Temporal Aspects of Smart Contracts for Financial Derivatives

Implementing smart contracts to automate the performance of high-value over-the-counter (OTC) financial derivatives is a formidable challenge. Due to the regulatory framework and the scale of financial risk if a contract were to go wrong, the performance of these contracts must be enforceable in law and there is an absolute requirement that the smart contract will be faithful to the intentions of the parties as expressed in the original legal documentation. Formal methods provide an attractive route for validation and assurance, and here we present early results from an investigation of the semantics of industry-standard legal documentation for OTC derivatives. We explain the need for a formal representation that combines temporal, deontic and operational aspects, and focus on the requirements for the temporal aspects as derived from the legal text. The relevance of this work extends beyond OTC derivatives and is applicable to understanding the temporal semantics of a wide range of legal documentation

Selective crossover in genetic algorithms

This paper proposes a recombination operator, “selective crossover” for use in genetic algorithm

Recursion, lambda abstraction and genetic programming

Module creation and reuse are essential for Genetic Programming (GP) to be effective with larger and more complex problems. This paper presents a particular kind of program structure to serve these purposes: modules are represented as λ abstractions and their reuse is achieved through an implicit recursion. A type system is used to preserve this structure. The structure of λ abstraction and implicit recursion also provides structure abstraction in the program. Since the GP paradigm evolves program structure and contents simultaneously, structure abstraction can reduce the search effort for good program structure. Most evolutionary effort is then focused on the search for correct program contents rather than the structure. Experiments on the Even-N-Parity problem show that, with the structure of λ abstractions and implicit recursion, GP is able to find a general solution which works for any value of N very efficiently

Genetic Programming with Gene Dominance

This paper proposes the use of haploid gene dominance in genetic programming

Multiobjective robustness for portfolio optimization in volatile environments

Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from high-return/high-risk to low-return/low-risk, and an investor can choose her preferred point on the risk-return frontier. However, there are no guarantees that a low-risk solution will remain low-risk . if the environment changes, the relative positions of previously identified solutions may alter. A low-risk solution may become high-risk and vice versa. The robustness of a Multiobjective Genetic Programming (MOGP) algorithm such as SPEA2 is vitally important in the context of the real-world problem of portfolio optimisation. We explore robustness in this context, providing new definitions and a statistical measure to quantify the robustness of solutions. A new robustness measure is incorporated into a MOGP fitness function to bias evolution towards more robust solutions. This new system ("R-SPEA2") is compared against the original SPEA2 and we present our results

A common graphical form

We present the Common Graphical Form, a low level, abstract machine independent structure which provides a basis for implementing graph reduction on distributed processors. A key feature of the structure is its ability to model disparate abstract machines in a uniform manner; this enables us to experiment with different abstract machines without having to recode major parts of the run-time system for each additional machine. Because we are dealing with a uniform data structure it is possible to build a suite of performance measurement tools to examine interprocessor data-flow and to apply these tools to different abstract machines in order to make relative comparisons between them at run-time. As a bonus to our design brief we exploit the unifying characteristics of the Common Graphical Form by using it as an intermediate language at compile-time

A Blockchain Grand Challenge: Smart Financial Derivatives

Blockchain and distributed ledger technology (DLT) research encompasses use cases ranging from social innovation to banking, and technical developments ranging from cryptography to semantics of legal text. Research in both academia and industry is highly interdisciplinary across domains such as computer science, linguistics, law, cryptography, banking, economics, and social sciences. The growing complexity of blockchain science and use cases, coupled with the interdisciplinary nature of the research, poses new challenges to our community. Research publication plays a key role in supporting this highly interdisciplinary work: supporting the need for rapid and reliable dissemination of preliminary and final results, and the need for longevity of results beyond the end of financial or management support for a research project. Industry teams rarely have subscriptions to academic journals, and an open access journal adds substantial value in supporting the research community. The field is young, with many research challenges to be addressed. One “grand challenge” for our research community is the implementation of high-value, long-lived, financial derivatives transactions running as smart contracts on DLT (“smart financial derivatives”). This is currently being explored by academia, banking practitioners, trade associations and technology vendors, and is driving research across a wide range of research groups, each focusing on a different aspect. What makes this a “grand” challenge is the need for a large number of diverse research problems to be solved simultaneously. The following outlines a few of the major research questions being investigated: some of these are general research problems that affect blockchain/DLT development broadly, whereas others are very specific to financial derivatives, but all of these aspects must be solved, and their solutions combined effectively, to provide efficient and resilient solutions to the grand challenge

Comparative Carcinogenicity for Mouse-Skin of Smoke Condensates Prepared from Cigarettes Made from the Same Tobacco Cured by Two Processes

Bright tobacco grown in Mexico was either flue-cured and redried (FC) or air-cured and bulk-fermented (AC). Both FC and AC were made into cigarettes standardized for draw resistance. FC and AC cigarettes were smoked under similar conditions in a smoking machine (one 2-second 25 ml. puff per minute down to a 20 mm. butt length). Condensates were kept at 0-4° C. until applied to the skin of mice

Using virtual reality to train infection prevention: what predicts performance and behavioral intention?

Training medical professionals for hand hygiene is challenging, especially due to the invisibility of microorganisms to the human eye. As the use of virtual reality (VR) in medical training is still novel, this exploratory study investigated how preexisting technology acceptance and in-training engagement predict VR hand hygiene performance scores. The effect of training in the VR environment on the behavioral intention to further use this type of training device (a component of technology acceptance) was also investigated. Participants completed a VR hand hygiene training comprising three levels of the same task with increasing difficulty. We measured technology acceptance, composed of performance expectancy, effort expectancy, and behavioral intention, pre- and post-training, and in-training engagement using adaptations of existing questionnaires. We used linear regression models to determine predictors of performance in level-3 and of behavioral intention to further use VR training. Forty-three medical students participated in this exploratory study. In-training performance significantly increased between level-1 and level-3. Performance in level-3 was predicted by prior performance expectancy and engagement during the training session. Intention to further use VR to learn medical procedures was predicted by both prior effort expectancy and engagement. Our results provide clarification on the relationship between VR training, engagement, and technology acceptance. Future research should assess the long-term effectiveness of hand hygiene VR training and the transferability of VR training to actual patient care in natural settings. A more complete VR training could also be developed, with additional levels including more increased difficulty and additional medical tasks