A Theoretical Approach to Evaluate Online and Traditional Trading on th NASDAQ Stock Exchange

The aim of this chapter is to discuss current online and traditional trading on the NASDAQ stock exchange using theoretical approach. The paper aims to derive future trends for the online stock trading. The following are objectives of this paper: (1) To describe the current state of online trading; (2) To compare the execution of quality trades between market makers and electronic communications networks (ECNs)

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A Theoretical Approach to Evaluate Online and Traditional Trading on the NASDAQ Stock Exchange

Selected Readings on Electronic Commerce Technologies ◽

10.4018/978-1-60566-096-7.ch013 ◽

2009 ◽

pp. 180-191

Author(s):

Haroun Alryalat

Keyword(s):

Theoretical Approach ◽

Stock Exchange ◽

Market Performance ◽

Future Trends ◽

Electronic Communications ◽

Communications Networks ◽

Market Makers ◽

Current State ◽

Online Trading ◽

Insight Into

The aim of this chapter is to discuss current online and traditional trading on the NASDAQ stock exchange using theoretical approach. The paper aims to derive future trends for the online stock trading. The following are objectives of this paper: (1) To describe the current state of online trading; (2) To compare the execution of quality trades between market makers and electronic communications networks (ECNs). By achieving set objectives, this paper will provide insight into how ECNs are used and what impact they have on the overall NASDAQ market performance.

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Electronic Trading in Stock Markets

The Journal of Economic Perspectives ◽

10.1257/089533006776526067 ◽

2006 ◽

Vol 20 (1) ◽

pp. 153-174 ◽

Cited By ~ 70

Author(s):

Hans R Stoll

Keyword(s):

Stock Markets ◽

Stock Exchange ◽

Electronic Trading ◽

Electronic Communications ◽

Communications Networks ◽

Face To Face ◽

Traditional Markets ◽

Face Negotiation ◽

Traditional Organization

Modern trading technology clashes with the traditional organization of a stock exchange, where transactions were consummated via face-to-face negotiation. The modern trading facility is no longer a place. Rather, it is a computer system over which transactions are entered, routed, executed and cleared electronically with little or no human intervention. In this article, I examine how electronic trading has altered stock markets. I begin with an overview of how the stock trading process works and then address a number of questions. How have the jobs of traditional stock market dealers on the NYSE and on Nasdaq been affected by electronic trading? How do electronic communications networks differ from traditional markets? How has electronic trading affected bid-ask spreads and commission costs? What subtle issues arise in electronic trading when dealer and customer interests diverge? Will computer programs replace human judgment? What is the effect of electronic trading on the number and types of securities markets? What is the role of regulation in electronic markets?

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PENGARUH FREKUENSI PERDAGANGAN PADA SEKTOR PROPERTY DAN REAL ESTATE TERHADAP HARGA SAHAM

Jurnal Ilmiah Binaniaga ◽

10.33062/jib.v7i02.311 ◽

2019 ◽

Vol 7 (02) ◽

pp. 51

Author(s):

Adri Wihananto

Keyword(s):

Real Estate ◽

Stock Price ◽

Stock Exchange ◽

Stock Trading ◽

Trading Frequency ◽

Important Thing ◽

Know How ◽

Stock Value ◽

Measuring Frequency ◽

Case Based

Trading frequency can be said as the implementation from trader of commerce. This case based on positive or negative trader reaction given by trader information. Stock trading in BEI always fluctuate with price of volume value and frequency particularly. Frequency itself shows the company involved or not. In trading frequency, if the indicator frequency it self shown the higher point, it means better. In spite of the most important thing is how the fluctuation or value conversion itself. On the frequencies we also could see which stocks is interested by the investor. When trading frequency high, it may be create sense of interest from investors.The aim of this research, in order to know how far the effect of trading frequency (X) with stock value (Y) using cover stock value. The information used is begin 2008 with sample from twelve property and real estate companies. According to the research can be conclude from twelve companies in Indonesia Stock Exchange in 2008, 75 % of trading frequency samples doesn’t have signification degree between trading frequency and stock value. This case can be explained count on smaller than t tableEvaluation of this research is the trading measuring frequency at property sector and real estate not influence to stock priceKeywords : Trading Frequency, Stock Price

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Drug Utilization Studies – An Overview

International Journal of Pharmaceutical Sciences and Nanotechnology ◽

10.37285/ijpsn.2010.3.1.2 ◽

2010 ◽

Vol 3 (1) ◽

pp. 803-810 ◽

Cited By ~ 3

Author(s):

Shalini S ◽

Ravichandran V ◽

Saraswathi R ◽

BK Mohanty ◽

Dhanaraj S K

Keyword(s):

Drug Utilization ◽

Evidence Based ◽

Future Trends ◽

Medical Prescription ◽

Drug Usage ◽

Current State ◽

Patterns Of Use ◽

Drug Utilization Studies ◽

Drug Expenditures

Aspire of the Drug Utilization Studies (DUS) is to appraise factors related to the prescribing, dispensing, administering and taking of medication, and it’s associated. Since the middle of twentieth century, interest in DUS has been escalating, first for market-only purposes, then for appraising the quality of medical prescription and comparing patterns of use of specific drugs. The scope of DUS is to evaluate the current state and future trends of drug usage, to estimate roughly disease pervasiveness, drug expenditures, aptness of prescriptions and adherence to evidence-based recommendations. The increasing magnitude of DUS as a valuable investigation resource in pharmacoepidemiology has been bridging it with other health allied areas, such as public health, rational use of drug, evidence based drug use, pharmacovigilance, pharmacoeconomics, eco-pharmacovigilance and pharmacogenetics.

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Conceptual Framework to Support Clinical Trial Optimization and End-to-End Enrollment Workflow

JCO Clinical Cancer Informatics ◽

10.1200/cci.19.00033 ◽

2019 ◽

pp. 1-10 ◽

Cited By ~ 3

Author(s):

Neha M. Jain ◽

Alison Culley ◽

Teresa Knoop ◽

Christine Micheel ◽

Travis Osterman ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Knowledge Representation ◽

Conceptual Framework ◽

Trial Design ◽

Clinical Trial Design ◽

Prospective Clinical Trial ◽

Future Trends ◽

Current State ◽

Evaluation Strategies

In this work, we present a conceptual framework to support clinical trial optimization and enrollment workflows and review the current state, limitations, and future trends in this space. This framework includes knowledge representation of clinical trials, clinical trial optimization, clinical trial design, enrollment workflows for prospective clinical trial matching, waitlist management, and, finally, evaluation strategies for assessing improvement.

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Future trends in diagnosis using laboratory-on-a-chip technologies

Parasitology ◽

10.1017/s0031182099004126 ◽

1999 ◽

Vol 117 (7) ◽

pp. 191-203 ◽

Cited By ~ 16

Author(s):

M. S. TALARY ◽

J. P. H. BURT ◽

R. PETHIG

Keyword(s):

Gene Expression ◽

Lower Cost ◽

Building Blocks ◽

Cancer Diagnostics ◽

Future Trends ◽

Biotechnological Applications ◽

Environmental Testing ◽

Current State ◽

Microelectronic Fabrication ◽

Wide Range

There has been an enormous growth in the development of biotechnological applications, where advances in the techniques of microelectronic fabrication and the technologies of miniaturization and integration in semiconductor industries are being applied to the production of Laboratory-on-a-Chip devices. The aim of this development is to create devices that will perform the same processes that are currently carried out in the laboratory in reduced timescales, at a lower cost, requiring less reagents, and with a greater resolution of detection and specificity. The expectations of this Laboratory-on-a-Chip revolution is that this technology will facilitate rapid advances in gene discovery, genetic mapping and gene expression with broader applications ranging from infectious diseases and cancer diagnostics to food quality and environmental testing. A review of the current state of development in this field reveals the scale of the ongoing revolution and serves to highlight the advances that can be perceived in the development of Laboratory-on-a-Chip technologies. Since miniaturization can be applied to such a wide range of laboratory processes, some of the sub-units that can be used as building blocks in these devices are described, with a brief description of some of the fabrication processes that can be used to create them.

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Simulation of Stock Prediction System using Artificial Neural Networks

International Journal of Business Analytics ◽

10.4018/ijban.2016070102 ◽

2016 ◽

Vol 3 (3) ◽

pp. 25-44 ◽

Cited By ~ 1

Author(s):

Omisore Olatunji Mumini ◽

Fayemiwo Michael Adebisi ◽

Ofoegbu Osita Edward ◽

Adeniyi Shukurat Abidemi

Keyword(s):

Test Data ◽

Stock Prices ◽

Prediction Accuracy ◽

Stock Exchange ◽

Training Data ◽

Prediction System ◽

Stock Trading ◽

Closing Price ◽

Non Linear ◽

Predicted Values

Stock trading, used to predict the direction of future stock prices, is a dynamic business primarily based on human intuition. This involves analyzing some non-linear fundamental and technical stock variables which are recorded periodically. This study presents the development of an ANN-based prediction model for forecasting closing price in the stock markets. The major steps taken are identification of technical variables used for prediction of stock prices, collection and pre-processing of stock data, and formulation of the ANN-based predictive model. Stock data of periods between 2010 and 2014 were collected from the Nigerian Stock Exchange (NSE) and stored in a database. The data collected were classified into training and test data, where the training data was used to learn non-linear patterns that exist in the dataset; and test data was used to validate the prediction accuracy of the model. Evaluation results obtained from WEKA shows that discrepancies between actual and predicted values are insignificant.

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