Artificial Intelligence Applied to Stock Trading
These days, most expert traders and investors draw stock charts, read stock
quotes, and follow financial news on their computer screens. Market
professionals also use various software for trading and investment analyses.
Internet sites such as AASTOCKS.com provide essential online tools for
stock quotes, news, research, and simple technical analyses.
Average stock traders, professional or independent, sit at their screens during
trading hours, monitoring financial news, examining stock charts,
considering all possible trade opportunities. Investors may decide
to buy or sell a stock based on a news tip, a grapevine rumor, or on the
discovery of a stock showing a typical buy or sell technical pattern. Often
they will sit before their screens for many hours without executing any trades,
because good picks are hard to find, especially without a systematic search method!
Conventional trading software may let users search for stocks that meet a certain
number of criteria, such as specifications of price, volume, and other indicators.
However, those tools usually ask the users to input their own search criteria.
Unfortunately, most users do not really know what conditions will lead to reliable
trading signals. Worse still, because these search tools are too simplistic, they
won't yield stocks with the desired pattern except by chance, no matter what
search criteria they input.
Live Technical Stock Search
The remarkable news is that AASTOCKS.com has designed much sharper
investment instruments than undependable traditional ones! To find stocks
displaying "ideal" chart patterns, we have pioneered a powerful set
of pattern- recognition and pattern-search methodologies. Applying these
methods and algorithms at five-minute intervals, AASTOCKS runs a computer
program that goes through all the liquid stocks traded on the SEHK
market to detect all the desired
stock patterns. We present each stock found by using our IntelliChart on
AASTOCKS. The IntelliChart shows stock charts
in the various modes (line chart, bar chart, candlestick chart)
using many popular indicators (volume, Bollinger Bands, K/D, RSI and MACD). IntelliChart
also draws auxiliary lines (such as support lines, range
lines, sides of triangles) and stop-loss lines. These lines enable our traders to
recognize chart pattern and visually assess profit and risk potential. Figure 25 shows
a typical Cup-With-A-Handle Breakout Trade, identified by the AASTOCKS stock
search engine.

Figure 25. A typical Cup-With-A-Handle Breakout Trade found by AASTOCKS Live
Technical Stock-Search Engine
Live Stock Comments
Most investors and traders research target-stocks to find essential performance
facts and significant background information; they also try to gain a firm
grasp of stock behavior before making any buy or sell decisions. Financial
services firms and brokerage houses happily provide their clients with costly
research materials and analysis results. Some stock analysts periodically issue
newsletter comments on popular stocks. Investors and traders often find those
comments helpful because they neatly summarize basic facts and technical
characteristics of stocks, providing company and industry profiles along with
accounts of past performance; they may also estimate risk and corrections
between stock prices and market sector performance.
Using these data, investors can then assemble their own views of stock and company
performance potential.

Figure 26. An example of our Artificial Intelligence Live Stock Commentary
However, professional investors and independent traders alike still face two
major inconveniences: first, summaries and newsletter comments are unavailable
for most stocks, and second, even when they are available, these comments are
often badly out of date soon after they are released.
The amazing news on this score is that AASTOCKS’s Live Stock Comment engine
overcomes such drawbacks by providing traders with consistent and reliable real
-time stock summaries and comments for all stocks! Just as the modern public has
witnessed IBM's Big Blue outmaster the masters of chess, the trading world is now
beginning to comprehend the potential of Artificial Intelligence in trading applications.
To provide the most consistent and incisive stock assessments for all stocks in real time,
AASTOCKS.com has recently pioneered its breakthrough invention, the Artificial
Intelligence Live Stock Commentary Engine (AILSCE ). Figure 26 shows an example
of live stock commentary provided by AILSCE on the Internet. The following is a description
of the system:
- AASTOCKS has
assembled a powerful stock database for historical and real-time
data.
AASTOCKS.com has built a powerful stock database to support AILSCE.
AASTOCKS stores in its database the daily and intra-day prices and volumes
of stocks traded on the SEHK, as well as other fundamental
data on all stocks. We have also stored the major indexes and market-sector indexes
in our database.
- AILSCE retrieves basic quotes and fundamental data for the first part of
AASTOCKS stock commentary.
- AILSCE analyzes stock price and volume
history to generate the liquidity and volatility/risk comments.
- AILSCE computes stocks' past performance,
along with short-term and long-term trends.
- AILSCE evaluates stocks' past return/risk
ratios in comparison with larger market trends and with the target
stock's own market sector.
- AILSCE analyzes the relationship of stocks
with the whole-market and market- sector indices; it then computes
the betas and correlation coefficients.
- AILSCE computes all of the stock's
important technical indicators to see if the stock is overbought
or oversold.
- AILSCE runs the Intelligent Stock Chart Pattern Search
program to see if the stock matches any of the typical technical
patterns.
- AILSCE runs the Artificial Neural Network
Stock Prediction Engine to predict the next five-day price
movements. It also assesses stock predictability by checking the
ratio of the directionality of the predicted prices against the
width of the prediction error bands.
- Finally, AILSCE combines all the above analyzes to issue AASTOCKS users
a complete commentary in plain English (or other human languages).
Neural
Network Forecast: AASTOCKS Neuro-Predictor
Numerous hard statistical and scientific studies have indicated that the stock
market, as well as other financial markets, are, like other complex natural
phenomena, to a certain degree predictable by means of newly developing methods
and tools.
Movements of the stock prices, as well as price movements of other financial
instruments, generally present a deterministic trend, on which are superimposed
some "noise" signals, in turn composed of truly random and chaotic signals.
deterministic trends can be detected and assessed by some maximum- likelihood methods.
Although a truly random signal, often represented by a Brownian motion, is unpredictable,
it can be estimated by its mean and standard deviation. The chaotic signal, seemingly
random but with deterministic nature, proves predictable to some degree by means of several
analysis techniques, among which the Artificial Neural Network (ANN) techniques have
proven most effective over the widest range of predictive variables.
What is Artificial Neural Network, and what is AASTOCKS Neurol-PredictorTM?
The Artificial Neural Network(ANN) is an important branch of Artificial
Intelligence. Motivated in its design by the human nervous system, ANN mimics
the human nervous system in its operations. At this extraordinary interface between
natural human systems and created electronic ones, ANN is capable of learning
by training to generalize from special cases--just like human beings can! The simplified ANN
(supervised) training and prediction process can be illustrated by
the following steps¡XThe crucial pre-processing and validation are
discussed separately.
Stage One:
Collect the training set, which includes the input data for the ANN to "see"
and the known target data for ANN to learn to output. For stock price predictions,
for example, the training set and target data would naturally be historical stock
prices. A vector of 100 consecutive historical stock prices, for instance, can
constitute training data and with the 101st stock price as a target datum.
Stage Two:
Feed the input data to ANN; compare ANN output with the known target, and adjust
ANN's internal parameters (weights and biases) so that ANN output and the known
target are close to one another—more precisely, so that a certain error function
is minimized.
Step Three:
Feed ANN some future input data (not seen by ANN); if ANN is well trained and if
the input data are predictable, then ANN will give accurate predictions.
Artificial Neural Networks: Proven?
ANN can be trained to adapt to and solve many complicated problems, such as adaptive
noise filtering, pattern recognition, and speech processing by voice recognition. ANN
noise-filters are now widely used in telephone systems to reduce echo noise and in airplanes
to reduce engine noise interference with the pilot's voice signal in communication
instruments. [More examples of successful applications of ANN can be found in a
report by DARPA (Defense Advanced Research Project Agency)]
The AASTOCKSTM Neuro-PredictorTM is essentially an Artificial Neural Network
trained for adaptive prediction of stock prices. During the prediction process, the
AASTOCKSTM Neuro-PredictorTM determines whether a particular stock
is predictable with the accuracy required for a statistically significant prediction. This
is accomplished, essentially, by comparing the ANN validation error against stock price
fluctuations. We know that stocks with larger chaotic components and smaller truly random
components tend to be more predictable than others. In addition to predicting stock prices,
the AASTOCKSTM Neuro-PredictorTM
also marks the range that the stock price would stay.
The AASTOCKSTM Neuro-PredictorTM has managed to yield prediction refinements
well beyond those of other systems by employing a pipelined recurrent ANN architecture
(best for time-series prediction) and an adaptive supervised training procedure. More
specifically, AASTOCKS's ANN has been developed to incorporate the strengths of
those artificial neural networks successfully used by leading research and industry leaders.
ANN pre-processing is based on the Nobel Prize-winning Black-Scholes log-normal stock price
model. Efficient computation algorithms have also been developed to realize AASTOCKS's
breakthrough in making real-time predictions.
6-month Target
6-month Target is an interactive valuation calculator that provides six-month price
targets for stocks specified by users. It has been developed with the prevailing valuation
methodologies utilized by leading Wall Street firms. This valuation is based on combined
data from over a dozen fundamental variables that significantly influence stock prices,
including interest-rate and cash-flow information. While some of the parameters are set
by AASTOCKS's historical data, traders can customize the analysis by modifying five
important underlying variables: long-bond rate, inflation rate, P/E, sales per share, and a
one-year Hang Seng Index outlook, a leading measure of market sentiment.
To use this model, the user first types a symbol in the upper-left corner of the AASTOCKS
textbox. Hitting "GO" button. Five modifiable parameters are loaded from database. Once the
user changes the parameters and hits the "Recalculate" button, a six-month target price will be
generated, along with an opinion on the value of the stock compared against the Hang Seng Index.
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