Forecasting stock market returns over multiple time horizons

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. (2015). This heterogeneous framework enables us to capture dynamics at multiple timescales, expanding the model's applications and improving precision. We study the heterogeneous model theoretically and empirically to highlight essential mechanisms underlying certain market behaviors, such as transitions between bull- and bear markets and the self-similar behavior of price changes. Most importantly, we apply this model to show that the stock market is nearly efficient on intraday timescales, adjusting quickly to incoming news, but becomes inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics, attributable to a feedback mechanism acting over these horizons. Then, using the model, we design algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested results suggest that the return is predictable to the extent that successful trading strategies can be constructed to harness this predictability.Comment: This is the version accepted for publication in a journal Quantitative Finance. A draft was posted here on 18 August 2015. 50 page

Predictable markets? A news-driven model of the stock market

We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.Comment: This is the version accepted for publication in a new journal Algorithmic Finance (http://algorithmicfinance.org). A draft was posted here on 29 Apri

Localized Surface Plasmon Resonance in Metamaterials Composed of As_1−<i>z</i>Sb_<i>z</i> Semimetal Nanoparticles in Al_<i>x</i>Ga_1−<i>x</i>As_1−<i>y</i>Sb_<i>y</i> Semiconductor Matrix

We analyze the possibility to realize a localized surface plasmon resonance in metamaterials composed of As1−zSbz nanoparticles embedded in an AlxGa1−xAs1−ySby semiconductor matrix. To this end, we perform ab initio calculations of the dielectric function of the As1−zSbz materials. Changing the chemical composition z, we trace the evolution of the band structure, dielectric function, and loss function. In terms of the Mie theory, we calculate the polarizability and optical extinction of a system of As1−zSbz nanoparticles in an AlxGa1−xAs1−ySby environment. We show a possibility to provide localized surface plasmon resonance near the band gap of the AlxGa1−xAs1−ySby semiconductor matrix by a built-in system of As1−zSbz nanoparticles strongly enriched by Sb. The results of our calculations are supported by available experimental data

Plasmon Resonance in a System of Bi Nanoparticles Embedded into (Al,Ga)As Matrix

We reveal the feasibility of the localized surface plasmon resonance in a system of Bi nanoparticles embedded into an AlxGa1−xAs semiconductor matrix. With an ab initio determined dielectric function for bismuth and well-known dielectric properties of AlxGa1−xAs solid solution, we performed calculations of the optical extinction spectra for such metamaterial using Mie’s theory. The calculations demonstrate a strong band of the optical extinction using the localized surface plasmons near a photon energy of 2.5 eV. For the semiconducting matrices with a high aluminum content x > 0.7, the extinction by plasmonic nanoparticles plays the dominant role in the optical properties of the medium near the resonance photon energyV.I.U. and V.V.C. acknowledge the financial support of the Russian Science Foundation, project No. 22-22-20105, https://rscf.ru/project/22-22-20105/ (accessed on 30 December 2023) and by grant of St. Petersburg Science Foundation, according to agreement No. 25/2022 as of 14 April 2022. V.M.S. acknowledges MCIN/AEI/10.13039/501100011033/ for financial support by Grant No. PID2019-105488GB-I00

Unveiling Influence of Dielectric Losses on the Localized Surface Plasmon Resonance in (Al,Ga)As:Sb Metamaterials

We perform numerical modeling of the optical absorption spectra of metamaterials composed of systems of semimetal antimony nanoparticles embedded into AlGa1−As semiconductor matrices. We reveal a localized surface plasmon resonance (LSPR) in these metamaterials, which results in a strong optical extinction band below, near, or above the direct band gap of the semiconductor matrices, depending on the chemical composition of the solid solutions. We elucidate the role of dielectric losses in AlGa1−As, which impact the LSPR and cause non-plasmonic optical absorption. It appears that even a dilute system of plasmonic Sb nanoinclusions can substantially change the optical absorption spectra of the medium.V.I.U. and V.V.C. acknowledge the financial support by the Russian Science Foundation, project No. 22-22-20105, https://rscf.ru/project/22-22-20105/ (accessed on 8 January 2024) and by the grant of St. Petersburg Science Foundation, according to agreement No. 25/2022 as of 14.04.2022. V.M.S. acknowledges MCIN/AEI/10.13039/501100011033/ for financial support by Grant No. PID2019-105488GB-I00. S.V.E. acknowledges the financial support provided by the government research assignment for ISPMS SB RAS (Project FWRW-2022-0001)

Modelling of the Process of Extraction of the Pine Bark of Water-Alkaline Solution

Optimization of process extraction pine bark of water-alkaline solution, by the regression equation. Shows the adequacy of this process, providing a mathematical model and parametric identification of the model. Defined and presented the technological parameters of extraction and characterization of the pine bark extract, received in the normal modeОптимизирован процесс экстракции коры сосны водно-щелочным раствором, установлено уравнение регрессии. Показана адекватность данного процесса, представлена математическая модель и параметрическая идентификация данной модели. Определены технологические параметры экстракции и дана характеристика экстракта коры сосны, полученного в оптимальном режим

Modelling of the Process of Extraction of the Pine Bark of Water-Alkaline Solution

Optimization of process extraction pine bark of water-alkaline solution, by the regression equation. Shows the adequacy of this process, providing a mathematical model and parametric identification of the model. Defined and presented the technological parameters of extraction and characterization of the pine bark extract, received in the normal modeОптимизирован процесс экстракции коры сосны водно-щелочным раствором, установлено уравнение регрессии. Показана адекватность данного процесса, представлена математическая модель и параметрическая идентификация данной модели. Определены технологические параметры экстракции и дана характеристика экстракта коры сосны, полученного в оптимальном режим