This website uses cookies to ensure you have the best experience. Learn more

Neural Networks In Investments Essay

2692 words - 11 pages

Neural Networks in Investments


Investment managers often find themselves overwhelmed with the large amount of data obtained from the financial markets. Most of the data available is numeric and noisy in nature, making the decision-making process harder. These decisions usually rely on the integration of statistical measures that attempt to compress much of the data and qualitative depictions such as graphs and bar charts with news events and other pertinent information. Investment decisions usually involve non-linear relationships among the various components of the data. Computers in general, are very adept at dealing with large amounts of numeric information. However, some algorithms are crucial in analyzing and combining disparate information that can impact security prices. Artificial Intelligence based methods uses clever algorithms and rules of thumb (heuristics) in the decision-making process. Neural Network and expert systems applications have been successfully deployed in the domain of Finance, and in the area of investment management.

This paper discusses the basics and the theory behind neural networks and provides an introduction to an application area of neural networks in the domain of Finance. The application areas of Neural Networks discussed in the paper are corporate finance, financial institutions, and the professional investor. The purpose of the second paper will be to discuss the specifics of each of these applications.

Neural network computing is an information processing method that was developed from research to make computers that could imitate the way people learned. The field initially grew from 1930s ideas about how biological systems like the human brain works. Today neural network systems are being used in business, government, and academic research because of their power to model data quickly and to produce better results than other more traditional data analysis techniques. At the simplest level, neural networks are a new way of analyzing data. The revolutionary aspect of neural networks is their ability to learn and trace the complex patterns and trends in data. Neural networks are made up of neurons and behave like the human brain, and has the ability to apply knowledge from past experience to new problems. Neural networks acquire this knowledge by training on a set of data. After the network has been trained and validated, the model may be applied to data it has not seen previously for prediction, classification, time series analysis or data segmentation.

Unlike traditional statistical methods, neural networks do not require assumptions about the model form. A statistical analysis requires a certain form to be assumed such as linearity, which characterizes relationships between variables. Neural networks are more tolerant of imperfect data, such as the presence of missing values or other data quality problems. Neural networks perform better than traditional...

Find Another Essay On Neural Networks in Investments

Neural Engineering Essay

617 words - 2 pages Neural engineering refers to a new discipline that has emerged by combining engineering technologies and mathematical/computational methods with neuroscience techniques. The objective is to enhance our understanding of the functions of the human nervous system. Neural engineering also holds promise to improve human performance, especially after injury or disease. As befits such a broad definition, the field is multidisciplinary, in that it draws

Artificial Neural Networks Essay

1124 words - 4 pages Artificial neural networks (ANNs) were built to model the brain for the purpose of solving the problems humans alone cannot as well as to advance, artificial intelligence. To approximate organic beings and gain great computational power, to become a technological hybrid between sentient beings and advanced electronics; they are the future of advanced robotics. They can be used in miscellaneous fields such as speech recognition, prediction of

Voting Based Extreme Learning Machine

1422 words - 6 pages . [10] T. Nitta, The computational power of complex-valued neuron, Artificial Neural Networks and Neural Information Processing ICANN/ICONIP, Lec- 325 ture Notes in Computer Science 2714 (2003) 993–1000. [11] T. Nitta, Orthogonality of decision boundaries of complex-valued neural networks, Neural Computation 16 (1) (2004) 73–97. 22 [ [12] T. Nitta, On the inherent property of the decision boundary in complex- valued neural networks, Neurocomputing

Potential of Applying the Radial Basis Function

651 words - 3 pages distinguishing pathologic fromnormal inmost cases and for heterogeneous fibrotic foci, achieving high values in terms of specificity and sensitivity. Index Terms—Image analysis, interstitial pulmonary fibrosis, neural networks, quantitative assessment of microscopic images, quantitative phenotypic classification, support vector machines. Manuscript received October 18, 2005; revised June 4, 2006 and September 21, 2006. I. Maglogiannis is

Artificial Neural Network for non-Linear Dynamic Process of a Cyclone Scrubber

1469 words - 6 pages [Galvan et al., 1996; Chouai et al., 2001; Roj and Wilk, 1998; Parisi and Labored, 2001; Iliuta and Lavric, 1999]. Although the neural network has been applied in several complex chemical engineering processes, it was very rarely applied in the cyclone scrubber system. In the present work, a model using three-layer feed-forward neural networks (3-FFNN) to estimate the overall CO2 absorbed flux is proposed. EXPERIMENTAL METHOD The experimental

Artificial Intelligence (AI)

2804 words - 11 pages This research Paper has problems with formatting ABSTRACT Current neural network technology is the most progressive of the artificial intelligence systems today. Applications of neural networks have made the transition from laboratory curiosities to large, successful commercial applications. To enhance the security of automated financial transactions, current technologies in both speech recognition and handwriting recognition are likely

Mind And Machine

2420 words - 10 pages AI Thesis. This hope lies in the advent of neural networks and the application of fuzzy logic engines. Fuzzy logic was created as a subset of boolean logic that was designed to handle data that is neither completely true, nor completely false. Intoduced by Dr. Lotfi Zadeh in 1964, fuzzy logic enabled the modelling of uncertainties of natural language. Dr. Zadeh regards fuzzy theory not as a single theory, but as "fuzzification", or

Artificial Inteligence

2576 words - 10 pages ABSTRACTCurrent neural network technology is the most progressive of the artificial intelligencesystems today. Applications of neural networks have made the transition from laboratorycuriosities to large, successful commercial applications. To enhance the security of automatedfinancial transactions, current technologies in both speech recognition and handwritingrecognition are likely ready for mass integration into financial

Mind and Machine, an essay on A.I

2375 words - 10 pages semantical output, but again, is it really cognizant?We, through Searle's arguments, have amply established that the future of AI lies not in the semantic cognition of data by machines, but in expert systems designed to perform ordered tasks.Technologically, there is hope for some of the proponents of Strong AI Thesis. This hope lies in the advent of neural networks and the application of fuzzy logic engines.Fuzzy logic was created as a subset of

A Novel Neuro-fuzzy Classification Technique

1002 words - 5 pages different aspects of uncertainties or incompleteness about real life situations. In a fuzzy system the features are associated with a degree of membership to different classes. Both NNs and fuzzy systems are very adaptable in estimating the input-output relationships. Neural networks deal with numeric and quantitative data while fuzzy systems can handle symbolic and qualitative information. Therefore it would be nice to combine these two approaches so

Speaker identification and verification over short distance telephone lines using artificial neural networks

2481 words - 10 pages SPEAKER IDENTIFICATION AND VERIFICATION OVER SHORT DISTANCE TELEPHONE LINES USING ARTIFICIAL NEURAL NETWORKS Ganesh K Venayagamoorthy, Narend Sunderpersadh, and Theophilus N Andrew Electronic Engineering Department, M L Sultan Technikon, P O Box 1334, Durban, South Africa. ABSTRACT Crime and corruption have become rampant today in our society and countless money is lost each year due

Similar Essays

Predicting Customer Churn In Telecom Industry Using Mlp Neural Networks

2470 words - 10 pages ]. Supervised ML concerns the developing of models whichcan learn from labeled data. ML includes a wide rangeof algorithms such as Decision trees, k-nearest neighbors,Linear regression, Naive Bayes, Neural networks, Supportvector machines (SVM), Genetic Programming and many others. For example, in [5] authors conducted a comparative analysis of linear regression and two machine learning techniques; neural networks and decision trees for predicting

Neural Networks Essay

1326 words - 5 pages Neural Networks Abstract This paper will provide an introductory level discussion of neural networks within the field of artificial intelligence. This discussion will briefly cover the history of the neural network as well as recent advances within this field. In addition, several real world applications of neural networks will be discussed. Introduction The primary goal in the field of artificial intelligence is to construct a machine

Study On The Rbf Neural Network Approach To Quick Cost Estimate Of Construction Projects

5512 words - 22 pages stages of conception to the construction phase. Several techniques have been suggested for conceptual cost estimation. Regression analysis, simulation, and neural networks are among these cost estimation techniques that are used during the early project stages. In regression analysis the project cost is estimated with a regression model including a number of independent variables. Because the type of building has an important effect on the project

Neural Network Concept In Artificial Intelligence

1918 words - 8 pages Neural Network Concept in Artificial Intelligence Abstract Since the 1980's there have been renewed research efforts dedicated to neural networks. The present interest is largely due to the difficult problems confronted by artificial intelligence, and due to the deeper understanding of how the brain works, the recent developments in theoretical models, technologies and algorithms. One motivation of neural network research is the desire to