Review of: An Agent Oriented Business Model for E-Commerse

based on the NYSE Specialist system, paper by Kenneth Griggs

Presented by: Alexander Sverdov

The Paper Outline

Description of different auctions. Description of NYSE Specialist role. Proposal of an agent architecture that

serves the same purpose as NYSE Specialists.

English Auction

Reserve Price (or bid floor) below which no bids are accepted.

Auctioneer guides the bidding process upwards until a final highest bid is accepted.

Dutch Auction

Reverse of an English Auction. Auctioneer states a high starting price. The Auctioneer proceeds to reduce the

price by a fixed amount until a bid is made. The first bid is taken.

Continuous Double Auction

Multiple buyers and sellers compete in the market.

Bids and Asks are cleared continuously.

Specialist in CDA at NYSE

Specialists are employees of independent specialist firms.

Manage trading of a certain stock. Governed by stock exchange rules.

Illustration

Specialists

Play the role of Market Makers. Always willing to buy and sell at a “fair” price

(even if they don’t own shares). Ensure orderly market; control the

rising/lowering of stock prices---by possibly buying/selling against the market trends (by using their own capital to cushion sharp price changes).

Can act as regular traders.

Roles of Specialists

Agents: buy/sell shares on customer’s request (act as floor broker).

Auctioneer: Provide a market for a security. Always be ready to buy/sell.

Catalyst: The specialist keeps track of all known interest in the stock, and alerts interested parties.

Principal: Buy and sell stock for their own account (with some rules).

Specialist Book

Maintain all transactions. All market and limit orders. Provides a unique view of the market.

Intelligent Software Agents

Autonomy: agents can operate without direct intervention by humans or others.

Social ability: agents can interact with other agents and/or humans.

Reactivity: agents perceive their environment and respond in a timely fashion to changes that occur in it.

Intelligent Software Agents, Cont.

Pro-activeness: agents can exhibit goal-directed behavior by taking the initiative.

Mobility: agents can move to other environments.

Temporal continuity: agents are continuously running processes.

Proposed Architecture

Architecture Details

More Detailed Details

Four Agent Types

Trading Agent Principal Agent Notification Agent Representation Agent

Trading Agent

Invokes trading rules Matches orders Maintains Bid/Ask spread Records transactions to the tape Updates Inventory Notifies other agents when required Records direct buyer-seller trades

Principal Agent

Performs an analysis using data from trade repository.

Invokes principal behavior rules. Requests trades from the trading agent.

Notification Agent

Catalyst function. Notifies possible buyers and sellers of market

conditions Maintains and updates the notification DB and

the tape. Requests trades from the trading agent. Notifies the representation agent when

applicable.

Representation Agent

Interacts with represented buyers and sellers.

Requests trades from trading agent. Negotiates commissions Updates trade repository

Database, Knowledge, etc.

The system maintains information about all participants, and all the relevant stock data.

Trading rules are handled using an expert system.

Principal behavior is determined by neural network or some heuristic system.

Things to be addressed

Consistent agent & market semantics. A deeper understanding of specialist knowledge

and functions (process model) Agent development tools. A high level agent scripting language. An analysis of knowledge representation

techniques to be used by the agents (rule-based, Expert System shell, neural net, genetic algorithm, etc.)

Conclusion

The paper provides a first attempt at modeling the NYSE specialist role using an agent based system.

The paper does not describe an implementation, but rather a possible design for such a system.

The End.