Готові списки джерел за темами / Trading automatisé

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Добірка наукової літератури з теми "Trading automatisé"

Автор: Grafiati

Опубліковано: 20 квітня 2024

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Статті в журналах з теми "Trading automatisé"

Oetama, Raymond Sunardi, and Raymond Sunardi Oetama. "DEVELOPING SALES FORCE AUTOMATION PROTOTYPE AT INDONESIAN FURNITURE TRADING COMPANY." IJISCS (International Journal of Information System and Computer Science) 7, no. 3 (October 10, 2023): 182. http://dx.doi.org/10.56327/ijiscs.v7i3.1537.

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Information technology plays a crucial role in enhancing company performance and driving business growth. Maintaining good customer relationships is essential, and Customer Relationship Management focuses on building customer commitment. Sales Force Automation systems automate sales processes and manage customer interactions. PT. Maju Jaya Kreasindo, a furniture company in East Jakarta, aims to automate its sales force and centralize operational information through a web-based Sales Force Automation system using Electronic Customer Relationship Management. The research adopts the "Prototyping" method, offering a shorter development duration and flexible implementation. Visual Studio Code and Xampp, along with PHP and MySQL, are utilized as development tools. The result is a Sales Force Automation system based on Electronic Customer Relationship Management that assists PT. Maju Jaya Kreasindo in automating its sales force. The design successfully automates tasks, supported by Electronic Customer Relationships and the prototyping method. The Sales Force Automation system passed the functionality evaluation, achieving high user acceptance test scores, and indicating its effectiveness in meeting user requirements.

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Al-Sulaiman, Talal. "Review of Recent Research Directions and Practical Implementation of Low-Frequency Algorithmic Trading." American Journal of Financial Technology and Innovation 2, no. 1 (February 26, 2024): 1–14. http://dx.doi.org/10.54536/ajfti.v2i1.2354.

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Financial trading has undergone substantial technological evolution, with automation taking center stage, leading to approximately 80% of US market trades being executed by computer systems, predominantly by large financial institutions. The rise of algorithmic trading, poised to engage smaller entities, international markets, and individual traders, drives this article’s exploration of research in this field. Providing a comprehensive overview, it outlines the evolution of trading practices and defines algorithmic trading as a computer-powered tool aiding investment decisions. The article details the steps involved in algorithmic trading, covering opportunity identification, quantitative research, implementation, testing phases, and continuous monitoring. It also examines prevalent programming languages and open-source platforms facilitating algorithm development. Focusing on trading frequencies across financial instruments, it delves into high-frequency trading as a subset, alongside methodologies like technical and fundamental analysis, time series analysis, option trading strategies, and machine learning techniques used in algorithm creation. Categorized by trading frequencies, analytical approaches, involved financial instruments, and analysis objectives, the reviewed papers contribute insights into algorithmic trading’s diverse landscape and methodologies, offering valuable perspectives for industry participants and researchers alike.

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Li, Yeti, Catherine Burns, and Rui Hu. "Representing Stages and Levels of Automation on a Decision Ladder." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 328–32. http://dx.doi.org/10.1177/1541931213601074.

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We propose that representing stages and levels of automation on a decision ladder (DL) could help to identify information requirements for designing automation interfaces. We look at automated financial trading systems, a domain with variable degrees of automation (DOA). We give examples of modelling a financial trading task for two DOAs: basket trading (a low DOA) and trend following trading (a high DOA). On the resulting DLs, both human and automated information-processing activities are presented. The steps and states of knowledge allocated to automation are first categorized by the commonly known four stages of automation, and then shaded to represent the level of automation in each stage. This work advances the understanding of automated trading, and automation in general, and may provide a deeper representation of human-automation interactions and thus better understanding of design requirements.

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Maciel, Leandro, and Rosangela Ballini. "Efeitos do pregão eletrônico sobre a eficiência e a volatilidade condicional no mercado de ações brasileiro." Brazilian Review of Finance 17, no. 1 (October 15, 2019): 80. http://dx.doi.org/10.12660/rbfin.v17n1.2019.76684.

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<p>Stock exchange automation, characterized by the replacement of floor trading systems by electronic trading systems, is one of the main restructuring processes observed in global capital markets in recent decades. This paper investigates the effects of automation in the São Paulo Stock Exchange (B3), which adopted an electronic trading system in October 2005. Empirical analysis of the Bovespa index rejects the random walk hypothesis for the periods before and after B3 automation, and provides evidence of distinct volatility regimes. After automation, there is an increase in the linear dependence of IBovespa returns, suggesting a negative effect of automation on the Brazilian stock market’s efficiency. On the other hand, in the same period, there is evidence for a reduction in the long-term persistence of conditional volatility, in response to shocks to returns.</p>

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Tzelgov, Joseph. "Trading automatic/nonautomatic for unconscious/conscious." Behavioral and Brain Sciences 25, no. 3 (June 2002): 356–57. http://dx.doi.org/10.1017/s0140525x02500066.

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In this commentary I show that the SOC framework implies automaticity of both the materialization of phenomenological conscious experience and the application of the primitives resulting from the emergence of consciousness. In addition, SOC implies that cognition refers to conscious experience. Consequently, I propose automatic/nonautomatic instead of unconscious/conscious as the basic contrast characterizing human cognition.

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Kazantsev, Dmitry A., and Natalya A. Mikhaleva. "PROCUREMENT AUTOMATION AS THE FUTURE OF THE CONTRACT SYSTEM." RUDN Journal of Law 24, no. 1 (December 15, 2020): 137–57. http://dx.doi.org/10.22363/2313-2337-2020-24-1-137-157.

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In the era of digital information electronic trading platforms have become an integral attribute to conduct procurement to meet public needs. Nowadays there is a consistent trend is that legislators transfer the vast majority of purchases to the electronic plane through the use of electronic trading platforms. This incentive of the legislator is attributed to a number of advantages of the electronic form of procurement procedures, which allow to increase their transparency and accessibility to an indefinite number of people. However, the role of electronic trading platforms must not be reduced solely to an electronic platform, which allows only to transfer the procurement procedure in a different form. On the contrary, the potential of electronic trading platforms can significantly simplify and automate business activities of customers, increase the efficiency of procurement not only by expanding competition but also by reducing the organizational burden on the parties of the procurement process, both customers and the participants. The purpose of the article is to present for review ways to improve the operation of electronic trading floors to automate the procurement process during competitive procedures for state and municipal needs. Research methods: formal legal, modeling, analysis and synthesis, induction and deduction. The results of the study. The article presents for review ways to optimize the operation of electronic trading platforms by attracting software and hardware when conducting competitive procedures. Ways of automation the procurement process are described, including integration of the functionality of electronic trading platforms with official registries in order to minimize the risk of a possible rejection of a participant’s procurement application when considering the second parts of applications. Other innovative services of the functionality of electronic trading platforms (auto-completion of forms, data inheritance, automated collection of proposals) have been suggested, the implementation of which will simplify and automate the process of conducting competitive procedures, reduce the administrative burden on the customer, ensure transparency and a competitive basis when holding tenders.

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Tkachenko, Olexandr, Mykyta Kutsenko, and Hlib Fleshner. "RODOFEBISU – Trading Support System." Digital Platform: Information Technologies in Sociocultural Sphere 5, no. 2 (December 27, 2022): 387–400. http://dx.doi.org/10.31866/2617-796x.5.2.2022.270145.

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Анотація:

The purpose of the article is to study, analyze and consider the general problems and prospects of developing software for trading RodOfEbisu with the possibility of automated trading based on a recommendation algorithm. The research methods are the basic methodologies and algorithms for successful trading. The article considers approaches to the development and operation of software for automated trading. The novelty of the research is the analysis of modern trading methods in different markets, the results of which can be used in the development of its own trading automation product, which is an assistant and, possibly, can become an independent unit. Conclusions. The paper investigates the existing views on the modern approach to decision-making and buying, which can be used to develop its own product – a trader’s assistant. Taking into account the results of the analysis, it was decided to develop software for trading RodOfEbisu, which can act as an advisor and executor, with the possibility of using different trading strategies.

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INAGAKI, Toshiyuki. "Adaptive Automation: Sharing and Trading of Control." Proceedings of the Transportation and Logistics Conference 2001.10 (2001): 79–84. http://dx.doi.org/10.1299/jsmetld.2001.10.79.

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Kim, Jin-Gyeom, and Bowon Lee. "Automatic P2P Energy Trading Model Based on Reinforcement Learning Using Long Short-Term Delayed Reward." Energies 13, no. 20 (October 14, 2020): 5359. http://dx.doi.org/10.3390/en13205359.

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Automatic peer-to-peer energy trading can be defined as a Markov decision process and designed using deep reinforcement learning. We consider prosumer as an entity that consumes and produces electric energy with an energy storage system, and define the prosumer’s objective as maximizing the profit through participation in peer-to-peer energy trading, similar to that of the agents in stock trading. In this paper, we propose an automatic peer-to-peer energy trading model by adopting a deep Q-network-based automatic trading algorithm originally designed for stock trading. Unlike in stock trading, the assets held by a prosumer may change owing to factors such as the consumption and generation of energy by the prosumer in addition to the changes from trading activities. Therefore, we propose a new trading evaluation criterion that considers these factors by defining profit as the sum of the gains from four components: electricity bill, trading, electric energy stored in the energy storage system, and virtual loss. For the proposed automatic peer-to-peer energy trading algorithm, we adopt a long-term delayed reward method that evaluates the delayed reward that occurs once per month by generating the termination point of an episode at each month and propose a long short-term delayed reward method that compensates for the issue with the long-term delayed reward method having only a single evaluation per month. This long short-term delayed reward method enables effective learning of the monthly long-term trading patterns and the short-term trading patterns at the same time, leading to a better trading strategy. The experimental results showed that the long short-term delayed reward method-based energy trading model achieves higher profits every month both in the progressive and fixed rate systems throughout the year and that prosumer participating in the trading not only earns profits every month but also reduces loss from over-generation of electric energy in the case of South Korea. Further experiments with various progressive rate systems of Japan, Taiwan, and the United States as well as in different prosumer environments indicate the general applicability of the proposed method.

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Plotnikov, Arkadiy P., Victor P. Glazkov, and Roman A. Shishlov. "Modification of long-term volatility trading methods based on a delta-neutral strategy." Vestnik of Samara University. Economics and Management 12, no. 3 (November 25, 2021): 70–79. http://dx.doi.org/10.18287/2542-0461-2021-12-3-70-79.

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Анотація:

Delta-neutral trading strategies for trading volatility allow you to make a profit regardless of the direction of change in the price of the underlying asset. Despite their popularity and high efficiency, they are usually made manually, which makes them less systematic and vulnerable to the negative influence of the human factor (emotions, late actions, erroneous submission of applications, etc.). The article proposes a unified delta- neutral strategy, taking into account several parameters for long-term volatility trading through transactions with underlying assets (futures or stocks) and options on these underlying assets, which creates prerequisites for its automation. The use of the strategy helps to increase the liquidity of investment assets traded on the exchange, increases the receipt of taxes, exchange fees and commissions, which brings great socio-economic benefits. Automation of the strategy significantly simplifies calculations, increases the speed of decision-making and can significantly increase the number of transactions made in the financial markets. In addition, the automatic calculation of the optimal values of the method parameters can make a significant contribution to the theoretical research of the modifications of the volatility trading methods.

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Більше джерел

Дисертації з теми "Trading automatisé"

Tran, Trung-Minh. "Contributions to Agent-Based Modeling and Its Application in Financial Market." Electronic Thesis or Diss., Université Paris sciences et lettres, 2023. http://www.theses.fr/2023UPSLP022.

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L'analyse de modèles complexes tels que les marchés financiers aide les gestionnaires à élaborer des politiques raisonnables et les commerçants à choisir des stratégies de négociation efficaces. La modélisation basée sur les agents est une méthodologie de calcul pour modéliser des systèmes complexes et analyser l'influence de différentes hypothèses sur les comportements des agents. Dans le cadre de cette thèse, nous considérons un modèle de marché financier qui comprend 3 types d'agents : les agents techniques, les agents fondamentaux et les agents de bruit. Nous commençons par l'agent technique avec le défi d'optimiser une stratégie de trading basée sur l'analyse technique à travers un système de trading automatisé. Ensuite, les méthodes d'optimisation proposées sont appliquées avec des fonctions objectives appropriées pour optimiser les paramètres du modèle ABM. L'étude a été menée avec un modèle ABM simple incluant uniquement des agents de bruit, puis le modèle a été étendu pour inclure différents types d'agents. La première partie de la thèse étudie le comportement commercial des agents techniques. Différentes approches sont introduites telles que : l'algorithme génétique, l'optimisation bayésienne et l'apprentissage par renforcement profond. Les stratégies de trading sont construites sur la base d'un indicateur avancé, Relative Strength Index, et de deux indicateurs retardés, Bollinger Band et Moving Average Convergence-Divergence. De multiples expériences sont réalisées sur différents marchés, notamment : le marché des crypto-monnaies, le marché boursier et le marché des contrats à terme cryptographiques. Les résultats montrent que les stratégies optimisées à partir des approches proposées peuvent générer des rendements plus élevés que leur forme typique et la stratégie Buy and Hold. En utilisant les résultats de l'optimisation des stratégies de trading, nous proposons une nouvelle approche pour optimiser les paramètres du modèle à base d'agents. La deuxième partie de la thèse présente une application de la modélisation multiagents au marché boursier. En conséquence, nous avons montré que les modèles ABM peuvent être optimisés en utilisant la méthode d'optimisation bayésienne avec plusieurs fonctions objectives. Les faits stylisés du marché réel peuvent être reproduits en construisant soigneusement les fonctions objectives de l'agent. Notre travail comprend le développement d'un environnement, les comportements des différents agents et leurs interactions. La méthode d'optimisation bayésienne avec le test de Kolmogorov-Smirnov comme fonction objective a montré des avantages et un potentiel dans l'estimation d'un ensemble optimal de paramètres pour un modèle de marché financier artificiel. Le modèle que nous proposons est capable de reproduire les faits stylisés du marché réel. En outre, un nouveau fait stylisé sur la proportion de commerçants sur le marché est présenté. Avec les données empiriques de l'indice Dow Jones Industrial Average, nous avons constaté que les traders fondamentaux représentent 9%-11% de tous les traders du marché boursier. À l'avenir, davantage de recherches seront menées pour améliorer le modèle et les méthodes d'optimisation, telles que l'application de modèles d'apprentissage automatique, l'apprentissage par renforcement multiagents ou l'examen de l'application sur différents marchés et instruments négociés
The analysis of complex models such as financial markets helps managers to make reasonable policies and traders to choose effective trading strategies. Agent-based modeling is a computational methodology to model complex systems and analyze the influence of different assumptions on the behaviors of agents. In the scope of this thesis, we consider a financial market model that includes 3 types of agent: technical agents, fundamental agents and noise agents. We start with the technical agent with the challenge of optimizing a trading strategy based on technical analysis through an automated trading system. Then, the proposed optimization methods are applied with suitable objective functions to optimize the parameters for the ABM model. The study was conducted with a simple ABM model including only noise agents, then the model was extended to include different types of agents. The first part of the thesis investigates the trading behavior of technical agents. Different approaches are introduced such as: Genetic Algorithm, Bayesian Optimization and Deep Reinforcement Learning. The trading strategies are built based on a leading indicator, Relative Strength Index, and two lagging indicators, Bollinger Band and Moving Average Convergence-Divergence. Multiple experiments are performed in different markets including: cryptocurrency market, stock market and crypto futures market. The results show that optimized strategies from proposed approaches can generate higher returns than their typical form and Buy and Hold strategy. Using the results from the optimization of trading strategies, we propose a new approach to optimize the parameters of the agent-based model. The second part of the thesis presents an application of agent-based modeling to the stock market. As a result, we have shown that ABM models can be optimized using the Bayesian Optimization method with multiple objective functions. The stylized facts of the actual market can be reproduced by carefully constructing the objective functions of the agent. Our work includes the development of an environment, the behaviors of different agents and their interactions. Bayesian optimization method with Kolmogorov-Smirnov test as objective function has shown advantages and potential in estimating an optimal set of parameters for an artificial financial market model. The model we propose is capable of reproducing the stylized facts of the real market. Furthermore, a new stylized fact about the proportion of traders in the market is presented. With empirical data of the Dow Jones Industrial Average index, we found that fundamental traders account for 9%-11% of all traders in the stock market. In the future, more research will be done to improve the model and optimization methods, such as applying machine learning models, multi-agent reinforcement learning or considering the application in different markets and traded instruments

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Larsen, Fredrik. "Automatic stock market trading based on Technical Analysis." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8707.

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The theory of technical analysis suggests that future stock price developement can be foretold by analyzing historical price fluctuations and identifying repetitive patterns. A computerized system, able to produce trade recommendations based on different aspects of this theory, has been implemented. The system utilizes trading agents, trained using machine learning techniques, capable of producing unified buy and sell signals. It has been evaluated using actual trade data from the Oslo Børs stock exchange over the period 1999-2006. Compared to the simple strategy of buying and holding, some of the agents have proven to yield good results, both during years with extremely good stock market returns, as well as during times of recession. In spite of the positive performance, anomalous results do exist and call for cautionous use of the system’s recommendations. Combining them with fundamental analysis appears to be a safe approach to achieve succesful stock market trading.

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Sauer, Václav. "Tvorba obchodní strategie pro měnový trh." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318623.

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This thesis deals with the design, implementation and optimization of the automated trading system for the foreign exchange market. Thesis analyses theoretical aspects for the system implementation, including introduction of foreign exchange market, types of market analysis, money management, risk management and technical indicators. The thesis further describes, what is required for development of such system and what important parts the system must contain. The work also describes how the system can be tested and optimised based on historical data.

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Raykhel, Ilya. "Real-time automatic price prediction for eBay online trading /." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2697.pdf.

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Raykhel, Ilya Igorevitch. "Real-Time Automatic Price Prediction for eBay Online Trading." BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1631.

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Анотація:

While Machine Learning is one of the most popular research areas in Computer Science, there are still only a few deployed applications intended for use by the general public. We have developed an exemplary application that can be directly applied to eBay trading. Our system predicts how much an item would sell for on eBay based on that item's attributes. We ran our experiments on the eBay laptop category, with prior trades used as training data. The system implements a feature-weighted k-Nearest Neighbor algorithm, using genetic algorithms to determine feature weights. Our results demonstrate an average prediction error of 16%; we have also shown that this application greatly reduces the time a reseller would need to spend on trading activities, since the bulk of market research is now done automatically with the help of the learned model.

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Trnik, Erik. "Návrh a optimalizace automatického obchodního systému pro forex." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318583.

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Анотація:

The master's thesis deals with the design of the proposed automatic trading system especially for daily trading on the currency markets. The aim of the thesis is to create a complex theoretical basis, in the practical part of the work to use the knowledge to create a suitable automatic trading system. The thesis focuses on the technical analysis of the currency markets. The proposed system will be optimally optimized to maximize profitability and stability with application to the most liquid currency pairs.

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Parro, Mattia <1991&gt. "Analisi tecnica e trading systems - sviluppo di un sistema di trading automatico basato sulla conformazione grafica a bandiera." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/18525.

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Анотація:

Trasformazione di una formazione grafica dei prezzi, la conformazione a bandiera, in un trading system automatizzato. Analisi dei risultati e confronto dei rendimenti con la strategia di investimento basata sul buy&hold

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PINTO, THIAGO REZENDE. "APPLICATION OF NONLINEAR MODELS FOR AUTOMATIC TRADING IN THE BRAZILIAN STOCK MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9141@1.

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Анотація:

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Esta dissertação tem por objetivo comparar o desempenho de modelos não lineares de previsão de retornos em 10 ativos do mercado acionário brasileiro. Entre os modelos escolhidos, pode-se citar o STAR-Tree, que combina conceitos da metodologia STAR (Smooth Transition AutoRegression) e do algoritmo CART (Classification And Regression Trees), tendo como resultado final uma regressão com transição suave entre múltiplos regimes. A especificação do modelo é feita através de testes de hipótese do tipo Multiplicador de Lagrange que indicam o nó a ser dividido e a variável explicativa correspondente. A estimação dos parâmetros é feita pelo método de Mínimos Quadrados Não Lineares para determinar o valor dos parâmetros lineares e não lineares. Redes Neurais, modelos ARMAX (estes lineares) e ainda o método Naive também foram incluídos na análise. Os resultados das previsões foram avaliados a partir de medidas estatísticas e financeiras e se basearam em um negociador automático que informa o instante correto de assumir uma posição comprada ou vendida em cada ativo. Os melhores desempenhos foram alcançados pelas Redes Neurais, pelos modelos ARMAX e pela forma de previsão ARC (Adaptative Regime Combination) derivada da metodologia STAR-Tree, sendo ambos ainda superiores ao retorno das ações durante o período de teste
The goal of this dissertation is to compare the performance of non linear models to forecast return on 10 equities in the Brazilian Stock Market. Among the chosen ones, it can be cited the STAR-Tree, which matches concepts from the STAR (Smooth Transition AutoRegression) methodology and the CART (Classification And Regression Trees) algorithm, having as the resultant structure a regression with smooth transition among multiple regimes. The model specification is done by Lagrange Multiplier hypothesis tests that indicate the node to be splitted and the corresponding explanatory variable. The parameter estimation is done by the Non Linear Least Squares method that determine the linear and non linear parameters. Neural Netwoks, ARMAX models (these ones linear) and the Naive method were also included in the analysis. The forecasting results were calculated using statistical and financial measures and were based on an automatic negociator that signaled the right instant to take a short or a long position in each stock. The best results were reached by the Neural Networks, ARMAX models and ARC (Adaptative Regime Combination ) forecasting method derived from STAR-Tree, with all of them performing better then the equity return during the test period.

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EPPRECHT, CAMILA ROSA. "MEAN AND REALIZED VOLATILITY SMOOTH TRANSITION MODELS APPLIED TO RETURN FORECASTING AND AUTOMATIC TRADING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13209@1.

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Анотація:

COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
O principal objetivo desta dissertação é comparar o desempenho de modelos lineares e não-lineares de previsão de retornos de 23 ativos do mercado acionário americano. Propõe-se o modelo STAR-Tree Heterocedástico, que faz uso da metodologia do STAR-Tree (Smooth Transition AutoRegression Tree) aplicada a séries temporais heterocedásticas. Com a disponibilidade de dados de retorno e da volatilidade realizada de ações intra-diários, as séries de retornos são transformadas através da divisão de cada retorno pela sua volatilidade realizada. A série transformada apresenta variância constante. O modelo é uma combinação da metodologia STAR (Smooth Transition AutoRegression) e do algoritmo CART (Classification and Regression Tree). O modelo resultante pode ser interpretado como uma regressão de múltiplos regimes com transição suave. A especificação do modelo é feita através de testes de Multiplicadores de Lagrange, que indicam o nó a ser dividido e a variável de transição correspondente. Os modelos de comparação usados são o modelo Média, o método Naive, modelos lineares ARX e Redes Neurais. As previsões dos modelos foram avaliadas através de medidas estatísticas e financeiras. Os resultados financeiros baseam-se em uma regra de negociação automática que informa o momento de comprar e vender cada ativo. O modelo STAR-Tree Heterocedástico teve resultados estatísticos equivalentes aos dos outros modelos, porém apresentou um desempenho financeiro superior para a maioria das séries. A volatilidade realizada também foi estimada usando a metodologia STAR-Tree, e sua previsão foi utilizada para fazer uma análise de alavancagem financeira.
The main goal of this dissertation is to compare the performance of linear and nonlinear models to forecast 23 assets of the American Stocks Market. The Heteroscedastic STAR-Tree Model is proposed using the STAR- Tree (Smooth Transition AutoRegression Tree) methodology applied to heteroscedastic time series. As assets returns and realized volatility intraday data are available, the returns series are transformed by dividing each return by its realized volatility, which gives homocedastic series. The model is a combination of the STAR (Smooth Transition AutoRegression) methodology and the CART (Classification and Regression Tree) algorithm. The resulting model can be interpreted as a smooth transition multiple regime regression. The model specification is done by Lagrange Multiplier tests that indicate the node to be split and the corresponding transition variable. The comparison models used are the Mean model, Naive method, ARX linear models and Neural Networks. The forecasting models were evaluated through statistical and financial measures. The financial results are based on an automatic trading rule that signals buy and hold moments in each stock. The Heteroscedastic STAR-Tree Model statistical performance was equivalent to the other models, however its financial performance was superior for most of the series. The STAR-Tree methodology was also applied for forecasting the realized volatility, and the forecasts were used in financial leverage analysis.

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Myslivec, Oldřich. "Využití technické analýzy při tvorbě obchodních systémů." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-11194.

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This thesis is devoted to the technical analysis with the emphasis on design, testing and using of trading systems. Its objective is to find out whether it is possible for a trader to design and trade his own profitable trading system with widely accessible tools and methods. First part of the thesis is focused on the chart analysis and description of candlestick charts including their rate of profit success, all based on hands-on experience in a real market. It continues with a breakdown of most used methods based on moving averages. The second chapter fully describes main stage of trading system development and follows up with third chapter on practical application of the theoretical assumption on the real market conditions, i.e. to design a profitable trading system

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Книги з теми "Trading automatisé"

Chan, Jacinta. Automation of Trading Machine for Traders. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9.

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Stock exchange automation. New York: Garland, 1994.

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Service, U. S. Customs. Customer satisfaction report: Commercial importers. [Washington, DC]: U.S. Customs Service, 1997.

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Service, U. S. Customs. Customer satisfaction report: Commercial importers. [Washington, DC]: U.S. Customs Service, 1997.

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Service, U. S. Customs. Customer satisfaction report: Commercial importers. [Washington, DC]: U.S. Customs Service, 1997.

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Committee, President's Management Council (U S. ). Electronic Processes Initiatives. Electronic commerce for buyers and sellers: A strategic plan for electronic federal purchasing and payment. [Washington, D.C: The Council?], 1998.

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American Bar Association. Committee on Law and Accounting. and American Bar Association. Committee on Federal Regulation of Securities., eds. The MD&A and the year 2000. [Chicago, Ill.]: ABA Section of Business Law, 1999.

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PLC, Euromoney Institutional Investor. Best practice in foreign exchange markets. 3rd ed. [New York]: FX Alliance, 2007.

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Munshi, Jamal. Stock Exchange Automation. Taylor & Francis Group, 2017.

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Chan, Jacinta. Automation of Trading Machine for Traders: How to Develop Trading Models. Palgrave Pivot, 2019.

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Частини книг з теми "Trading automatisé"

Kera, Denisa Reshef. "Governance ‘Trading Zones’." In Algorithms and Automation, 192–202. London: Routledge India, 2023. http://dx.doi.org/10.4324/9781003189411-17.

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Conlan, Chris. "Organizing and Automating Scripts." In Automated Trading with R, 155–60. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_10.

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Bensdorp, Laurens. "The Automation of Tharp Think." In Trading Beyond the Matrix, 25–35. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119204770.ch2.

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Chan, Jacinta. "Introduction to Model Trading." In Automation of Trading Machine for Traders, 1–18. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_1.

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Chan, Jacinta. "Technical Indicators: Market Technicians Trading Tools." In Automation of Trading Machine for Traders, 19–36. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_2.

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Chan, Jacinta. "Development of Technical Algorithm Trading Systems." In Automation of Trading Machine for Traders, 45–66. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_4.

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Chan, Jacinta. "Development of Artificial Intelligence Algorithm Trading Systems." In Automation of Trading Machine for Traders, 67–79. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_5.

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Chan, Jacinta. "Market Data Analysis." In Automation of Trading Machine for Traders, 37–43. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_3.

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Chan, Jacinta. "Test Results of the Profitability of New Trading Model." In Automation of Trading Machine for Traders, 81–88. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_6.

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Chan, Jacinta. "Evaluation and Stops." In Automation of Trading Machine for Traders, 89–104. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9945-9_7.

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Тези доповідей конференцій з теми "Trading automatisé"

Padovani, Matheus Rosisca, and João Roberto Bertini Junior. "A stock trading algorithm based on trend forecasting and time series classification." In Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/eniac.2021.18272.

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Algorithm trading relies on the automatic identification of buying and selling points of a given asset to maximize profit. In this paper, we propose the Trend Classification Trading Algorithm (TCTA) which is based on time series classification and trend forecasting to perform trade. TCTA first employs the K-means to cluster 5-days closing price segments and label them according to its trend. A deep learning classification model is then trained with these label sequences to estimate the next trend. Trading points are given by the alternation on trend estimates. Results considering 20 shares from Ibovespa show TCTA present higher profit than buy-and-hold and trading schemes based on Moving Average Converge Divergence (MACD) or Bollinger bands.

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Sihananto, Andreas Nugroho, Anggraini Puspita Sari, Muhammad Eko Prasetyo, Mochammad Yanuar Fitroni, Wahyu Nugroho Gultom, and Henni Endah Wahanani. "Reinforcement Learning for Automatic Cryptocurrency Trading." In 2022 IEEE 8th Information Technology International Seminar (ITIS). IEEE, 2022. http://dx.doi.org/10.1109/itis57155.2022.10010206.

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Li, Ziqian, Caixia Wang, Xiaoning Ye, Wei Wang, and Shuang Hao. "China's Green Certificate Trading Mode Design and Trading Volume Evaluation Model Establishment." In 2019 Chinese Automation Congress (CAC). IEEE, 2019. http://dx.doi.org/10.1109/cac48633.2019.8996576.

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Dekker, Pieter, and Vasilios Andrikopoulos. "Automating Bulk Commodity Trading Using Smart Contracts." In 2020 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS). IEEE, 2020. http://dx.doi.org/10.1109/dapps49028.2020.00006.

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Li, Yi, Yuanjie Ni, Wei Liu, and Wenxing Yan. "Two Patterns of Knowledge Trading." In Control and Automation 2014. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/astl.2014.76.22.

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Abouloula, Khalid, and Salah-ddine Krit. "Using a Robot Trader for Automatic Trading." In the Fourth International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3234698.3234701.

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Gulin, S. V., and A. G. Pirkin. "FEATURES OF BUSINESS-PROCESSES IN THE CREATION OF ELECTROTECHNOLOGICAL SYSTEMS FOR THE AGRICULTURAL INDUSTRIAL COMPLEX." In INNOVATIVE TECHNOLOGIES IN SCIENCE AND EDUCATION. DSTU-Print, 2020. http://dx.doi.org/10.23947/itno.2020.357-362.

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This article offers a universal methodology for the design, creation and operation of complex electrotechnological systems. This methodology is based on a system-process approach to business modeling. The article provides a detailed description of all private business processes that provide a full cycle of business engineering, and offers a General mathematical expression for a comprehensive assessment of the effectiveness of the business engineering process. The proposed methodology has been tested on the example of designing, creating and operating vegetation climate systems (VCS). This example shows that it is possible to conduct quite serious scientific research at the intersection of plant physiology and electric power engineering, which allows us to create modern self-adjusting systems for automatic microclimate control when growing plants. Application of engineering methods allows to increase the efficiency of development of information systems for automatic control of parameters of the most important physiological processes (photosynthesis, transpiration, etc.) in plants under the influence of environmental factors. The article outlines the prospects for the development of the subject area of engineering in the direction of solving specific problems to integrated energy engineering, and the energy business - from trading individual services to trading models and technologies.

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Chau, Tan, Minh-Tri Nguyen, Duc-Vu Ngo, Anh-Duc T. Nguyen, and Trong-Hop Do. "Deep Reinforcement Learning methods for Automation Forex Trading." In 2022 RIVF International Conference on Computing and Communication Technologies (RIVF). IEEE, 2022. http://dx.doi.org/10.1109/rivf55975.2022.10013861.

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Kaur, Inderpreet, Yashica Chauhan, Utsav Gupta, and Sagar Malik. "Investigating the Use of Automation in Cryptocurrency Trading." In 2024 2nd International Conference on Disruptive Technologies (ICDT). IEEE, 2024. http://dx.doi.org/10.1109/icdt61202.2024.10489073.

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Worasucheep, Chukiat, Sirapop Nuannimnoi, Ratchanon Khamvichit, and Papon Attagonwantana. "An automatic stock trading system using Particle Swarm Optimization." In 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). IEEE, 2017. http://dx.doi.org/10.1109/ecticon.2017.8096283.

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