DEFINITION of 'Neural Network'
A neural network is a series of algorithms that attempts to identify underlying relationships in a set of data by using a process that mimics the way the human brain operates. Neural networks have the ability to adapt to changing input so the network produces the best possible result without the need to redesign the output criteria. The concept of neural networks is rapidly increasing in popularity in the area of developing trading systems.
BREAKING DOWN 'Neural Network'
In finance, neural networks are used for timeseries forecasting, algorithmic trading, securities classification, credit risk modeling and constructing proprietary indicators and price derivatives.
How a Neural Network Operates
A neural network operates similar to the brain’s neural network. A “neuron” in a neural network is a simple mathematical function capturing and organizing information according to an architecture. The network closely resembles statistical methods such as curve fitting and regression analysis.
A neural network consists of layers of interconnected nodes. Each node is a perceptron and resembles a multiple linear regression. The perceptron feeds the signal generated by a multiple linear regression into an activation function that may be nonlinear.
In a multilayered perceptron (MLP), perceptrons are arranged in interconnected layers. The input layer receives input patterns. The output layer contains classifications or output signals to which input patterns may map. For example, the patterns may be a list of quantities for technical indicators regarding a security; potential outputs could be “buy,” “hold” or “sell.” Hidden layers adjust the weightings on the inputs until the error of the neural network is minimal. It is theorized that hidden layers extract salient features in the input data that have predictive power with respect to the outputs. This describes feature extraction, which performs a function similar to statistical techniques such as principal component analysis.
Application of Neural Networks
Neural networks are widely used in financial operations, enterprise planning, trading, business analytics and product maintenance. Neural networks are common in business applications such as forecasting and marketing research solutions, fraud detection and risk assessment.
A neural network analyzes price data and uncovers opportunities for making trade decisions based on thoroughly analyzed data. The networks can detect subtle nonlinear interdependencies and patterns other methods of technical analysis cannot uncover. However, a 10% increase in efficiency is all an investor can expect from a neural network. There will always be data sets and task classes for which previously used algorithms remain superior. The algorithm is not what matters; it is the wellprepared input information on the targeted indicator that determines the success of a neural network.

Networking
A process that fosters the exchange of information and ideas ... 
Economic Network
A combination of individuals, groups or countries interacting ... 
Value Network Analysis
The analysis of the members and the interactions of these members ... 
Value Network
A set of connections between organizations and/or individuals ... 
Distribution Network
An interrelated arrangement of people, storage facilities and ... 
Social Networking
The use of internetbased social media programs to make connections ...

Trading
Neural Networks: Forecasting Profits
Take a look at the algorithmic approach to technical trading  you may never go back! 
Trading
Technical Analysis Works In Forex Markets
Technical analysis is a hotly debated topic. Discover evidence showing that it works in forex markets. 
Trading
Arbitrage Squeezes Profit From Market Inefficiency
This influential strategy capitalizes on the relationship between price and liquidity. 
Trading
What are Genetic Algorithms?
Genetic algorithms are problemsolving methods that mimic natural evolution processes. 
Insights
4 Networking Stocks that You Must Own (AKAM, CSCO)
Understand how networking stocks fit into the technology sector. Learn about four leading networking companies that investors should own in 2015. 
Personal Finance
Does an Insurance Plan Network Affect Your Health?
Socalled narrow networks have been criticized. But it's not necessarily true that they have a negative impact on the medical care you get. 
Markets
WWE Network Proves to Be What's Best for Business
World Wrestling Entertainment (NYSE: WWE) has established its overthetop streaming network as a replacement for payperview revenue. Even though network subscriber numbers move up and down ... 
Trading
Using Genetic Algorithms To Forecast Financial Markets
Genetic algorithms are unique ways to solve complex problems by harnessing the power of nature. 
Financial Advisor
A Networking Cheat Sheet for Advisors
Effective networking is essential for financial advisors looking to grow their practice. Here are some tips on how to make the process easier. 
Managing Wealth
10 Tips for Strategic Networking
Learn the rules of networking so you can operate like a pro. After all, maintaining a strong network is essential in today's job environment.

What's the difference between diminishing marginal returns and returns to scale?
Understand the main differences between the law of diminishing marginal returns and the concept of returns to scale through ... Read Answer >> 
What bachelor's degree would help me begin my climb to the top of a hedge fund?
I am currently in school pursuing my AA and will be transferring to FIT next year. I am convinced that ... Read Answer >> 
What are some of the more common types of regressions investors can use?
Learn about the most common types of regressions investors use to model asset prices including linear regressions and multiple ... Read Answer >> 
What is the difference between linear regression and multiple regression?
Learn the difference between linear regression and multiple regression and how multiple regression encompasses not only linear ... Read Answer >> 
How can I run linear and multiple regressions in Excel?
Learn the steps involved in running a regression in Microsoft Excel: preparations, uploading data and using the regression ... Read Answer >> 
How is productivity calculated?
Learn about productivity, what productivity measures and how to compute a company's productivity level by measuring its outputs ... Read Answer >>