A dynamic space pricing system based on spatial variable k-line

Abstract

The application discloses a dynamic space pricing system based on space variable K line, which comprises a space pricing system, wherein the space pricing system comprises a trend line display module, an account security module, a magic block pricing module, a K line pricing module, a K line variable calculation module and a data output module; the system is adaptive to the size of market level, the points of each magic block are calculated by subtracting the closing price from the opening price, and the number of magic blocks is less in the same space relative to K lines and brick graphs; the less number represents less closing price, reduces noise, avoids unnecessary interference signals in index transmission, and solves the problem of various space changes by the advantages of self-adaptation and self-variable; the space variable K line is based on the original space variable K line, the number of direction changes is quantified, coordinates are given to market, and the number of direction changes in a month is usually divided into 1-3 times; the number of trial and error times is limited to 1-3 times, and the target income can be stably achieved with low trial and error cost.

Description

Technical Field

[0001] This invention relates to the field of foreign exchange market pricing technology, specifically a dynamic spatial pricing system based on spatial variable K-lines. Background Technology

[0002] Candlestick charts clearly show price fluctuations by displaying the opening, closing, highest, and lowest prices of a currency pair within a specific timeframe. In an uptrend, a bullish candlestick closing higher than its opening price indicates strong buying pressure; in a downtrend, a bearish candlestick closing lower than its opening price indicates that selling pressure is dominant. Candlestick charts help identify important support and resistance levels. When prices repeatedly encounter resistance or find support near a certain level, that level forms a key resistance or support level. These levels are crucial for developing trading strategies; for example, considering selling near resistance levels and buying near support levels. Candlestick patterns such as the "hammer" and "hanging man" candlesticks are significant indicators of price movement. Candlestick charts are of significant reference value. A hammer candlestick appearing in a downtrend indicates a possible reversal, while a hanging man candlestick appearing in an uptrend suggests an impending reversal. These patterns help investors capture market reversal signals. Candlestick charts also reflect the balance of power between buyers and sellers. The longer the body of a bullish candlestick, the stronger the buying power; the longer the body of a bearish candlestick, the stronger the selling power. The length of the upper and lower shadows also reflects the intensity of market competition. By observing the arrangement and combination of candlestick charts, investors can quickly determine the main trend of the market and determine entry and exit points. Long-term candlestick chart analysis can also help identify the main market trend, thereby formulating corresponding investment strategies.

[0003] In many trading systems in the forex market, most indicator signals are read from the closing price of candlestick charts. However, in actual trading, it is found that candlestick charts often cannot cope with sudden changes in market conditions. When the direction changes in a short period of time, candlestick charts, constrained by the time cycle, cannot quickly close and issue signals, causing indicators to fail to transmit buy and sell orders in a timely manner. In volatile markets, candlestick charts are too static, ignoring the size of the market movement and only closing according to the time cycle, issuing a large number of meaningless false signals. In view of the characteristics of candlestick charts, the market later developed price charts based on price space, removing the time constraint and increasing the number of price chart closing prices in fast-changing markets, thus solving the problem of slow signal reception by indicators.

[0004] However, traditional brick plans priced based on space have the following drawbacks:

[0005] Since the number of points in each brick within a brick chart priced in space is fixed, if the closing price is too dense in a wide-range oscillating market, it still cannot solve the problem of providing false signals to the indicator.

[0006] The first-generation time-based candlestick chart / Candle records price changes with a fixed time period, such as 1 hour. During consolidation periods, there are many false signals, leading investors to trade repeatedly and incurring high trial-and-error costs. During rapidly changing market conditions, the signals are delayed, causing missed opportunities.

[0007] The second-generation spatial candlestick chart / Renko fixed point number change triggers new candlesticks, shortening signal delay in fast-changing market conditions, but still resulting in more false signals in consolidating market conditions. Summary of the Invention

[0008] The purpose of this invention is to provide a dynamic spatial pricing system based on spatial variable candlestick charts to solve the problem mentioned in the background art: because the number of points in each candlestick chart within the spatial pricing chart is fixed, the closing prices become too dense in a wide-range oscillating market, which still cannot solve the problem of providing false signals to the indicator. The first-generation time-based candlestick chart / Candle records price changes with a fixed time period, such as 1 hour. During consolidation, there are many false signals, leading to repeated trading by investors and high trial-and-error costs. In fast-changing markets, the signals are delayed, resulting in missed opportunities. The second-generation spatial candlestick chart / Renko uses fixed point changes to trigger new candlesticks, which shortens the signal delay in fast-changing markets, but still results in many false signals in consolidation markets.

[0009] To achieve the above objectives, the present invention provides the following technical solution: a dynamic spatial pricing system based on spatial variable K-lines, comprising a spatial pricing system, wherein the spatial pricing system includes a trend line display module, an account security module, a block pricing module, a K-line pricing module, a K-line variable calculation module, and a data output module;

[0010] The trend line display module is an important indicator for reference direction, and the trend line will automatically adjust as the market changes; the account security module sets access restrictions for the encrypted index based on specific application needs through account and password settings, including release time; the block pricing module uses a pure spatial pricing method to display the changes in bullish and bearish markets by adapting to price fluctuations under a certain energy standard; the candlestick pricing module helps investors judge market trends; the candlestick variable calculation module adds 3D thinking concepts, artificial intelligence, econometrics, and statistical calculations to the block chart, evolving from the original static block chart into a more advanced variable candlestick; and the data output module outputs the final foreign exchange pricing value.

[0011] As a preferred technical solution of the present invention, the K-line variable calculation module includes a quantitative calculation submodule, a statistical calculation submodule, an artificial intelligence calculation submodule, and a 3D thinking concept calculation submodule;

[0012] The econometrics calculation module uses moving averages to smooth price data and display trends. The calculation formula is as follows:

[0013] MA = (P1 + P2 + P3 + ... + Pn) / n

[0014] Where MA is the value of the moving average, P1 to Pn are the corresponding price data, n is the selected period number, and the Relative Strength Index (RSI) is used to measure the degree of overbought or oversold conditions in the market. The calculation formula is as follows:

[0015] RSI = 100 - (100 / (1+RS))

[0016] Where RS is the relative intensity RS, and the formula for calculating RS is:

[0017] RS = (Average closing price increase during an uptrend / Average closing price decrease during an downtrend)

[0018] The stochastic oscillator is an indicator used to determine whether the market is overbought or oversold. Its calculation formula is as follows:

[0019]

[0020] Where C is the current closing price, L is the lowest price, H is the highest price, n is the selected period, MA is the moving average, and the exponential moving average (EMA) is a weighted average calculated based on historical data, and the calculation formula is as follows:

[0021] EMA = (Today's closing price * 2 / (selected period number + 1)) + (Yesterday's EMA * (1 - 2 / (selected period number + 1)))

[0022] The basic formula for profit and loss calculation in the statistical calculation submodule is as follows:

[0023] Profit / Loss = (Closing Position - Opening Price) × Value per Point × Contract Terms - Transaction Fees

[0024] The direct exchange rate calculation formula of the artificial intelligence calculation submodule is as follows:

[0025] Direct transfer = target goods / basic goods

[0026] Indirect exchange rates are calculated as follows:

[0027] Indirect exchange rate = Base currency / Intermediate currency · Target currency / Intermediate currency

[0028] The 3D thinking concept calculation submodule measures volatility by calculating the fluctuation range of exchange rates over a period of time. The calculation formula is as follows:

[0029] Historical volatility = (Current closing price - n-day closing price) / n-day closing price * Standard deviation of daily returns

[0030] Volatility is estimated by calculating the standard deviation of daily returns, using the following formula:

[0031]

[0032] Where σ is the standard deviation, r i Let r represent the daily rate of return, r be the average of all rates of return, and n be the number of days.

[0033] As a preferred embodiment of the present invention, the data output module includes a data comparison submodule, a data removal submodule, a data storage submodule, and a data display submodule;

[0034] The data comparison submodule compares the K-line pricing data and the block data; the data removal submodule removes the calculated abnormal data; the data storage submodule stores the calculated data in real time; and the data display submodule displays the final foreign exchange data.

[0035] As a preferred embodiment of the present invention, the K-line pricing module includes a pattern analysis submodule, a moving average analysis submodule, and a volume-price analysis submodule;

[0036] The pattern analysis submodule helps investors predict price trends through patterns such as head and shoulders top, head and shoulders bottom, double top, and double bottom. The moving average analysis submodule provides buy and sell signals for investors through the 5-day, 10-day, and 20-day moving averages, as well as the crossover and arrangement of these moving averages. The volume and price analysis submodule increases the accuracy of the analysis by showing that the increase or decrease in trading volume often corroborates the rise and fall of prices.

[0037] As a preferred embodiment of the present invention, the block pricing module includes a multi-block sub-module and a non-block sub-module;

[0038] When the market price rises, the number of points in the Bullish Block submodule increases accordingly. This means that when the market is rising, the Bullish Block captures more upward signals, helping investors seize buying opportunities in a timely manner. When the market price falls, the number of points in the Bearish Block submodule increases. This means that when the market is falling, the Bearish Block captures more downward signals, helping investors seize selling opportunities in a timely manner.

[0039] As a preferred embodiment of the present invention, the account security module includes an account application submodule, an account password submodule, and an encryption permission submodule;

[0040] The account application submodule applies for an account, the account password submodule applies for the corresponding password, and the encryption permission submodule generates and uploads the encrypted index and authorizes others to search, and sets access restrictions with release time for the encrypted index.

[0041] As a preferred embodiment of the present invention, the trend line display module includes a red trend line sub-module, a green trend line sub-module, and a yellow trend line sub-module;

[0042] The red trend line submodule is used as an important indicator for reference in the direction of going long, the green trend line submodule is used as an important indicator for reference in the direction of going short, and the yellow trend line submodule is used as an important indicator for reference in the direction of staying on the sidelines.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] This system adapts to the size of the market data level, changing the number of points on a daily basis. The number of points for each block is calculated by subtracting the closing price from the opening price. The smaller the number of points, the more blocks there will be relative to the candlestick chart and the overall chart pattern within the same space. A larger number of blocks indicates a higher closing price, which transmits signals to the indicator more quickly. Conversely, the larger the number of points, the fewer blocks there will be relative to the candlestick chart and the overall chart pattern within the same space. A smaller number of blocks indicates a lower closing price, reducing noise and avoiding transmitting unnecessary interference signals to the indicator. It addresses the challenges of various market data changes with its adaptive and variable features.

[0045] Based on the unique spatial variable K-line, the number of directional changes is quantified, and coordinates are assigned to the market. The number of directional changes within a month is usually divided into 1-3 times, limiting the number of trials and errors to between 1-3 times. This has the characteristics of low trial and error costs and stable achievement of target returns. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the spatial pricing system of the present invention;

[0047] Figure 2 This is a schematic diagram of the architecture of the trend line display module of the present invention;

[0048] Figure 3 This is a schematic diagram of the architecture of the account security module of the present invention;

[0049] Figure 4 This is a schematic diagram of the architecture of the block pricing module of the present invention;

[0050] Figure 5 This is a schematic diagram of the architecture of the K-line pricing module of the present invention;

[0051] Figure 6 This is a schematic diagram of the architecture of the K-line variable calculation module of the present invention;

[0052] Figure 7 This is a schematic diagram of the architecture of the data output module of the present invention;

[0053] Figure 8 This is a schematic diagram illustrating the use of the rapid market information update of this invention. Detailed Implementation

[0054] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0055] Please see Figure 1-8 This invention provides a dynamic spatial pricing system based on spatial variable K-lines, including a spatial pricing system, which comprises a trend line display module, an account security module, a block pricing module, a K-line pricing module, a K-line variable calculation module, and a data output module.

[0056] The trend line display module is an important indicator for reference direction, and the trend line will automatically adjust as the market changes; the account security module sets access restrictions for the encrypted index based on specific application needs through account and password settings, including release time; the block pricing module uses a pure spatial pricing method to display the changes in bullish and bearish markets by adapting to price fluctuations under a certain energy standard; the candlestick pricing module helps investors judge market trends; the candlestick variable calculation module adds 3D thinking concepts, artificial intelligence, econometrics, and statistical calculations to the block chart, evolving from the original static block chart into a more advanced variable candlestick; and the data output module outputs the final foreign exchange pricing value.

[0057] The K-line variable calculation module includes a quantitative calculation submodule, a statistical calculation submodule, an artificial intelligence calculation submodule, and a 3D thinking concept calculation submodule;

[0058] The econometrics calculation module uses moving averages to smooth price data and display trends. The calculation formula is as follows:

[0059] MA = (P1 + P2 + P3 + ... + Pn) / n

[0060] Where MA is the value of the moving average, P1 to Pn are the corresponding price data, n is the selected period number, and the Relative Strength Index (RSI) is used to measure the degree of overbought or oversold conditions in the market. The calculation formula is as follows:

[0061] RSI = 100 - (100 / (1+RS))

[0062] Where RS is the relative intensity RS, and the formula for calculating RS is:

[0063] RS = (Average closing price increase during an uptrend / Average closing price decrease during an downtrend)

[0064] The stochastic oscillator is an indicator used to determine whether the market is overbought or oversold. Its calculation formula is as follows:

[0065]

[0066] Where C is the current closing price, L is the lowest price, H is the highest price, n is the selected period, MA is the moving average, and the exponential moving average (EMA) is a weighted average calculated based on historical data, and the calculation formula is as follows:

[0067] EMA = (Today's closing price * 2 / (selected period number + 1)) + (Yesterday's EMA * (1 - 2 / (selected period number + 1)))

[0068] The basic formula for profit and loss calculation in the statistical calculation submodule is as follows:

[0069] Profit / Loss = (Closing Position - Opening Price) × Value per Point × Contract Terms - Transaction Fees

[0070] The direct exchange rate calculation formula of the artificial intelligence calculation submodule is as follows:

[0071] Direct transfer = target goods / basic goods

[0072] Indirect exchange rates are calculated as follows:

[0073] Indirect exchange rate = Base currency / Intermediate currency · Target currency / Intermediate currency

[0074] The 3D thinking concept calculation submodule measures volatility by calculating the fluctuation range of exchange rates over a period of time. The calculation formula is as follows:

[0075] Historical volatility = (Current closing price - n-day closing price) / n-day closing price * Standard deviation of daily returns

[0076] Volatility is estimated by calculating the standard deviation of daily returns, using the following formula:

[0077]

[0078] Where σ is the standard deviation, r i Let r represent the daily rate of return, r be the average of all rates of return, and n be the number of days.

[0079] The data output module includes a data comparison submodule, a data removal submodule, a data storage submodule, and a data display submodule;

[0080] The data comparison submodule compares the K-line pricing data and the block data; the data removal submodule removes the calculated abnormal data; the data storage submodule stores the calculated data in real time; and the data display submodule displays the final foreign exchange data.

[0081] The candlestick pricing module includes a pattern analysis submodule, a moving average analysis submodule, and a volume-price analysis submodule.

[0082] The pattern analysis submodule helps investors predict price trends through patterns such as head and shoulders top, head and shoulders bottom, double top, and double bottom. The moving average analysis submodule provides buy and sell signals for investors through the 5-day, 10-day, and 20-day moving averages, as well as the crossover and arrangement of these moving averages. The volume and price analysis submodule increases the accuracy of the analysis by showing that the increase or decrease in trading volume often corroborates the rise and fall of prices.

[0083] The block pricing module includes a multi-block sub-module and a short-block sub-module;

[0084] When the market price rises, the number of points in the Bullish Block submodule increases accordingly. This means that when the market is rising, the Bullish Block captures more upward signals, helping investors seize buying opportunities in a timely manner. When the market price falls, the number of points in the Bearish Block submodule increases. This means that when the market is falling, the Bearish Block captures more downward signals, helping investors seize selling opportunities in a timely manner.

[0085] The account security module includes an account application submodule, an account password submodule, and an encryption permission submodule;

[0086] The account application submodule applies for an account, the account password submodule applies for the corresponding password, and the encryption permission submodule generates and uploads the encrypted index and authorizes others to search, and sets access restrictions with release time for the encrypted index.

[0087] The trend line display module includes a red trend line sub-module, a green trend line sub-module, and a yellow trend line sub-module;

[0088] The red trend line submodule is used as an important indicator for reference in the direction of going long, the green trend line submodule is used as an important indicator for reference in the direction of going short, and the yellow trend line submodule is used as an important indicator for reference in the direction of staying on the sidelines.

[0089] In this invention, the account application submodule applies for an account, the account password submodule applies for the password corresponding to the account, the encryption permission submodule generates and uploads an encrypted index and authorizes others to search for it, and sets access restrictions with release time for the encrypted index, the pattern analysis submodule helps investors predict price trends through head and shoulders tops, head and shoulders bottoms, double tops, and double bottoms, etc., the moving average analysis submodule provides buy and sell signals to investors through the 5-day, 10-day, and 20-day moving averages, and the crossover and arrangement of the moving averages, and the volume and price analysis submodule observes that the increase or decrease in trading volume is often related to price. The rise and fall of prices corroborate each other, increasing the accuracy of the analysis. In the "Bull Block" submodule, when the market price rises, the number of points in the Bull Block increases accordingly. This means that when the market is rising, the Bull Block captures more upward signals, helping investors seize buying opportunities in a timely manner. In the "Bear Block" submodule, when the market price falls, the number of points in the Bear Block increases. This means that when the market is falling, the Bear Block captures more downward signals, helping investors seize selling opportunities in a timely manner. The Econometrics Calculation submodule uses moving averages to smooth price data and display trends. The calculation formula is as follows:

[0090] MA = (P1 + P2 + P3 + ... + Pn) / n

[0091] Where MA is the value of the moving average, P1 to Pn are the corresponding price data, n is the selected period number, and the Relative Strength Index (RSI) is used to measure the degree of overbought or oversold conditions in the market. The calculation formula is as follows:

[0092] RSI = 100 - (100 / (1+RS))

[0093] Where RS is the relative intensity RS, and the formula for calculating RS is:

[0094] RS = (Average closing price increase during an uptrend / Average closing price decrease during an downtrend)

[0095] The stochastic oscillator is an indicator used to determine whether the market is overbought or oversold. Its calculation formula is as follows:

[0096]

[0097] Where C is the current closing price, L is the lowest price, H is the highest price, n is the selected period, MA is the moving average, and the exponential moving average (EMA) is a weighted average calculated based on historical data, and the calculation formula is as follows:

[0098] EMA = (Today's closing price * 2 / (selected period number + 1)) + (Yesterday's EMA * (1 - 2 / (selected period number + 1)))

[0099] The basic formula for profit and loss calculation in the statistical calculation submodule is as follows:

[0100] Profit / Loss = (Closing Position - Opening Price) × Value per Point × Contract Terms - Transaction Fees

[0101] The direct exchange rate calculation formula of the artificial intelligence calculation submodule is as follows:

[0102] Direct transfer = target goods / basic goods

[0103] Indirect exchange rates are calculated as follows:

[0104] Indirect exchange rate = Base currency / Intermediate currency · Target currency / Intermediate currency

[0105] The 3D thinking concept calculation submodule measures volatility by calculating the fluctuation range of exchange rates over a period of time. The calculation formula is as follows:

[0106] Historical volatility = (Current closing price - n-day closing price) / n-day closing price * Standard deviation of daily returns

[0107] Volatility is estimated by calculating the standard deviation of daily returns, using the following formula:

[0108]

[0109] Where σ is the standard deviation, r i This represents the daily rate of return. This is the average of all returns, where n is the number of days. Refer to the appendix in the instruction manual. Figure 8 When the market is changing rapidly, the number of blocks priced purely in space increases, which can transmit the signal of bullish or bearish reversal to the trend line more quickly and accurately, and capture the trend in time. When the market is in a transitional phase, the number of blocks priced purely in space decreases, which reduces the false signal of insufficient energy transmitted to the trend line and reduces cost consumption.

[0110] The formula for calculating profit is as follows:

[0111] Profit = Price difference × Quantity

[0112] The correct direction determines the nature of profit and loss, while price difference and quantity control determine the scale of profit. For example, shorting 1 lot of EUR / USD from 1.1050 to closing at 1.1040 yields a profit of $100. With margin trading leverage, a $1000 principal → 1% margin → controls a $100,000 contract. A 1% price fluctuation → 100% return on principal. Traditional investment requires 100% principal to achieve this. In some currency pairs, such as GBP / JPY, research shows that monthly fluctuations average 700-800 pips, with at least 200 pips. The key to trading strategy is capturing this 200-pip price difference when the direction is correct (either short or long). We use a "follow" approach for directional indicators, such as using 1%... A margin order with a 200-point spread is placed. If the direction is correct and the target spread is reached, a 2% profit is achieved, ending the month's trading. If the target profit is not reached, the position is closed immediately when the direction indicator changes, and the loss is added to the target profit to calculate the next order size. This process continues until a correct "following" is achieved. Verification using a real account over 7.5 years shows: the success rate of the first two correct followings is >80%; the success rate of the first three correct followings is >97%, and there have been no instances of more than three failed attempts, meaning the success rate of the first four correct followings is currently 100%. Therefore, a single currency pair yields a stable monthly return of 2%, or 24% annually. Trading two currency pairs yields a monthly return of 4%, or 48% annually, conservatively estimated at 36%. Combined with other quantitative trading strategies, the maximum drawdown is controlled to no more than 10%.

[0113] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic spatial pricing system based on spatial variable K-lines, comprising a spatial pricing system, characterized in that: The spatial pricing system includes a trend line display module, an account security module, a block pricing module, a candlestick pricing module, a candlestick variable calculation module, and a data output module. The trend line display module is an important indicator for reference direction, and the trend line will automatically adjust as the market changes; the account security module sets access restrictions for the encrypted index by account and password settings according to specific application needs, and releases the time limit; the block pricing module is a tool to show the changes in bullish and bearish markets by using a pure spatial pricing method and adapting to the price fluctuations of the market under a certain energy standard; the candlestick pricing module helps investors judge market trends. The K-line variable calculation module incorporates 3D thinking, artificial intelligence, econometrics, and statistical calculations into the brick chart, evolving from the original static brick chart into a more advanced variable K-line. The data output module outputs the final foreign exchange pricing value.

2. The dynamic spatial pricing system based on spatial variable K-lines according to claim 1, characterized in that: The K-line variable calculation module includes a quantitative calculation submodule, a statistical calculation submodule, an artificial intelligence calculation submodule, and a 3D thinking concept calculation submodule; The econometrics calculation module uses moving averages to smooth price data and display trends. The calculation formula is as follows: MA = (P1 + P2 + P3 + ... + Pn) / n Where MA is the value of the moving average, P1 to Pn are the corresponding price data, n is the selected period number, and the Relative Strength Index (RSI) is used to measure the degree of overbought or oversold conditions in the market. The calculation formula is as follows: RSI = 100 - (100 / (1+RS)) Where RS is the relative intensity RS, and the formula for calculating RS is: RS = (Average closing price increase during an uptrend / Average closing price decrease during an downtrend) The stochastic oscillator is an indicator used to determine whether the market is overbought or oversold. Its calculation formula is as follows: Where C is the current closing price, L is the lowest price, H is the highest price, n is the selected period, MA is the moving average, and the exponential moving average (EMA) is a weighted average calculated based on historical data, and the calculation formula is as follows: EMA = (Today's closing price * 2 / (selected period number + 1)) + (Yesterday's EMA * (1 - 2 / (selected period number + 1))) The basic formula for profit and loss calculation in the statistical calculation submodule is as follows: Profit / Loss = (Closing Position - Opening Price) × Value per Point × Contract Terms - Transaction Fees The direct exchange rate calculation formula of the artificial intelligence calculation submodule is as follows: Direct transfer = target goods / basic goods Indirect exchange rates are calculated as follows: Indirect exchange rate = Base currency / Intermediate currency · Target currency / Intermediate currency The 3D thinking concept calculation submodule measures volatility by calculating the fluctuation range of exchange rates over a period of time. The calculation formula is as follows: Historical volatility = (Current closing price - n-day closing price) / n-day closing price * Standard deviation of daily returns Volatility is estimated by calculating the standard deviation of daily returns, using the following formula: Where σ is the standard deviation, r i This represents the daily rate of return. It is the average of all returns, and n is the number of days.

3. The dynamic spatial pricing system based on spatial variable K-lines according to claim 1, characterized in that: The data output module includes a data comparison submodule, a data removal submodule, a data storage submodule, and a data display submodule; The data comparison submodule compares the K-line pricing data and the block data; the data removal submodule removes the calculated abnormal data; the data storage submodule stores the calculated data in real time; and the data display submodule displays the final foreign exchange data.

4. The dynamic spatial pricing system based on spatial variable K-lines according to claim 1, characterized in that: The K-line pricing module includes a pattern analysis submodule, a moving average analysis submodule, and a volume-price analysis submodule; The pattern analysis submodule helps investors predict price trends through patterns such as head and shoulders top, head and shoulders bottom, double top, and double bottom. The moving average analysis submodule provides buy and sell signals for investors through the 5-day, 10-day, and 20-day moving averages, as well as the crossover and arrangement of these moving averages. The volume and price analysis submodule increases the accuracy of the analysis by showing that the increase or decrease in trading volume often corroborates the rise and fall of prices.

5. A dynamic spatial pricing system based on spatial variable K-lines according to claim 1, characterized in that: The block pricing module includes a multi-block sub-module and a non-block sub-module; When the market price rises, the number of points in the Bullish Block submodule increases accordingly. This means that when the market is rising, the Bullish Block captures more upward signals, helping investors seize buying opportunities in a timely manner. When the market price falls, the number of points in the Bearish Block submodule increases. This means that when the market is falling, the Bearish Block captures more downward signals, helping investors seize selling opportunities in a timely manner.

6. A dynamic spatial pricing system based on spatial variable K-lines according to claim 1, characterized in that: The account security module includes an account application submodule, an account password submodule, and an encryption permission submodule; The account application submodule applies for an account, the account password submodule applies for the corresponding password, and the encryption permission submodule generates and uploads the encrypted index and authorizes others to search, and sets access restrictions with release time for the encrypted index.

7. A dynamic spatial pricing system based on spatial variable K-lines according to claim 1, characterized in that: The trend line display module includes a red trend line sub-module, a green trend line sub-module, and a yellow trend line sub-module; The red trend line submodule is used as an important indicator for reference in the direction of going long, the green trend line submodule is used as an important indicator for reference in the direction of going short, and the yellow trend line submodule is used as an important indicator for reference in the direction of staying on the sidelines.

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