Stock market prediction
Encyclopedia
Stock market prediction is the act of trying to determine the future value of a company stock
or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price could yield significant profit. Some believe that stock price movements are governed by the random walk hypothesis
and thus are unpredictable. Others disagree and those with this viewpoint possess a myriad of methods and technologies which purportedly allow them to gain future price information.
states that the price of this instrument is governed by a random walk
and hence is unpredictable. If the random walk hypothesis
is false then there will exist some (potentially non-linear) correlation
between the instrument price and some other indicator(s) such as trading volume or the previous day's instrument closing price. If this correlation can be determined then a potential profit can be made.
, technical analysis
(charting) and technological methods.
. Warren Buffett
is perhaps the most famous of all Fundamental Analysts.
or cup and saucer. Alongside the patterns, statistical techniques are utilised such as the exponential moving average (EMA).
The most common form of ANN in use for stock market prediction is the feed forward network utilising the backward propagation of errors
algorithm to update the network weights. These networks are commonly referred to as Backpropagation
networks. Since NNs require training and have a large parameter space, it is useful to modify the network structure for optimal predictive ability. Recently this has involved pairing NNs with genetic algorithm
s, a method of finding optima in multi-dimension parameter spaces utilising the biological concepts of evolution
and natural selection
.
Moreover, some researchers have tried to extract meaningful indicators from the news flash and discussion rooms about a certain stock using Data Mining
techniques. But people can have different opinion about the same stock at the same time.
Stock
The capital stock of a business entity represents the original capital paid into or invested in the business by its founders. It serves as a security for the creditors of a business since it cannot be withdrawn to the detriment of the creditors...
or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price could yield significant profit. Some believe that stock price movements are governed by the random walk hypothesis
Random walk hypothesis
The random walk hypothesis is a financial theory stating that stock market prices evolve according to a random walk and thus the prices of the stock market cannot be predicted. It is consistent with the efficient-market hypothesis....
and thus are unpredictable. Others disagree and those with this viewpoint possess a myriad of methods and technologies which purportedly allow them to gain future price information.
The random walk hypothesis
When applied to a particular financial instrument, the random walk hypothesisRandom walk hypothesis
The random walk hypothesis is a financial theory stating that stock market prices evolve according to a random walk and thus the prices of the stock market cannot be predicted. It is consistent with the efficient-market hypothesis....
states that the price of this instrument is governed by a random walk
Random walk
A random walk, sometimes denoted RW, is a mathematical formalisation of a trajectory that consists of taking successive random steps. For example, the path traced by a molecule as it travels in a liquid or a gas, the search path of a foraging animal, the price of a fluctuating stock and the...
and hence is unpredictable. If the random walk hypothesis
Random walk hypothesis
The random walk hypothesis is a financial theory stating that stock market prices evolve according to a random walk and thus the prices of the stock market cannot be predicted. It is consistent with the efficient-market hypothesis....
is false then there will exist some (potentially non-linear) correlation
Correlation
In statistics, dependence refers to any statistical relationship between two random variables or two sets of data. Correlation refers to any of a broad class of statistical relationships involving dependence....
between the instrument price and some other indicator(s) such as trading volume or the previous day's instrument closing price. If this correlation can be determined then a potential profit can be made.
Prediction methods
Prediction methodologies fall into three broad categories which can (and often do) overlap. They are fundamental analysisFundamental analysis
Fundamental analysis of a business involves analyzing its financial statements and health, its management and competitive advantages, and its competitors and markets. When applied to futures and forex, it focuses on the overall state of the economy, interest rates, production, earnings, and...
, technical analysis
Technical analysis
In finance, technical analysis is security analysis discipline for forecasting the direction of prices through the study of past market data, primarily price and volume. Behavioral economics and quantitative analysis incorporate technical analysis, which being an aspect of active management stands...
(charting) and technological methods.
Fundamental analysis
Fundamental Analysts are concerned with the company that underlies the stock itself. They evaluate a company's past performance as well as the credibility of its accounts. Many performance ratios are created that aid the fundamental analyst with assessing the validity of a stock, such as the P/E ratioP/E ratio
The P/E ratio of a stock is a measure of the price paid for a share relative to the annual net income or profit earned by the firm per share...
. Warren Buffett
Warren Buffett
Warren Edward Buffett is an American business magnate, investor, and philanthropist. He is widely regarded as one of the most successful investors in the world. Often introduced as "legendary investor, Warren Buffett", he is the primary shareholder, chairman and CEO of Berkshire Hathaway. He is...
is perhaps the most famous of all Fundamental Analysts.
Technical analysis
Technical analysts or chartists are not concerned with any of the company's fundamentals. They seek to determine the future price of a stock based solely on the (potential) trends of the past price (a form of time series analysis). Numerous patterns are employed such as the head and shouldersHead and shoulders (chart pattern)
The Head and Shoulders formation is one of the most well known reversal patterns.On the technical analysis chart, when a price trend is in the process of reversal either from a bullish or bearish trend, a characteristic pattern takes shape and is recognized as reversal formation.-Head and shoulders...
or cup and saucer. Alongside the patterns, statistical techniques are utilised such as the exponential moving average (EMA).
Technological methods
With the advent of the digital computer, stock market prediction has since moved into the technological realm. The most prominent technique involves the use of artificial neural networks (ANNs) and Genetic Algorithms. ANNs can be thought of as mathematical function approximators. Their value in stock market prediction is that if a (potentially non-linear) relationship exists then it is possible that it could be found with enough indicators, the correct network structure and a large enough dataset.The most common form of ANN in use for stock market prediction is the feed forward network utilising the backward propagation of errors
Backpropagation
Backpropagation is a common method of teaching artificial neural networks how to perform a given task. Arthur E. Bryson and Yu-Chi Ho described it as a multi-stage dynamic system optimization method in 1969 . It wasn't until 1974 and later, when applied in the context of neural networks and...
algorithm to update the network weights. These networks are commonly referred to as Backpropagation
Backpropagation
Backpropagation is a common method of teaching artificial neural networks how to perform a given task. Arthur E. Bryson and Yu-Chi Ho described it as a multi-stage dynamic system optimization method in 1969 . It wasn't until 1974 and later, when applied in the context of neural networks and...
networks. Since NNs require training and have a large parameter space, it is useful to modify the network structure for optimal predictive ability. Recently this has involved pairing NNs with genetic algorithm
Genetic algorithm
A genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems...
s, a method of finding optima in multi-dimension parameter spaces utilising the biological concepts of evolution
Evolution
Evolution is any change across successive generations in the heritable characteristics of biological populations. Evolutionary processes give rise to diversity at every level of biological organisation, including species, individual organisms and molecules such as DNA and proteins.Life on Earth...
and natural selection
Natural selection
Natural selection is the nonrandom process by which biologic traits become either more or less common in a population as a function of differential reproduction of their bearers. It is a key mechanism of evolution....
.
Moreover, some researchers have tried to extract meaningful indicators from the news flash and discussion rooms about a certain stock using Data Mining
Data mining
Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...
techniques. But people can have different opinion about the same stock at the same time.