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In observational studies of treatment effects, matched samples are created so treated and control groups are similar in terms of observable covariates. Traditionally such matched samples consist of matched pairs. If a pair match fails to…

Methodology · Statistics 2014-10-22 Luke Keele , Sam Pimentel , Frank Yoon

Efficient markets are characterised by profit-driven participants continuously refining their positions towards the latest insights. Margins for profit generation are generally small, shaping a difficult landscape for automated trading…

Computational Engineering, Finance, and Science · Computer Science 2025-04-16 Robin Bruneel , Mathijs Schuurmans , Panagiotis Patrinos

We consider pure-jump transaction-level models for asset prices in continuous time, driven by point processes. In a bivariate model that admits cointegration, we allow for time deformations to account for such effects as intraday seasonal…

Statistics Theory · Mathematics 2014-04-15 Alexander Aue , Lajos Horváth , Clifford M. Hurvich , Philippe Soulier

The literature on using yield curves to forecast recessions customarily uses 10-year--three-month Treasury yield spread without verification on the pair selection. This study investigates whether the predictive ability of spread can be…

Econometrics · Economics 2023-10-19 Jaehyuk Choi , Desheng Ge , Kyu Ho Kang , Sungbin Sohn

By opportunistically engaging mobile users (workers), mobile crowdsensing (MCS) networks have emerged as important approach to facilitate sharing of sensed/gathered data of heterogeneous mobile devices. To assign tasks among workers and…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-21 Houyi Qi , Minghui Liwang , Seyyedali Hosseinalipour , Xiaoyu Xia , Zhipeng Cheng , Xianbin Wang , Zhenzhen Jiao

Designing robust frameworks for precise prediction of future prices of stocks has always been considered a very challenging research problem. The advocates of the classical efficient market hypothesis affirm that it is impossible to…

Statistical Finance · Quantitative Finance 2021-08-31 Jaydip Sen , Sidra Mehtab

Market timing is an investment technique that tries to continuously switch investment into assets forecast to have better returns. What is the likelihood of having a successful market timing strategy? With an emphasis on modeling…

Portfolio Management · Quantitative Finance 2018-07-20 Guy Metcalfe

We consider the viability of a modularised mechanistic online machine learning framework to learn signals in low-frequency financial time series data. The framework is proved on daily sampled closing time-series data from JSE equity…

Statistical Finance · Quantitative Finance 2021-01-11 Joel da Costa , Tim Gebbie

This work considers stochastic operators in general inner-product spaces, and in particular, systems with stochastically time-varying input delays of a known probability distribution. Stochastic dissipativity and stability are defined from…

Optimization and Control · Mathematics 2024-04-22 Ethan LoCicero , Amy Strong , Leila Bridgeman

With the steady increase in global logistics and freight transport demand, the need for efficient and sustainable intermodal transport systems becomes increasingly important. This study addresses the optimization of container movement by…

Optimization and Control · Mathematics 2025-08-22 Jeremiah Gbadegoye , Mustafa C. Camur , Xueping Li

The time proximity of trades across stocks reveals interesting topological structures of the equity market in the United States. In this article, we investigate how such concurrent cross-stock trading behaviors, which we denote as…

Trading and Market Microstructure · Quantitative Finance 2024-05-14 Yutong Lu , Gesine Reinert , Mihai Cucuringu

We study optimal liquidation in the presence of linear temporary and transient price impact along with taking into account a general price predicting finite-variation signal. We formulate this problem as minimization of a cost-risk…

Trading and Market Microstructure · Quantitative Finance 2022-01-17 Eyal Neuman , Moritz Voß

We present an approach to deep estimation of discrete conditional probability distributions. Such models have several applications, including generative modeling of audio, image, and video data. Our approach combines two main techniques:…

Machine Learning · Statistics 2017-03-01 Wesley Tansey , Karl Pichotta , James G. Scott

We study logistical investment flexibility provided by modular processing technologies for mitigating risk. Specifically, we propose a multi-stage stochastic programming formulation that determines optimal capacity expansion plans that…

Optimization and Control · Mathematics 2021-02-10 Yue Shao , Yicheng Hu , Victor M. Zavala

With an increasing share of volatile renewables, more flexibility is needed to balance the electricity system. In order to enable local flexibility, we suggest a three-stage stochastic market clearing model using community-based…

Optimization and Control · Mathematics 2019-10-28 Sigurd Bjarghov , Christian Ø. Naversen , Kasper Thorvaldsen , Hossein Farahmand

This paper addresses the problem of testing for persistence in the effects of the shocks affecting the prices of renewable commodities, which have potential implications on stabilization policies and economic forecasting, among other areas.…

Econometrics · Economics 2024-02-05 Manuel Landajo , María José Presno

In this paper we provide a comprehensive analysis of a structural model for the dynamics of prices of assets traded in a market originally proposed in [1]. The model takes the form of an interacting generalization of the geometric Brownian…

Statistical Finance · Quantitative Finance 2018-06-06 Kartik Anand , Jonathan Khedair , Reimer Kuehn

Rising economic instability and continuous evolution in international relations demand a self-reliant trade and commodity flow networks at regional scales to efficiently address the growing human needs of a nation. Despite its importance in…

Physics and Society · Physics 2022-07-26 Sujata S Kulkarni , Raviraj Dave , Udit Bhatia , Rohini Kumar

Stable matching, a classical model for two-sided markets, has long been studied with little consideration for how each side's preferences are learned. With the advent of massive online markets powered by data-driven matching platforms, it…

Machine Learning · Computer Science 2020-07-14 Lydia T. Liu , Horia Mania , Michael I. Jordan

This paper examines the implementation of a statistical arbitrage trading strategy based on co-integration relationships where we discover candidate portfolios using multiple factors rather than just price data. The portfolio selection…

Portfolio Management · Quantitative Finance 2014-05-13 Wenbin Zhang , Zhen Dai , Bindu Pan , Milan Djabirov