Automated Execution of Financial Contracts on Blockchains

The paper investigates financial contract management on distributed ledgers and provides a working solution implemented on the Ethereum blockchain. The system is based on a domain-specific language for financial contracts that is capable of expressing complex multi-party derivatives and is conducive to automated execution. The authors propose an architecture for separating contractual terms from contract execution: a contract evaluator encapsulates the syntax and semantics of financial contracts without actively performing contractual actions; such actions are handled by user-definable contract managers that administer strategies for the execution of contracts. Hosting contracts and contract managers on a distributed ledger, side-by-side with digital assets, facilitates automated settlement of commitments without the need for an intermediary. The paper discusses how the proposed technology may change the way financial institutions, regulators, and individuals interact in a financial system based on distributed ledgers

TRADING GREEN BONDS USING DISTRIBUTED LEDGER TECHNOLOGY

The promising markets for voluntary carbon credits are faced with crippling challenges to the certification of carbon sequestration, and the lack of scalable market infrastructure in which institutions can invest in carbon offsetting. This amounts to a funding problem for the agricultural sector, as farmers are unable to access the liquidity needed to fund the transition to sustainable practices. We explore the feasibility of mitigating infrastructural challenges based on a DLT Trading and Settlement System, for ‘green bonds’. The artefact employs a multi-sharded architecture, in which the set of nodes retains carefully orchestrated responsibilities in the functioning of the network. We evaluate the artefact in the supranational context with an EU-based regulator as part of a regulatory sandbox program mandated by the new EU DLT Pilot regime. By conducting design-driven research with stakeholders from industrial and governmental bodies, we contribute to the IS literature on the practical implications of DLT

Relational Algebra by Way of Adjunctions

Bulk types such as sets, bags, and lists are monads, and therefore support a notation for database queries based on comprehensions. This fact is the basis of much work on database query languages. The monadic structure easily explains most of standard relational algebra—specifically, selections and projections—allowing for an elegant mathematical foundation for those aspects of database query language design. Most, but not all: monads do not immediately offer an explanation of relational join or grouping, and hence important foundations for those crucial aspects of relational algebra are missing. The best they can offer is cartesian product followed by selection. Adjunctions come to the rescue: like any monad, bulk types also arise from certain adjunctions; we show that by paying due attention to other important adjunctions, we can elegantly explain the rest of standard relational algebra. In particular, graded monads provide a mathematical foundation for indexing and grouping, which leads directly to an efficient implementation, even of joins

Optimally Streaming Greedy Regular Expression Parsing

Abstract. We study the problem of streaming regular expression parsing: Given a regular expression and an input stream of symbols, how to output a serialized syntax tree representation as an output stream during input stream processing. We show that optimally streaming regular expression parsing, outputting bits of the output as early as is semantically possible for any regular expression of size m and any input string of length n, can be performed in time O(2 m log m + mn) on a unit-cost random-access machine. This is for the wide-spread greedy disambiguation strategy for choosing parse trees of grammatically ambiguous regular expressions. In particular, for a fixed regular expression, the algorithm's run-time scales linearly with the input string length. The exponential is due to the need for preprocessing the regular expression to analyze state coverage of its associated NFA, a PSPACE-hard problem, and tabulating all reachable ordered sets of NFA-states. Previous regular expression parsing algorithms operate in multiple phases, always requiring processing or storing the whole input string before outputting the first bit of output, not only for those regular expressions and input prefixes where reading to the end of the input is strictly necessary