Agent-based model with asymmetric trading and herding for complex financial systems

Background: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results: With the model parameters determined for six representative stock-market indices in the world respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions: We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.Comment: 17 pages, 6 figure

HAPI Beds: A Quality Improvement Project to Reduce Hospital-Acquired Pressure Injuries

Hospital acquired pressure injuries (HAPIs) remain a detrimental health problem that plagues hospital institutions and patients with a significant increase in morbidity and mortality. The development of HAPIs takes a tremendous toll on the patient, their family, as well as the healthcare system. Research has shown that there are multiple approaches in the prevention and treatment of HAPIs and one of the prominent methods includes choosing the appropriate bed surface tailored for the patient’s condition. This evidenced-based practice intervention was initiated with extensive literature review to contribute to the development of a new pressure injury surface selection algorithm for the adult Medical-Surgical Telemetry Stroke unit at KF hospital. The new algorithm is supported by the stakeholders to ensure compliance and support for a smooth transition and implementation. Individuals involved in the development of this new algorithm include the quality and risk team, wound nurse, bedside nurses, wound champions, and nurse leaders. Furthermore, audits, interviews, and HAPI interviews were conducted during this project. The pre-implication results showed a significant number of nurses with an apparent knowledge gap in prevention and treatment of HAPIs when ordering the specialized beds. However, through the implementation of the new surface algorithm and support from the stakeholders, the post survey data and analysis are projected to show an increase in nurse knowledge and competency at 3 months after implementation. Overall, the evidence-based bed selection algorithm was developed for the adult Medical-Surgical Telemetry Stroke Unit to reduce the knowledge gap among the nurses and reduce the incidence of HAPIs. Keywords: Hospital-acquired pressure injury (HAPI), bed algorithm, knowledge gaps, stakeholders, prevention, treatment

How volatilities nonlocal in time affect the price dynamics in complex financial systems

What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time.Comment: 16 pages, 7 figure

Do price shocks change electricity consumption? Evidence from New Zealand industrial users

Honors (Bachelor's)EconomicsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/98849/1/tanjje.pd

Towards the AlexNet Moment for Homomorphic Encryption: HCNN, theFirst Homomorphic CNN on Encrypted Data with GPUs

Deep Learning as a Service (DLaaS) stands as a promising solution for cloud-based inference applications. In this setting, the cloud has a pre-learned model whereas the user has samples on which she wants to run the model. The biggest concern with DLaaS is user privacy if the input samples are sensitive data. We provide here an efficient privacy-preserving system by employing high-end technologies such as Fully Homomorphic Encryption (FHE), Convolutional Neural Networks (CNNs) and Graphics Processing Units (GPUs). FHE, with its widely-known feature of computing on encrypted data, empowers a wide range of privacy-concerned applications. This comes at high cost as it requires enormous computing power. In this paper, we show how to accelerate the performance of running CNNs on encrypted data with GPUs. We evaluated two CNNs to classify homomorphically the MNIST and CIFAR-10 datasets. Our solution achieved a sufficient security level (> 80 bit) and reasonable classification accuracy (99%) and (77.55%) for MNIST and CIFAR-10, respectively. In terms of latency, we could classify an image in 5.16 seconds and 304.43 seconds for MNIST and CIFAR-10, respectively. Our system can also classify a batch of images (> 8,000) without extra overhead

Optimizing Survivorship Care Services for Asian Adolescent and Young Adult Cancer Survivors: A Qualitative Study.

Purpose: With an increasing focus on developing survivorship services tailored for adolescent and young adult (AYA) cancer survivors, incorporation of viewpoints from both survivors and health care professionals (HCPs) is important. This study aims to explore the perceptions of current and prospective survivorship services from both groups in Singapore to propose service design and delivery strategies. Methods: Focus group discussions with 23 AYA cancer survivors between the ages of 16 and 39 years at diagnosis and 18 HCPs were conducted in National Cancer Centre Singapore (NCCS) and Singapore Cancer Society (SCS). All focus group discussions were transcribed verbatim. Deductive thematic analysis was performed according to the components of a design thinking model: empathizing with AYA survivors, defining care gaps, proposing services, and implementation strategies. Results: AYA survivors preferred age-specific services that are aligned with their personal goals. Current survivorship care failed to address the needs of survivors' dependents (caregivers and children) and to consider the utility of each service temporally. Prospective services should clarify disease disclosure obligation in job search and introduce a care navigator. Key implementation strategies included (1) training HCPs on communication techniques with AYA, (2) selecting engagement platforms that complement survivors' information-seeking behavior, (3) improving outreach to survivors through appropriate branding and publicity, and (4) consolidating services from multiple providers. Conclusions: The design of survivorship care services for AYA survivors should be systematic in its conceptualization process and employ implementation strategies. The coordination of the wide spectrum of services warrants a concerted effort by cancer centers, community partners, and the government

(2,4-Dihydroxy­benzyl­idene)dimethyl­ammonium dichloro­phosphinate

In the title compound, C9H12NO2 +·Cl2PO2 −, the mol­ecular skeleton of the cation is nearly planar with an r.m.s. deviation of 0.0336 Å. In the crystal structure, inter­molecular O—H⋯O hydrogen bonds link cations and anions into chains running along [10]

Electrostatic effect due to patch potentials between closely spaced surfaces

The spatial variation and temporal variation in surface potential are important error sources in various precision experiments and deserved to be considered carefully. In the former case, the theoretical analysis shows that this effect depends on the surface potentials through their spatial autocorrelation functions. By making some modification to the quasi-local correlation model, we obtain a rigorous formula for the patch force, where the magnitude is proportional to ${\frac{1}{{{a}^{2}}}{{(\frac{a}{w})}^{\beta (a/w)+2}}}$ with ${a}$ the distance between two parallel plates, ${w}$ the mean patch size, and ${\beta}$ the scaling coefficient from ${-2}$ to ${-4}$. A torsion balance experiment is then conducted, and obtain a 0.4 mm effective patch size and 20 mV potential variance. In the latter case, we apply an adatom diffusion model to describe this mechanism and predicts a ${f^{-3/4}}$ frequency dependence above 0.01 ${\rm mHz}$. This prediction meets well with a typical experimental results. Finally, we apply these models to analyze the patch effect for two typical experiments. Our analysis will help to investigate the properties of surface potentials