User:Alex loo

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Looking up at a computerized stocks-value board at the Philippine Stock Exchange
Bond market
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hk.rec.travel is a USENET newsgroup publicly available to the internet users. It focuses on the travel-related discussions, within the community of Hong Kong people. Traditional Chinese in Big-5 is the most common language used in the newsgroup.

Technical analysis, also known as charting, is the study of the trading history (the price and volume over time) of any type of security (stocks, commodities, etc.) to attempt to predict future prices. In its purest form, technical analysis is concerned only with the actual price behavior of the instrument, based on the theory that all other factors affecting valuation will be reflected in the price before an investor can become aware of them through other channels.

Background and History

USENET newsgroups were one of the popular channels of online discussion forum during 1990's. In early 1997, creation of a travel-related newsgroup was proposed. In 12-Mar-1997, hk.rec.travel was created. Since then, hk.rec.travel has gathered a number of netters who are enthusiatic with sharing experience from trips they have made. In August 2007, the group of regular visitors to hk.rec.travel, in view of the growing number of disturbing spams to the newsgroup, has decided to move away from the unmoderated usenet environment into a HongKong-based discussion server at NNTP. The new newsgroup created there was called interest.travel.hrt.

Systematic trading and technical analysis

Neural networks

Since the early 90's when the first practically usable types emerged, artificial neural networks (ANNs) have rapidly grown in popularity. They are artificial intelligence adaptive software systems that have been inspired by how biological neural networks work. Their use comes in because they can learn to detect complex patterns in data. In mathematical terms, they are universal non-linear function approximators meaning that given the right data and configured correctly, they can capture and model any input-output relationships. This not only removes the need for human interpretation of charts or the series of rules for generating entry/exit signals but also provides a bridge to fundamental analysis as that type of data can be used as input.

In addition, as ANNs are essentially non-linear statistical models, their accuracy and prediction capabilities can be both mathematically and empirically tested. In various studies neural networks used for generating trading signals have significantly outperformed buy-hold strategies as well as traditional linear technical analysis methods.[1] [2] [3]

While the advanced mathematical nature of such adaptive systems have kept neural networks for financial analysis mostly within academic research circles, in recent years more user friendly neural network software has made the technology more accessible to traders.

Rule-based trading

Rule-based trading is an approach to make one's trading plans by strict and clear-cut rules. Unlike some other technical methods or most fundamental analysis, it defines a set of rules that determines all trades, leaving minimal discretion.

For instance, a trader might make a set of rules stating that he will take a long position whenever the price of a particular instrument closes above its 50-day moving average, and shorting it whenever it drops below.

Charting terms and indicators

The five very common charting techniques used by everyday traders are:

  • Balance days or "dojis"
  • Double tops
  • Channels
  • Lines of resistance
  • Pennants and/or flags

Other widely-known technical analysis concepts include:

Books

  • Ichimoku Charts, Nicole Elliott, Harriman House, 2007, ISBN 9781897597842
  • Getting Started in Technical Analysis, Jack D. Schwager, Wiley, 1999, ISBN 0-471-29542-6
  • New Concepts in Technical Trading Systems, J. Welles Wilder, Trend Research, 1978, ISBN 0-89459-027-8
  • Reminiscences of a Stock Operator, Edwin Lefèvre, John Wiley & Sons Inc, 1994, ISBN 0-471-05970-6
  • Street Smarts, Connors/Raschke, 1995, ISBN 0-9650461-0-9
  • Technical Analysis of Futures Markets, John J. Murphy, New York Institute of Finance, 1986, ISBN 0-13-898008-X
  • Technical Analysis of Stock Trends, 8th Edition (Hardcover), Robert D. Edwards, John Magee, W. H. C. Bassetti (Editor), American Management Association, 2001, ISBN 0-8144-0680-7
  • Technical Analysis of the Financial Markets, John J. Murphy, New York Institute of Finance, 1999, ISBN 0-7352-0066-1
  • The Profit Magic of Stock Transaction Timing, J.M. Hurst, Prentice-Hall, 1972, ISBN 0-13-726018-0
  • The Free E-Book of Technical Analysis, Wallstreetcourier, www.wallstreetcourier.com/ebook/The_E-Book_of_Technical_Market_Indicators.pdf

Notes

  1. ^ R. Lawrence. Using Neural Networks to Forecast Stock Market Prices
  2. ^ B.Egeli et al. Stock Market Prediction Using Artificial Neural Networks
  3. ^ M. Zekić. Neural Network Applications in Stock Market Predictions - A Methodology Analysis

See also

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