Limited negotiation in embedded ultimatum games

This study expands on previous work done on signaling/screening take-it-or-leave-it asymmetric information games where excess disputes occur. Two players engage in an embedded ultimatum game in a stylized legal framework of plaintiff versus defendant. The plaintiff has either a low or a high claim on the uninformed defendant. There is a computerized version of the embedded ultimatum game to test replicability of literature results. Two novel variations are introduced. In the first variation multiple sequential offers can be made by the proposer during a single period of the embedded game and in the second real time offers and counteroffers can be made by both the plaintiff and the defendant. The effect of adding those negotiation mechanisms is studied. Overall replication results are consistent with theory. Subjects make use of the multiple offer mechanism. Multiple offers facilitate higher rates of settlement especially in high claim plaintiffs. When a high claim case settles the defendant earns most of the gains from settlement. The bilateral multiple offer mechanism increases settlement between bluffing low claim plaintiff and defendant by giving the plaintiff an opportunity to accept the defendant’s offer

Centralized Trading, Transparency, and Interest Rate Swap Market Liquidity: Evidence from the Implementation of the Dodd–Frank Act

We use proprietary transaction data on interest rate swaps to assess the effects of centralized trading, as mandated by Dodd-Frank, on market quality. Contracts with the most extensive centralized trading see liquidity metrics improve by between 12% and 19% relative to those of a control group. This is driven by a clear increase in competition between dealers, particularly in US markets. Additionally, centralized trading has caused inter-dealer trading in EUR swap markets to migrate from the US to Europe. This is consistent with swap dealers attempting to avoid being captured by the trade mandate in order to maintain market power

Bridging the Simulation to Reality gap in robotics

Recent advances in Machine and Reinforcement Learning, particularly in visuomotor control policies for robotics, have increased reliance on simulation frameworks and physics engines. These tools generate synthetic data and create sandbox environments to meet the substantial data demands of neural network training. However, given the inherit discrepancies between simulation and reality, the Simulation to Reality (Sim2Real) Gap in Robotics refers to all factors and specialized techniques that affect a transfer of an agent from the simulation to the real-world. Our literature review revealed that this field is largely empirical, fragmented across the robotics landscape, and heavily influenced by technical aspects of visuomotor policy design. To address this, our methodology covers the Sim2Real domain comprehensively, establishing performance metrics, identifying Reinforcement Learning design considerations, and developing a taxonomy of specialized Sim2Real techniques. We also create a detailed taxonomy of available simulation frameworks and physics engines for robotics. The next phase of our research focuses on mushroom harvesting, an unsolved problem in industrial food automation. This interdisciplinary challenge involves complex kinodynamic task and motion planning under constraints and environment uncertainties related to deformable bodies and material failure modes. We develop a practical Sim2Real pipeline for mushroom harvesting using a robotic gripper, allowing us to evaluate several Sim2Real techniques, including system identification with modeling approximations and explicit transferable abstractions. Contrary to conventional Sim2Real approaches, we show that the simulation framework is not just a tool for training but should be an integral component of the perception and planning system. This is a key statement of the thesis, demonstrating the predictive power of simulation in real-world applications. Our concluding remark and future work directions, based on the experience gained during this work, point to a holistic point-of-view for active inference, where the robotic agent actions are point towards an active, life-long, real-world model discovery

Profiting from Mimicking Strategies in Non-Anonymous Markets

We explore the information content of counterparty identities and how their disclosure can be exploited by other investors in a post-trade transparent market. Using data from the Helsinki Stock Exchange, we form dynamic mean-variance strategies with daily rebalancing which condition on the net flow of individual brokers. We find that investors can benefit greatly, up to 36% in annualized risk adjusted returns, from knowing who has been trading. We demonstrate a link between the information content of broker order flow and the sophistication of their clients. Brokers who have clients that trade with a momentum style or who are predominantly institutions or foreign investors have much more informative flow than do others. In the Finnish setting, this means that brokers with large market share have uninformative flows

Profiting from Mimicking Strategies in Non-Anonymous Markets

We explore the information content of counterparty identities and how their disclosure can be exploited by other investors in a post-trade transparent market. Using data from the Helsinki Stock Exchange, we form dynamic mean-variance strategies with daily rebalancing which condition on the net flow of individual brokers. We find that investors can benefit greatly, up to 36% in annualized risk adjusted returns, from knowing who has been trading. We demonstrate a link between the information content of broker order flow and the sophistication of their clients. Brokers who have clients that trade with a momentum style or who are predominantly institutions or foreign investors have much more informative flow than do others. In the Finnish setting, this means that brokers with large market share have uninformative flows

The Application of Morrison in an Era of Electronic Trading and Increasingly Global Markets

Article published in the Michigan State Journal of Business and Securities Law

Centralized trading, transparency and interest rate swap market liquidity: evidence from the implementation of the Dodd-Frank Act

We use proprietary transaction data on interest rate swaps to assess the impact of centralized trading, as mandated by Dodd-Frank, on market quality. We show that it has led to activity increasing and liquidity improving, with the largest improvements for contracts most affected by the mandate. Associated reductions in execution costs are economically significant eg daily end-user costs of trading USD relative to EUR mandated contracts drop by $3 million–$4 million. We show that requiring centralized trading in the United States caused swap markets to fragment geographically and give evidence which suggests that fragmentation is due to dealers trying to maintain market power

Relation of Maternal Pre-Pregnancy Factors and Childhood Asthma: A Cross-Sectional Survey in Pre-School Children Aged 2–5 Years Old

Background and Objectives: Asthma constitutes a constant, prolonged, inflammation-related pulmonary disorder in childhood with serious public health concerns. Several maternal risk factors can enhance the prevalence of its development in this stage of life; however, the currently available data remain contradictory and/or inconsistent. We aim to evaluate the potential impacts of mothers\u27 sociodemographic, anthropometric and prenatal and perinatal factors on the prevalence of developing asthma in pre-school children. Materials and Methods: This is a retrospective cross-sectional survey, which includes 5133 women and their matched pre-school children. Childhood asthma was diagnosed using validated questionnaires. Statistical analysis was accomplished to evaluate whether maternal sociodemographic, anthropometric and prenatal and perinatal factors can increase the probability of childhood asthma in pre-school age. Results: A prevalence of 4.5% of childhood asthma was recorded in pre-school age. Maternal age and pre-pregnancy overweight and obesity, caesarean section, gestational diabetes and hypertension and not breastfeeding were associated with childhood asthma after adjustment for multiple confounding factors. Conclusion: Our research showed that several maternal factors increase the prevalence of childhood asthma in pre-school age. Suitable and effective health policies and strategies should be taken into account to confront the predominant maternal factors that increase its prevalence in pre-school age