Trading Strategies Generated Pathwise by Functions of Market Weights

Almost twenty years ago, E.R. Fernholz introduced portfolio generating functions which can be used to construct a variety of portfolios, solely in the terms of the individual companies' market weights. I. Karatzas and J. Ruf recently developed another methodology for the functional construction of portfolios, which leads to very simple conditions for strong relative arbitrage with respect to the market. In this paper, both of these notions of functional portfolio generation are generalized in a pathwise, probability-free setting; portfolio generating functions are substituted by path-dependent functionals, which involve the current market weights, as well as additional bounded-variation functions of past and present market weights. This generalization leads to a wider class of functionally-generated portfolios than was heretofore possible, and yields improved conditions for outperforming the market portfolio over suitable time-horizons.Comment: 45 pages, 3 figure

Development of an Agent Based Urban Simulation Model

Since the pioneering work of Lowry in the 1960s, many urban models has developed to understand how urban systems work and change. Early urban models tend to focus on the relationship and interaction between land use and transportation. Yet, recent urban models pay more attention to urban morphology with an interest on self-organising nature of urban systems. Agent based urban modelling approach is gaining popularity as a new means to study an urban systems in this context. The methodology has roots in the natural science field such as the complexity science, but it also provides meaningful insights for social systems as well as urban systems. The key strength is that it offers a way to understand urban systems through the interaction among individual members in the systems such as households and developers. This research aims to develop an agent based urban model as a new scientific tool to understand changes in urban systems and to support planning policy making. It starts with reviewing history and issue in urban modeling and then move on the trend of urban development in general and in Korea. The research then defines the key behaviour and algorithms of the model before developing it as a functional computer program. We developed the model by using an open source programming platform, Repast Simphony. Then the model was applied to a case study area of Busan Metropolitan Area(Busan, Gimhae, Yangsan) to see if it properly works and generates valid simulation outcomes. We has confirmed that the model offers new and meaningful ways to understand urban future and to support planning policy. Yet, the model developed in this study is subject to further development. It is necessary to analyse more empirical data on agents’ type and behaviour. At the same time, it is desirable to improve technical interfaces to make is as a planning support system. These require continued research and development

Gas-Assisted Powder Injection Molding: A Comparison of Residual Wall Thickness Between Metal Cavity vs. SLA Cavity and Effect of Mold Temperature on Residual Wall Thickness

The effects of processing variables on gas penetration depth and Residual Wall Thickness (RWT) in an aluminum (Al) cavity of Gas-Assisted Injection Molding (GAIM) were investigated with Polypropylene (PP) and Stainless Steel Powder Feedstock (SSPF). The selected processing variables were melt temperature, shot size, gas pressure, and gas delay time. By using a Taguchi L9 array, the results were compared with previous work. For PP, there were no significant differences on gas penetration depth. However, the significance of gas delay time was relatively higher in an Al cavity as compared to a Stereolithography (SLA) cavity from previous work with SSPF. The most significant parameter affecting RWT was melt temperature for PP and gas delay time for SSPF, respectively. Additionally for SSPF, we found that gas penetration depth and RWT decreased with increasing mold temperature

The Integration of Heterogeneous Open Source Software to Develop an Urban Simulation Model

Recent development of open source geospatial software offers new opportunities for the spatial analysis and urban modeling fields. The use of open source software enables analysts and modelers to build dedicated and advanced models through computer programing. However, many open source geospatial software usually provides building blocks for the static data management, analysis, and visualisation. Hence, development of dynamic simulation model with open source geospatial software is not yet fully fledged. The goals of this study are twofold. Firstly, it aims to develop a dynamic urban growth simulation model by using and integrating heterogeneous open source software. Secondly, by doing so, it aims to suggest a new way to use logistic regression model as a method for dynamic urban growth simulation. The research uses R and Processing to develop an urban growth simulation model. The former is a well-known open source statistical software, and the latter is an open source software for data visualisation. The integration of two open source software and the model development are carried out in a Java programming environment. The reason of such integration is to build a dynamic urban growth simulation from a conventional binominal logistic regression model. Binominal logistic regression is well-known method to calculate a certain choice probability, and it has often been used to analyse the possibility of future urban development. However, the result from such logistic regression by nature is stochastic and static. To make it as a method for urban growth simulation, what this research has done is the integration of following tasks: execution of logistic regression, extraction of coefficients from the result, calculation of development probability, iterative allocation of new development, and visualisation of such urban development. The model was applied to a case study area, Busan Metropolitan Area, Korea in order to examine its usability.It has produced statistically meaningful outcome, and the model shows a new way of developing dynamic urban simulation model. However, all data processing and manipulation is done in a separateGIS environment, and it is not integrated into the model. A tight-coupling with open source geospatial software could be a possible future research

Special issue on smart interactions in cyber-physical systems: Humans, agents, robots, machines, and sensors

In recent years, there has been increasing interaction between humans and non‐human systems as we move further beyond the industrial age, the information age, and as we move into the fourth‐generation society. The ability to distinguish between human and non‐human capabilities has become more difficult to discern. Given this, it is common that cyber‐physical systems (CPSs) are rapidly integrated with human functionality, and humans have become increasingly dependent on CPSs to perform their daily routines.The constant indicators of a future where human and non‐human CPSs relationships consistently interact and where they allow each other to navigate through a set of non‐trivial goals is an interesting and rich area of research, discovery, and practical work area. The evidence of con- vergence has rapidly gained clarity, demonstrating that we can use complex combinations of sensors, artificial intelli- gence, and data to augment human life and knowledge. To expand the knowledge in this area, we should explain how to model, design, validate, implement, and experiment with these complex systems of interaction, communication, and networking, which will be developed and explored in this special issue. This special issue will include ideas of the future that are relevant for understanding, discerning, and developing the relationship between humans and non‐ human CPSs as well as the practical nature of systems that facilitate the integration between humans, agents, robots, machines, and sensors (HARMS).Fil: Kim, Donghan. Kyung Hee University;Fil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Matson, Eric T.. Purdue University; Estados UnidosFil: Kim, Gerard Jounghyun. Korea University

Arbitrage theory in a market of stochastic dimension

This paper studies an equity market of stochastic dimension, where the number of assets fluctuates over time. In such a market, we develop the fundamental theorem of asset pricing, which provides the equivalence of the following statements: (i) there exists a supermartingale num\'eraire portfolio; (ii) each dissected market, which is of a fixed dimension between dimensional jumps, has locally finite growth; (iii) there is no arbitrage of the first kind; (iv) there exists a local martingale deflator; (v) the market is viable. We also present the Optional decomposition theorem, which characterizes a given nonnegative process as the wealth process of some investment-consumption strategy. These results are developed in an equity market model where the price process is given by a piecewise continuous semimartingale of stochastic dimension. Without the continuity assumption on the price process, we present similar results but without explicit characterization of the num\'eraire portfolio

Quantifying dimensional change in stochastic portfolio theory

In this paper, we develop the theory of functional generation of portfolios in an equity market with changing dimension. By introducing dimensional jumps in the market, as well as jumps in stock capitalization between the dimensional jumps, we construct different types of self-financing stock portfolios (additive, multiplicative, and rank-based) in a very general setting. Our study explains how a dimensional change caused by a listing or delisting event of a stock, and unexpected shocks in the market, affect portfolio return. We also provide empirical analyses of some classical portfolios, quantifying the impact of dimensional change in portfolio performance relative to the market.Comment: 41 pages, 4 figure

DynaCon: Dynamic Robot Planner with Contextual Awareness via LLMs

Mobile robots often rely on pre-existing maps for effective path planning and navigation. However, when these maps are unavailable, particularly in unfamiliar environments, a different approach become essential. This paper introduces DynaCon, a novel system designed to provide mobile robots with contextual awareness and dynamic adaptability during navigation, eliminating the reliance of traditional maps. DynaCon integrates real-time feedback with an object server, prompt engineering, and navigation modules. By harnessing the capabilities of Large Language Models (LLMs), DynaCon not only understands patterns within given numeric series but also excels at categorizing objects into matched spaces. This facilitates dynamic path planner imbued with contextual awareness. We validated the effectiveness of DynaCon through an experiment where a robot successfully navigated to its goal using reasoning. Source code and experiment videos for this work can be found at: https://sites.google.com/view/dynacon.Comment: Submitted to ICRA 202