scholarly journals The Psychophysiology of Real-Time Financial Risk Processing

2002 ◽  
Vol 14 (3) ◽  
pp. 323-339 ◽  
Author(s):  
Andrew W. Lo ◽  
Dmitry V. Repin
Keyword(s):  
Financial Markets ◽  
Real Time ◽  
Financial Risk ◽  
Emotional Responses ◽  
Decision Making Process ◽  
Electrodermal Responses ◽  
Cardiovascular Variables ◽  
Risk Processing ◽  
Volume Pulse ◽  
Blood Volume Pulse

A longstanding controversy in economics and finance is whether financial markets are governed by rational forces or by emotional responses. We study the importance of emotion in the decision-making process of professional securities traders by measuring their physiological characteristics (e.g., skin conductance, blood volume pulse, etc.) during live trading sessions while simultaneously capturing real-time prices from which market events can be detected. In a sample of 10 traders, we find statistically significant differences in mean electrodermal responses during transient market events relative to no-event control periods, and statistically significant mean changes in cardiovascular variables during periods of heightened market volatility relative to normal-volatility control periods. We also observe significant differences in these physiological responses across the 10 traders that may be systematically related to the traders' levels of experience.

Risk early warning management and intelligent real-time system of financial enterprises based on fuzzy theory

2020 ◽  
pp. 1-11
Author(s):  
Qiaoying Ding
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Financial Risk ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Theory ◽  
Fuzzy Comprehensive Evaluation ◽  
Real Time System ◽  
Enterprise Risk ◽  
Early Warning Management

The financial market is changing rapidly. Since joining the WTO, our country’s financial companies have faced pressure from dual competition at domestic and abroad. The complex internal and external environment has forced financial enterprise managers to improve risk prevention awareness, early warning and monitoring, so as to responding to emergencies and challenges in the financial market. However, traditional forecasting and analysis methods have problems such as large workload, low efficiency, and low accuracy. Therefore, this article applies intelligent computing to the forecast of financial markets, using related concepts of fuzzy theory and Internet intelligent technology, and proposes to establish a model system for financial enterprise risk early warning management and intelligent real-time monitoring based on fuzzy theory. This article first collected a large amount of data through the literature investigation method, and made a systematic and complete introduction to the related theoretical concepts of fuzzy theory and financial risk early-warning management, has laid a sufficient theoretical foundation for the subsequent exploration of the application of fuzzy theory in financial enterprise risk early warning management and intelligent real-time systems; Then a fuzzy comprehensive evaluation method that combines the analytic hierarchy process and fuzzy evaluation method is proposed, taking a listed company mainly engaged in automobile sales in our province as a case, the company’s financial risk management and modeling experiment of the intelligent real-time system; Finally quoted specific cases again, used the fuzzy comprehensive evaluation method to carry out risk warning and evaluation on the PPP projects of private enterprises in our province, and concluded that the project risk score is between 20-60, which is meet the severe-medium range in the risk level. Research shows that the use of fuzzy theory and modern network technology can make more accurate warnings and assessments of potential and apparent risks of financial enterprises, greatly improving the safety of financial enterprise management and reducing the losses caused by various risks.

scholarly journals Real-Time Measurement of Drilling Fluid Rheological Properties: A Review

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3592
Author(s):  
Naipeng Liu ◽  
Di Zhang ◽  
Hui Gao ◽  
Yule Hu ◽  
Longchen Duan
Keyword(s):  
Decision Making ◽  
Rheological Properties ◽  
Real Time ◽  
Drilling Fluid ◽  
Time Measurement ◽  
Decision Making Process ◽  
Rate Of Penetration ◽  
The Real ◽  
Real Time Measurement ◽  
Fluid Properties

The accurate and frequent measurement of the drilling fluid’s rheological properties is essential for proper hydraulic management. It is also important for intelligent drilling, providing drilling fluid data to establish the optimization model of the rate of penetration. Appropriate drilling fluid properties can improve drilling efficiency and prevent accidents. However, the drilling fluid properties are mainly measured in the laboratory. This hinders the real-time optimization of drilling fluid performance and the decision-making process. If the drilling fluid’s properties cannot be detected and the decision-making process does not respond in time, the rate of penetration will slow, potentially causing accidents and serious economic losses. Therefore, it is important to measure the drilling fluid’s properties for drilling engineering in real time. This paper summarizes the real-time measurement methods for rheological properties. The main methods include the following four types: an online rotational Couette viscometer, pipe viscometer, mathematical and physical model or artificial intelligence model based on a Marsh funnel, and acoustic technology. This paper elaborates on the principle, advantages, limitations, and usage of each method. It prospects the real-time measurement of drilling fluid rheological properties and promotes the development of the real-time measurement of drilling rheological properties.

COVID-19 pandemic and connectedness across financial markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Abubakr Naeem ◽  
Saba Sehrish ◽  
Mabel D. Costa
Keyword(s):  
Financial Markets ◽  
Financial Risk ◽  
Negative Impact ◽  
Spillover Effect ◽  
External Shocks ◽  
Content Type ◽  
Time Frequency ◽  
Long Run ◽  
Short Run ◽  
Momentum Trading

Purpose This study aims to estimate the time–frequency connectedness among global financial markets. It draws a comparison between the full sample and the sample during the COVID-19 pandemic. Design/methodology/approach The study uses the connectedness framework of Diebold and Yilmaz (2012) and Barunik and Krehlik (2018), both of which consider time and frequency connectedness and show that spillover is specific to not only the time domain but also the frequency (short- and long-run) domain. The analysis also includes pairwise connectedness by making use of network analysis. Daily data on the MSCI World Index, Barclays Bloomberg Global Treasury Index, Oil future, Gold future, Dow Jones World Islamic Index and Bitcoin have been used over the period from May 01, 2013 to July 31, 2020. Findings This study finds that cryptocurrency, bond and gold are hedges against both conventional stocks and Islamic stocks on average; however, these are not “safe havens” during an economic crisis, i.e. COVID-19. External shocks, such as COVID-19, strengthen the return connectedness among all six financial markets. Research limitations/implications For investors, the study provides important insights that during external shocks such as COVID-19, there is a spillover effect, and investors are unable to hedge risk between conventional stocks and Islamic stocks. These so-called safe haven investment alternatives suffer from the similar negative impact of systemic financial risk. However, during an external shock such as COVID-19, cryptocurrencies, bonds and gold can be used to hedge risk against conventional stocks, Islamic stocks and oil. Moreover, the findings imply that by engaging in momentum trading, active investors can gain short-run benefits before the market processes any new information. Originality/value The study contributes to the emergent literature investigating the connectedness among financial markets during the COVID-19 pandemic. It provides evidence that the return connectedness among six global financial markets, namely, conventional stocks, Islamic stocks, bond, oil, gold and cryptocurrency, is extremely strong. From a methodological standpoint, this study finds that COVID-19 pandemic shock has a significant short-run impact on the connectedness among financial markets.

Pervasive Business Intelligence Platform to Support the Decision-Making Process in Waiting Lists

2021 ◽  
pp. 848-863
Author(s):  
Marisa Esteves ◽  
Filipe Miranda ◽  
António Abelha
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Business Intelligence ◽  
Waiting Times ◽  
Waiting Lists ◽  
Decision Making Process ◽  
The North ◽  
Health Institutions ◽  
Private Network ◽  
The Web

In recent years, the increase of average waiting times in waiting lists is an issue that has been felt in health institutions. Thus, the implementation of new administrative measures to improve the management of these organizations may be required. Hereupon, the aim of this present work is to support the decision-making process in appointments and surgeries waiting lists in a hospital located in the north of Portugal, through a pervasive Business Intelligence platform that can be accessed anywhere and anytime by any device connected within the hospital's private network. By representing information that facilitate the analysis of information and knowledge extraction, the Web tool allows the identification in real-time of average waiting times outside the outlined patterns. Thereby, the developed platform permits their identification, enabling their further understanding in order to take the necessary measures. Thus, the main purpose is to enable the reduction of average waiting times through the analysis of information in order to, subsequently, ensure the satisfaction of patients.

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