Identification des régimes et regroupement des séquences pour la prévision des marchés financiers

Abstract : Regime switching analysis is extensively advocated to capture complex behaviors underlying financial time series for market prediction. Two main disadvantages in current approaches of regime identification are raised in the literature: 1) the lack of a mechanism for identifying regimes dynamically, restricting them to switching among a fixed set of regimes with a static transition probability matrix; 2) failure to utilize cross-sectional regime dependencies among time series, since not all the time series are synchronized to the same regime. As the numerical time series can be symbolized into categorical sequences, a third issue raises: 3) the lack of a meaningful and effective measure of the similarity between chronological dependent categorical values, in order to identify sequence clusters that could serve as regimes for market forecasting. In this thesis, we propose a dynamic regime identification model that can identify regimes dynamically with a time-varying transition probability, to address the first issue. For the second issue, we propose a cluster-based regime identification model to account for the cross-sectional regime dependencies underlying financial time series for market forecasting. For the last issue, we develop a dynamic order Markov model, making use of information underlying frequent consecutive patterns and sparse patterns, to identify the clusters that could serve as regimes identified on categorized financial time series. Experiments on synthetic and real-world datasets show that our two regime models show good performance on both regime identification and forecasting, while our dynamic order Markov clustering model also demonstrates good performance on identifying clusters from categorical sequences.L'analyse de changement de régime est largement préconisée pour capturer les comportements complexes sous-jacents aux séries chronologiques financières pour la prédiction du marché. Deux principaux problèmes des approches actuelles d'identifica-tion de régime sont soulevés dans la littérature. Il s’agit de: 1) l'absence d'un mécanisme d'identification dynamique des régimes. Ceci limite la commutation entre un ensemble fixe de régimes avec une matrice de probabilité de transition statique; 2) l’incapacité à utiliser les dépendances transversales des régimes entre les séries chronologiques, car toutes les séries chronologiques ne sont pas synchronisées sur le même régime. Étant donné que les séries temporelles numériques peuvent être symbolisées en séquences catégorielles, un troisième problème se pose: 3) l'absence d'une mesure significative et efficace de la similarité entre les séries chronologiques dépendant des valeurs catégorielles pour identifier les clusters de séquences qui pourraient servir de régimes de prévision du marché. Dans cette thèse, nous proposons un modèle d'identification de régime dynamique qui identifie dynamiquement des régimes avec une probabilité de transition variable dans le temps afin de répondre au premier problème. Ensuite, pour adresser le deuxième problème, nous proposons un modèle d'identification de régime basé sur les clusters. Notre modèle considère les dépendances transversales des régimes sous-jacents aux séries chronologiques financières avant d’effectuer la prévision du marché. Pour terminer, nous abordons le troisième problème en développant un modèle de Markov d'ordre dynamique, en utilisant les informations sous-jacentes aux motifs consécutifs fréquents et aux motifs clairsemés, pour identifier les clusters qui peuvent servir de régimes identifiés sur des séries chronologiques financières catégorisées. Nous avons mené des expériences sur des ensembles de données synthétiques et du monde réel. Nous démontrons que nos deux modèles de régime présentent de bonnes performances à la fois en termes d'identification et de prévision de régime, et notre modèle de clustering de Markov d'ordre dynamique produit également de bonnes performances dans l'identification de clusters à partir de séquences catégorielles

Trough-silicon-via inductor: Is it real or just a fantasy?

Through-silicon-vias (TSVs) can potentially be used to implement inductors in three-dimensional (3D) integrated system for minimal footprint and large inductance. However, different from conventional 2D spiral inductor, TSV inductors are buried in lossy substrate, thus suffering from low quality factors. This thesis presents how various process and design parameters affect their performance. A few interesting phenomena that are unique to TSV inductors are observed. We then proposed a novel shield mechanism utilizing the micro-channel, a technique conventionally used for heat removal, to reduce the substrate loss. The technique increases the quality factor and inductance of the TSV inductor by up to 21x and 17x respectively. It enables us to implement TSV inductors of up to 38x smaller area and 33% higher quality factor, compared with spiral inductors of the same inductance. To the best of the authors\u27 knowledge, this is the very first in-depth study on TSV inductors. We hope our study shall point out a new and exciting research direction for 3D IC designers --Abstract, page iii

Independent modal variable structure fuzzy active vibration control of thin plates laminated with photostrictive actuators

AbstractPhotostrictive actuators can produce photodeformation strains under illumination of ultraviolet lights. They can realize non-contact micro-actuation and vibration control for elastic plate structures. Considering the switching actuation and nonlinear dynamic characteristics of photostrictive actuators, a variable structure fuzzy active control scheme is presented to control the light intensity applied to the actuators. Firstly, independent modal vibration control equations of photoelectric laminated plates are established based on modal analysis techniques. Then, the optimal light switching function is derived to increase the range of sliding modal area, and the light intensity self-adjusting fuzzy active controller is designed. Meanwhile, a continuous function is applied to replace a sign function to reduce the variable structure control (VSC) chattering. Finally, numerical simulation is carried out, and simulation results indicate that the proposed control strategy provides better performance and control effect to plate actuation and control than velocity feedback control, and suppresses vibration effectively

Achieving Least Relocation of Existing Facilities in Spatial Optimisation: A Bi-Objective Model (Short Paper)

Spatial optimisation models have been widely used to support locational decision making of public service systems (e.g. hospitals, fire stations), such as selecting the optimal locations to maximise the coverage. These service systems are generally the product of long-term evolution, and there usually are existing facilities in the system. These existing facilities should not be neglected or relocated without careful consideration as they have financial or management implications. However, spatial optimisation models that account for the relocation or maintenance of existing facilities are understudied. In this study, we revisit a planning scenario where two objectives are adopted, including the minimum number of sites selected and the least relocation of existing facilities. We propose and discuss three different approaches that can achieve these two objectives. This model and the three approaches are applied to two case studies of optimising the retail stores in San Francisco and the large-scale COVID-19 vaccination network in England. The implications of this model and the efficiency of these approaches are discussed

An Algorithm Combining Statistics-based and Rules-based for Chunk Identification of Chinese Sentences

PACLIC 20 / Wuhan, China / 1-3 November, 200

An Anonymous System Based on Random Virtual Proxy Mutation

Anonymous systems are usually used to protect users\u27 privacy in network communication. However, even in the low-latency Tor system, it is accompanied by network communication performance degradation, which makes users have to give up using the anonymity system in many applications. Therefore, we propose a novel anonymity system with rotated multi-path accompanying virtual proxy mutation for data transmission. Unlike onion routing, in our system the randomly generated virtual proxies take over the address isolation executing directly on the network layer and expand the anonymity space to all terminals in the network. With the optimal algorithm of selecting the path, the network communication performance improved significantly also. The verification experiments show that the anonymity system terminal sends and receives data at 500 kbps, and only a slight delay jitter occurs at the receiving end, and the other network performance is not significantly reduced