AMENDED CLAIMS

received by the International Bureau on 19.08.2019

1. A computer- implemented seamless system, apparatus and method of utilizing an autonomous decentralized system of distributed ledger infrastructure and self-executing smart contracts for trading assests on one or more trading platforms or exchanges with zero-loss efficiency, securely, confidentially and equitably sharing with or leasing to participating peers, top performing algorithmic trading strategies designed by an algorithmic trading robot (ATR), based on performance of that algorithm on a trading algorithm global leaderboard that dynamically updates in real-time, wherein the specific trading strategy of the top performing algorithm is automatically and seamlessly encrypted and secured using private key and public key infrastructure in real-time, so that it can neither be replicated nor reconfigured nor reversed engineered by the peers who lease it for placing their trades. .

2. The system of claim 1 wherein the financial instruments or assets belong to one or more of the asset class consisting of currencies, stocks, equities, futures, options, commodities, bonds, warrants or cryptocurrencies.

3. The system of claim 1 wherein the trading algorithm performance leaderboard is updated and published either in real time, every minute, every hour, every l2-hours, every 24- hours or every week, and consequently top performing algorithms made available for equitable sharing with or leasing to peers for a consideration that may either be on fixed fee basis, or based on a share in the trading profits according to specific terms defined in the self-executing smart contract.

4. The method of claim 1 wherein the self-executing smart contract between the lessor and the lessee of the leased algorithm is verified by consensus of participating peers and immutably maintained in a database of distributed ledger amongst the participating nodes, and it limits the use of the contracted algo to trading specific financial 2/7

instruments during specific time periods within specific trading exchanges deploying artificial intelligence for eliminating any residual risk in trading decisions due to any real time changes in market conditions that impact the profitability of the leased algorithm.

5. The zero-loss trading system of claim 1 wherein the top -performing algorithm has a profitability half-life estimated by a built-in deep learning module based on stochastic modeling of data obtained via global and local surveillance of financial markets, such profitability half life is dynamic and varies widely depending on the type of financial instrument traded and random events influencing financial markets.

6. The zero-loss trading system of claim 1 wherein artificial intelligence eliminates all possibilities of losses by:

a. deploying only the most profitable algo within it’s estimated profitability half life; b. killing the algo if unpredictable extreme market conditions makes the algo unprofitable within it’s profitability half life;

c. insuring against unforeseeable losses.

7. The method of claim 1 wherein the participating peers are extremely impoverished individuals or their cooperatives with no capital or trading experience, and their tradable financial instruments or assets are acquired through 100% secured zero-loss financing (ZLF) nano-loans or micro-loans not less than $100 and not more than $1000, under terms that the loaned principle is exclusively used for trading but cannot be withdrawn, and the trading profits are withdrawable only to the extent that they are over and above estimated loan interest accrued.

8. The system of claim 1 wherein the apparatus is an automatic teller machine (ATM) for last mile delivery of financial and profit making algo-sharing, algo-trading and financial instrument exchange services to remote end-users who do not have a computer device or chose not to use a personal computer device. 3/7

9. The method of claim 1 wherein the algorithmic trading in financial instruments is high frequency trading (HFT) based on value and frequency of the trades defined by each individual peer operating the automated trading robot.

10. The method of claim 1 wherein the algorithmic trading is inter-exchange arbitrage trading or intra-exchange arbitrage trading.

11. The method of claim 1 wherein the algorithm sharing is not limited to financial instruments but includes any asset that represents value of ownership.

12. The method of claim 1 wherein the autonomous decentralized system is either a low latency scalable blockchain infrastructure or other decentralized network architectures such as Directed Acyclic Graph (DAG).

13. The method of claim 1 wherein instead of a decentralized blockchain infrastructure or other decentralized network architectures such as Directed Acyclic Graph (DAG), or the algorithm sharing is implemented using a traditional centralized database infrastructure, or the ATR and the decentralized algo-sharing protocols are integrated and implemented within a trading exchange itself.

14. A computer-implemented, automated and seamless method of zero-loss trading utilizing a decentralized system of self-executing smart contracts for equitable sharing or leasing of top performing algorithmic trading strategies among peers for a fee, comprising of the steps of:

signing in to an algorithmic trading robot (ATR) at a user node,

using the trading strategy module of the robot for creating a custom algorithmic strategy (algo) by selecting a combination of indicators,

entering the value and frequency of the trades to be executed at the user node, 4/7

using the custom algo for executing the trades at the user node, encrypting the custom algo at user node, publishing the trading results to a global leaderboard of top performing algos for sharing it with peers,

achieving the top spot in the global leaderboard,

encrypting and securing the winning algo using the private key / public key infrastructure so that it can neither be replicated nor reconfigured nor reengineered by the lessee peers,

leasing use of the winning algo to peers by executing a smart contract, transferring the winning algo to the algorithmic trading robot at a peer node,

entering the value and frequency of trades to be executed at the peer node,

decrypting the algo at the peer node,

executing the trade or trades by the trading robot at the peer node,

calculating the fee payable by the peer to the user for the volume of trading executed by the leased algo at the peer node,

transferring the fee from the peer node to the user node,

validating each step to be in compliance with the terms of the smart contract and recording the transaction in the distributed public ledger.

15. The method of claim 14, wherein the algorithmic trading pertains to assets belonging to one or more of the asset class consisting of currencies, stocks, equities, futures, options, commodities, bonds, warrants or cryptocurrencies.

16. The method of claim 14, wherein the algo performance leaderboard is updated and published either in real time, every minute, every hour, every l2-hours, every 24-hours or every week, and consequently top performing algos made available for sharing with or leasing to peers for a consideration that may either be on a fixed fee basis, or based on a share in the trading profits according to specific terms defined in the self-executing smart contract.

17. The method of claim 14, wherein the self-executing smart contract between the lessor and the lessee of the leased algorithm is verified by consensus of participating peers and immutably maintained in a database of distributed ledger amongst the participating nodes, and it limits the use of the contracted algo to trading specific financial instruments during specific time periods within specific trading exchanges deploying artificial intelligence for eliminating any residual risk in trading decisions due to any real time changes in market conditions that impact the profitability of the leased algorithm.

18. The zero-loss trading system of claim 14, wherein the top-performing algorithm has a profitability half-life estimated by a built-in deep learning module based on stochastic modeling of data obtained via global and local surveillance of financial markets, such profitability half life is dynamic and varies widely depending on the type of financial instrument traded and random events influencing financial markets.

19. The system of zero-loss trading of claim 14, wherein artificial intelligence eliminates all possibilities of losses by:

a. deploying only the most profitable algo within it’s estimated profitability half life; b. killing the algo if unpredictable extreme market conditions makes the algo unprofitable within it’s profitability half life;

c. insuring against unforeseeable losses.

20. The method of claim 14, wherein the participating peers are extremely impoverished individuals or their cooperatives with no capital or trading experience, and their tradable financial instruments or assets are acquired through 100% secured zero-loss financing (ZLF) nano-loans or micro-loans not less than $100 and not more than $1000, under terms that the loaned principle is exclusively used for trading but cannot be withdrawn, and the trading profits are withdrawable only to the extent that they are over and above estimated loan interest accrued.

21. The method of claim 14, wherein the peer node is a shared node such as an automatic teller machine (ATM) for last mile delivery of financial and profit making algosharing, algotrading and financial instrument exchange services to remote end-users who do not have a computer device or chose not to use a personal computer device.

22. The method of claim 14, wherein the peer nodes run an artificial intelligence engine with deep learning algorithms for analyzing the trading history, patterns and real time market conditions for making a decision on leasing or not leasing a specific winning algorithm despite it’s top position on the leaderboard, and for pretesting the profitability of the leased algorithm prior to placing a trade for the purpose of minimizing or eliminating the probability of losses.

23. The method of claim 14, wherein the algorithmic trading in financial instruments is high frequency trading (HFT) based on value and frequency of the trades defined by each individual peer operating the trading robot (ATR).

24. The method of claim 14, wherein the algorithmic trading is inter-exchange arbitrage trading or intra-exchange arbitrage trading.

25. The method of claim 14, wherein the algorithm sharing is not limited to financial instruments but includes any asset that represents value of ownership.

26. The method of claim 14, wherein the autonomous decentralized system is either a low latency scalable blockchain infrastructure or other decentralized network architectures such as Directed Acyclic Graph (DAG).

27. The method of claim 14, wherein instead of a decentralized blockchain infrastructure or other decentralized network architectures such as Directed Acyclic Graph (DAG), or the algorithm sharing is implemented using a traditional centralized database infrastructure, 7/7

or the ATR and the decentralized algo- sharing protocols are integrated and implemented within a trading exchange itself.