New Brownian bridge construction in quasi-Monte Carlo methods for computational finance

AbstractQuasi-Monte Carlo (QMC) methods have been playing an important role for high-dimensional problems in computational finance. Several techniques, such as the Brownian bridge (BB) and the principal component analysis, are often used in QMC as possible ways to improve the performance of QMC. This paper proposes a new BB construction, which enjoys some interesting properties that appear useful in QMC methods. The basic idea is to choose the new step of a Brownian path in a certain criterion such that it maximizes the variance explained by the new variable while holding all previously chosen steps fixed. It turns out that using this new construction, the first few variables are more “important” (in the sense of explained variance) than those in the ordinary BB construction, while the cost of the generation is still linear in dimension. We present empirical studies of the proposed algorithm for pricing high-dimensional Asian options and American options, and demonstrate the usefulness of the new BB

Why do nonlinearities matter? The repercussions of linear assumptions on the dynamic behaviour of assemble-to-order systems

The hybrid assembly-to-order (ATO) supply chain, combining make-to-stock and make-to-order (MTS-MTO) production, separated by a customer order decoupling point (CODP), is well recognised in many sectors. Based on the well-established Inventory and Order Based Production Control Systems (the IOBPCS family), we develop a hybrid ATO system dynamics model and analytically study the impact of nonlinearities on its dynamic performance. Nonlinearities play an important, sometimes even a dominant, role in influencing the dynamic performance of supply chain systems. However, most IOBPCS based analytical studies assume supply chain systems are completely linear and thereby greatly limit the applicability of published results, making it difficult to fully explain and describe oscillations caused by internal factors. We address this gap by analytically exploring the non-negative order and capacity constraint nonlinearities present in an ATO system. By adopting nonlinear control engineering and simulation approaches, we reveal that, depending on the mean and amplitude of the demand, the non-negative order and capacity constraints in the ATO system may occur and their significant impact on system dynamics performance should be carefully considered. Failing to monitor non-negative order constraints may underestimate the mean level of inventory and overestimate the inventory recovery speed. Sub-assemblers may suffer increased inventory cost (i.e. the consequence of varying inventory levels and recovery speed) if capacity and non-negative order constraints are not considered at their production site. Future research should consider the optimal trade-off design between CODP inventory and capacity and the exploration of delivery lead-time dynamics

Automated 3D weaving continuous natural fibre and optimising harakeke fibre characterisation : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University, Albany, New Zealand

Some possibly copyrighted Figures remain for the sake of clarity.This research investigated the design and implementation of a continuous natural fibre filament winding robot for modern artistic and structural architectural design. The idea of a new architectural construction technique based on Arduino integration was inspired by the underwater nesting structure of water spiders. It consists of the motion component, a 3-axis sliding table with limit switches, the construction of the machine, the programming and testing of the resulting microcomputer software through to a robot manufacturing process. This was based on Arduino’s new integrated development environment. In addition, the intelligent programming mode forms the preconceived pattern through winding, producing a model with unique architectural quality, and at the same time, making a structure with superior material efficiency. In terms of hardware design, the first conceptual model focused on using an open-source integrated development environment (IDE) that could be easily configured. Arduino hardware was the primary microcontroller of choice for simplicity and ease of hardware integration and software development. Stepper motor drivers are used to control the three stepper motors to accurately move the fibre feeding mechanism on the sliding table into position. The path of the sliding table is controlled by the controller, and the machine can make forward, backward, wire feed and other movements according to the programmed commands. The developed system automatically weaves and feeds natural fibre into the desired structure. The resulting lightweight natural fibre material forms a model with unique architectural quality. The results show that the model is of great value and significance, and it can be used to make the required structure with the desired natural fibre. Additionally, to establish the feasibility of future work focusing on harakeke fibre development in design and construction, the tensile strength of native New Zealand flax fibre (harakeke fibre) was evaluated with a view for use in these load bearing and architectural design applications. Single filament fibres were selected in batches and tensile tested. The longitudinal strength of specimens was established, and the mechanical properties of the fibres were summarised. Comparison of these attributes with existing data was used to determine if the harakeke fibre can be applied usefully in the construction industry. This research is based on the novel concept of architectural design in the construction industry using 3D weaving with natural fibres, in particular harakeke fibres. To achieve this, several related topics are under investigation, such as the need to design an improved feeding system (including hardware and software control), impregnation of fibre and resin (epoxy and polyester) to make preimpregnated (prepreg) fibre/resin filament, adaptive controlled programme and hardware for the required architecture and structure, and properties testing and characterisation. This project is one of the first attempts to develop an automated robot arm system combined with new material, in this case harakeke fibre, and has made a valuable contribution to this field of research

System dynamics modelling, analysis and design of assemble-to-order supply chains

Background and purpose: The assemble-to-order supply chains (ATO) is commonly-adopted in personal computer (PC) and semiconductor industries. However, the system dynamics of PC and semiconductor ATO systems, one of the main sources of disruption, is not well-explored. Thereby this thesis aims to 1) develop a nonlinear system dynamics model to represent the real-world PC and semiconductor ATO systems, 2) explore the underlying mechanisms of ATO system dynamics in the nonlinear environment and 3) assess the delivery lead times dynamics, along with bullwhip and inventory variance. Design/methods: Regarding the semiconductor industry, the Intel nonlinear ATO system dynamics model, is used as a base framework to study the underlying causes of system dynamics. The well-established Inventory and Order based Production Control System archetypes, or the IOBPCS family, are used as the benchmark models. Also, the IOBPCS family is used to develop the PC ATO system dynamics model. Control engineering theory, including linear (time and frequency response techniques) and nonlinear control (describing function, small perturbation theory) approaches, are exploited in the dynamic analysis. Furthermore, system dynamics simulation is undertaken for cross-checking results and experimentation. Findings: The ATO system can be modelled as a pull (order driven) and a push (forecasting driven) systems connected by the customer order decoupling point (CODP). A framework for dynamic performance assessment termed as the ‘performance triangle’, including customer order delivery lead times, CODP inventory and bullwhip (capacity variance), is developed. The dynamic analysis shows that, depending on the availability of CODP Abstract iii inventory, the hybrid ATO system state can be switched to the pure push state, creating poor delivery lead times dynamics and stock-out issues. Limitations: This study is limited to the analysis of a closely-coupled two-echelon ATO systems in PC and semiconductor industries. Also, the optimization of control policies is not considered. Practical implications: Maintaining a truly ATO system state is important for both customer service level and low supply chain dynamics cost, although the trade-off control design between CODP inventory and capacity variance should be considered. Demand characteristics, including variance and mean, play an important role in triggering the nonlinearities present in the ATO system, leading to significant change in the average level of inventory and the overall transient performance. Originality / value: This study developed system dynamics models of the ATO system and explored its dynamic performance within the context of PC and semiconductor industries. The main nonlinearities present in the ATO system, including capacity, non-negative order and CODP inventory constraints, are investigated. Furthermore, a methodological contribution has been provided, including the simplification of the high-order nonlinear model and the linearization of nonlinearities present in the ATO system, enhancing the understanding of the system dynamics and actual transient responses. The ‘performance triangle’ analysis is also a significant contribution as past analytical studies have neglected customer order lead time variance as an inclusive metric

Sentiment Analysis and Political Party Classification in 2016 U.S. President Debates in Twitter

We introduce a framework of combining tweet sentiment analysis with available default user profiles to classify political party of users who posted tweets in 2016 U.S. president debates. The main works focus on extracting event-related information in short event period instead of collecting tweets in a long-time period as most previous works do. Our framework is not limited in debate event, it can be used by researchers to build rationale of other events study. In sentiment analysis, we show that all three Naïve Bayes classifiers with different distributions obtain accuracy above 75% and the results reveal positive tweets most likely follow Gaussian or Multinomial distributions while negative tweets most likely follow Bernoulli distribution in our training data. We also show that under unbalanced sparse term document setting, instead of using “Add-1” parameter, tuning Laplace smoothing parameter to adjust the weights of new terms in a tweet can help improve the classifier’s performance in targeted direction. Finally, we show sentiment might help classifying political part

Generating realistic stock market order streams

We propose an approach to generate realistic and high-fidelity stock market data based on generative adversarial networks (GANs). Our Stock-GAN model employs a conditional Wasserstein GAN to capture history dependence of orders. The generator design includes specially crafted aspects including components that approximate the market's auction mechanism, augmenting the order history with order-book constructions to improve the generation task. We perform an ablation study to verify the usefulness of aspects of our network structure. We provide a mathematical characterization of distribution learned by the generator. We also propose statistics to measure the quality of generated orders. We test our approach with synthetic and actual market data, compare to many baseline generative models, and find the generated data to be close to real data