Papers Algorithmic Trading
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Inference of Binary Regime Models with Jump Discontinuities
Identifying the instances of jumps in a discrete-time-series sample of a jump diffusion model is a challenging task. We have developed a novel statistical technique for jump detection and volatility estimation in a retur…
Algorithmic TradingTime SeriesTime Series AnalysisValidating Weak-form Market Efficiency in United States Stock Markets with Trend Deterministic Price Data and Machine Learning
The Efficient Market Hypothesis has been a staple of economics research for decades. In particular, weak-form market efficiency -- the notion that past prices cannot predict future performance -- is strongly supported by…
Algorithmic TradingBIG-bench Machine LearningFormRandom walk model from the point of view of algorithmic trading
Despite the fact that an intraday market price distribution is not normal, the random walk model of price behaviour is as important for the understanding of basic principles of the market as the pendulum model is a start…
Algorithmic TradingAn instantaneous market volatility estimation
Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the or…
Algorithmic TradingMean Field Games with Partial Information for Algorithmic Trading
Financial markets are often driven by latent factors which traders cannot observe. Here, we address an algorithmic trading problem with collections of heterogeneous agents who aim to perform optimal execution or statisti…
Algorithmic TradingFinancial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks
Even though computational intelligence techniques have been extensively utilized in financial trading systems, almost all developed models use the time series data for price prediction or identifying buy-sell points. How…
Algorithmic TradingTime SeriesTime Series AnalysisA new approach to learning in Dynamic Bayesian Networks (DBNs)
In this paper, we revisit the parameter learning problem, namely the estimation of model parameters for Dynamic Bayesian Networks (DBNs). DBNs are directed graphical models of stochastic processes that encompasses and ge…
Algorithmic TradingOrder-book modelling and market making strategies
Market making is one of the most important aspects of algorithmic trading, and it has been studied quite extensively from a theoretical point of view. The practical implementation of so-called "optimal strategies" howeve…
Algorithmic TradingAlgorithmic Trading with Fitted Q Iteration and Heston Model
We present the use of the fitted Q iteration in algorithmic trading. We show that the fitted Q iteration helps alleviate the dimension problem that the basic Q-learning algorithm faces in application to trading. Furtherm…
Algorithmic TradingQ-LearningAlgorithmic trading in a microstructural limit order book model
We propose a microstructural modeling framework for studying optimal market making policies in a FIFO (first in first out) limit order book (LOB). In this context, the limit orders, market orders, and cancel orders arriv…
Algorithmic TradingPoint ProcessesQuantizationClassification-based Financial Markets Prediction using Deep Neural Networks
Deep neural networks (DNNs) are powerful types of artificial neural networks (ANNs) that use several hidden layers. They have recently gained considerable attention in the speech transcription and image recognition commu…
Algorithmic TradingClassificationGeneral ClassificationPredictionDynamics of Order Positions and Related Queues in a Limit Order Book
Order positions are key variables in algorithmic trading. This paper studies the limiting behavior of order positions and related queues in a limit order book. In addition to the fluid and diffusion limits for the proces…
Algorithmic TradingDynamic Mode Decomposition for Financial Trading Strategies
We demonstrate the application of an algorithmic trading strategy based upon the recently developed dynamic mode decomposition (DMD) on portfolios of financial data. The method is capable of characterizing complex dynami…
Algorithmic TradingHeavy-Tailed Features and Empirical Analysis of the Limit Order Book Volume Profiles in Futures Markets
This paper poses a few fundamental questions regarding the attributes of the volume profile of a Limit Order Books stochastic structure by taking into consideration aspects of intraday and interday statistical features, …
Algorithmic TradingLe trading algorithmique
The algorithmic trading comes from digitalisation of the processing of trading assets on financial markets. Since 1980 the computerization of the stock market offers real time processing of financial information. This te…
Algorithmic TradingDecision Making