Predicting stock market movements using network science: An information theoretic approach

A stock market is considered as one of the highly complex systems, which consists of many components whose prices move up and down without having a clear pattern. The complex nature of a stock market challenges us on making a reliable prediction of its future movements. In this paper, we aim at building a new method to forecast the future movements of Standard & Poor's 500 Index (S&P 500) by constructing time-series complex networks of S&P 500 underlying companies by connecting them with links whose weights are given by the mutual information of 60-minute price movements of the pairs of the companies with the consecutive 5,340 minutes price records. We showed that the changes in the strength distributions of the networks provide an important information on the network's future movements. We built several metrics using the strength distributions and network measurements such as centrality, and we combined the best two predictors by performing a linear combination. We found that the combined predictor and the changes in S&P 500 show a quadratic relationship, and it allows us to predict the amplitude of the one step future change in S&P 500. The result showed significant fluctuations in S&P 500 Index when the combined predictor was high. In terms of making the actual index predictions, we built ARIMA models. We found that adding the network measurements into the ARIMA models improves the model accuracy. These findings are useful for financial market policy makers as an indicator based on which they can interfere with the markets before the markets make a drastic change, and for quantitative investors to improve their forecasting models.Comment: 13 pages, 7 figures, 3 table

An Experimental Study on the Measurement of Fuel to Air Ratio Using Flame Chemiluminescence

This study is aiming at establishing the relationship between the optical signal of flame and an equivalent ratio of flame. In this experiment, flame optical signal in a furnace is measured using photodiode. The combustion system which is composed of metal fiber burner and vertical furnace and flame chemiluminescence is measured at various experimental conditions. In this study, the flame chemiluminescence of laminar premixed flame is measured by using commercially available photodiode. It is experimentally investigated the relationship between equivalent ratio and photodiode signal. In addition, The strategy of combustion control method is proposed by using the optical signal and fuel pressure. The results showed that certain relationship between optical data of photodiode and equivalence ratio exists and this leads to the successful application of this system for instantaneous measurement of equivalence ration of the combustion system

Influence of Evacuation Policy on Clearance Time under Large-Scale Chemical Accident: An Agent-Based Modeling

Large-scale chemical accidents that occur near areas with large populations can cause significant damage not only to employees in a workplace but also to residents near the accident site. Despite the increasing frequency and severity of chemical accidents, few researchers have argued for the necessity of developing scenarios and simulation models for these accidents. Combining the TRANSIMS (Transportation Analysis and Simulation System) agent-based model with the ALOHA (Areal Location of Hazardous Atmospheres) dispersion model, this study aims to develop a modeling framework for simulating emergency evacuations in response to large-scale chemical accidents. The baseline accident scenario assumed the simultaneous leakage of toxic chemicals from industrial complexes near residential areas. The ALOHA model results showed that approximately 60% of residents in the scenario's city were required to evacuate their homes. The majority of evacuees completed their evacuations within 5 h in the baseline scenario (evacuating maximum number of private vehicles without any intervention), while the distribution of the population and street network density caused geographical variability in clearance time. Clearance time can be significantly reduced by changing both the evacuees' behaviors and the evacuation policy, which suggests the necessity for proper public intervention when the mass evacuation of residents is required due to chemical accidents

Development of a Remote Testing System for Performance of Gas Leakage Detectors

In this research, we designed a remote system to test parameters of gas detectors such as gas concentration and initial response time. This testing system is available to measure two gas instruments simultaneously. First of all, we assembled an experimental jig with a square structure. Those parts are included with a glass flask, two high-quality cameras, and two Ethernet modems for transmitting data. This remote gas detector testing system extracts numerals from videos with continually various gas concentrations while LCDs show photographs from cameras. Extracted numeral data are received to a laptop computer through Ethernet modem. And then, the numerical data with gas concentrations and the measured initial response speeds are recorded and graphed. Our remote testing system will be diversely applied on gas detector’s test and will be certificated in domestic and international countries

Harnessing bacterial power in microscale actuation

This paper presents a systematic analysis of the motion of microscale structures actuated by flagellated bacteria. We perform the study both experimentally and theoretically. We use a blotting procedure to attach flagellated bacteria to a buoyancy-neutral plate called a microbarge. The motion of the plate depends on the distribution of the cells on the plate and the stimuli from the environment. We construct a stochastic mathematical model for the system, based on the assumption that the behavior of each bacterium is random and independent of that of its neighbors. The main finding of the paper is that the motion of the barge plus bacteria system is a function of a very small set of parameters. This reduced-dimensional model can be easily estimated using experimental data. We show that the simulation results obtained from the model show an excellent match with the experimentally-observed motion of the barge

Advanced nanoporous material–based QCM devices: A new horizon of interfacial mass sensing technology

Mass interfacial processes have been considered as one of the crucial factors supporting fundamental research. Due to the low cost and conceptual simplicity, significant advancements have been achieved in the development of methodologies based on piezoelectric devices for in situ determination of mass changes on the surfaces of deposited materials under various conditions. The introduction of nanomaterials for designing sensors and monitoring systems becomes essential to create advanced detection systems for selective sensing of toxic analytes for environmental remediation. The integration of materials with predesignated nanostructures into sensor devices, such as surface acoustic wave (SAW), quartz crystal microbalance (QCM), and QCM with dissipation (QCM-D) monitoring, has led to an immense progress in the sensing applications of toxic target analytes at the nanogram range. Here, an overview is introduced of recent advancement in the fabrication of piezoelectric devices for the interfacial mass sensing of targeted chemical vapors and ions through combination with nanoporous materials including mesoporous materials carbon-based nanomaterials, metal–organic frameworks (MOFs), MOF-derived nanoporous carbons, Prussian blue (PB) and its analogues (PBA), zeolites and related materials. Challenges and future prospect are also summarized by the advanced QCM technique associated with properties of nanostructured materials

Enhancement of thermoelectric properties of La-doped SrTiO3 bulk by introducing nanoscale porosity

Electron-doped SrTiO3 is a well-known n-type thermoelectric material, although the figure of merit of SrTiO3 is still inferior compared with p-type metal oxide-based thermoelectric materials due to its high lattice thermal conductivity. In this study, we have used a different amount of the non-ionic surfactant F127 during sample preparation to introduce nanoscale porosities into bulk samples of La-doped SrTiO3. It has been observed that the porosities introduced into the bulk sample significantly improve the Seebeck coefficient and reduce the thermal conductivity by the charge carrier and phonon scattering respectively. Therefore, there is an overall enhancement in the power factor (PF) followed by a dimensionless figure of merit (zT) over a wide scale of temperature. The sample 20 at% La-doped SrTiO3 with 600 mg of F127 surfactant (SLTO 600F127) shows the maximum PF of 1.14 mW m−1 K−2 at 647 K which is 35% higher than the sample without porosity (SLTO 0F127), and the same sample (SLTO 600F127) shows the maximum value of zT is 0.32 at 968 K with an average enhancement of 62% in zT in comparison with the sample without porosity (SLTO 0F127)