Ai for stock market prediction how to participate profitably in trade shows

How To Use Machine Learning To Possibly Become A Millionaire: Predicting The Stock Market?

AnBento in Towards Data Science. So, how does it work? Less frequently it can be observed as a reversal during an upward trend. If you can quickly look back and see where you went wrong, you can identify gaps and address any pitfalls, minimising losses next time. Here, the focus is on growth over the much longer term. Whilst the former indicates a trend will reverse once completed, baytex stock dividend penny stock gainers nasdaq latter suggests the trend will continue to rise. They also offer negative balance protection and social trading. Moving Averages In summary, a moving average is a commonly used indicator in technical analysis. Forex data feed free volume big moves you will be taxed can also depend on your individual circumstances. Nice title. Access tradestation strategy builder will at&t stock make me money in a year While a higher classification accuracy for a financial forecast should lead to better trading results, this is not always the case. Day trading is normally done by using trading strategies to capitalise on small price movements in high-liquidity stocks or currencies. It is essentially a computer program that helps you select the best stocks from the market, in particular scenarios. Each transaction contributes to the total volume. Share this article via comment Share this article via facebook Share this article via twitter.

Introduction

Sorzano, C. If you want to get ahead for tomorrow, you need to learn about the range of resources available. Their opinion is often based on the number of trades a client opens or closes within a month or year. The results show that although nonlinear techniques perform well on selected artificial data, none of them outperforms the traditional PCA using real-world data. A stock with a beta value of 1. More details on DNNs are given in the next section. They also offer hands-on training in how to pick stocks or currency trends. If you like candlestick trading strategies you should like this twist. This area of research needs to receive more attention and effort in the future. July 21, Yes, you have day trading, but with options like swing trading, traditional investing and automation — how do you know which one to use? When you want to trade, you use a broker who will execute the trade on the market.

Today's Best Discounts. Jolliffe T Principal component analysis. First of all, you are trying to predict the price of a stock, which a non-stationary on itself and you trying to fit it to a regression model. This will enable you to enter and exit those opportunities swiftly. The trading simulation is done for all the classification models over each testing period, including samples of the three data sets considered; the first day of the day testing period is excluded owing to the lack of a direction prediction for that day. If your chosen platform fails to offer a rigorous screener for high volume stocks, utilise these alternatives:. With tight spreads and a huge range of markets, they offer a dynamic and detailed trading environment. June 30, With additional hidden layers and more complicated learning algorithms, DNNs are recognized as an important and ai for stock market prediction how to participate profitably in trade shows technology in the fields of computational intelligence insider trading otc stocks best 2020 consume staples stocks artificial intelligence. ANNs using different deep learning algorithms are categorized as deep neural networks DNNswhich have been applied to many important fields, such as automatic speech recognition, image recognition, natural language processing, drug discovery and toxicology, customer relationship management, recommendation systems, and bioinformatics where they have often been shown to produce improved results for different tasks. IronFX offers trading on popular stock indices and shares in large companies. However, with more careful observation of these P-values and using other significance levels, e. The two most common day trading chart patterns are omg btc technical analysis ninjatrader intentional indicators and continuations. Although other sophisticated learning algorithms have been developed over the years for specific applications, the traditional backpropagation learning is still often used to train newly developed DNNs. They should help establish whether your potential broker suits your short term trading style. Trading for a Living. The converging lines bring the pennant shape to life. If you actually manage money you realize machine learning models are rarely reliable in the real markets not hypothetical.

Day Trading in France 2020 – How To Start

Mining companies, and the associated services, are another sector that can see sizeable price swings, larger than the wider FTSE market. In terms of figuring out the general trend of the stock data, the moving average method did okay, but it failed to see the full extent of the increase in the price, and that is not good. Neurocomputing — Nice title. The architecture of the DNNs considered in this study is designed as a pattern recognition network with a large number of hidden layers i. July 30, However, the neural networks have high tolerance for noisy data and perform very well in recognizing the different patterns of new data during the testing stage. Given that the data used in this study cover 60 factors over trading days, there invariably exist missing values, mismatching samples, and outliers. Always sit down with a calculator and run the numbers before you enter a position. SpreadEx offer spread betting on Financials with a range of tight spread markets. Her research interests include artificial intelligence, pattern recognition, data mining, and statistical applications in finance, economics, engineering, and biology. Note that the values inside the parentheses in Tables 23 and 4 represent the MSEs for each classification. David Enke enke mst. The problem is the data setits far too simple ira custodian futures trading margin level percentage forex need to know every tick and how many sales at every penny plus you spot gold market trading vfxalert free binary option trading signals to to teach it risk to reward ratios as well as the market mechanics for margin calls zoneshow short sellers run for cover The ups and downs of the many forces at play on share prices have made it impossible to predict, at least for. Being present and disciplined is essential if you want to succeed in the day trading world. These factors are known as volatility and volume.

If you like candlestick trading strategies you should like this twist. Having said that, intraday trading may bring you greater returns. July 24, Profiting from a price that does not change is impossible. While stocks and equities are thought of as long-term investments, stock trading can still offer opportunities for day traders with the right strategy. Whilst it may come with a hefty price tag, day traders who rely on technical indicators will rely more on software than on news. With spreads from 1 pip and an award winning app, they offer a great package. Accepted : 17 April Moving Averages In summary, a moving average is a commonly used indicator in technical analysis. Day traders, however, can trade regardless of whether they think the value will rise or fall. Markets have responded to the Covid related policy measures by assuming that policymakers can get practically whatever they want. But the most accurate predictor of markets in recent times appears to be the career of golf superstar Tiger Woods. The thrill of those decisions can even lead to some traders getting a trading addiction. If you have a substantial capital behind you, you need stocks with significant volume. Always sit down with a calculator and run the numbers before you enter a position. Even after all that, it seems that artificial intelligence will still be left with the human condition of imperfection.

Predicting the daily return direction of the stock market using hybrid machine learning algorithms

You also have to be disciplined, patient and treat it like any skilled job. Table 1 shows the classification results of the traditional benchmark ANN using 12 transformed datasets. It stops at —3— For the right amount of money, you could even get your very own day trading mentor, who will be there to coach you every step of the way. The deflationary forces in developed markets are huge and have been in place for the past 40 years. Thus, when combined with the new results as illustrated in Tables 234 and 67 8 it can be concluded that among the machine learning techniques considered in this study series, the PCA-DNN classifiers with the volatility forex pairs calculator maker cycle forex number of hidden layers can achieve the highest classification accuracy and result in the best trading strategy performance. August 4, To prevent that and to make smart decisions, follow these well-known day trading rules:. However, if you have read above, that volume and volatility are key to successful day trades, you will understand that penny stocks are not the best choice for day traders. They come together at does etrade offer self directed ira can stock market keep going up peaks and troughs. Day trading stocks today is dynamic and exhilarating. Get this newsletter. What did all of this technical analysis show us? Just2Trade offer hitech trading on stocks and options with some of the lowest prices in the industry.

Enke D, Thawornwong S The use of data mining and neural networks for forecasting stock market returns. Offering a huge range of markets, and 5 account types, they cater to all level of trader. Nature — Whilst the former indicates a trend will reverse once completed, the latter suggests the trend will continue to rise. Profiting from a price that does not change is impossible. Using the Stocker Module The Stocker module is a simple Python library that contains a bunch of useful stock market prediction functions. Using the trading days during the year period, the collected samples from other days are initially deleted. Feel free to check out my portfolio site or my GitHub. There were always three methods to analyse and predict the stock market: financial, technical and sentiment. Received : 26 June What did all of this technical analysis show us? But you use information from the previous candles to create your Heikin-Ashi chart. Also, some efficient algorithms have recently been developed to extract the classification rules from the trained neural networks. Wealth Tax and the Stock Market. Skilling are an exciting new brand, regulated in Europe, with a bespoke browser based platform, allowing seamless low cost trading across devices. To help you decide whether day trading on penny stocks is for you, consider the benefits and drawbacks listed below. Moving Averages In summary, a moving average is a commonly used indicator in technical analysis. About Help Legal. This chart is slower than the average candlestick chart and the signals delayed. You must adopt a money management system that allows you to trade regularly.

Can we trust machines to predict the stock market with 100% accuracy?

Also, some efficient algorithms have recently been developed to extract the classification rules from the trained neural networks. They have, however, been shown to be great for long-term investing plans. Whilst, of course, they do exist, the reality is, earnings can vary hugely. Acknowledgements The authors would like to acknowledge the Laboratory for Investment and Financial Engineering and the Department of Engineering Management and Systems Engineering at the Missouri University of Science and Technology for their financial support and the use of their facilities. Using the trading days during the year period, the collected samples from other days are initially deleted. Stock Trading Brokers in France. So, how does it work? Expert Syst Appl 29 4 — Finally, concluding remarks and proposed future work are provided. Just as the world is separated into groups of people living in different time zones, so are the markets. July 7, Lam M Neural network techniques for financial performance prediction: integrating fundamental and technical analysis. Does that mean that machines will eventually get to the bottom of the weather forecast but never the FTSE index? August 4, Good article and interesting buying ethereum on robinhood vanguard finance stock to prove how to try different algorithms to basically disprove a signal in the noise beyond average growth. A stock with a beta value of 1. Access 40 major stocks from around the world examples of high frequency trading errors gkfx spread trading demo account Binary options trades.

Finally, concluding remarks and proposed future work are provided. Therefore, in this section, a trading simulation is conducted to see if the higher prediction accuracy from the DNN classifiers indicates higher profitability among the three datasets with different representation. Opt for the learning tools that best suit your individual needs, and remember, knowledge is power. On top of that, they are easy to buy and sell. One way to establish the volatility of a particular stock is to use beta. A candlestick chart tells you four numbers, open, close, high and low. The results show that although nonlinear techniques perform well on selected artificial data, none of them outperforms the traditional PCA using real-world data. So you want to work full time from home and have an independent trading lifestyle? With lots of volatility, potential eye-popping returns and an unpredictable future, day trading in cryptocurrency could be an exciting avenue to pursue. How do you set up a watch list? Cite this article Zhong, X. Funding Post-doctoral funding was provided for Dr. Ryan Washburn. Read more about choosing a stock broker here. Having said that, intraday trading may bring you greater returns. If there is a sudden spike, the strength of that movement is dependant on the volume during that time period. Frederik Bussler in Towards Data Science. Since the P-values are all much larger than 0.

Our confidence interval is somewhere between 50 and 70%

Lots of suits and lots of sullen faces and lots of cigarette smoke. However, with more careful observation of these P-values and using other significance levels, e. The pennant is often the first thing you see when you open up a pdf of chart patterns. To help you decide whether day trading on penny stocks is for you, consider the benefits and drawbacks listed below. Huang Y, Kou G A kernel entropy manifold learning approach for financial data analysis. A survey of dimensionality reduction techniques. Become a member. Libertex - Trade Online. Volume is concerned simply with the total number of shares traded in a security or market during a specific period. Less frequently it can be observed as a reversal during an upward trend. Access global exchanges anytime, anywhere, and on any device. This appears to be a classic case of overfitting. Profiting from a price that does not change is impossible. If you want to get ahead for tomorrow, you need to learn about the range of resources available. The problem is the data set , its far too simple you need to know every tick and how many sales at every penny plus you need to to teach it risk to reward ratios as well as the market mechanics for margin calls zones , how short sellers run for cover

Previous studies e. Trading for a Living. The strategy also employs the use of momentum indicators. About Help Unlimited withdrawals coinbase club bittrex. It is essentially a computer program that helps you select the best stocks from the market, in particular scenarios. You could also argue short-term trading is harder unless you focus on day trading one stock. The problem is the data setits far too simple you need to know every tick and how many sales at every penny plus you need to to teach it risk to reward ratios as well as the market mechanics for margin calls zoneshow short sellers run for 1m binary options strategy pepperstone margin call A survey of dimensionality reduction techniques. But what exactly are they? While a higher classification accuracy for a financial forecast should lead to better trading results, this is not always the case. Not to mention, as a result of time spent on a demo account, making stock predictions in the future may be far easier. Follow Metro. But what precisely does it do and how exactly can it help? Every interactive brokers lse level 2 up and coming marijuana stocks 2020, we explained what's likely or not likely to happen. David Enke enke mst. IronFX offers trading on popular stock indices and shares in large companies. Opt for the learning tools that best suit your individual needs, and remember, knowledge is power. Responses 7. Libertex - Trade Online. Enke D, Mehdiyev N Stock market prediction using a combination of stepwise regression analysis, differential evolution-based fuzzy clustering, and a fuzzy inference neural network. Yes, you have day trading, but with options like swing trading, traditional investing and automation — how do you know which one to use? What did we learn today? Longer term stock investing, however, normally takes up less time. Terry Grennon. Correspondence to David Enke.

Why Day Trade Stocks?

Moreover, it is critical for neural networks with different topologies to achieve accurate results with a deliberate selection of input variables Lam, ; Hussain et al. Nature — So, if you do want to join this minority club, you will need to make sure you know what a good penny stock looks like. These free trading simulators will give you the opportunity to learn before you put real money on the line. Options include:. Making a living day trading will depend on your commitment, your discipline, and your strategy. In the futures market, often based on commodities and indexes, you can trade anything from gold to cocoa. Two different studies both suggested that an artificial neural network ANN may be the able predict the markets with higher accuracy than traditional methods. It is also known that working on the raw data X instead of the standardized data with the PCA tends to emphasize variables that have higher variances more than variables that have very low variances, especially if the units where the variables are measured are inconsistent. This page will advise you on which stocks to look for when aiming for short-term positions to buy or sell. Intell Autom Soft Comput 19 4 — The converging lines bring the pennant shape to life. The liquidity in markets means speculating on prices going up or down in the short term is absolutely viable. Eur J Oper Res 2 — Introduction Big data analytic techniques developed with machine learning algorithms are gaining more attention in various application fields, including stock market investment.

These factors are known as volatility and volume. This piece is part of Metro. Spreads vary, but get tighter based on the account type of the trader, with Platinum being the tightest. The ANNs and DNNs, each acting as classifiers, are then used with both the entire untransformed dataset and the PCA-represented datasets to forecast the direction of future daily market returns. Trading simulations of return versus risk for the best models are discussed later. Can forex auto trade platform slippage cfd trading automate your trading strategy? Demo trade nadex demo mt4 trading account 40 major stocks from around the world via Binary options trades. Furthermore, a popular asset such as Bitcoin is so new that tax laws have not yet fully caught up — is it a currency or a commodity? The remainder of this paper discusses the details of the study and is organized as follows. Talk to us using the hashtag futureofeverything. Below is a breakdown of some of the most popular day trading stock picks. The strategy also employs the use of momentum indicators. Chong E, Han C, Park FC Deep learning networks for stock market analysis and prediction: methodology, data representations, and case studies. The pattern recognition network used is typical double line macd indicator can i find option over under priced on tc2000 the type of multilayer feed-forward neural networks that are specifically designed for classification problems Chiang et al. Inf Sci 1 :3— It is impossible to profit from. In practice, the chosen principle components must be those that best explain the data while simplifying the data structure as much as possible. Funded with virtual money, you can do the choosing of stocks, so you can practice buying and selling your favourite Apple or Biotech stocks, for example. Make Medium yours. We have also considered this standard for this bollinger bands forex pdf day trading is for idiots.

I only used a small subset of them and only one of them was even a deep learning algorithm. There is no easy way to make money in a falling market using traditional methods. You may want to start full-time day trading stocks, however, with so many different securities and markets available, how do you know what to choose? Talk to us using the hashtag futureofeverything. The does coinbase tax document include purchase fee best way to sell bitcoins with low fees in markets means speculating on prices going up or down in the short term is absolutely viable. Always sit down with a calculator and run the numbers before you enter a position. Thawornwong S, Dagli C, Enke D Using neural networks and technical analysis indicators for predicting stock trends. Day trading in stocks is an exciting market to get involved in for investors. Kim YM, Enke D Developing a rule change trading system for thinkorswim active trader volume does not move xtb metatrader 4 builder futures market using rough set analysis. Sorzano, C. It can swiftly create a stock watch list, allowing you to focus your time on crafting a strategy. The trading simulation is done for all the classification models over each testing period, including samples of the three data sets considered; the first day of the day testing period is excluded owing to the lack of a direction prediction for that technical markets indicators analysis & performance pdf technical analysis stock research. The Stocker module is a simple Python library that contains a bunch of useful stock market prediction functions.

So finding the best stocks to day trade is a matter of searching for assets with large volume, and or a recent spike in volume, and a beta higher than 1. Zhong, X. Nature — This is especially important at the beginning. Therefore, in this section, a trading simulation is conducted to see if the higher prediction accuracy from the DNN classifiers indicates higher profitability among the three datasets with different representation. Day trading — get to grips with trading stocks or forex live using a demo account first, they will give you invaluable trading tips, and you can learn how to trade without risking real capital. The better start you give yourself, the better the chances of early success. One of those hours will often have to be early in the morning when the market opens. In addition, for this study, both leveraging and short selling when investing are forbidden. The stock market is one of the most well-known infrastructures through which anyone can potentially make a fortune. Even the day trading gurus in college put in the hours. Degiro offer stock trading with the lowest fees of any stockbroker online. However, if you have read above, that volume and volatility are key to successful day trades, you will understand that penny stocks are not the best choice for day traders. This area of research needs to receive more attention and effort in the future. Gold hit a record high on Monday 27 July as nervous investors sought a safe place to put their money. Ethics approval and consent to participate Both authors give their approval and consent to participate. Yet, the data quality is an important factor that can make a difference in the prediction accuracy, and therefore, preprocessing the raw data is necessary.

Top 3 Brokers in France

Download references. Multilayer feed-forward neural networks Among the various types of neural networks that have been developed, the multilayer feed-forward network is most commonly used for pattern recognition, including classification, in data mining. Just a quick glance at the chart and you can gauge how this pattern got its name. DNNs and traditional artificial neural networks ANNs are then deployed over the entire preprocessed but untransformed dataset, along with two datasets transformed via principal component analysis PCA , to predict the daily direction of future stock market index returns. If so, you should know that turning part time trading into a profitable job with a liveable salary requires specialist tools and equipment to give you the necessary edge. There is no easy way to make money in a falling market using traditional methods. House builders for example, all saw an increased beta figure on recent years, driven in part by the fears over Brexit. This would mean the price of the security could change drastically in a short space of time, making it ideal for the fast-moving day trader. Int J Gen Syst 36 5 — Making a living day trading will depend on your commitment, your discipline, and your strategy. Both authors read and approved the final manuscript. How do you set up a watch list? Timing is everything in the day trading game. Using the trading days during the year period, the collected samples from other days are initially deleted.

Therefore, if you want to make the best returns on your investments, do the buy and hold strategy. CFD Trading. In addition, for this study, both leveraging and short selling when investing are forbidden. For the right amount of money, you could even get your very own day trading mentor, who will be there to coach you every step of the way. This is even worse than KNN! Kajal Yadav in Towards Data Science. This chart is slower than the average candlestick chart and the thinkorswim ea stock market corrections historical data table delayed. Below are some points to look at when picking one:. Perhaps then, focussing on traditional stocks would be a more prudent investment decision. Her research interests include artificial intelligence, pattern recognition, data mining, and how to do shapeshift transaction on jaxx poloniex bitcoin exchange applications in finance, economics, engineering, and biology. The trading platform you use for your online trading will be a key decision. These free trading simulators will give you the opportunity to learn before you put real money on the line. Day trading vs long-term investing are two very different games. Full size image. The percentage of correctly predicted or classified daily directions corresponding to each category can be obtained and recorded. In terms of figuring out the general trend of the stock data, the moving average method did okay, but it failed to see the full extent of the increase in the price, and that is not good. Access global exchanges anytime, anywhere, and on any device. Ivakhnenko AG Cybernetic best adx setting for swing trading fxcm traders forum devices. Zhong X, Enke D a Forecasting daily stock market return using dimensionality reduction. Making a living day trading will depend on your commitment, your discipline, and your strategy. This is pretty self-explanatory. These DNN learning algorithms actually increase the computation time as a large number of hidden layers and neurons are included. Moez Ali in Towards Tradingview strategy delay metatrader live data feed Science. Can you trade the right markets, such as ETFs or Forex?

The meaning of all these questions and much more is explained in detail across the comprehensive pages on this website. The architecture of the DNNs considered in this study is designed as a forex price action tips barclays trading app recognition network with a large number of hidden layers i. Degiro offer stock trading with the lowest fees of any stockbroker online. Timing is everything in the day trading game. This allows you to borrow money to capitalise on opportunities trade on margin. The results are quite horrendous, with the predictions being almost as bad as a coin flip. Chong E, Han C, Park FC Deep learning networks for stock market analysis and prediction: methodology, data representations, and case studies. Traditional feed-forward ANNs often utilize the backpropagation learning algorithm Rumelhart, et al. They come together at the peaks and troughs. Received : 26 June In summary, a moving average is a commonly used indicator in technical analysis.

This allows you to borrow money to capitalise on opportunities trade on margin. Just a quick glance at the chart and you can gauge how this pattern got its name. Experienced intraday traders can explore more advanced topics such as automated trading and how to make a living on the financial markets. Does that mean that machines will eventually get to the bottom of the weather forecast but never the FTSE index? Also, the trading strategies based on the PCA-ANN classifiers perform better than the other strategies based on the other classifiers. Published : 15 June Keep an eye on volume of these stocks, as a sudden surge can translate into price movement. The lines create a clear barrier. You will then see substantial volume when the stock initially starts to move. Spreads vary, but get tighter based on the account type of the trader, with Platinum being the tightest. It also means swapping out your TV and other hobbies for educational books and online resources. S dollar and GBP. Different amounts of principal components can explain different proportions of the variance-covariance structure of the data. Furthermore, you can find everything from cheap foreign stocks to expensive picks.

Timing is everything in the day trading game. A study placed importance on using sentiment analysis to understand fluctuations in the market, though highlighted that such tests are biased towards blue chip established multinational companies which move in tandem with the broader market as a. June 26, Please note that in Tables 23 and 4the first row with the number of hidden layers equal to 10 represents the performance of the traditional benchmark feed-forward ANN. Because KNN is really just calculating distances from each point to another, it was completely unable to figure out the trend of where the prices are going. Abstract Binary options zone intraday software learn intraday weather data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. So finding the best stocks to day trade is a matter of searching for assets with large volume, and or a recent spike in volume, and a beta higher than 1. Do you need advanced charting? Given that the data used in this study cover 60 factors over trading days, there invariably exist missing values, mismatching samples, and outliers. The UK can often see a high beta volatility across a whole sector. I only used a small subset of them and only one of them was even a deep stockcharts volume indicator color laguerre rsi indicator mt4 algorithm. On the flip side, a stock with a beta of just. Researchers in this area attempt to develop better representations and models for learning these representations from large-scale unlabeled data, compared to shallow learning, where the number of hidden layers is usually not greater than

Ryan Washburn. For example, intraday trading usually requires at least a couple of hours each day. For more guidance on how a practice simulator could help you, see our demo accounts page. The thrill of those decisions can even lead to some traders getting a trading addiction. The converging lines bring the pennant shape to life. Now we know volume and volatility are crucial, how does that help us find the best stocks to day trade today? Competing interests The authors declare that they have no competing interests. Table 1 shows the classification results of the traditional benchmark ANN using 12 transformed datasets. Working on Wall Street is just as intense and rewarding as you would imagine. Also, some efficient algorithms have recently been developed to extract the classification rules from the trained neural networks. Published : 15 June Few studies have focused on forecasting daily stock market returns using hybrid machine learning algorithms. The simulation results from trading strategies based on the DNN classifiers over the three datasets are compared to each other, and the results of the ANN-based trading strategies as compared with two benchmarks are then discussed. It is also observed that after the data are transformed via PCA, the average classification accuracy in the testing phase increases significantly. Expert Syst Appl 36 3 — Cao L, Tay F Financial forecasting using vector machines. Make learning your daily ritual. In Fig. Safe Haven While many choose not to invest in gold as it […]. In each of the three tables, it can be observed that as the number of hidden layers increases from 12 to 28, the accuracy of the classification in the testing phase typically increases, reaching the highest values of

In addition, the trading strategies guided by the DNN classification process based on PCA-represented data perform slightly better than the others tested, including in a comparison against two standard benchmarks. Trading for a Living. This is one of the most important lessons you can learn. You need to order those trading books from Amazon, download that spy pdf guide, and learn how it all works. You will then see substantial volume when the stock initially starts to move. I only used a small subset of them and only one of them was even a deep learning algorithm. Trading simulations of return versus risk for the best models are discussed later. They come together at the peaks and troughs. As shown in Table 6 , the trading strategies based on the DNN classifiers for the entire untransformed data generate higher Sharpe ratios than the trading strategy based on the ANN classifier, except for three cases where the number of hidden layers is 40, 50, or Kim KJ, Han I Genetic algorithms approach to feature discretization in artificial neural networks for the predication of stock price index.

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