Hierarchical Portfolios in Intelligent Investment Systems

Hierarchical Portfolios in Intelligent Investment Systems

Term Definitions AI view A recommendation or opinion about a hierarchical portfolio generated by an intelligent investment system. Blockchain A decentralized distributed ledger for securely recording transactions and data. Distributed Ledger A database shared and synchronized among multiple participants. Hierarchical Portfolio A portfolio organized in a hierarchical structure based on asset class, risk level, geographic location, etc. Intelligent Investment System A system that uses artificial intelligence and machine learning techniques to provide investment advice and manage investment portfolios. Machine Learning An artificial intelligence technique that enables computers to learn from data and improve their performance without being explicitly programmed. Multilayer Neural Network A computational model composed of multiple layers of neurons used to identify complex patterns in data. Portable Personal Financial Record (PFR) A secure and transferable financial record stored on a blockchain that contains an individual's investment history and advice. Multigenerational Family Record (MFR) Similar to PFR, but covers the financial information of family members over multiple generations. Smart Contract A piece of code stored on the blockchain that is automatically executed when predefined conditions are met. State Trie A data structure in the blockchain used to efficiently store and retrieve account states. Merkle Patricia Trie (MPT) A cryptographic data structure used to store key-value pairs, commonly used in blockchains. Transaction Trie A tree-shaped data structure used to store transaction data in the blockchain. UTXO (Unspent Transaction Output) An unspent output in a Bitcoin transaction that can be used as an input for subsequent transactions. Short Answer Question

How do smart investment systems use AI views?

Smart investment systems use AI views to generate and record recommendations for client tiered portfolios. These views may include adjustments to existing portfolios, new asset allocations, or any other recommendations based on market conditions and client goals.

Why is blockchain a suitable platform for storing financial records?

Blockchain offers decentralization, transparency, security, and immutability, making it ideal for storing sensitive data such as financial records. Its tamper-proof properties ensure the integrity of records, while its distributed nature improves censorship resistance and resilience to data loss.

Explain the role of the state tree in a blockchain.

The state tree is a data structure in a blockchain database that allows for efficient storage and retrieval of the current state associated with each account. It stores cryptographic hashes of all account balances, smart contract code, and other information related to the blockchain state, ensuring data integrity and verifiability.

How are smart contracts used to manage AI views in smart investment systems?

Smart contracts can automate tasks related to AI views, such as storage, access control, and version control. They can be programmed so that only authorized parties can access and modify views, ensuring transparency and accountability.

Distinguish between two main approaches to storing AI views on a blockchain.

The first approach involves recording all AI views (approved, rejected, and partially rejected) to the blockchain for use in machine learning model training. The second approach focuses on recording only approved AI views to create portable financial records.

Describe how to strike a balance between security and transparency when storing AI views on a blockchain.

Cryptography can ensure the confidentiality of AI views without compromising transparency. Access control mechanisms can limit access to authorized parties, while technologies such as zero-knowledge proofs can verify the validity of information without revealing the underlying data.

Explain the concept of portable personal financial records (PFRs).

A PFR is a comprehensive and verifiable record of an individual’s financial history, stored on a blockchain, that allows individuals to securely share and control their data across different financial institutions and advisors.

How does a multigenerational family financial record (MFR) differ from a PFR?

MFRs expand the concept of PFRs to include financial information from multiple generations of family members, facilitating wealth management, estate planning, and financial decision-making across generations.

Discuss the advantages of using machine learning models to generate tiered portfolio recommendations.

Machine learning models can analyze large amounts of data and identify complex patterns that traditional methods may miss. This enables them to generate more accurate and personalized portfolio recommendations that are tailored to individual clients’ financial goals, risk tolerance, and market conditions.

Explain the importance of data transformation when building machine learning models for portfolio recommendations.

Data transformation is essential to converting raw data into a format suitable for machine learning algorithms. It involves converting categorical variables into numerical representation, normalizing numerical features, and performing feature engineering to improve the accuracy and efficiency of the model.