Neural networks are state-of-the-art, trainable algorithms that emulate certain major aspects in the functioning of the human brain.

Stock market prediction - Wikipedia

This gives them a unique, self-training ability, the ability to formalize unclassified information and, most importantly, the ability to make forecasts based on the historical information they have at their disposal. Neural networks have been used increasingly in a variety of business applications, including forecasting and marketing research solutions.

In some areas, such as fraud detection or risk assessment , they are the indisputable leaders. The major fields in which neural networks have found application are financial operations, enterprise planning, trading, business analytics and product maintenance.

Stock Market Predicition with Feed-Forward Neural Networks

Neural networks can be applied gainfully by all kinds of traders, so if you're a trader and you haven't yet been introduced to neural networks, we'll take you through this method of technical analysis and show you how to apply it to your trading style.

Common Delusions Most people have never heard of neural networks and, if they aren't traders, they probably don't need to know what they are. What's really surprising, however, is the fact that a huge number of those who could benefit richly from neural network technology have never even heard of it, take it for a lofty scientific idea or think of it as of a slick marketing gimmick.

There are also those who pin all their hopes on neural networks, lionizing the nets after some positive experience with them and regarding them as a silver-bullet solution to any kind of problem. However, like any trading strategy , neural networks are no quick-fix that will allow you to strike it rich by clicking a button or two. In fact, the correct understanding of neural networks and their purpose is vital for their successful application. As far as trading is concerned, neural networks are a new, unique method of technical analysis, intended for those who take a thinking approach to their business and are willing to contribute some time and effort to make this method work for them.

Best of all, when applied correctly, neural networks can bring a profit on a regular basis. Use Neural Networks to Uncover Opportunities A major misconception is that many traders mistake neural networks for a forecasting tool that can offer advice on how to act in a particular market situation.

Neural networks do not make any forecasts. Instead, they analyze price data and uncover opportunities. Using a neural network, you can make a trade decision based on thoroughly analyzed data, which is not necessarily the case when using traditional technical analysis methods.

For a serious, thinking trader, neural networks are a next-generation tool with great potential that can detect subtle non-linear interdependencies and patterns that other methods of technical analysis are unable to uncover.

The Best Nets Just like any kind of great product or technology, neural networks have started attracting all those who are looking for a budding market.

Torrents of ads about next-generation software have flooded the market - ads celebrating the most powerful of all the neural network algorithms ever created. In other words, it doesn't produce miraculous returns and regardless of how well it works in a particular situation, there will be some data sets and task classes for which the previously used algorithms remain superior.

Well-prepared input information on the targeted indicator is the most important component of your success with neural networks. Is Faster Convergence Better? Many of those who already use neural networks mistakenly believe that the faster their net provides results, the better it is. This, however, is a delusion.

A good network is not determined by the rate at which it produces results and users must learn to find the best balance between the velocity at which the network trains and the quality of the results it produces. Correct Application of Neural Nets Many traders apply neural nets incorrectly because they place too much trust in the software they use all without having been provided with proper instructions on how to use it properly.

To use a neural network the right way and, thus, gainfully, a trader ought to pay attention to all the stages of the network preparation cycle.

It is the trader and not his or her net that is responsible for inventing an idea, formalizing this idea, testing and improving it, and, finally, choosing the right moment to dispose of it when it's no longer useful. Let us consider the stages of this crucial process in more detail:. Finding and Formalizing a Trading Idea A trader should fully understand that his or her neural network is not intended for inventing winning trading ideas and concepts.

Neural Networks - Applications

It is intended for providing the most trustworthy and precise information possible on how effective your trading idea or concept is. Therefore, you should come up with an original trading idea and clearly define the purpose of this idea and what you expect to achieve by employing it.

This is the most important stage in the network preparation cycle. Improving the Parameters of Your Model Next, you should try to improve the overall model quality by modifying the data set used and adjusting the different the parameters. Disposing of the Model When it Becomes Obsolete Every neural-network based model has a life span and cannot be used indefinitely. The longevity of a model's life span depends on the market situation and on how long the market interdependencies reflected in it remain topical.

However, sooner or later any model becomes obsolete. When this happens, you can either retrain the model using completely new data i.

Many traders make the mistake of following the simplest path - they rely heavily on and use the approach for which their software provides the most user-friendly and automated functionality.

This simplest approach is forecasting a price a few bars ahead and basing your trading system on this forecast. Other traders forecast price change or percentage of the price change. This approach seldom yields better results than forecasting the price directly.

Both the simplistic approaches fail to uncover and gainfully exploit most of the important longer-term interdependencies and, as a result, the model quickly becomes obsolete as the global driving forces change.

The Most Optimal Overall Approach to Using Neural Networks A successful trader will focus and spend quite a bit of time selecting the governing input items for his or her neural network and adjusting their parameters.

He or she will spend from at least several weeks - and sometimes up to several months - deploying the network. A successful trader will also adjust his or her net to the changing conditions throughout its life span. Because each neural network can only cover a relatively small aspect of the market, neural networks should also be used in a committee.

Use as many neural networks as appropriate - the ability to employ several at once is another benefit of this strategy. In this way, each of these multiple nets can be responsible for some specific aspect of the market, giving you a major advantage across the board.

However, it is recommended that you keep the number of the nets you use within the range of five to Finally, neural networks should be combined with one of the classical approaches.

This will allow you to better leverage the results achieved in accordance with your trading preferences. Conclusion You will experience real success with neural nets only when you stop looking for the best net.

After all, the key to your success with neural networks lies not in the network itself, but in your trading strategy.

Therefore, to find a profitable strategy that works for you, you must develop a strong idea about how to create a committee of neural networks and use them in combination with classical filters and money management rules.

For related reading, check out Neural Trading: Biological Keys To Profit and the Trading Systems Coding Tutorial. Dictionary Term Of The Day. A measure of what it costs an investment company to operate a mutual fund. Latest Videos PeerStreet Offers New Way to Bet on Housing New to Buying Bitcoin?

This Mistake Could Cost You Guides Stock Basics Economics Basics Options Basics Exam Prep Series 7 Exam CFA Level 1 Series 65 Exam. Sophisticated content for financial advisors around investment strategies, industry trends, and advisor education. Forecasting Profits By Dima Vonko Share. Let us consider the stages of this crucial process in more detail: Specifying the optimization algorithm and its properties 3.

Technical analysis is a hotly debated topic. Discover evidence showing that it works in forex markets. This influential strategy capitalizes on the relationship between price and liquidity. Elon Musk's latest company Neuralink aims to bridge the gap between human cognition and computers by developing neural lace technology. Facebook says they have AI technology that can translate languages nine times faster than its peers. This article will take an objective look at day trading, who does it and how it is done.

Understand how networking stocks fit into the technology sector. Learn about four leading networking companies that investors should own in Effective networking is essential for financial advisors looking to grow their practice.

Here are some tips on how to make the process easier. Having a network of people in the same profession as you can improve your career prospects.

Here's how to build a professional network while you are still in school. Find out the who, the how and the why of using networking to move up in your career. Gather information and keep in touch through networking without bombarding clients or you may risk losing a client in a challenging Read about who founded LinkedIn and what factors led its founder to develop the Internet's largest social network of professionals. Understand the difference between financial forecasting and financial modeling, and learn why a company should conduct both An expense ratio is determined through an annual A hybrid of debt and equity financing that is typically used to finance the expansion of existing companies.

A period of time in which all factors of production and costs are variable.

In the long run, firms are able to adjust all A legal agreement created by the courts between two parties who did not have a previous obligation to each other. A macroeconomic theory to explain the cause-and-effect relationship between rising wages and rising prices, or inflation.

A statistical technique used to measure and quantify the level of financial risk within a firm or investment portfolio over No thanks, I prefer not making money. Content Library Articles Terms Videos Guides Slideshows FAQs Calculators Chart Advisor Stock Analysis Stock Simulator FXtrader Exam Prep Quizzer Net Worth Calculator. Work With Investopedia About Us Advertise With Us Write For Us Contact Us Careers. Get Free Newsletters Newsletters.

All Rights Reserved Terms Of Use Privacy Policy.