Computer network stabilization system and method

Abstract

A computer-implemented network stabilization method and system, the system comprising: a controller; a first computing system having a centralized network architecture; and a second computing system having a distributed network architecture. The controller is configured to: receive a plurality of commands; converting into a group of computer executable actions; generating a first command signal and a second command signal according to one or more control parameters generated or accessible by the controller; and transmitting the first command signal to the first computing system, and transmitting the second command signal to the second computing system.

Description

Technical Field

[0001] The invention relates to a computer network stabilization system and method. Background Art

[0002] Computerization of various functions of banking and capital markets has proven valuable in providing, for example, greater security, faster transfer of funds, and more efficient settlement of transactions. However, capital markets remain susceptible to speculative booms and busts that can harm economic development, and some of these swings are at least partially due to automation. For example, the “flash crash” of May 3, 2022, which resulted in $315 billion in losses in European stocks, highlighted the risks of a single human error exacerbated by a computer-initiated sell order (see Bloomberg, 2022). The first flash crash occurred on May 6, 2010, when the Dow Jones Industrial Average fell almost 1,000 points in 10 minutes. The cost of the crash was $1 trillion. Flash crashes have occurred in stocks, foreign exchange (FX), bonds, and cryptocurrencies (see The Balance, 2022).

[0003] The recurrence of flash crashes in financial markets is a growing concern for regulators and market authorities. Stability and efficiency are therefore important properties of financial markets, but can be at odds with each other. It is well known in engineering that fast-responding systems tend to be unstable: stability indicates an inherent resistance to change, while fast response requires the opposite resistance (see, e.g., Stewart, 2013 and Das et al., 2011). The object of the present invention is to design algorithms for stabilizing organized markets without compromising efficiency.

[0004] In a free market, prices are a function of supply and demand, and in particular the difference or gap between supply and demand. When supply exceeds demand, prices tend to fall, but when demand exceeds supply, prices tend to increase. In an organized exchange, orders to sell (supply) and buy (demand) are automated. If the gap between supply and demand is driven purely by economic fundamentals, the resulting price adjustments contribute to the normal operation of the market. However, capital or financial markets may exhibit "excessive volatility", that is, volatility that is not driven by economic fundamentals, which is harmful to economic development. In some cases, authorities regulate with the goal of stabilizing capital markets, but often at great cost to public funds and capital reserves. For example, stabilization funds are proposed to stabilize such markets, but these funds have proven to be ineffective for several reasons: if they are to have a significant impact in the capital market, the resources required for the fund (i.e., the amount of capital) are generally too large; those resources, even if available, are unlikely to be sustainable; speculators can exhaust the resources of the fund in a relatively short period of time; and speculators can predict the movement of the fund to a certain extent, which may make the fund ineffective even before it is exhausted.

[0005] As discussed by Alderighi, S. et al., Circuit breakers and other market safeguards, World Federation of Exchanges (May 2021), "circuit breakers" have been proposed as a mechanism for controlling price volatility in organized exchanges. A financial transaction tax has been proposed for the same purpose: see Congressional Research Service, Financial Transaction Tax; Overview, R42078 crsreports.congress.gov (February 2021).

[0006] Cryptocurrencies may be useful in this regard if their market value is sufficiently stable. The stability of cryptocurrencies is essential if these currencies are to serve the real economy by facilitating the exchange of goods and services. Unstable cryptocurrencies such as Bitcoin cannot be reliably used as a measure of value and medium of exchange. In general, there are two methods for producing stablecoins (that is, coins adjusted to stable cryptocurrencies):

[0007] i) Reserve: The coin is backed by a reserve (e.g., USD, gold, a basket of commodities, etc.) obtained from users (e.g., savings) or donations or ICOs, etc.

[0008] ii) Algorithm: If the price of a coin goes up (e.g. against the US dollar), more coins are issued; if the price of a coin goes down, the coin is destroyed or removed from circulation.

[0009] Tether(TM), MakerDAO(TM), Haven(TM), and Libra(TM) use a reserve approach, while Basis(TM), Ampl(TM), Fatfi(TM), and TerraUSD(TM) use an algorithmic approach (although TerraUSD collapsed in early May 2022).

[0010] However, first, and as discussed above, reserves are expensive and difficult to scale. On the other hand, algorithmic stablecoins are actually also based on (expensive) reserves. For example, Basis (see Al-Naji, N. et al., 2018) actually includes more than one coin:

[0011] i) Basis, the core currency of the system, pegged to USD;

[0012] ii) Bond tokens, which are auctioned by the blockchain when the supply of Basis needs to be reduced, where the bond pays exactly 1 Basis coin when the price of Basis is above $1; and

[0013] iii) Equity tokens, which are fixed and provide the capital or reserves needed to stabilize the value of Basis; shareholders provide stability and therefore receive dividends from fees charged to users.

[0014] Second, the above algorithms (and others) that manage stablecoins are passive: they react when prices have already changed. after In addition, algorithmic approaches assume (based on the quantity theory of money) that changes in the supply of money automatically find their way to prices. For coins, this implies that changes in the number of coins are automatically reflected in the currency exchange market (i.e., the exchange of coins for USD). However, as has been shown in many studies, this assumption is unfounded. Managing the quantity of money does not necessarily produce the desired price changes. The "transmission mechanism" is a key step in managing the supply of money and is omitted from these algorithms, which fail to allow for effects such as hoarding stablecoins and purchasing goods and services with stablecoins outside of the exchange market. Essentially, these algorithms assume that users are most interested in the currency exchange market (exchanging coins for USD), rather than the commodity market. Summary of the invention

[0015] It is an object of the present invention to provide a system having an improved balance of stability and efficiency for managing certain financial markets including digital currencies.

[0016] According to a first aspect of the present invention, there is provided a computer-implemented network stabilization method, the method comprising:

[0017] receiving a plurality of commands at a controller;

[0018] Converting the command into a set of computer executable actions using a controller;

[0019] generating, with the controller, a first command signal and a second command signal according to the computer executable actions based on one or more control parameters generated by or accessible to the controller;

[0020] sending a first command signal from the controller to a first computing system having a centralized network architecture; and

[0021] sending a second command signal from the controller to a second computing system having a distributed network architecture;

[0022] wherein the first command signal is configured to control the first computing system to perform a first subset of the set of computer-executable actions; and

[0023] The second command signal is configured to control the second computing system to perform a second subset of the set of computer-executable actions.

[0024] The method can be used to reduce volatility in the price of an asset (e.g., a stock or coin) by managing the gap between supply and demand (e.g., expressed as the difference between the market price and a price limit). Defined deductions can be applied based on the gap, and the deductions are used as reserves to support the stability of the system. By managing excess supply or demand, the method proactively reduces pressure on prices (unlike existing systems that respond after price changes). In addition, the method does not require upfront resources to support the stabilization mechanism. The parameters of the method are flexible, so the method can be adapted to a variety of assets as well as stablecoins.

[0025] The second computing system may include a peer-to-peer network configured to host a public distributed ledger.

[0026] An order may indicate a purchase, sale, or other financial transaction.

[0027] A set of computer executable actions may constitute a transaction including a buy and a sell.

[0028] In an embodiment, a first at least one command in the commands is a purchase command instructing the purchase of a product or asset, and a second at least one command in the commands is a sell command instructing the sale of a product or asset; converting the commands into a set of computer executable actions includes: pairing or matching the purchase command and the sell command; and generating matched purchase and sell commands, and generating a first command signal and a second command signal includes forming a comparison between at least one parameter related to the purchase command and at least one parameter related to the sell command.

[0029] In an example, at least one parameter associated with a buy command and at least one parameter associated with a sell command is a price of a product or other asset (such that a comparison between a parameter associated with a buy command and a parameter associated with a sell command is a measure of the difference, for example, between a purchase price and a sell price or between a market price and a price limit); and generating the first command signal and the second command signal includes generating a deduction applicable to the price (e.g., based on the comparison) such that the first command signal and the second command signal are both functions of the deduction.

[0030] For example, forming the comparison may include comparing a sell limit order to a buy market order and / or comparing a buy limit order to a sell market order.

[0031] In an embodiment, the gap between supply and demand is defined as the gap between the market price and the price limit. In one example, the gap G is defined as the absolute size of the difference (e.g., percentage) between the market price and the price limit, such as G = |P(m)-P| / (max(P(m), P( / ))) or |P(m)-P| / P(m) or |P(m)-P(l)| / P(l) or |P(m)-P(l)|.

[0032] In an embodiment, the deduction is a function of the size of the gap.

[0033] In an embodiment, the deduction is zero below a first threshold of the difference. In this embodiment, the deduction may have a finite value above the first threshold and a greater value above a second threshold of the difference, the second threshold being greater than the first threshold.

[0034] The deduction may increase, for example, in a stepwise or continuous manner. For example, the deduction may be zero below a first threshold of the gap, a small percentage deduction (e.g., between 2% and 4%) between the first and second thresholds of the gap, and a larger percentage (e.g., between 40% and 100%) above the second threshold of the gap.

[0035] The method may include generating a first command signal to include a sell command adjusted according to a deduction and a buy command, or a buy command adjusted according to a deduction and a sell command, and generating a second command signal to include a deduction.

[0036] The first computing system may include a controller.

[0037] According to a second aspect of the present invention, there is provided a network stabilization system, the network stabilization system comprising:

[0038] Controller;

[0039] a first computing system having a centralized network architecture; and

[0040] a second computing system having a decentralized network architecture;

[0041] Wherein the controller is configured to: receive a plurality of commands; convert the commands into a set of computer executable actions; generate a first command signal and a second command signal according to the computer executable actions based on one or more control parameters generated by or accessible by the controller; and send the first command signal to the first computing system and the second command signal to the second computing system;

[0042] The first command signal is configured to control the first computing system to perform a first subset of the set of computer-executable actions; and

[0043] The second command signal is configured to control the second computing system to perform a second subset of the set of computer-executable actions.

[0044] The second computing system may include a peer-to-peer network configured to host a public distributed ledger.The command may indicate a purchase, sale, or other financial transaction.

[0045] A set of computer executable actions may constitute a transaction including a buy and a sell.

[0046] In an embodiment, at least one of the first commands is a purchase command instructing the purchase of a product or asset, and at least one of the second commands is a sell command instructing the sale of a product or asset, and the controller converts the commands into a set of computer executable actions including: pairing or matching the purchase command and the sell command; and generating matching purchase and sell commands, and the controller generates a first command signal and a second command signal including forming a comparison between at least one parameter related to the purchase command and at least one parameter related to the sell command.

[0047] For example, at least one parameter associated with a buy command and at least one parameter associated with a sell command may be the price of a product or other asset (such that a comparison between a parameter associated with the buy command and a parameter associated with the sell command is a measure of the difference between the buy price and the sell price), and generating the first command signal and the second command signal by the controller may include generating a deduction applicable to the price (e.g., based on the comparison) such that the first command signal and the second command signal are both functions of the deduction.

[0048] The first command signal may include a sell command adjusted according to a deduction and a buy command, or a buy command adjusted according to a deduction and a sell command; the second command signal deduction.

[0049] In an embodiment, the first computing system includes a controller.

[0050] According to a third aspect of the invention, there is provided a computer program comprising program code, the program code being configured to implement the method of the first aspect when executed by one or more computing devices. According to this aspect, there is also provided a computer readable medium (which may be non-transitory) comprising such a computer program.

[0051] It should be noted that any of the various individual features of each of the above aspects of the present invention, as well as any of the various individual features of the embodiments described herein and included in the claims, can be combined as applicable and required. In particular, the various embodiments and examples of the first aspect are also applicable to the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order that the present invention may be more clearly ascertained, embodiments will now be described by way of example with reference to the following drawings, in which:

[0053] Figure 1 is a schematic architectural diagram of a stabilization system according to an embodiment of the present invention.

[0054] Figure 2A yes Figure 1 Schematic diagram of the exchange platform of the stabilization system.

[0055] Figure 2B yes Figure 1 Schematic diagram of the stabilizing network of a stable system.

[0056] Figure 2C yes Figure 1 Schematic diagram of the controller platform of the stabilization system.

[0057] Figure 3 yes Figure 1 A simplified flow chart of the operation of an implementation of a stabilization system.

[0058] Figure 4 According to one embodiment Figure 1 A detailed flow chart of the operation of the implementation of the stabilization system.

[0059] Figure 5 According to another embodiment Figure 1 A detailed flow chart of the operation of the implementation of the stabilization system. DETAILED DESCRIPTION

[0060] Figure 11 is a schematic architectural diagram of a stable system 10 according to an embodiment of the present invention. The system 10 includes a first layer in the form of an asset trading or exchange platform 12, a second layer in the form of a stable network 14, a controller 16, and an administrator interface 18 implementing a GUI 19 (for use by administrators). The exchange platform 12 has a centralized network architecture (including, for example, a centralized server or a networked server). The stable network 14 has a decentralized network architecture. The system 10 thus integrates the exchange platform 12 having a centralized network architecture with such high efficiency / response rate and the stable network 14 having a decentralized network architecture with such high stability / reliability, so that the system 10 can be both highly responsive and reliable and stable.

[0061] It should be noted that the stable network 14 is depicted and described below as a single computing device, but it should be understood that the stable network 14 actually includes distributed computing devices that host one or more distributed ledgers for storing blockchains.

[0062] The system 10 is suitable for facilitating the exchange (i.e., buying and selling) of assets such as stocks, securities, coins, etc., and does so in a manner that manages the gap G between supply and demand in the asset market in a consistent manner to reduce the volatility of the asset's price while maintaining the role of the gap in causing changes in the asset's price. However, without loss of generality, the following describes the application of the system 10 to the exchange of assets in the form of stocks.

[0063] therefore, Figure 1 The system 10 shown in has a user computing device 20 that can be controlled by a respective stock trader 1, 2, ..., n (individual or institution) to transmit control signals to a controller 16 of the system 10; the control signals indicate buy orders and sell orders for those stocks that can be bought or sold using the system 10. The control signals each identify the stock of interest and the parameters indicating the buy order or the sell order as described in detail below. Each of the user computing devices 20 has a respective user digital wallet 22.

[0064] The controller 16 includes a flow controller 24, an order storage device 26, an order parser 28, an order matcher and sequencer 30, a gap determiner 32 (described below) configured to determine a gap G between the supply and demand of the stock, and a deduction engine 34 (also described below) configured to determine and apply deductions. The controller 16 is configured to: - during each preset time window of duration T (starting at time t) - receive orders indicated by control signals received during the instantaneous time window; control the order parser 28 to extract key parameters of each order (including the identification of the stock to be bought or sold, the number of stocks to be bought or sold, whether the order is a buy order or a sell order, whether the order is a market order or a limit order, and - in the case of a limit order - the price identified in the limit order); and sort the sell limit orders by price limit in ascending order, the buy market orders by quantity in ascending order, the buy limit orders by price limit in descending order, and the sell market orders by quantity in ascending order. The order parser 28 is further configured to: save the order to the order storage 26 ; and pass the sorted order to the order matcher and sorter 30 .

[0065] [Note: Conventionally, a buy market order comprises an order to buy a number Q(m) of a particular stock at the current market price P(m) of those stocks; a sell market order comprises an order to sell a number Q(m) of a particular stock at the current market price P(m) of those stocks; a buy limit order comprises an order to buy a number Q(l) of a particular stock once those stocks become available (i.e., at the present or future time) at a price at or below a specified maximum price limit P(l); a sell limit order comprises an order to sell a number Q(l) of a particular stock once those stocks become available (i.e., at the present or future time) to a buyer who will pay a price at or above a specified minimum price limit P(l).]

[0066] The controller 16 is configured to respond to the closing of the immediate time window by controlling the order matcher and sequencer 30 to match the sequenced sell limit orders with buy market orders, and to match the buy limit orders with sell market orders, and to pass the matched orders to the gap determiner 32. The gap determiner 32 is configured to determine the size of the gap G (if any) between supply and demand for each matched order pair.

[0067] The flow controller 24 defines a set of rules and stabilization parameters according to which the controller 16 controls the exchange platform 12 and the stabilization platform 14, including whether the stabilization platform 14 becomes active when processing orders after the immediate time window closes.

[0068] The deduction engine 34 is configured to determine whether a deduction should be applied to an order (based on the above rules and stability parameters), and if so, to determine the appropriate deduction and apply it to the order. The deduction engine 34 operates as follows.

[0069] Typically, in cases of excess demand, cash is deducted from buyers, while in cases of excess supply, assets are deducted from sellers.

[0070] In the case of excess demand, the seller requires a limit price P(l)>P(m) and quantity Q(l), and expects to receive an amount of funds equal to V(k)=P(l).Q(l) as compensation. The quantity exchanged will be the minimum of the limit order quantity and the market order quantity. (For simplicity, the minimum quantity is represented by Q(l). However, the price will be the adjusted or stabilized price P(m′). Therefore, the buyer pays V(l)=P(l).Q(l), but the seller receives V(m′)=P(m′), Q(l)<V(l). The deduction engine 34 determines the difference V(l)-V(m′)=Q(l).(P(l)-P(m′)) to be deducted from the buyer, applies the deduction to the order, and deposits the deduction in the stabilization fund of the stabilization network 14. The specific deduction is controlled by a series of stabilization parameters (discussed below) (including at least one throttling parameter, which is generally represented as θ in this document).

[0071] To compensate the seller, the Stability Fund issues S tokens with a value equal to V(l)-V(m'). The buyer also needs to be compensated, because he or she now receives a certain amount of assets with a value of V(m'), which is less than the funds paid by the buyer. Therefore, the same number of S tokens should be issued to the buyer by the Stability Network 14. The result is that the total S tokens are only covered by 50% of their (book) value.

[0072] In the case of excess supply, the buyer demands a limit price P(l) < P(m) and quantity Q(l). The seller offers quantity Q(m) at any price. Since there is excess supply, the deduction determined by the deduction engine 34 will be applied to the asset by the deduction engine 34. The deduction engine 34 determines the deduction as follows.

[0073] First, the deduction engine 34 receives (from the price determiner 38: see below) a stabilizing price P(m′)>P(l). The buyer is willing to pay V(l)=P(l).Q(l) (where Q(l) is the minimum of the number of market orders and the number of limit orders), so the deduction engine 34 calculates the quantity that would produce the same V(l) at the stabilizing price: Q(m′)=V(l) / P(m′), where Q(m′)<Q(l). This is the quantity that will be delivered to the buyer. Therefore, the buyer receives Q(m′) at the price P(m′), where the total value is V(l)=V(m′)=P(m′).Q(m′).

[0074] On the other hand, the seller delivers Q(l), but receives funds V(m′), which reflects the value of the smaller amount of assets Q(m′) < Q(l). Therefore, the seller needs to be compensated, so the Stability Fund 14 issues him or her an S token with a value equivalent to P(m′).(Q(l)-Q(m′)).

[0075] Although the buyer received an amount of the asset at a price that produced the same value the buyer was willing to pay in the absence of the stabilization, the buyer received a smaller amount at a higher price. The buyer will not be fully satisfied because the chance of future profit is now lower: the buyer gave up an amount equal to Q(l)-Q(m′) at the new market price of P(m′). Therefore, the buyer is compensated by S tokens that are equivalent in value to P(m′).(Q(l)-Q(m)) (which is the same value as the seller).

[0076] These different parameters and formulas are summarized in Table 1.

[0077] Table 1: Stability formula

[0078]

[0079] (Note that Table 1 includes step functions as well as smooth functions, each with appropriate adjustments to the signs: see below.)

[0080] The controller 16 is configured to direct orders that do not cause deductions to the exchange platform 12. The controller 16 is configured to separate orders that cause deductions into two components: (i) orders that have been deducted, and (ii) deductions; the controller 16 is configured to: direct the first component to the exchange platform 12; and direct the second component to the stabilization platform 14 (for storage in the stabilization fund).

[0081] More specifically, the rules and stability parameters of the flow controller 24 dictate that the controller 16 direct orders received within the immediate closing window to the control exchange platform 12 and the stability network 14 for processing. These rules and stability parameters are as follows:

[0082] Rule 1: At or below a predefined first threshold in the absolute size of the gap G between supply and demand, the controller 16 controls the exchange platform 12 to process all orders without invoking the stable network 14 (as described below);

[0083] Rule 2: Above the first threshold and at or below a predefined second threshold in the gap G between supply and demand, the controller 16 controls the exchange platform 12 to process the order and calls the stable network 14 to perform a portion of the processing of the order (as described below);

[0084] Rule 3: Above a second threshold in the gap G between supply and demand, the controller 16 controls the exchange platform 12 to process the order, and calls upon the stable network 14 to perform a larger portion of the processing of the order (as described below).

[0085] The gap G between supply and demand can be defined in any suitable way consistent with the concept of "gap" (or difference). In this embodiment, for example, the gap G is defined as the absolute size of the percentage difference between the market price and the price limit, that is:

[0086] G=|P(m)-P(l)| / (max(P(m),P(l))).

[0087] The absolute value in the numerator makes this definition of G suitable for both sell limit orders and buy limit orders, i.e., whichever of P(m) and P(l) is greater, makes G ≥ 0. Setting the denominator to the maximum of P(m) or P(l) ensures that G < 1.

[0088] In other embodiments, the gap G can be defined, for example, as G = |P(m)-P(l)| / P(m), or as G = |P(m)-P(l)| / P(l), or as G = |P(m)-P(l)|, where other parameters are changed accordingly if necessary.

[0089] These rules are implemented by the controller 16 according to the following stability parameters:

[0090] Stability parameter 1: defines the first threshold, which is denoted as α in this paper 0 , where 0≤α 0 <01 (e.g., 3%);

[0091] Stability parameter 2: defines the second threshold, which is denoted as α in this paper 1 , where α 0 <α 1 ≤1 (e.g., 50%);

[0092] Stability (or “first throttle”) parameter 3a: defines when the gap G is within the limit α 0 ≤G<α 1 , the degree of intervention of the stable network 14 (and therefore the degree of throttling of the switching platform 12) and is denoted herein as θ 0 , where 0<θ 0 ≤1 (e.g., 3%);

[0093] Stability (or “second throttling”) parameter 3b: defined when the gap G ≥ α 1 , the degree of intervention of the stabilizing network 14, and is denoted by θ 1 , where θ 0 <θ 1 ≤ 1 (e.g., 99%)

[0094] Stability parameter 4: defines the duration of the order accumulation window T (e.g., 30s or 60s);

[0095] Stabilization Parameter 5: controls the minimum redemption period for S Tokens (e.g., 18 months (i.e., from the issuance date)), after which the owner can redeem the S Tokens from the stabilization fund;

[0096] Stability Parameter 6: controls the minimum trading period for S tokens (e.g. 12 months (i.e. from the issue date) after which the owner can trade S tokens with other owners (so that transactions can be performed, for example, via a centralized network or via a decentralized network and - in either case - are not affected by the stability parameter since they are already part of the stable network);

[0097] Stabilization Parameter 7: A stabilizer that controls disturbances to the system 10 as a last resort, as described below.

[0098] Any one or more of these parameters (particularly parameters 1, 2, 3a and 3b) may be constants. In addition, any one or more of these parameters may be a function of the size of the control signal stream, a function of the content of the control signal, or a function of other variables of the system 10, or a function of a combination thereof (particularly parameters 3a, 3b).

[0099] It should also be understood that other rules and stabilization parameters may be implemented. For example, alternative rule 2' may replace rules 2 and 3 above (without stabilization parameters 3a or 3b):

[0100] Rule 2': Above a first threshold in the gap G between supply and demand, the controller 16 controls the exchange platform 12 to process the order and calls the stable network 14 to perform a portion of the processing of the order (essentially equivalent to setting α 1 =1).

[0101] The rules and stabilization parameters are initially set by an administrator of the system 10 via the administrator interface 16. Subsequently, the rules and stabilization parameters may be modified, such as by the administrator or based on consensus among traders.

[0102] The exchange platform 12 includes an order executor 36 configured to execute orders and a price determiner 38. To facilitate the execution of orders (by executing transactions), order parameters extracted from orders submitted by users of user devices 20 in corresponding order windows are provided to the order executor 36 by the controller 16. Thus, the order executor 36 typically receives in parsed form one or more buy market orders 40a (each buy market order includes a desired number of shares to buy Q(m)), sell market orders 40b (each sell market order includes a desired number of shares to sell Q(m)), buy limit orders 40c (each buy limit order includes a desired number of shares to buy Q(l) and a price limit P(l)), and sell limit orders 40d (each sell limit order includes a desired number of shares to sell Q(l) and a price limit P(I)).

[0103] The price determiner 2 is configured to: receive order and trade data from the order executor 36; and for any particular stock, determine (from existing orders) the current price P(m) at time t, the new price P(m′) of the stock after each subsequent trade in that stock has been executed by the order executor 37, and the price (or value) of the S token P(t) at time t.

[0104] The stabilization network 14 , which is in data communication with the controller 16 and the switching platform 12 , includes a rules and stabilization parameter engine 44 that establishes or accesses the rules and stabilization parameters discussed above and communicates them to the traffic controller 24 .

[0105] The stable network 14 optionally includes a blockchain consensus engine 46 that implements user consensus decisions to determine the rules governing the S tokens and the rules regarding market intervention by the system 10 as a stabilizer of last resort. The users in this case are typically traders using the system 10.

[0106] The stabilization network 14 also optionally includes an artificial intelligence (AI) engine 48, which is configured to improve the overall functionality of the system 10 by enhancing the determination of stabilization parameters. To this end, the AI ​​engine 48 communicates with the order parser 28 and with the rules and stabilization parameter engine 36. For example, the AI ​​engine 48 can determine the stabilization parameters (particularly θ 0 and θ 1) affects the performance of the system 10, and in particular stability learning, and can respond by determining changes in the values ​​of those parameters (e.g., by increasing or decreasing θ 0 and / or θ 1 ), which will increase or maximize the stability of the system 10. The AI ​​engine 48 then transmits the modified parameter values ​​to the order parser 28 and / or the stable parameter engine 36 as appropriate.

[0107] The administrator interface 18 is configured to communicate with the rules and stabilization parameters engine 44 and can be controlled by a system administrator to set or modify rules and stabilization parameters.

[0108] The stable network 14 includes an S token blockchain database 50 (recording S tokens and cash held by the system 10 as a stable fund), and a first smart contract 52, a second smart contract 54, a third smart contract 56, and a fourth smart contract 58, which respectively define a buy market order, a sell market order, a buy limit order, and a sell limit order that can be implemented by the system 10. The stable network 14 also includes a blockchain (including a block 62 1 , 62 2 , 62 3 …, blockchain 60 is an example), which records transactions implemented by system 10, including buying stocks, selling stocks, and transferring cash or stocks (as a deduction from the purchase or sale of stocks) to a stabilization fund maintained by system 10 in or by stabilization network 14.

[0109] The flow of processing of orders is controlled in a manner that keeps the response rate of the exchange platform 12 as close as possible to that of a conventional exchange platform (i.e., a platform without a stabilization component), but the type of response varies depending on the size and nature of those orders. Thus, the control signal is configured to control the exchange platform 12 to perform a first set of actions (as described below), but as that flow increases, a small portion or percentage θ of the flow is diverted from the exchange platform 12 to the stabilization network 14. Alternatively, the control signal is diverted to the stabilization network 14 to control the stabilization network 14 to perform a second (and different) set of actions (also as described below). Thus, the diversion of the control signal (according to the stabilization parameter) acts as a throttle between the exchange platform 12 and the stabilization network 14 to variously increase or reduce demand or supply on the exchange platform 12 in response to the control signal.

[0110] Figure 2A , Figure 2B and Figure 2C The schematic diagrams are respectively the switching platform 12, the stable network 14 (with the administrator interface 18) and the controller 16. Figure 2A, the exchange platform 12 includes a processor 70 and a memory 72. The processor 70 includes the above-mentioned order executor 36 and price determiner 38, as well as a transaction output 74, which is configured to output the relevant details of each transaction executed by the exchange platform 12 to the stable network 14 and to the user wallet 22 of the corresponding transaction party after the transaction is completed.

[0111] The exchange platform 12 typically includes both volatile and non-volatile memory, as well as more than one of each type of memory, wherein such memory is collectively represented by memory 72 in data communication with the processor 70. The memory 72 includes program code 76 for controlling the operation of the processor 70, an order storage device 78 for receiving and storing buy market orders 40a, sell market orders 40b, buy limit orders 40c, and sell limit orders 40d, and a price storage device 80 for storing current prices and adjusted prices.

[0112] Reference Figure 2B , the stable network 14 includes a processor 84 and a memory 86 (which also typically includes both volatile memory and non-volatile memory and more than one of each type of memory) in data communication with the processor 84. The processor 84 includes a blockchain processor 88 and a timestamp server 90, which perform the functions required to process blocks and maintain the portion of the distributed ledger of S tokens and smart contracts stored in the stable network 14.

[0113] The processor 84 also includes the above-mentioned rules and stability parameter engine 44, blockchain consensus engine 46 and AI engine 48, and optionally includes a stability parameter determiner 92, which is configured to dynamically determine the stability parameters (and in particular α 0 , α 1 ,θ 0 and θ 1 ).

[0114] The memory 86 stores program code and system algorithm 94 (for controlling the operation of the processor 84), the above-mentioned S token blockchain database 50 (which stores the S token of the system 10), the smart contract blockchain database 96 (which stores the first to fourth smart contracts 52, 54, 56, 58), the transaction blockchain database 98 (which stores the executed transactions in the form of blockchain 60, for example), the flow controller rules 100 (which reflects the flow controller rules of the flow controller 24) and the stability parameters (including α 0 , α 1 ,θ 0 ,θ 1, p and T) 102 (which reflects the stability parameters of the flow controller 24).

[0115] Reference Figure 2C , the controller 16 includes a processor 104 and a memory 106 (which also typically includes both volatile and non-volatile memory and more than one of each type of memory) in data communication with the processor 104. The processor 104 includes the above-mentioned flow controller 24, order parser 28, order matcher and sequencer 30, gap determiner 32 and deduction engine 34. The controller 16 also includes an order router 108, which is configured to direct the order (or its component) to the exchange platform 12 and / or the stable network 14 based on whether the deduction has been applied by the deduction engine 34.

[0116] Thus, as discussed above, the exchange platform 12 performs transactions of assets (e.g., stocks or stablecoins) of funds. The stable network 14 sets stable policy parameters (including α 0 , α 1 ,θ 0 and θ 1 ). These parameters are set primarily by consensus reached by blockchain network users (i.e., traders), with possible input from the optional AI engine 48 and administrators via the administrator interface 18. The Stable Network 14 also manages the issuance of S tokens in exchange for deductions for asset trading orders (as discussed below).

[0117] In general, the system 10 is as follows Figure 3 The operation is schematically shown in the flowchart 120 of . At step 122, the market price is set or accessed by the price determiner 38 (e.g., based on past transactions). At step 124, the controller 16 receives an order for an asset transaction from the user device 20, and at step 126, the order parser 28 parses the order into a limit order and a market order in particular. At step 130, the order matcher and sequencer 30 pairs any matching buy market orders and sell market orders, and sorts the remaining orders. At step 132, the order matcher and sequencer 30 matches the corresponding sell limit orders and buy market orders according to the sorting, and matches the corresponding buy limit orders and sell market orders according to the sorting.

[0118] If the order matcher and sequencer 30 finds no orders to match, processing continues at step 134 where new order parts are received or identified for processing.

[0119] If the order matcher and sequencer 30 finds orders to match, processing continues at step 136 where the gap determiner 32 determines the gap G between each pair of remaining matched buy and sell orders as the absolute percentage difference between the price limit and the market price (see definition above) based on rules 1 to 3 (see above).

[0120] At step 138, the deduction engine 34 determines whether any deductions should be applied, and in this embodiment applies the deductions as follows:

[0121] For G ≤ α 0 For matching orders, no deduction shall be applied;

[0122] For α 0 <G≤α 1 The deduction engine 34 of the controller 16 applies a first deduction formula (whose form depends on the order type) to the matching order, and thereby determines the first deduction D 0 , the deduction engine 34 will deduct the first 0 Applied on the excess side (supply or demand)

[0123] The order then splits each of these matching orders into two parts:

[0124] (i) deduction orders (being excess orders to which a determined first deduction has been applied) and non-deduction orders (non-excess orders); and

[0125] (ii) Determined first deduction

[0126] For G>α 1 The deduction engine 34 applies a second deduction formula (whose form depends on the type of order) to the matching order, and thereby determines the second deduction D 1 , the controller 16 deducts the second 1 Applied to matching orders, each of these matching orders is then split into two parts:

[0127] (i) deduction orders (which are excess orders to which a determined second deduction has been applied) and non-deduction orders (which are non-excess orders); and

[0128] (ii) Determined second deduction

[0129] In this embodiment, the first subtraction formula is as follows:

[0130]

[0131] Among them, V(l)=P(l).Q(l), P(l) and Q(l) are price limit and quantity limit respectively.

[0132] V(m′ 0 )=P(m′ 0 )Q(l);Q(m′ 0 )=V(l) / P(m′ 0 ); P(m′ 0 )=θ 0 P(m)+(1-θ 0 ).P(l), and θ 0 (eg, 3%) is the stable (or "first throttle") parameter 3a.

[0133] In this embodiment, the second subtraction formula is as follows:

[0134]

[0135] Among them, P(m′ 1 )=θ 1 P(m)+(1-θ 1 ).P(l), and θ 1 is the stability (or "second throttling") parameter 3b (where the other parameters are as defined above, where m' is used 1 m′ 0 Make appropriate substitutions)

[0136] It should be noted that in other embodiments, a single deduction formula, or alternative first deduction formula and / or second deduction formula, or more than two deduction formulas may be employed. However, in all embodiments, the stabilization price falls within the range from the market price to the limit price, and the deduction is configured to reduce the gap, and therefore reduce the price variation.

[0137] In other embodiments, a single throttling parameter and a single deduction formula may be used. For example, the throttling parameter and deduction formula of this embodiment may be defined in other embodiments as a single throttling parameter of the following form: To express:

[0138]

[0139] Among them, θ 0 and θ 1 is a constant in this embodiment. Therefore, then, a single deduction for all values ​​of G This can be adopted by using the following deduction formula:

[0140]

[0141] Among them, stable prices are now based on is defined so that

[0142]

[0143] However, in yet another embodiment, the throttling parameter may be defined as a function that varies continuously over some or all values ​​of G (e.g., in particular, when G>α 0 =5%). For example, in some embodiments, the first throttling parameter and the second throttling parameter are defined such that:

[0144] Where 0<θ 0 <1.

[0145] Parameter θ 0 Determine θ 1 The curvature in G is therefore determined by the degree to which the gap θ is exceeded in the unit interval 1 Instructions. Since θ 0 is between 0 and 1, so θ 1 cannot exceed 1. In this example, the throttling parameter θ implemented by the system 10 * Then it is defined by:

[0146]

[0147] For example, if G = 3%, and α 0 =5%, G<α 0 , then θ * = 0. However, if G = 9%, α 0 =5% and θ 0 =0.75, throttling parameter θ * =16.4%, then 16.4% of the gap will be deducted. However, as before, in all cases the stabilization price falls within the range from the market price to the limit price, and the deduction is configured to reduce the gap, and therefore reduce the price variation. The two parameters θ 0 and α 0 It can be adjusted based on the expected volatility level of the environment. For example, for a stablecoin where volatility must be strictly controlled, θ 0 and α 0 will have relatively low values. In a more flexible environment such as the stock market, θ 0 and α 0 will have a relatively high value.

[0148] Reference Figure 3 At step 140, the order router 108 of the controller 16 routes the order (or its components) to the exchange platform 12 and / or the stable network 14 as follows:

[0149] The order router 108 routes the paired buy market order and sell market order to the exchange platform 12 .

[0150] The order router 108 matches the matching sell limit orders and buy market orders and the matching buy limit orders and sell market orders without deductions (i.e., where the gap G≤α 0 ) is routed to the switching platform 12.

[0151] In the event that an order has been determined to apply a deduction, the order router 108 routes the deducted order and the non-deducted order to the exchange platform 12 and routes the determined deduction (whether a first deduction or a second deduction) to the stable network 14.

[0152] At step 142, the order executor 36 of the exchange platform 12 executes the order, and at step 144, the price determiner 38 updates the market price. At step 144, the details of each transaction are stored in the blockchain in the transaction database 98 and transmitted to the user wallet 22 of the corresponding transaction party. Then, the processing of the immediate part of the order ends.

[0153] Note that the deduction 148a (whether cash or assets) routed to the Stability Network 14 by the Order Router 108 is deposited in the Stability Fund, and the user (buyer or seller) who has waived the deduction is issued S tokens 50, that is, units 148b of the corresponding value in the Stability Fund (e.g., the book value of the asset), by the blockchain processor 88 of the Stability Network 14. Thus, those units represent his or her share of the Stability Fund caused by the deduction.

[0154] Thus, the system 10 mitigates price volatility by reducing the gap between supply and demand by: (i) deducting according to the gap between market orders, and (ii) deducting according to limit orders that match the limits of the other side of the market. In addition, in this example, the system 10 can mitigate price volatility by maintaining and managing a stabilization fund held in a blockchain (e.g., blockchain 60 of the stable network 14) to act as a "last resort stabilizer" within the limits of the accumulated cash and asset resources of the stabilization fund (see below).

[0155] A matched limit order is actually a market order. Therefore, the gap in the overall market order indicates the pressure on price movement. By deducting a portion of such a gap, the pressure on price can thus be controlled. This deduction is compensated by S tokens.

[0156] S tokens, units of the Stability Fund, cannot be traded for a predefined period p (e.g., 2 or 3 years) in order to maintain the role of the system 10 in reducing volatility. Therefore, S tokens can be described as "forced savings" for investors. Investors allocate a portion of their demand or supply to the Stability Fund and cannot use or cash out that portion within the predetermined period p.

[0157] The stabilization fund is managed according to the following two scenarios:

[0158] 1. During normal times, the assets of the stabilization fund are held passively. The stabilization fund can distribute a portion of its assets (e.g. 30%) to investors every 2 to 3 years.

[0159] 2. In times of major turmoil, stabilization funds can intervene to actively stabilize the market, for example by buying stocks during a recession and / or selling stocks during a bubble. Thus, stabilization funds can act as a "stabilizer of last resort."

[0160] System Parameters

[0161] To employ the system 10, for example, initially by setting the stability parameters (particularly, α 0 , α 1 ,θ 0 and θ 1 ), but then, the stabilization parameters are subsequently adjusted using the AI ​​engine 48 to adjust the stabilization parameters to the stablecoin.

[0162] For example, system 10 may use α 0 =0.1% and α 1 = 2%, which would mean that price fluctuations less than or equal to 0.1% would not be affected by the deduction. Fluctuations greater than 0.1% but less than or equal to 2% would be 0 However, when demand or supply exceeds the other by more than α 1 (2% in this example), the excess is affected by θ 1 >θ 0 (For example, θ 1 =0.99). This high deduction rate is intended to stabilize the price of the coin.

[0163] Deduct all or most of the excess supply or demand in excess of α 1 It may seem harsh or excessive, but it should be noted that the purpose of stablecoins is to be used as a medium of exchange for goods and services. Therefore, the stability of the stablecoin replaces the flexibility of exchange for the US dollar. Users have reason to have confidence in the stability of the stablecoin in the knowledge that all or most of the excess supply or demand in excess of 2% will be replaced by the stabilization fund units, and are therefore discouraged from entering the currency exchange market (i.e., replacing the stablecoin with a currency such as the US dollar to purchase goods), but rather use the stablecoin in the commodity market.

[0164] As noted above, these parameters need not be constants. These parameters can be formulated as functions that adjust as needed according to market conditions. The adjustment process may depend, among other things, on artificial intelligence.

[0165] Fund Parameters

[0166] The stablecoin's fund units have their own parameters. Each unit will be restricted from trading or transfer during a specific period. After that period, the unit can be publicly traded or redeemed for the underlying US dollar and stablecoin.

[0167] Fund management can decide how much of each unit is unrestricted, and to which assets. For example, for units issued 1 year ago, the fund can decide that 50% of each unit is unrestricted in USD only, or in Bitcoin only, or in both USD and Bitcoin. These parameters can be decided in a way that helps manage the stability of the stablecoin.

[0168] Therefore, the system 10 does not use conventional funds. Instead, the system 10 manages assets with a stable network 14 based on blockchain for asset management. The benefits of blockchain technology are well known. At the same time, transactions on the stable network 14 do not require high-speed systems (such as those used by the exchange platform 12). Therefore, the verification process of the blockchain can be completed without time pressure.

[0169] The system 10 can be funded by the above deductions received from transactions conducted through the exchange platform 12. These deductions are cash or assets (see above) and are compensated in S tokens. Two important consequences of stabilizing the network 12 are as follows.

[0170] S tokens represent quasi-shares in the assets of the system 10 resulting from these deductions. S tokens have a number of advantages over conventional “fund units”:

[0171] 1. S tokens are restricted from trading or redemption for a predefined period (e.g., years or months) defined by the stability parameters 6 and 7. Such restrictions are intended to provide stability. Unlike standard fund units, restrictions can be easily implemented on S tokens through smart contracts and verified by the stability network 14.

[0172] 2. If a user wishes to adjust or modify the rules governing S tokens, the user may adopt a consensus strategy (e.g., a simple voting system) via the blockchain consensus engine 46 to modify the rules so that the user has a certain degree of control over the rules governing trading S tokens.

[0173] It should be noted that the stabilization fund can provide an additional layer of stability in turbulent situations by actively participating in the market. Through blockchain technology, users can decide when and how the fund should intervene in the market as a stabilizer of last resort. In addition, the system 10 can implement a suitable consensus strategy (or majority rule) to make the necessary decisions.

[0174] The stable network 14 provides two important benefits to the system 10:

[0175] 1. The stabilization network 14 provides a trusted protection layer to the switching platform 12 and the system 10. If the system 10 is intended to stabilize the switching platform 12, and thus protect the switching platform 12, the stabilization network 14 is intended to protect the switching platform 12 and thus protect the system 10. The interaction between the switching platform 12 and the stabilization network 14 is synergistic.

[0176] 2. The Stable Network 14 provides users with a reliable mechanism for managing the exchange platform 12 and making key decisions about market stability. When user contributions are deducted, users jointly own the assets of the exchange platform 12, so users can be given the ability to manage those assets. The Stable Network 14 provides a decentralized mechanism for managing these assets (rather than having decisions made centrally by, for example, a third party).

[0177] In more detail, the system 10 operates as follows when applied to the trading of stocks, cryptocurrencies, or any other tradable asset. (Exchanges of other tradable assets will differ in detail, but such variations can be readily accommodated).

[0178] There are generally two types of orders received by the controller 16 from the user device 20: market orders and limit orders. The market price changes in response to the interaction between these two types of orders.

[0179] Sorting and matching

[0180] After the order parser 28 parses and tags the received order into its corresponding type, the order parser 28 passes the order to the order matcher and sequencer 30. The order matcher and sequencer 30 identifies and pairs matching buy market orders and sell market orders: the resulting pair, if any, constitutes a transaction that the controller 16 forwards to the exchange platform 12 for execution without further processing.

[0181] Then, the order matcher and sequencer 30 sorts any remaining received limit orders before matching them with market orders. The order matcher and sequencer 30 sorts the sell limit orders in ascending order. This makes the sell order limited by, for example, $80 mean that the seller wants $80 or more. The sell order limited by $100 will require $100 or more. Therefore, by starting with the lowest limit, a larger range is provided for the transaction that occurs. If the amount (that is, the number of stocks, etc.) determined by the $80 limit order is sold, the exchange platform 12 will move to the next limit order, and therefore the price (after matching and execution) increases.

[0182] For virtually the same reasons, the order matcher and sequencer 30 sequences the buy limit orders in descending order.

[0183] The order matcher and sequencer 30 passes the sequenced orders to the order matcher and sequencer 30 .

[0184] For each of the sorted limit orders, the order matcher and sequencer 30 checks for a market order on the other side of the trade. That is, for a sell limit order, the order matcher and sequencer 30 checks for a buy market order, and for a buy market order, the order matcher and sequencer 30 checks for a sell limit order. Market orders receive the best available price, and since the limit orders have already been sorted by the order matcher and sequencer 30, the order matcher and sequencer 30 can then easily match the orders and pass the matched orders in pairs to the gap determiner 32.

[0185] The gap between supply and demand

[0186] The gap determiner 32 determines the gap G between supply and demand for each pair of ranked matching orders, and based on the gap G, the deduction engine 34 determines whether a deduction should be applied to the corresponding transaction (i.e., the transaction caused by the matched order pair), and if so, determines the size and manner of the deduction. The order is then sent to the exchange platform 12 and / or the stable platform 14.

[0187] The process is applied every time period T (e.g., every 30 seconds or 60 seconds), which is predefined or determined by the exchange platform 12, but implemented by the controller 16. During each of these time periods, orders are collected by the controller 16 and then processed according to the following process.

[0188] Once the orders are collected, the order matcher and sequencer 30 of the controller 16 groups the market orders (whether buy orders or sell orders) and then matches the grouped sell orders with the buy orders when possible. The order router 108 marks the matched orders for later transmission to the exchange platform 12 (e.g., with other orders in the immediate part of the order), or immediately transmits the matched orders for execution by the exchange platform 12, which executes the matched orders. Note that the execution of market orders does not affect the current market price (which is considered the price of the most recently executed transaction and is therefore recorded in the system 10).

[0189] The order matcher and sequencer 30 checks whether there are any remaining (i.e., unmatched) market orders, that is, sell market orders that are not matched with the buy order (do not have the same counterpart or counterparts), and vice versa. If there are no unmatched market orders, processing stops until the next session (i.e., of duration T).

[0190] If the order matcher and sequencer 30 determines that there are such remaining (ie, unmatched) market orders, these orders may be buy market orders (which is the case of excess demand) or sell market orders (excess supply).

[0191] In case of excess demand, the order matcher and sequencer 30 sorts the buy market orders by quantity in ascending order and sorts the sell limit orders by price in ascending order. The order matcher and sequencer 30 creates a table with two columns: the first column is the buy market orders, and the second column is the sell limit orders.

[0192] Starting from the first line, the order matcher and sequencer 30 checks the price limit against the current market price. (Assume that the quantity of the limit order is the same as the quantity Q(l) of the market order. If not, the exchange platform 12 can be configured to allow fractional or partial fulfillment of the order, where Q(l) is the lower of the two quantities Q(l) and Q(m)).

[0193] The buy limit price P(l) will be higher than the current market price P(m) by a certain amount. If the price gap G (defined above) is such that G ≤ α 0 , where 0≤α 0 ≤1, the difference between P(l) and P(m) is within an acceptable range, so the exchange platform 12 does not apply deductions, and processing proceeds as usual.

[0194] However, if the price gap G is such that α 0 <G≤α 1 , then the exchange platform 12 application (using the above θ 0 The calculated price is deducted to reduce the gap between the desired price and the current market price. The stable price becomes:

[0195] P(m′ 0 )=θ 0 P(m)+(1-θ 0 )P(l)

[0196] That is, the stabilization price will be a weighted average of the current market price and the limit price. This formula ensures that the deduction is only applied to the difference between P(m) and P(l). This can be shown by noting that:

[0197] P(m′ 0)=P(m)+(1-θ 0 )(P(l)-P(m))=θ 0 P(m)+(1-θ 0 )P(l).

[0198] In the case of excess demand, P(m) < P(l), so we add the net difference between the limit price and the market price after deduction to P(m) to obtain the new market price P(m′ 0 ). By rearranging, we obtain the formula above.

[0199] The buyer pays V(l) = P(l).Q(l) in cash and receives Q(l) of the asset (e.g., stock). The new market price P(m') 0 ) will be lower than P(l) (see below), so the buyer’s payment is greater than the market value of the asset he or she receives; therefore, the Stable Network 14 is 0 He or she is compensated in the form of S tokens, the number of which is N 0 The S Tokens have a total value equal to this overpayment. The number of S Tokens is calculated by dividing the buyer’s overpayment by the price of the S Tokens:

[0200]

[0201] Where P(s) is the price of a single S token. P(s) can be calculated using different valuation methods (e.g., book value, net asset value, fair value, or any valid valuation method).

[0202] The limit seller delivers Q(l) assets and receives V(m′ 0 )=P(m′ 0 )Q(l) cash plus N 0 Tokens.

[0203] Stable network 14 receives V(l)-V(m′) cash and issues N 0 S tokens.

[0204] As mentioned above, θ 0 is a stable parameter 3a that controls the size of the deduction. In this embodiment, θ 0 is a fixed value, but θ 0 Can be variable (e.g., a function of the gap between P(l) and P(m) and / or other market conditions).

[0205] The exchange platform 12 sets the new market price P(m′) as defined above. 0). This is the price at which the trade between the sell limit order and the buy market order is executed. Note that this price will be lower than the limit price P(l) in order to achieve the goal of the system 10, that is, to reduce the gap between the sell limit price and the current market price.

[0206] Transactions are registered as P(m′ 0 ) is executed, so both parties—buyer and seller—get less than they expected. The buyer pays V(l) = P(l).Q(l), but with P(m′ 0 )<P(l) to obtain Q(l). This means that the buyer paid more than the value of the stock (or other asset) he received. For this reason, the buyer also needs to be compensated: the buyer receives Q(l) stocks + N 0 S tokens (where N 0 as defined above).

[0207] This means that the stable network 14 issues 2N 0 tokens, i.e., twice the value received by StableNetwork 14 (discussed further below).

[0208] When the gap G is determined such that G ≥ α 1 A similar process is followed when θ 1 ) instead of the stability parameter 3a (i.e., θ 0 ), and the number of S tokens is defined as:

[0209]

[0210] The deductions, compensations and new price calculations are detailed in Table 1.

[0211] At this stage, the first row of the table of sell limit orders sorted for buy market orders has been completed. Repeat the above steps for any remaining rows until all orders are matched.

[0212] When the remaining or unmatched market orders are sell orders (excess supply), the buy limit orders are sorted against the sell market orders and the above steps are performed with appropriate changes to the items, as shown in the following table - where P(m) = current market price; P(l) = price limit; Q(l) = quantity limit; V(l) = P(l).Q(l); Q(m) = quantity market; V(m) = P(m).Q(m); P(m′) = new market price; P(s) = price of S tokens at time t; 0≤α 0 ≤1; α 0 <α 1 <1; 0≤θ 0 ≤1.

[0213] We note that in the case of excess supply, P(m)>P(l), so we must subtract the net difference (after applying the deduction) from P(m) to obtain the new market price:

[0214] P(m′ 0 )=P(m)-(1-θ 0 )(P(m)-P(l))=θ 0 P(m)+(1-θ 0 )P(l).

[0215] This shows that the same weighted average formula is applied in both cases of excess demand and excess supply. Furthermore, the formula ensures that the stabilization price falls within the current market price and the limit price, regardless of the size of the gap between the two.

[0216] Table 2 Reference Figure 4 The flowchart 150 summarizes the process (which includes 0 and α 1 steps for use).

[0217] Table 2: Order processing process

[0218]

[0219]

[0220]

[0221]

[0222] Note that after steps 164 and 194, the market orders (sell market orders and buy market orders, respectively) should be sorted in ascending order by quantity, due to the optional ascending sorting of orders by quantity at the earlier step 152. However, if there is any doubt in this regard (e.g., the optional sorting of step 152 is omitted), steps 164 and 194 should additionally include "sort sell market orders in ascending order by quantity" and "sort buy market orders in ascending order by quantity," respectively.

[0223] If the throttling parameter is defined to be higher than α 0 A smooth function of all values ​​of G follows the alternative process. For example, the throttling parameter θ * This can be defined as follows (as discussed above):

[0224]

[0225] Where 0<θ 0<1. When there is a net sell market order, there will be an excess supply of the asset. In this case, the buy limit price will be lower than the current market price, P(l)<P(m). Therefore, in this example, the deduction process is as follows:

[0226] 1. If G ≤ α 0 , then no deduction applies and the stabilizing price will be the limit buy price only, ie, P(m′)=P(l).

[0227] 2. If G>α 0 , then the adjusted or new market price will be:

[0228] P(m′ * )=θ * .P(m)+(1-θ * )P(l).

[0229] As explained above, the same formula applies to both excess demand and excess supply.

[0230] The method of this alternative embodiment is Figure 5 The process is substantially the same as in Table 2, except that a single or uniform throttling parameter θ is used. * , instead of two throttling parameters (i.e., θ 0 and θ 1 ), and the same reference numerals are used to identify the same steps. (For simplicity, Figure 5 From θ * superscript asterisk omitted).

[0231] However, in flowchart 250, if at step 166, the deduction engine 34 determines that G>α 0 , then in all cases in this example the process continues at step 252, since the second stabilization parameter (α 1 At step 252, the price determiner 38 determines the adjusted price P(m′) * )=θ * .P(m)+(1-θ * )P(l). At step 254, in the case of excess supply, the buyer pays V(l) and receives Q(m') = V(l)*P(m') * ) and N S tokens, where

[0232]

[0233] At step 256, the seller delivers Q(l), receives V(l)+N S tokens, and at step 258, the price determiner 38 updates the price P(m) to the new or adjusted price P(m′) *). At step 260, the stable network 14 receives Q(l)-Q(m′ * ) and issue 2N S tokens. Then, the process continues at step 180.

[0234] If at step 196, the deduction engine 34 determines that G>α 0 , processing continues at step 262, where the price determiner 38 determines the adjusted price P(m′ * )=θ * .P(m)+(1-θ * )P(l). At step 264, in the case of excess demand, the buyer pays V(l) and receives Q(l) and N S tokens. At step 266, the seller delivers Q(l) and receives V(m′ * )=P(m′ * ).Q(l) and N S tokens. At step 268, the price determiner 38 updates the price P(m) to the new or adjusted price P(m′) * ). At step 270, the stabilization network 14 receives V(l)-V(m′) * ) and issue 2N S tokens. Then, the process continues at step 202.

[0235] Funding Stable Coins

[0236] The deduction (where applicable) means that the buyer and seller give up some of the value they are entitled to, so each party should be compensated. However, the exchange platform 12 is configured to collect from only one of the buyers and sellers, so the stable network 14 issues tokens equivalent to twice the collected resources of the stable fund. In other words, the S tokens are covered by 50%, not 100%; this is caused by the fact that transactions are executed between buyers and sellers at adjusted prices, which affects both parties at the same time, while the deduction is applied to only one of them. Therefore, if the fund is fully liquidated, only 50% of the tokens will be repaid.

[0237] If the system 10 is viewed as a collaborative insurance system, a 50% funding or reserve ratio is much better than the standard ratio in the insurance industry. Nevertheless, our goal is better, and therefore we propose a set of parameters to ensure the viability and stability of the exchange platform 12.

[0238] As already discussed, S tokens will be subject to restrictions on trading or redemption to give the network enough time to grow and accumulate funds (cash and assets). These restrictions are intended to avoid "runs" on the network and ensure the ability to redeem each token from the available reserves. For example, tokens may not be redeemed for 18 months from the date of issuance.

[0239] To avoid redemption issues (or “runs”), the blockchain consensus engine 46 can implement different dates for different traders. Limit order owners tend to be more patient than market order owners, so the market order tokens are more likely to be redeemed on the same day. redemption The date may be set by the blockchain consensus engine 46 to be earlier than the redemption date of the limit order (e.g., one month earlier). To compensate the limit order owner, the S token trade The date may be earlier than for a market order. For example, the redemption period for a market order may be 18 months, and the trading period may also be 18 months from issuance. For a limit order, in this example, the redemption period would then be 19 months, and the trading period would be 17 months. The exact values ​​of these dates or periods may be adjusted as appropriate for users of the exchange platform 12 via the administrator interface 18 and / or the blockchain consensus engine 46.

[0240] The stable network 14 may optionally include a dedicated AI engine trained to guide consensus regarding redemption periods and trading periods, such as to extend the periods in response to greater risk of a run.

[0241] In this way, no more than 50% of the tokens can be redeemed in any given month (or any suitable unit period). Since the deductions flow to the network, the network can accumulate funds (cash and assets) to meet the redemption requirements of the next month, and so on. Therefore, the network is able to support S tokens while facing a small run risk. In exceptional circumstances, trading and redemptions can be suspended until the market stabilizes.

[0242] It should be noted that investors or traders have an incentive to keep the value of S tokens stable (e.g., $1 per S token) because these tokens will compensate them for their deductions. Therefore, the redemption system provides harmony between the system mechanism and the incentives of traders.

[0243] Example

[0244] This example explains the above process in detail and assumes that the current market price of Company XYZ's stock (i.e., the price at which the last transaction to trade the asset in the exchange platform 12 was executed) is $100. A list of notional market orders and limit orders is presented in Table 3.

[0245] Table 3: Market and Limit Orders

[0246]

[0247] Market orders are initially matched (because they do not affect the current market price) as shown in Table 4.

[0248] Table 4: Total market orders

[0249] Buy it in Sell net 10,045 8,732 Buy 1,303

[0250] In this example, there are net buy market orders, so they are matched with sell limit orders. According to Table 3, the first sell limit order is at price 112 for quantity 1658. Therefore, the minimum of the two quantities is 1313. Therefore, without stabilization, the trade transaction will be executed at price $112 for quantity 1313 shares. The new market price becomes $112. With this transaction, there are no more market orders, and therefore no trade will occur until the next trading session.

[0251] Table 5: Orders

[0252]

[0253] This example uses a continuous stable function, as discussed above, whereby

[0254]

[0255] G=|P(m)-P(l)| / (max(P(m),P(l))),

[0256] as well as:

[0257]

[0258] Note that the gap between supply and demand (based on price) is G = |100-112| / 112 = 10.71%. If, for example, α 0 =5% (and therefore G>α 0 ) and θ 0 =0.75, then θ * =θ 1 =(10.71%) 0.75 = 18.72% and the stabilized or adjusted price will be:

[0259] P(m′)=(18.72%*100)+(1-18.72%)*112=109.75

[0260] Therefore, the transaction occurs at a price of $109.75, which is lower than the limit price of $112. The seller gives up a total of V(l)-V(m') = (112-109.75)*1,313 = $2,950.65. Therefore, the seller and the buyer each need to be compensated by an equal value of S tokens.

[0261] With stabilization, the new market price is $109.75. Also, following this transaction, no more market orders exist, so no trade will occur until the next trading session.

[0262] simulation

[0263] Monte Carlo simulations of the operation of system 10 were performed at two levels: static and dynamic.

[0264] In the static simulation, the price fluctuations were determined by simulating both the system 10 and the system without stabilization. In the dynamic simulation, the price fluctuations from one session to another were studied, and furthermore, the price fluctuations from one session to another were studied in the case of both the system 10 and the system without stabilization.

[0265] Static simulation

[0266] Takes the following parameters and variables:

[0267] Table 6: Simulation parameters used in the static Monte Carlo simulation

[0268] parameter value <![CDATA[α 0 ]]> 5％ <![CDATA[θ 0 ]]> 0.75 Initial price t = 0 $100 Price Distribution – Limit Buy Pt=1~uni(40:99) Price Distribution – Sell Limit Pt=1~uni(101:160) Quantity distribution Qt=1~uni(2,500±60%) The number of iterations 50.000

[0269] It should be noted that the price distribution for a buy limit order is different from that for a sell limit order. For a buy limit, the prices are evenly distributed between 40 and 99. The current (initial) market price of $100 is not included in the distribution because this would make the order a market order. Similarly, for a sell limit order, the prices are evenly distributed between 101 and 160.

[0270] The simulations were performed using @Risk 8.2. The results are summarized in Table 7.

[0271] Table 7: Static simulation results

[0272]

[0273] Overall, the stabilization algorithm reduces the standard deviation of the price by about 37%, from 21.8 to 13.6. Although both scenarios have essentially the same mean and median, the 10%-90% interval (10% percentile and 90% percentile) is shorter for the stabilization system: 71-128 vs. 82-119. This is a reduction of about 35%.

[0274] Q represents the limit quantity of an asset for which transactions occur. With stability, there is a slight decrease in the mean and standard deviation of quantity. A similar pattern is seen in V (price per limit transaction multiplied by quantity). As explained above, this is natural since there will be a decrease in quantity in the case of excess supply.

[0275] The average total assets of the stable network is $9809 (see Table 8). This represents about 4.8% of the restricted amount traded. Since the number of S tokens issued is twice that amount, an average of $19,618 worth of S tokens were issued for Round 1.

[0276] Table 8: Stable Network (Fund), Round 10 only

[0277]

[0278] Dynamic simulation

[0279] In the dynamic simulation, the same assumptions about parameters and variables in the static simulation are used for the initial round. However, for subsequent rounds, the initial price will be the market price generated by the last transaction of the previous round. This creates a dynamic dependency of each round on the previous round, which is closer to the real world than assuming a single round.

[0280] To control the analysis, the dependence is assumed to be only on price. Quantity is assumed to have the same distribution in each round, independent of the previous round. This helps to narrow down the sources of volatility and simplifies the analysis.

[0281] Initially, the simulation was run for 10 rounds for ease of analysis, but a 10-round sequence was required to be run 50,000 times. The assumptions for the dynamic simulation are summarized in Table 9. The results are summarized in Tables 10 and 11.

[0282] Table 9: Simulation parameters used in the dynamic Monte Carlo simulation

[0283] parameter value <![CDATA[α 0 ]]> 5％ <![CDATA[θ 0 ]]> 0.75 Initial price t = 0 $100 Price Distribution – Limit Buy <![CDATA[Pt~uni(0.4P t-1 :P t-1 -1)]]> Price Distribution – Sell Limit <![CDATA[Pt~uni(P t-1 +1: 1.6P t-1 )]]> Quantity distribution Qt~uni(2,500±60%)

[0284] Table 10: Dynamic simulation results, only round 10

[0285]

[0286] Table 11: Dynamic simulation results, 10 rounds

[0287]

[0288] Table 10 reports the results for the last round of trading, round 10 only. The standard deviation of prices drops from 77 in the case without stabilization to 41 in the case with stabilization, a decrease of 46%. In addition, the 10%-90% interval (the range between the 10% percentile and the 90% percentile) shrinks from 52-159 to 73-136, a decrease of 41%. In the case with stabilization, the average price is slightly higher, while the median is significantly higher. This reflects the dispersion of the price distribution in the case without stabilization.

[0289] V is the limit order volume (price times the number of transactions that affect price and are therefore affected by stabilization). Market order transactions are not reported here because they have no effect on price. The average limit volume is slightly higher with stabilization, while the median is significantly higher. The standard deviation is substantially lower with stabilization. This is noteworthy because it indicates an improvement in stability not only in price but also in volume.

[0290] Table 11 shows the results for the 10-round sequence. These results show the average of the prices for all 10 rounds after repeating the sequence 50,000 times. The same pattern is observed as in round 10. The standard deviation drops from 45.3 to 25.5, a 43% drop. The 10%-90% interval shrinks from 52-159 to 73-136, a drop of about 40%.

[0291] For quantity, with stability, a lower mean, but higher median will be noted. A lower standard deviation is also shown, and the 10%-90% interval has also dropped by about 30%, indicating improved stability of quantity.

[0292] For StableNetwork 10, cumulative deductions were measured for each 10-round sequence. The results are presented in Table 12. Note that the StableNetwork 14 Stable Fund accumulates approximately 52% of the limit transaction volume. This indicates that over a longer period of time, StableNetwork 14 should be able to accumulate a large amount of assets without affecting the actual transaction volume in the exchange. Therefore, StableNetwork 14 has the potential to provide a solid line of defense for the stability of the market.

[0293] Table 12: Stable Network (Fund), 10 rounds, cumulative

[0294]

[0295] Thus, the reserve of stablecoins or "S tokens" is built internally (i.e., within the stable network 14) by managing excess supply and demand, without relying on bond tokens or equity tokens. In addition, the parameters of the liquidation of stable fund units play a role in managing the supply of stablecoins. The system 10 preemptively intervenes to stabilize prices before the balance of supply and demand changes.

[0296] Thus, the system 10 employs a stablecoin that is adjusted so that the system 10 can preemptively intervene to stabilize the price, thereby stabilizing the stablecoin, before the balance of supply and demand changes (essentially, before the price changes), as well as accumulating reserves in the fund to provide another source of stability for the stablecoin. Thus, the stablecoin of this embodiment: requires no upfront capital - it is self-funded; manages excess supply or demand for stablecoins; proactively works to reduce price changes; and scales in proportion to the use of the stablecoin.

[0297] discuss

[0298] By integrating layers with centralized network architectures and layers with decentralized network architectures, System 10 improves stability without unduly sacrificing efficiency. When applied to capital markets, System 10 also differs from existing approaches in three main ways:

[0299] 1) System 10 changes in price Before Managing pressure on prices is therefore forward-looking.

[0300] Conventional strategies aim to after Controls for price volatility and is therefore a posteriori.

[0301] 2) System 10 is self-funded and investors' rights are protected.

[0302] 3) The stabilization fund, while self-funded, provides an additional layer of stability in the event of a major crisis or market collapse.

[0303] It might be argued that system 10 does not meet the requirements of traders: sellers who set limits on prices receive shares at a lower value than requested, and similarly for buyers; traders do not know exactly how much asset they will receive, or what the value of the asset they will receive will be.

[0304] However, such concerns are common in modern financial markets. For example, circuit breakers can cause trading halts and order cancellations without prior notice. Under Basel III (the regulatory framework for bank capital adequacy, stress testing, etc., also known as "Basel III"), holders of Tier 1 additional capital instruments do not know exactly when regulators decide to cancel their documents.

[0305] However, uncertainty in system 10 is controlled: all traders receive a majority of the requested trade (cash or assets), and the remainder in the form of S-Tokens. Given the restrictions on S-Tokens, traders have the ability to keep the value of S-Tokens and therefore have a high degree of confidence in the overall value of their trades.

[0306] Compared to taxes, the deductions of System 10 provide a better compensation scheme. Traders pay taxes, and this causes a difference between their claims and the actual results they receive. However, unlike taxes, which are not compensated in any direct way, System 10 provides S tokens to traders to compensate for deductions.

[0307] Thus, the system 10 can be viewed as an insurance system where deductions can be compared to premiums, where traders pay premiums to stabilize their investments. The premiums are variable, but the compensation for those premiums is also stable. As discussed above, it is in the interest of traders to keep the value of S tokens stable (e.g., $1 per token), which maximizes the extent to which S tokens are covered under an orderly redemption mechanism.

[0308] In general, the system 10 aims to stabilize the value of an asset. Like insurance, stabilization has a cost, and the users of the system 10 (ie, traders) bear the cost so that the system 10 is stable.

[0309] discuss

[0310] Analogy with physical systems

[0311] In defining the present invention, it may be useful to consider system 10 by analogy with the physical system of a sink or pool having a drain outlet and an overflow outlet. If water flows into the sink faster than the drain can drain the water, the water level will rise to the level of the overflow outlet providing additional drainage. This is not yet a stable system. To create a stable system, the water discharged from the overflow outlet is stored (e.g., using a pump) in a reservoir that can be used when the water inflow is low. This is a statically stable system.

[0312] To transform this stabilization system into a "smart" or dynamically stabilization system, a gap function between the inflow rate and the outflow rate is determined. (The gap is a function because these rates will change with water depth.) The size of the overflow outlet is dynamically adjusted (i.e., opened or throttled) based on this gap function: the larger the gap, the larger the overflow outlet. Alternatively, a pump in or attached to the overflow outlet can be used to speed up or slow down the drainage through the overflow outlet, draining at a higher rate when the water level is high. (In cases where the water inflow is low, the same pump can be used to draw water from a reservoir.)

[0313] This is a dynamically stable system, but it is not sustainable. To be sustainable, the system needs to obtain energy from the inflow itself, to be used to dynamically adjust the capacity of the overflow outlet. For example, the higher the water level in the tank, the more it weighs, and this extra weight (due to gravity) can be used as a source of energy. In addition, the higher the water level, the faster the discharge rate (and therefore the greater the force of the drainage), which can also be used as a source of energy.

[0314] The difference between the inflow and outflow of water can be based on a parameter α (with multiple values, e.g. 0 and α 1 ) for classification. When the gap exceeds α 0When θ = θ, the overflow pump will work to discharge water. Then, the speed of the overflow pump is the analog of θ of the system 10, and so on.

[0315] in conclusion

[0316] System 10 is thus a general system for controlling and mitigating price volatility in organized exchanges. System 10 is a forward-looking system that seeks to manage the gap between supply and demand in an orderly manner. The same system can be applied to digital or cryptocurrencies to create stablecoins. Self-funded stabilization funds add another line of defense against price volatility.

[0317] refer to

[0318] Bloomberg, https: / / www.bloomberg.com / news / articles / 2022-05-03 / citi-s-painful-flash-crash-highlights-market-risks-from-algos(2022).

[0319] The Balance, https: / / www.thebalance.com / what-is-a-flash-crash-3306184(2022).

[0320] Ian Stewart, In Pursuit of the Unknown: 17Equations That Changed the World, Basic Books (2013) 314 pages.

[0321] Vinu V. Das, Janahanlal Stephen, and Yogesh Chaba, Computer Networks and Information Technologies, Springer (2011), 224 pages.

[0322] James A. Momoh and Mohamed E. El-Hawary, Electric Systems, Dynamics, and Stability with Artificial Intelligence Applications, CRC Press (2018), 23 pages.

[0323] Nikos Hatziargyriou and Iony Patriota de Siqueira, Electricity SupplySystems of the Future, Springer Nature (2020), 468 pages.

[0324] Mitchell, C. and Boyle, M., Market Price, Investopedia, www.investopedia.com (November 15, 2022)

[0325] Al-Naji, N., et al., Basis: A Price-Stable Cryptocurrency with an Algorithmic Central Bank, (2018) www.basis.io

[0326] Those skilled in the art of the invention will appreciate that many modifications may be made without departing from the scope of the invention. In particular, it is apparent that certain features of an embodiment of the invention may be used to form additional embodiments.

[0327] It should be appreciated that, if any prior art is referred to herein, such reference does not constitute an admission that this prior art forms part of the common general knowledge in the art in any country.

[0328] In the appended claims and in the preceding description of the invention, unless the context requires otherwise due to express language or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" are used in an inclusive sense, i.e. specifying the presence of stated features but not excluding the presence or addition of further features in various embodiments of the invention.

Claims

1. A computer-implemented network stabilization method, the method comprising: receiving, at a controller, a plurality of commands; converting, by the controller, the commands into a set of computer-executable actions; generating, by the controller, a first command signal and a second command signal based on the computer-executable actions according to one or more control parameters generated by or accessible to the controller; sending the first command signal from the controller to a first computing system having a centralized network architecture; and sending the second command signal from the controller to a second computing system having a decentralized network architecture; wherein the first command signal is configured to control the first computing system to execute a first subgroup of the set of computer-executable actions; and the second command signal is configured to control the second computing system to execute a second subgroup of the set of computer-executable actions.

2. The method according to claim 1, wherein the second computing system includes a peer-to-peer network configured to host a public distributed ledger.

3. The method according to claim 1 or 2, wherein the commands indicate a purchase, a sale, or other financial transactions.

4. The method according to any one of the preceding claims, wherein the set of computer-executable actions constitutes a transaction including a purchase and a sale.

5. The method according to any one of the preceding claims, wherein: a first at least one of the commands is a purchase command indicating the purchase of a product or an asset, and a second at least one of the commands is a sale command indicating the sale of the product or the asset; converting the commands into the set of computer-executable actions includes: pairing or matching the purchase command and the sale command; and generating a matched purchase and sale command, and generating the first command signal and the second command signal includes forming a comparison between at least one parameter related to the purchase command and at least one parameter related to the sale command.

6. The method according to claim 5, wherein: forming the comparison includes comparing a sell limit order and a buy market order and / or comparing a buy limit order and a sell market order.

7. The method according to claim 5 or 6, wherein the at least one parameter related to the purchase command and the at least one parameter related to the sale command is the price of the product or other asset; and generating the first command signal and the second command signal includes generating a deduction applicable to the price such that both the first command signal and the second command signal are functions of the deduction.

8. The method according to any one of claims 5 to 7, comprising: generating the first command signal to include the sell command adjusted according to the deduction and the purchase command, or to include the purchase command adjusted according to the deduction and the sell command; and generating the second command signal to include the deduction.

9. The method according to any one of the preceding claims, wherein the first computing system includes the controller.

10. A network stabilization system, comprising: a controller; A first computing system having a centralized network architecture; and A second computing system having a decentralized network architecture; wherein the controller is configured to: receive a plurality of commands; convert the commands into a set of computer-executable actions; generate a first command signal and a second command signal according to the computer-executable actions based on one or more control parameters generated by or accessible to the controller; and send the first command signal to the first computing system and send the second command signal to the second computing system; The first command signal is configured to control the first computing system to execute a first subgroup of the set of computer-executable actions; and The second command signal is configured to control the second computing system to execute a second subgroup of the set of computer-executable actions.

11. The system according to claim 10, wherein, The second computing system includes a peer-to-peer network configured to host a public distributed ledger.

12. The system according to claim 10 or 11, wherein, The commands indicate purchases, sales, or other financial transactions.

13. The system according to any one of claims 10 to 12, wherein, The set of computer-executable actions constitutes a transaction including purchases and sales.

14. The system according to any one of claims 10 to 13, wherein: The first at least one command in the commands is a purchase command indicating the purchase of a product or asset, and the second at least one command in the commands is a sell command indicating the sale of the product or the asset; The conversion of the commands by the controller into the set of computer-executable actions includes: pairing or matching the purchase command and the sell command; and generating a matched purchase and sell command; and The generation of the first command signal and the second command signal by the controller includes forming a comparison between at least one parameter related to the purchase command and at least one parameter related to the sell command.

15. The system according to claim 14, wherein: Forming the comparison includes comparing a sell limit order and a buy market order and / or comparing a buy limit order and a sell market order.

16. The system according to claim 14 or 15, wherein, The at least one parameter related to the purchase command and related to the sell command is the price of the product or other asset; and The generation of the first command signal and the second command signal by the controller includes generating a deduction applicable to the price such that the first command signal and the second command signal are both functions of the deduction.

17. The system according to any one of claims 14 to 16, wherein: The first command signal includes the sell command adjusted according to the deduction and the purchase command or the purchase command adjusted according to the deduction and the sell command; and The second command signal includes the deduction.

18. The system according to any one of claims 10 to 17, wherein, The first computing system includes the controller.

19. A computer program comprising program code configured to implement the method according to any one of claims 1 to 9 when executed by one or more computing devices.

20. A computer-readable medium comprising the computer program according to claim 19.

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