the price range: total day's price range then divide by 4. Or ($20.41-$19.81)= $.60/4= 15 cents. So we know that'/. of the day's price range is 15 cents.
Seament 1: The lowest price segment would range from $19.81 to $19.96. In this simplified example, we see that there are 4 transactions in this range, totaling 2150 shares in volume. That is 2150/20050 or 11 % of the volume for the day. This is 25% of the price range but only 11 % of the day's volume.
Sepment 2: The next higher price segment, would be $19.97 to $20.11. Again, there are 4 transactions, totaling 2100 shares in volume. 2100120050= 10% of the total volume. This is 25% of the price range but only 10% of the day's volume.
Segment 3: The next higher segment would be the range of $20.12 to $20.26. In this price range segment, there are 5 transactions totaling 4300 sha-es. 4300120050= 21%
of the total volume in 25% of the price range.
Segment 4: The highest 25% price range segment is $20.27-$20.41. In this price range segment there are 7 transactions totaling 11500 shares in volume. 11500120050=
57% of the total volume. So 57% of the volume is transacted in only 25% of the price range.
How is this useful? This example dearly shows that the bulk of the volume is in the upper price range. A typical stock chart would show you open, high, low, close and total daily volume. On a conventional chart, the user would have no indication of the volume distribution and may assume that the voiume is evenly distributed on that day. Using this method, the user gets a different picture of volume distribution, and therefore a different picture of supply and demand.
This charting method provides a valuable tool to a user who believes that volume is as important as price. A user could opt to view a conventional 'intra day' chart, looking at all of the activity on one chart. However, the present method summarizes an entire day's activities on one price bar, allowing the user to view the volume distribution for dozens of days at a glance.
B- Equal Segments by Volume (see Fig 2. attached):
What is it?: Using the ranked transaction data, the price range is divided into equal portions of volume, rather than price. The equal-volume segments will usually span varying price ranges, showing different sized segments on the price bar. The relative size of the segment indicates density of volume.
How is it calculated?: Starting at the lowest or highest price on the ranked transaction list, add up the volume until you get to 25% of the volume (in this case 4, but this can vary depending on the number of segments desired).
- When the price at which the 25% volume mark is reached, the transaction at this price is indicated on the price range bar as the first segment. This is repeated at each 25% volume segment.
- In the example in Table 1, above, the total volume for the day is 20050. If we want to divide the day's volume into 4 segments, they would result in 4 segments of approx 5012 units. The lowest priced 5012 segment of would range the first 9 transactions, from $19.81 to $20.13. So a hash mark is indicated at $20.13 on the price bar. We know that 25% of the daily price range is 15 cents. In this instance, the lowest priced 25% of the volume spans 32 cents.
This indicates very low density trading at the lower price ranges. The next segment is from $20.14 to $20.29 [the next hash mark would be at $20.29], which is 15 cents, so volume is perfectly proportionate to the price range within this segment. The next segments are calculated in the same manner, by summing the volume totals as you progress upward in price through the ranked data.
How is this useful?: The relative size (i.e. price range) of each segment will indicate the density of volume. A relatively large segment in the price range indicates reiatively low volume vs. the price range. A small segment shows that volume is concentn3ted there. As in the example above, if the daily price range is 60 cents, 1/4 of the price range is 15 cents, but the lowest priced 25%
segment of the volume is 32 cents, indicating 'thin' trading at the lower end of the price range.
- Unless the volume is evenly distributed for that day, the resulting chart will show 4 segments of unequal size, each representing a price segment with equal volume.
- Rather than using a wide, candlestick-type bar, this chart could also be drawn with normal 'narrow' bars with hash marks on the bar indicating the divisions.
- Dividing the daily volume into 3 to 5 segments would probably be the most practical unless one is using weekly or monthly indicators with large price ranges. Note that if you divide the price range into 2 equal volume segments, you effectively produce the chart in method 'D' [page 10, below], the 'Average Volume' Indicator.
C- The Median Transaction Indicator (See Fig 3, attached):
What is it? -The raw data can be processed to allow the user to view on the price bar the price of the 'median transaction' for the day. This could be a hash mark on the intra day price bar (such as a sideways 'T').
- The median transaction is that which half of the day's transactions are at a higher price and half are at a lower price.
How is it Calculated?: The total number of transactions are counted for the day on the ranked transaction list then transactions are counted starting from the lowest (or highest) price. The price of the 'middle' transaction is used to indicate the median transaction. E.g.
if there are 200 transaction for the day, the 100"' transaction from the bottom on the ranked list is the median transaction. Then the price for this transaction is indicated on the price bar.
How is this Useful? - This is useful in indicating whether the bulk of the transaction are occurring nearer to the high or low end of the price range rather than evenly distributed. A conventional chart gives a user no indication of transaction distribution within a day. The conventional chart user may assume that the transactions are evenly distributed on any given day.
Using this method, on a day in which the median transaction is significantly deviant from the middle of the price range, the user may interpret aberrant trading action.
D- Mean/Average Volume Indicator (see Fig 4, attached):
What is it?: The 'mean volume indicatoP shows the price at which half of the daily volume occurs below that price and half occurs above.
The point on the bar can be can be shown via a hash mark or unique symbol, such as a 'V' on the daily price bar.
How is it calculated?: This indicator is calculated by first adding up the total daily volume, then adding up the volume from the bottom of the ranked list upward until HALF of the daily total is reached. The price at which this occurs is the 'average volume transaction' and is indicated as such on the price bar.
How is this useful?: Unless the volume is evenly distributed within the day, this price indicator will be somewhat removed from the middle of the day's price range. The true 'middle' of the pricing action is better indicated when incorporating volume.
The farther the indicator is from the middle of the price range, the stronger the indication that volume is not evenly distributed. Any day in which the mean/average volume indicator is significantly removed from the mid-point in the price range, could indicate to the user aberrant trading action.
E- Cropping Off Aberrant Extreme Priced Volume:
What is it? Using the same transaction ranking process shown in table 1, the user can choose to "crop off" the extreme high and low priced volume for a day. E.g. The highest and lowest priced 1%, 5% or 10% (or other proportion chosen by the user) volume can be cropped off of the intra-day price bar, eliminating aberrant transactions which may not indicate true demand.
As the user crops off the ends, he ends up seeing the 'middle' 80% [if cropping off the top and bottom 10%] or 90% [if cropping off 5% at either end] of the volume action.
Note: this is NOT simply a matter of cropping off a % of the price by price range but rather the highest and lowest priced VOLUME on the ranked list.
Table 3: The user in the table below has chosen to crop off the highest and lowest priced 10% of the volume. The cropped off transactions are shown shaded below.
The ranked data from Table 1:
Transaction Price Volume Running Total:
4 19.81 300 300 9 19.86 1000 1300 1 19.92 750 2050 2 19.94 100 2150 6 20.02 400 2550 20.06 400 2950 3 20.07 500 3450 7 20.09 800 4250 8 20.13 600 4850 20.14 600 5450 14 20.18 100 5550 12 20.21 2000 7550 11 20.23 1000 8550 13 20.29 500 9050 20.31 2000 11050 16 20.32 1000 12050 17 20.35 1000 13050 20.36 2000 15050 18 20.38 3000 18050 19 20.41 2000 20050 Total: 20050 10% of volume= 2005 Il How is this calculated?: The user selects a % to crop off; for example 10%.
Then, using the ranked data, the running total volume is added up from the lowest price upward until the desired cropping % is reached. This point becomes the new'intra day low'. The same is done for the highest priced transactions. Volume is added up from the highest price downward in a running total until the desired % is reached, the price at that transaction becomes the new 'intra day high'.
This will be shown on the stock chart as a normal price bar, with the new high and low ends indicating the 'middle' 80%, rather than the conventional, absolute intraday high and low.
Using the data from table 3 above, we can see that cropping off the 10% lowest priced volume means that the first three transactions would be cropped off with a price range of 11 cents [19.81 +
19.86 + 19.92] because their corresponding volume = 10% of the total volume.
Likewise, cropping off the 10% hiahest priced volume means cropping off only one transaction, the one at $20.41.
So the resultin4 price bar would show a modified daily price range of $19.94 to $20 38 How is this useful?: This would be useful in situa6ons in which a low volume spike occurs at either a very low price or very high price for perhaps only a few minutes within a trading day.
- On a conventional chart, these low volume price spikes may show a user that a technical 'barrier has been breached or that a specific type of pattem is forming. But if these spikes are simply a few low volume, deviant transactions, such conclusions may be erroneous.
- This method can be used with 'transactions' and 'volume' with equal utility.
i.e. substitute cropping off the lowest priced volume with the lowest and highest priced % of transactions.
- With this method, the user gets a'cleaner view of the trading action by looking at the 'middle' 90% (or other %) of the volume. On days in which volume is evenly distributed, the cropping effect will be minimal.
- since the user will be looking at an entire chart with each price bar showing the same cropped-off proportions, there is no fear that this will show a skewed representation of the data. Quite the opposite; it eliminates skewed and aberrant data.
Notes on above charting methods:
1- The user may choose to superimpose any of the above indicators in any reasonable combination on the same chart and price bar includinc conventional open and close prices. E.g.
Average/mean volume hashmark indicator could be superimposed on a'cropped-ofP
price bar.
2- Methods C and D [median transacBon and mean volume indicaators] may also be used to show the price at which any specified proportion (other than 50%) of transactions or volume occurs. eg.
the point at which 20% of the transaction occur above a specific price or the point at which 70% of the volume occurs above a certain point. The 50% indicator would be the default measure.
3- Methods C and D may also be used to indicate by shading the price bar [as in a conventional candle stick chart] whether the day was an 'up' dav or a'down' day. That is, whether the indicator mark is at higher or lower price vs. the day before. Again note that opening and closing prices are irrelevant.
4- It should also be noted that the traditional bolume' bar in conventional stock chart, as a lower indicator, should always be used in conjunction with all of the above charting tools. This gives the user the absolute volume measurement by which he can better assess the significance of the indicators discussed presently.
A Broad description of the invention:
A computerized system will take the raw transaction data [number of units and arice for each transaction] within a day and rank the transactions byprice within that day with no regard to the time within that day.
The ranked data is then used to produce 5 new stock charting methods.
A clear and complete description of the invention and its usefulness:
l: The Transaction Ranking method:
Raw transaction data for a day [week or month can also be used] is taken for any financial instrument involving price per transaction and volume per transaction.
The raw data is fed into a spreadsheet with 'sorting' capabilities and all of the transactions are ranked by the 'price' column. See table below.
Table 1: Raw Transaction Data for Financial Instrument XYZ in chronological order. Then shown after ranking by price.
Chronological Order After Ranking by Price Transaction Price Volume Transaction Price Volume 1 19.92 750 4 19.81 300 2 19.94 100 9 19.86 1000 3 20.07 500 1 19.92 750 4 19.81 300 2 19.94 100 20.06 400 6 20.02 400 6 20.02 400 5 20.06 400 7 20.09 800 3 20.07 500 8 20.13 600 7 20.09 800 9 19.86 1000 8 20.13 600 20.14 600 10 20.14 600 11 20.23 1000 14 20.18 100 12 20.21 2000 12 20.21 2000 13 20.29 500 11 20.23 1000 14 20.18 100 13 20.29 500 20.31 2000 15 20.31 2000 16 20.32 1000 16 20.32 1000 17 20.35 1000 17 20.35 1000 18 20.38 3000 20 20.36 2000 19 20.41 2000 18 20.38 3000 20.36 2000 19 20.41 2000 Total: Total:
Price range: $ 0.60 20050 Price range: $ 0.60 20050 II: Charts Produced by using the Sorted Data:
The sorted data in the sorted/ranked table can then be processed to produce any of the charts/graphs below. [this section composes the remainder of the specifications section of the present application.] The chart types are:
A- The 'Equal Segments by Price' chart B- The 'Equal Segments by Volume' chart C- The 'Median Transaction Indicator' chart D- The 'Average/mean Volume Indicator chart E- The 'Cropped off Price Bar' chart.
Summary of chart types:
A- The 'Eaual Seaments by Price' chart: divides the price bar into egual price segments.
Then segments are shaded or colour coded to show relative volume in segment.
B- The'Eaual Seaments by Volume' chart: divides the price bar into equal segments by volume. This will usually show varying segment sizes with vary prices ranges, indicating unequal volume distribution.
C- The 'Median Transaction Indicator' chart: indicates on price bar the point at which half of the transactions are below the indicated price and half above.
D- The 'Average/mean Volume Indicator' chart: indicates on price bar the point at which half of the volume is below the indicated price and half above.
E- The 'CroDoed off Price Bar' chart: crops off a selected % of the highest and/or lowest priced volume. This eliminates high priced and low priced low-volume spikes which are not true indicators of demand.
A Detailed Descrigtion of the Chart types:
A- Eciual Segments by Price (see Fig 1, attached):
What is it? - A conventional intra-day higMow price bar will be augmented by dividing it into several equal price segments.
- For example, if the price range for the day is 60 cents, the user can choose to divide the bar into 4 equal 15 cent segments. The relative volume, the % vs the total, within each price segment will be indicated by different degrees of shading, colour or width on the price bar itself. The higher the volume density, the darker the shading.
- The user chooses the number of segments he wishes to use and chooses the time range for each price bar (ie. day, week or month). So a user would choose parameters to build the chart such as: 'daily chart', '4 segments per day', '6 week range'.
- dividing the price range into 2 to 5 segments would probably be the most practical unless one is using weekly or monthly indicators with larger price ranges; then 6-10 segments may be useful.
- As the user chooses a varying number of segments, a key is produced indicating the % of the total volume that each shade represents. In other words, if dividing into 5 segments, the 'even distribution' would show 20% of the volume in each segment. The 'even distribution' would be indicated by a neutral shade. A 5 segment bar would indicate a neutral shade for volume in the range of 15-25%, lighter shades for 5-14% and the lightest shading for <5%. Conversely, slightly darker than neutral shading would be used to indicate 26-40% of the volume and the darkest shading to indicate >40% volume within that segment. However, if the user chooses a 2 segment bar, then 'neutral' would be in the 40-60% range, lighter shades would be required for <40% volume and darker shades for >60% volume. A total of 4-6 different shades should suffice for any situation.
How is it calculated? - The segments are generated by dividing the ranked transaction list into equal parts by price; total price range divided by the number of segments desired. The volume [number of shares] of all the transactions within each price segment are added up and then compared to the total volume to generate the % of the total. The volume within each segment will almost always vary, indicating that volume is not evenly distributed.
Table 2: Ranked Data Showing $0.15 segments.
For price bar showing 4 Equal Segments by Price. Indicated by colour. 4 Segments of $0.15 each.
Volume Volume Transaction Price Volume Running Total Segment Total:
4 19.81 300 9 19.8f3 4000 130O
1 19.92 760 2O0 2 19.94 100 2150 Segment 1: 2150 6 20.02 400 2550 20.06 400 2950 3 20.07 500 3450 7 20.09 800 4250 Segment 2: 2100 8 20.13 600 4850 20.14 B00 5450 14 20.18 100 5560 12 20.21 2000 7550 11 20.23 1000 8550 Sogmertt 3: 4300 13 20.29 500 9050 20.31 2000 11050 16 20.32 1000 12050 17 20.35 1000 13050 20.36 2000 15050 18 20.38 3000 18050 19 20.41 2000 20050 Segment 4:11500 Range $ 0.60 20050 25% of Range: $ 0.15 Low 25% 19.81-19.96 =2150 med lovw 2590 19.97-20.11 =2100 med high 25% 20.12-20.26 =4300 high 25% 20.27-20.41 =11500 [See next page for notes on this table.]
Eaual Seaments by Price lcontinuedl In the example above [Table 2], to find the volume in the lowest 25% of the price range: total day's price range then divide by 4. Or ($20.41-$19.81)= $.60/4= 15 cents. So we know that'/. of the day's price range is 15 cents.
Seament 1: The lowest price segment would range from $19.81 to $19.96. In this simplified example, we see that there are 4 transactions in this range, totaling 2150 shares in volume. That is 2150/20050 or 11 % of the volume for the day. This is 25% of the price range but only 11 % of the day's volume.
Sepment 2: The next higher price segment, would be $19.97 to $20.11. Again, there are 4 transactions, totaling 2100 shares in volume. 2100120050= 10% of the total volume. This is 25% of the price range but only 10% of the day's volume.
Segment 3: The next higher segment would be the range of $20.12 to $20.26. In this price range segment, there are 5 transactions totaling 4300 sha-es. 4300120050= 21%
of the total volume in 25% of the price range.
Segment 4: The highest 25% price range segment is $20.27-$20.41. In this price range segment there are 7 transactions totaling 11500 shares in volume. 11500120050=
57% of the total volume. So 57% of the volume is transacted in only 25% of the price range.
How is this useful? This example dearly shows that the bulk of the volume is in the upper price range. A typical stock chart would show you open, high, low, close and total daily volume. On a conventional chart, the user would have no indication of the volume distribution and may assume that the voiume is evenly distributed on that day. Using this method, the user gets a different picture of volume distribution, and therefore a different picture of supply and demand.
This charting method provides a valuable tool to a user who believes that volume is as important as price. A user could opt to view a conventional 'intra day' chart, looking at all of the activity on one chart. However, the present method summarizes an entire day's activities on one price bar, allowing the user to view the volume distribution for dozens of days at a glance.
B- Equal Segments by Volume (see Fig 2. attached):
What is it?: Using the ranked transaction data, the price range is divided into equal portions of volume, rather than price. The equal-volume segments will usually span varying price ranges, showing different sized segments on the price bar. The relative size of the segment indicates density of volume.
How is it calculated?: Starting at the lowest or highest price on the ranked transaction list, add up the volume until you get to 25% of the volume (in this case 4, but this can vary depending on the number of segments desired).
- When the price at which the 25% volume mark is reached, the transaction at this price is indicated on the price range bar as the first segment. This is repeated at each 25% volume segment.
- In the example in Table 1, above, the total volume for the day is 20050. If we want to divide the day's volume into 4 segments, they would result in 4 segments of approx 5012 units. The lowest priced 5012 segment of would range the first 9 transactions, from $19.81 to $20.13. So a hash mark is indicated at $20.13 on the price bar. We know that 25% of the daily price range is 15 cents. In this instance, the lowest priced 25% of the volume spans 32 cents.
This indicates very low density trading at the lower price ranges. The next segment is from $20.14 to $20.29 [the next hash mark would be at $20.29], which is 15 cents, so volume is perfectly proportionate to the price range within this segment. The next segments are calculated in the same manner, by summing the volume totals as you progress upward in price through the ranked data.
How is this useful?: The relative size (i.e. price range) of each segment will indicate the density of volume. A relatively large segment in the price range indicates reiatively low volume vs. the price range. A small segment shows that volume is concentn3ted there. As in the example above, if the daily price range is 60 cents, 1/4 of the price range is 15 cents, but the lowest priced 25%
segment of the volume is 32 cents, indicating 'thin' trading at the lower end of the price range.
- Unless the volume is evenly distributed for that day, the resulting chart will show 4 segments of unequal size, each representing a price segment with equal volume.
- Rather than using a wide, candlestick-type bar, this chart could also be drawn with normal 'narrow' bars with hash marks on the bar indicating the divisions.
- Dividing the daily volume into 3 to 5 segments would probably be the most practical unless one is using weekly or monthly indicators with large price ranges. Note that if you divide the price range into 2 equal volume segments, you effectively produce the chart in method 'D' [page 10, below], the 'Average Volume' Indicator.
C- The Median Transaction Indicator (See Fig 3, attached):
What is it? -The raw data can be processed to allow the user to view on the price bar the price of the 'median transaction' for the day. This could be a hash mark on the intra day price bar (such as a sideways 'T').
- The median transaction is that which half of the day's transactions are at a higher price and half are at a lower price.
How is it Calculated?: The total number of transactions are counted for the day on the ranked transaction list then transactions are counted starting from the lowest (or highest) price. The price of the 'middle' transaction is used to indicate the median transaction. E.g.
if there are 200 transaction for the day, the 100"' transaction from the bottom on the ranked list is the median transaction. Then the price for this transaction is indicated on the price bar.
How is this Useful? - This is useful in indicating whether the bulk of the transaction are occurring nearer to the high or low end of the price range rather than evenly distributed. A conventional chart gives a user no indication of transaction distribution within a day. The conventional chart user may assume that the transactions are evenly distributed on any given day.
Using this method, on a day in which the median transaction is significantly deviant from the middle of the price range, the user may interpret aberrant trading action.
D- Mean/Average Volume Indicator (see Fig 4, attached):
What is it?: The 'mean volume indicatoP shows the price at which half of the daily volume occurs below that price and half occurs above.
The point on the bar can be can be shown via a hash mark or unique symbol, such as a 'V' on the daily price bar.
How is it calculated?: This indicator is calculated by first adding up the total daily volume, then adding up the volume from the bottom of the ranked list upward until HALF of the daily total is reached. The price at which this occurs is the 'average volume transaction' and is indicated as such on the price bar.
How is this useful?: Unless the volume is evenly distributed within the day, this price indicator will be somewhat removed from the middle of the day's price range. The true 'middle' of the pricing action is better indicated when incorporating volume.
The farther the indicator is from the middle of the price range, the stronger the indication that volume is not evenly distributed. Any day in which the mean/average volume indicator is significantly removed from the mid-point in the price range, could indicate to the user aberrant trading action.
E- Cropping Off Aberrant Extreme Priced Volume:
What is it? Using the same transaction ranking process shown in table 1, the user can choose to "crop off" the extreme high and low priced volume for a day. E.g. The highest and lowest priced 1%, 5% or 10% (or other proportion chosen by the user) volume can be cropped off of the intra-day price bar, eliminating aberrant transactions which may not indicate true demand.
As the user crops off the ends, he ends up seeing the 'middle' 80% [if cropping off the top and bottom 10%] or 90% [if cropping off 5% at either end] of the volume action.
Note: this is NOT simply a matter of cropping off a % of the price by price range but rather the highest and lowest priced VOLUME on the ranked list.
Table 3: The user in the table below has chosen to crop off the highest and lowest priced 10% of the volume. The cropped off transactions are shown shaded below.
The ranked data from Table 1:
Transaction Price Volume Running Total:
4 19.81 300 300 9 19.86 1000 1300 1 19.92 750 2050 2 19.94 100 2150 6 20.02 400 2550 20.06 400 2950 3 20.07 500 3450 7 20.09 800 4250 8 20.13 600 4850 20.14 600 5450 14 20.18 100 5550 12 20.21 2000 7550 11 20.23 1000 8550 13 20.29 500 9050 20.31 2000 11050 16 20.32 1000 12050 17 20.35 1000 13050 20.36 2000 15050 18 20.38 3000 18050 19 20.41 2000 20050 Total: 20050 10% of volume= 2005 Il How is this calculated?: The user selects a % to crop off; for example 10%.
Then, using the ranked data, the running total volume is added up from the lowest price upward until the desired cropping % is reached. This point becomes the new'intra day low'. The same is done for the highest priced transactions. Volume is added up from the highest price downward in a running total until the desired % is reached, the price at that transaction becomes the new 'intra day high'.
This will be shown on the stock chart as a normal price bar, with the new high and low ends indicating the 'middle' 80%, rather than the conventional, absolute intraday high and low.
Using the data from table 3 above, we can see that cropping off the 10% lowest priced volume means that the first three transactions would be cropped off with a price range of 11 cents [19.81 +
19.86 + 19.92] because their corresponding volume = 10% of the total volume.
Likewise, cropping off the 10% hiahest priced volume means cropping off only one transaction, the one at $20.41.
So the resultin4 price bar would show a modified daily price range of $19.94 to $20 38 How is this useful?: This would be useful in situa6ons in which a low volume spike occurs at either a very low price or very high price for perhaps only a few minutes within a trading day.
- On a conventional chart, these low volume price spikes may show a user that a technical 'barrier has been breached or that a specific type of pattem is forming. But if these spikes are simply a few low volume, deviant transactions, such conclusions may be erroneous.
- This method can be used with 'transactions' and 'volume' with equal utility.
i.e. substitute cropping off the lowest priced volume with the lowest and highest priced % of transactions.
- With this method, the user gets a'cleaner view of the trading action by looking at the 'middle' 90% (or other %) of the volume. On days in which volume is evenly distributed, the cropping effect will be minimal.
- since the user will be looking at an entire chart with each price bar showing the same cropped-off proportions, there is no fear that this will show a skewed representation of the data. Quite the opposite; it eliminates skewed and aberrant data.
Notes on above charting methods:
1- The user may choose to superimpose any of the above indicators in any reasonable combination on the same chart and price bar includinc conventional open and close prices. E.g.
Average/mean volume hashmark indicator could be superimposed on a'cropped-ofP
price bar.
2- Methods C and D [median transacBon and mean volume indicaators] may also be used to show the price at which any specified proportion (other than 50%) of transactions or volume occurs. eg.
the point at which 20% of the transaction occur above a specific price or the point at which 70% of the volume occurs above a certain point. The 50% indicator would be the default measure.
3- Methods C and D may also be used to indicate by shading the price bar [as in a conventional candle stick chart] whether the day was an 'up' dav or a'down' day. That is, whether the indicator mark is at higher or lower price vs. the day before. Again note that opening and closing prices are irrelevant.
4- It should also be noted that the traditional bolume' bar in conventional stock chart, as a lower indicator, should always be used in conjunction with all of the above charting tools. This gives the user the absolute volume measurement by which he can better assess the significance of the indicators discussed presently.
5- Whereas in all of the above descxiptions, I have referred mostly to stockslequities; the method can be used with any financial instrument which involve a transaction with price and volume.
6- Whereas in all of the above descriptions, I have referred mostly to 'day' as the period in which the data will be ranked. The data from an entire week or month can be likewise processed to produce week or month price bars for long term charts. In many instances these will be more relevant than the daily charted data.
7- Methods 'A' and 'B' above can also be produced by measuring transactions, rather than volume.
8- Price bar 'shading' or 'colouring' could be substituted or augmented with varying degrees of bar width.
9- Whereas in the examples shown in the tables 1-3 above show only 20 transactions, most stocks will produce hundreds or thousands of transactions per day. The resulting segments or cropped off sections would likely contain dozens or hundreds of transactions, resulting in more precise and significant indicators.
Preferred Practice:
These graphing techniques could be used by any person who uses conventional price/volume stock charts. They give the user a better indication of supply/demand at specific prices or narrow price ranges and rather than indicating open and close prices.
Whereas most traditional chart analysis emphasize intra day highs, lows, open and close pricing. The present charting methods will be a tool for users who believe that open and closing prices are less important (or even arbitrary) points in the day and that price and volume must be looked at together.
The scope of the invention - the materials, compositions, conditions, etc., used to obtain good results:
Required:
a- raw market transaction data.
b- Spreadsheet column ranking software.
c- a means to make the raw data compatible with the spreadsheet software.
d- software to produce charts using the processed data.
Other relevant patents:
Lists of relevant patents or technical articies you've already found in any literature search, including full details such as name of inventor, number of patent, country and date of issue, or name of periodical and date. Indicate the similarities and differences of practices or products relevant to your invention.
Other relevant patents:
1- CA2356577 (abandoned).. STATUS: DEAD APPLICATION.
Uses shading within price bar to indicate % of transactions at bid and ask.
(Other relevant patents, continued) 2- CA2375114: Incorporates price and volume in lechnical' analysis.
Inventors (Country): BAKAYA, DHIRAJ DYLAN (United States) BAKAYA, ANIL (United States) (73) Owners (Country): BAKAYA, ANIL (United States) (71) Applicants (Country): BAKAYA, ANIL (United States) (74) Agent:
(45) Issued:
(86) PCT Filing Date: May 25, 2000 (87) PCT Publication Date: Dec.7,2000 Examination requested: May 19, 2005 (51) Intemationai Class (IPCI: G06Q30100(2006.01) G06F 17Af0 (2000.01) G06Q 40A10 (2006.01) Patent Cooueration Treaty (PCT): Yes (85) National Entry: Nov. 26,2001 (86) PCT Filing number: PCT/AU2000/000551 (87) International publication number: W02000/073946 (30) Application orioritv data:
Application No. Country Date PQ 0593 Australia May 27, 1999 Similarity: Processes pricing and volume market data.
Differences: No indication that this system produces new charting methods.
(other relevant patents continued) 3- CA2324195: METHOD FOR DETECTING ABERRANT BEHAVIOR OF A
FINANCIAL INSTRUMENT.
Inventors (Country): THOMAS, CHRISTOPHER K. (Canada) (73) Owners (Country): MEASUREDMARKETS INC. (Canada) (71) Applicants (Country): MEASUREDMARKETS INC. (Canada) (74) Agent: BERESKIN & PARR
(45) Issued:
(22) Ei(ed: Oct. 25,2000 (41) Open to Public Inspection: Apr. 25,2001 Examination requested: Oct. 24, 2005 (51) International C'lass (tPC): G06F17/60(2000.01) Patent Coooeration Treaty (PCT): No (30) Application priority data:
Application No. Country Date 60/161,083 United States Oct. 25, 1999 Similarities: Processes price and volume data.
Differences: Uses data to establish 'averages' for specific securities, then flags future deviations from this average.
(other relevant patents continued) 4- CA2518487:
Inventors (Country): HUANG, CHQi-WEI (United States) (73) Owners (Country): HUANG, CHIH-WEI (United States) (71) Apalicants (Country): HUANG, CHIH-WEI (United States) (74) A ent SMART & BIGGAR
(45) Issued:
(86) PCT Filing Date: Mar. 5, 2004 (87) PCT Publication Date: Sep. 23, 2004 Examination requested: Nov. 1, 2005 (51) InternationalC'lass(IPC'): G06F17/60(2000.01) Patent Cooperation Treaty (PCT): Yes (85) National Entry: Sep. 8, 2005 (86) PCT Filing number: PCTIUS2004/006744 (87) International publication number: W02004/081724 (30) Application priority data:
Application No. Country Date 10/385,959 United States Mar. 11, 2003 Similarities: The shown in the application diagram shows a'trading value generator' which generates the total dollar value of a trade. By adding a few steps, this could be used to generate the 'average volume indicatoP [charting method D above]. I don't believe the applicant makes this claim. Here's how it could work: 1- add up the total dollar value of all the trades for that stock for that day 2- divide this sum by the total volume of the day. 3- n:sult= average price for the day.
Differences: applicant always compares at least two instruments. No similarity to present application.
(other relevant patents, continued) Inventors: Garcia; Crisostomo B. (Rancho Santa Fe, CA) Appl. No.: 09/246,304 Filed: February 8,1999 Current U.S. Class: 705/36R; 705/35 Current International Class: G06T 11/20 (20060101) Field of Search: 705/35,36,37 Similarities: processes price and volume market data. Generates coloured indicators on price bars.
Differences: Indicates % and volume of trades at the 'ask', % and volume of trades at the 'bid', also % above and below bid and ask.
~ ----End of 'other relevant patents'--~
Aaplicant's Name. Address and Citizenshic):
Jason Mcisaac 47 St. Andrew's Ave Mt. Pearl, NL
Citizenship: Canadian All countries in which you would like to file for a ratent.
Canada & USA
Statement that a gatent is sought:
I, Jason Mclsaac, hereby assert my intention to seek a patent for the present subject matter.
Aug 10/2006 Description of the attached Figures:
Fipune 1: 'Eaual Segments by Price' chart [also see page 5 above]: The varying 'density' of volume is shown by varying shades or colours.
Figure 2: Equal Segments by Volume chart [also see paae 8 abovel: The segments are derived by dividing the total daily volume into equal parts then showing the corresponding price range for each segment. Using this method, a large segment on a price bar represents a 'low volume density' segment. In other words, the volume is spread out over a large price span so that price move through this range may not be a true indication of demand.
Fipure 3: The 'Median Transaction' chart [also see page 9 above] is produced by looking at transactions only, ignoring volume. The 'median transaction' is such that half of the transactions are at a lower price, half higher. The corresponding price is indicated with a sideways 'T' on the price bar.
Figure 4: The 'Average Volume' chart. [also see page 10 above] The price indicated represents the transaction at which half of the volume is at a higher price, half lower. The corresponding price is indicated with a'V on the price bar.
Preferred Practice:
These graphing techniques could be used by any person who uses conventional price/volume stock charts. They give the user a better indication of supply/demand at specific prices or narrow price ranges and rather than indicating open and close prices.
Whereas most traditional chart analysis emphasize intra day highs, lows, open and close pricing. The present charting methods will be a tool for users who believe that open and closing prices are less important (or even arbitrary) points in the day and that price and volume must be looked at together.
The scope of the invention - the materials, compositions, conditions, etc., used to obtain good results:
Required:
a- raw market transaction data.
b- Spreadsheet column ranking software.
c- a means to make the raw data compatible with the spreadsheet software.
d- software to produce charts using the processed data.
Other relevant patents:
Lists of relevant patents or technical articies you've already found in any literature search, including full details such as name of inventor, number of patent, country and date of issue, or name of periodical and date. Indicate the similarities and differences of practices or products relevant to your invention.
Other relevant patents:
1- CA2356577 (abandoned).. STATUS: DEAD APPLICATION.
Uses shading within price bar to indicate % of transactions at bid and ask.
(Other relevant patents, continued) 2- CA2375114: Incorporates price and volume in lechnical' analysis.
Inventors (Country): BAKAYA, DHIRAJ DYLAN (United States) BAKAYA, ANIL (United States) (73) Owners (Country): BAKAYA, ANIL (United States) (71) Applicants (Country): BAKAYA, ANIL (United States) (74) Agent:
(45) Issued:
(86) PCT Filing Date: May 25, 2000 (87) PCT Publication Date: Dec.7,2000 Examination requested: May 19, 2005 (51) Intemationai Class (IPCI: G06Q30100(2006.01) G06F 17Af0 (2000.01) G06Q 40A10 (2006.01) Patent Cooueration Treaty (PCT): Yes (85) National Entry: Nov. 26,2001 (86) PCT Filing number: PCT/AU2000/000551 (87) International publication number: W02000/073946 (30) Application orioritv data:
Application No. Country Date PQ 0593 Australia May 27, 1999 Similarity: Processes pricing and volume market data.
Differences: No indication that this system produces new charting methods.
(other relevant patents continued) 3- CA2324195: METHOD FOR DETECTING ABERRANT BEHAVIOR OF A
FINANCIAL INSTRUMENT.
Inventors (Country): THOMAS, CHRISTOPHER K. (Canada) (73) Owners (Country): MEASUREDMARKETS INC. (Canada) (71) Applicants (Country): MEASUREDMARKETS INC. (Canada) (74) Agent: BERESKIN & PARR
(45) Issued:
(22) Ei(ed: Oct. 25,2000 (41) Open to Public Inspection: Apr. 25,2001 Examination requested: Oct. 24, 2005 (51) International C'lass (tPC): G06F17/60(2000.01) Patent Coooeration Treaty (PCT): No (30) Application priority data:
Application No. Country Date 60/161,083 United States Oct. 25, 1999 Similarities: Processes price and volume data.
Differences: Uses data to establish 'averages' for specific securities, then flags future deviations from this average.
(other relevant patents continued) 4- CA2518487:
Inventors (Country): HUANG, CHQi-WEI (United States) (73) Owners (Country): HUANG, CHIH-WEI (United States) (71) Apalicants (Country): HUANG, CHIH-WEI (United States) (74) A ent SMART & BIGGAR
(45) Issued:
(86) PCT Filing Date: Mar. 5, 2004 (87) PCT Publication Date: Sep. 23, 2004 Examination requested: Nov. 1, 2005 (51) InternationalC'lass(IPC'): G06F17/60(2000.01) Patent Cooperation Treaty (PCT): Yes (85) National Entry: Sep. 8, 2005 (86) PCT Filing number: PCTIUS2004/006744 (87) International publication number: W02004/081724 (30) Application priority data:
Application No. Country Date 10/385,959 United States Mar. 11, 2003 Similarities: The shown in the application diagram shows a'trading value generator' which generates the total dollar value of a trade. By adding a few steps, this could be used to generate the 'average volume indicatoP [charting method D above]. I don't believe the applicant makes this claim. Here's how it could work: 1- add up the total dollar value of all the trades for that stock for that day 2- divide this sum by the total volume of the day. 3- n:sult= average price for the day.
Differences: applicant always compares at least two instruments. No similarity to present application.
(other relevant patents, continued) Inventors: Garcia; Crisostomo B. (Rancho Santa Fe, CA) Appl. No.: 09/246,304 Filed: February 8,1999 Current U.S. Class: 705/36R; 705/35 Current International Class: G06T 11/20 (20060101) Field of Search: 705/35,36,37 Similarities: processes price and volume market data. Generates coloured indicators on price bars.
Differences: Indicates % and volume of trades at the 'ask', % and volume of trades at the 'bid', also % above and below bid and ask.
~ ----End of 'other relevant patents'--~
Aaplicant's Name. Address and Citizenshic):
Jason Mcisaac 47 St. Andrew's Ave Mt. Pearl, NL
Citizenship: Canadian All countries in which you would like to file for a ratent.
Canada & USA
Statement that a gatent is sought:
I, Jason Mclsaac, hereby assert my intention to seek a patent for the present subject matter.
Aug 10/2006 Description of the attached Figures:
Fipune 1: 'Eaual Segments by Price' chart [also see page 5 above]: The varying 'density' of volume is shown by varying shades or colours.
Figure 2: Equal Segments by Volume chart [also see paae 8 abovel: The segments are derived by dividing the total daily volume into equal parts then showing the corresponding price range for each segment. Using this method, a large segment on a price bar represents a 'low volume density' segment. In other words, the volume is spread out over a large price span so that price move through this range may not be a true indication of demand.
Fipure 3: The 'Median Transaction' chart [also see page 9 above] is produced by looking at transactions only, ignoring volume. The 'median transaction' is such that half of the transactions are at a lower price, half higher. The corresponding price is indicated with a sideways 'T' on the price bar.
Figure 4: The 'Average Volume' chart. [also see page 10 above] The price indicated represents the transaction at which half of the volume is at a higher price, half lower. The corresponding price is indicated with a'V on the price bar.
Claims (17)
1- A computerized method for monitoring for a user the price and volume activities of a financial instrument traded in a financial market in a selected timeframe, showing modified price bars within said timeframe representing price and volume within discrete segments of time, comprising the steps of: (a) collection of the price and volume data for each transaction for a selected period for the financial instrument (b) sorting the transactions by price within the selected period, preserving both the price and volume data for each transaction (c) using the sorted data to produce new chart types.
2- The method of claim 1, wherein said transaction sorting method produces a list of the transactions, from lowest to highest, or alternatively from highest to lowest, and ignores the time for each transaction within the selected period.
3- The method of claim 1, producing the "Equal Segments by Price" chart type comprising of a series of two dimensional price bars spanning the prices between the high and low prices for the selected period, having a non-zero width sufficient to display shading or colouring and each price bar being segmented vertically into a number of equal priced segments, each segment then indicating the segment volume relative to the volume for the entire period by the use of shading or colouring within the segment.
4- The method of claim 1 producing the "Equal Segments by Volume" chart comprising of a two dimensional price bar spanning the prices between the high and low prices for the selected period, having a non-zero width sufficient to display shading or colouring and being segmented vertically into equal portions by volume, each segment then indicating the relative price range and volume density within the period by its relative size within the period and by shading or colouring.
5- The method of claim 1 producing the "Median Transaction Indicator" chart type comprising of a price bar spanning the prices between the high and low prices for the selected period and indicating on said price bar a hash mark representing the price at which half of the transactions are at a higher price within the period and half are at a lower price within the period.
6- The method of claim 1 producing "The Average Volume Indicator" chart type comprising of a price bar spanning the prices between the high and low prices for the selected period and indicating on said price bar a hash mark representing the price at which half of the volume is at a higher price within the period and half is at a lower price within the period.
7- The method of claim 1 producing the "Cropped Off Price Bar" chart type comprising of a price bar which shows a modified high and modified low price within the period, the portion of said price bar being cropped off representing a selected percentage of the highest and lowest priced volume as indicated by the sorted transaction data.
8- The methods from claims 3 to 7 further comprising plotting a plurality of bars on a price-time chart by a processor wherein said price-time chart is a two dimensional chart, with the Y-coordinate representing price and X-coordinate representing time, with the X-axis divided into a predetermined plurality of discrete intervals, each interval representing an amount of time equal to that chosen by the user, most commonly representing a single trading day.
9- The method of claim 1 further comprising a computerized system with sorting capabilities.
10- The method of claims 3 to 7 further comprising a computerized system capable of producing the new chart types.
11- The method of claims 3 to 7 wherein said chart types will show price bars, the values of which shall correspond to the prices indicated on the Y-axis price indicator.
12- The method of claims 3 and 4 wherein said chart type is an enhancement to a conventional bar chart which is augmented by being divided into discrete segments, and said segments being partitioned vertically by using horizontal dividers across the width of the bar.
13- The method of claims 3 and 4 further comprising of a colour or shading key to provide interpretation of the value of each colour or shade within each segment in terms of relative volume density.
14- The method of claims 3 and 4 further comprising a means to allow the user to select the number of segments desired.
15- The method of claim 7 further comprising of a means to allow the user to select the percentage of volume being cropped off the price bar.
16- The method of claims 3-7, further comprising: allowing the user to select and combine on one chart, and on one modified price bar, the graphical functions of more than one chart such that the 'median transaction indicator' of claim 5 may be displayed on a bar in the chart types for claims 3, 4, 6 and 7.
17- The method of claims 3-7, further comprising: allowing the user to select combine on one chart and on one price bar, the graphical functions of the 'average volume indicator' of claim 6 to be displayed on the bar from chart types for claims 3, 4, 5 and 7.
These drawings are incorporated in and constitute a part of this specification, illustrate preferred embodiments of the invention, and together with the description, serve to explain the principles of this invention.
These drawings are incorporated in and constitute a part of this specification, illustrate preferred embodiments of the invention, and together with the description, serve to explain the principles of this invention.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA 2555967 CA2555967A1 (en) | 2006-08-14 | 2006-08-14 | Mcisaac method for charting financial instrument price and volume activities |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA 2555967 CA2555967A1 (en) | 2006-08-14 | 2006-08-14 | Mcisaac method for charting financial instrument price and volume activities |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA2555967A1 true CA2555967A1 (en) | 2008-02-14 |
Family
ID=39103072
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA 2555967 Abandoned CA2555967A1 (en) | 2006-08-14 | 2006-08-14 | Mcisaac method for charting financial instrument price and volume activities |
Country Status (1)
| Country | Link |
|---|---|
| CA (1) | CA2555967A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109410042A (en) * | 2017-08-16 | 2019-03-01 | 李卓然 | Price data expression based on fixed unit exchange hand |
-
2006
- 2006-08-14 CA CA 2555967 patent/CA2555967A1/en not_active Abandoned
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109410042A (en) * | 2017-08-16 | 2019-03-01 | 李卓然 | Price data expression based on fixed unit exchange hand |
| CN109410042B (en) * | 2017-08-16 | 2022-06-21 | 李卓然 | Price data expression method based on fixed unit volume |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20020194114A1 (en) | Multi-dimensional representation of financial data | |
| Al-Tamimi | Factors influencing individual investor behavior: an empirical study of the UAE financial markets | |
| Gimba | Testing the weak-form efficiency market hypothesis: Evidence from Nigerian stock market | |
| Mokhtar et al. | Comparative study on performance measures and attributes between ISO and non-ISO certification companies | |
| Röller et al. | Why firms form Research Joint Ventures: theory and evidence | |
| Ukpong et al. | Determinants of industry herding in the US stock market | |
| Cotterill et al. | A PIMS analysis of the structure profit relationship in food manufacturing | |
| Bertolis et al. | An investigation into South African general equity unit trust performance during different economic periods | |
| Economou | Herding in frontier markets: evidence from the Balkan region | |
| Lin et al. | The association between–market risk disclosure reporting and firm risk: the impact of SEC FRR No. 48 | |
| Parvi | „Share price of the companies listed on the WIG-UKRAINE and their fair value” | |
| Day et al. | Do clean energy indices outperform using contrarian strategies based on contrarian trading rules? | |
| Khan et al. | Testing strong form market efficiency of Indian capital market: Performance appraisal of mutual funds | |
| CA2555967A1 (en) | Mcisaac method for charting financial instrument price and volume activities | |
| Antunes | Co-movement of revisions in short-and long-term inflation expectations | |
| Zimmermann | Explaining the high P/E ratios: The message from the Gordon model | |
| Gami | An analysis of factors affecting equity mutual fund performance | |
| Samad et al. | The perception of risk and uncertainty and the usage of capital budgeting techniques: Evidence from public listed firms in Malaysia | |
| Mandaci | Testing capital structure models for Turkish non-financial firms: the analysis of firm-specific financial factors and agency variables | |
| Sinha et al. | Selection of a discount rate or minimum acceptable IRR | |
| Johansson et al. | Size and Performance of Swedish Mutual Funds: Does Size Matter? | |
| Hand et al. | The dual use of residual income and discounted cash flow valuation methods by US sell-side equity analysts | |
| Primbs et al. | Trader behavior and its effect on asset price dynamics | |
| Miller et al. | Discount Rates, Cost of Capital, and Property Acquisition Evaluations | |
| LAOKULRACH et al. | Price Effect of Changing in the Stock Exchange of Thailand 100 Index's Constituents. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| EEER | Examination request | ||
| FZDE | Dead |
Effective date: 20141007 |