What did exactly cause the recent sell-off ? There are different opinions among experts - debt-ceiling standoff, US credit rating downgrade, disappointing economic growth statistics, Europe troubles, or all combined together. As usually, it happened suddenly and quickly. There might be at least two ideas why recent declines happen faster and faster. The first one is that investors reaction to uncertainty and tolerance for risk have changed; it takes less and less to scare investors.
The second reason is a fast electronic trading. It allows programmed computers to sell under particular circumstances in milliseconds that develops a temporal disconnection between the actual factors and reasonable market prices - the market overreacts and makes irrational movements before reaching an after-crash equilibrium. As a matter of fact, the latest huge swings with changing directions every day have never been seen before in S&P-500 history.
In new era of globalization, mutual dependencies, and markets interconnection, the system crises turned out to be a new threat to our global well-being. Nonetheless, it seems the investors' expectation now has changed - the US and global economic growth is likely to be less healthy in the near future than previously estimated.
Some resources: Trading Strategies for a Stock Market Crash,
How to Escape from a Bear
2011-08-17
2011-07-13
The Stock Market Is Ready To Advance To New Highs
The US unemployment rate increased during the last three months and reached 9.2%. Even so, in a long-term perspective, a high unemployment is on its new "normal" level and a small increase looks rather as a noise, not a strong signal. Also normally, unemployment rate is considered as a lagging indicator and does not indicate what will happen in the future. Often, unemployment numbers continue to increase even after the economy is recovering because businesses are reluctant to hire new employees.
After careful consideration some analysts have made a conclusion that ending the bond-buying program can actually have a positive effect on the market. Although US housing is not changing, it is in almost the same bad shape for two years without strong factors that may prevent it from positive moves. The factory orders increased in May. Oil price is down that helps the economy to gather a recovery momentum. Credit availability and business investments are improving.
From quarter to quarter, corporate earnings are fluctuating and it might be a sign that the economic recovery is in a early developing stage. Many chronic problems did not disappear yet but their influence is already reflected in the indexes. Everyday bad news have almost no effect on a strengthening market. July opens second-quarter earnings season. In terms of valuation, the stocks are trading now at attractive levels and if corporate balance sheets still remain healthy, almost nothing left to prevent the stock market from advancing to new highs.
After careful consideration some analysts have made a conclusion that ending the bond-buying program can actually have a positive effect on the market. Although US housing is not changing, it is in almost the same bad shape for two years without strong factors that may prevent it from positive moves. The factory orders increased in May. Oil price is down that helps the economy to gather a recovery momentum. Credit availability and business investments are improving.
From quarter to quarter, corporate earnings are fluctuating and it might be a sign that the economic recovery is in a early developing stage. Many chronic problems did not disappear yet but their influence is already reflected in the indexes. Everyday bad news have almost no effect on a strengthening market. July opens second-quarter earnings season. In terms of valuation, the stocks are trading now at attractive levels and if corporate balance sheets still remain healthy, almost nothing left to prevent the stock market from advancing to new highs.
2011-06-30
How To Use Chart Patterns To Predict Trend
There are many classical well-know chart patterns that found a long time ago and now considered as "typical" ones. Also there are many other patterns that can signal a particular, bullish or bear trend, but not described yet. Known or unknown patterns that are persistent can be repeatable in the future; therefore, they can be used to predict the future price movement.
To ease the job to memorize all patterns and analyze a huge amount of charts, many chartists use different software tools - pattern recognition systems. These tools normally perform statistical classification of patterns assuming that the patterns are generated by a probabilistic system (the stock market is a semi-probabilistic system).
Technical Analyzer TA-1 (TA) by Addaptron Software has a feature to predict a future trend of stock, ETF, or index prices using pattern similarity. The prediction period can be chosen within a range 1..60 trading days; the period of historical data that used for matching recommended in 4..16 times longer than prediction period. TA searches for the best matches by scanning all historical data from the internal database.
TA ranks all possible matches on the basis of maximum correlation and minimum deviation within given historical period. TA performs pattern matching using open, high, low, and close prices and volume data. When scanning is completed, depending on degree of similarity, it ranks all possible matches within given historical period and then combine them. TA composes forecast using several best matched patterns (top ranked). Since the statistical regularities of the patterns help to create more stable picture, TA allows adding up many top-rated patterns. The composite result is built as a weighted average with weights proportionally pattern ranks.
To try free fully-functional version of TA, visit Addaptron Software download page to download and install it.
To ease the job to memorize all patterns and analyze a huge amount of charts, many chartists use different software tools - pattern recognition systems. These tools normally perform statistical classification of patterns assuming that the patterns are generated by a probabilistic system (the stock market is a semi-probabilistic system).
Technical Analyzer TA-1 (TA) by Addaptron Software has a feature to predict a future trend of stock, ETF, or index prices using pattern similarity. The prediction period can be chosen within a range 1..60 trading days; the period of historical data that used for matching recommended in 4..16 times longer than prediction period. TA searches for the best matches by scanning all historical data from the internal database.
TA ranks all possible matches on the basis of maximum correlation and minimum deviation within given historical period. TA performs pattern matching using open, high, low, and close prices and volume data. When scanning is completed, depending on degree of similarity, it ranks all possible matches within given historical period and then combine them. TA composes forecast using several best matched patterns (top ranked). Since the statistical regularities of the patterns help to create more stable picture, TA allows adding up many top-rated patterns. The composite result is built as a weighted average with weights proportionally pattern ranks.
To try free fully-functional version of TA, visit Addaptron Software download page to download and install it.
2011-06-28
Two More Indicators Implemented in Technical Analyzer
Collected and analyzed data allow comparing different technical analysis indicators. However, according to statistical researches, the problem is that depending on time-frame, market conditions, industry specifics, type of stock or ETF, and other factors, some indicators might be best but other worst, and vice versa. In general, the question can be answered only for some average analysis. As example, according to average predictions success based on the statistics during 2010, the five of top winning indicators are: Relative Strength Index, Money Flow Index, Twiggs Money Flow, On Balance Volume, and Directional Movement System.
Technical analysts know that it is better to select the best indicators for a particular case. Evidently, it can be a time-consuming process. One of the solutions is to allow a computer program to decide which indicator should be trusted more and another less for particular market conditions and a specific shares using back-testing. Such computer program could compose the forecast with weights accordingly to predictive ability of each technical indicator. The example of such program is Technical Analyzer TA-1 (TA).
The recent researches showed that predictive abilities of some classical indicators can be improved by additional transformations. In short, if an indicator is trend-differentially coupled with price - it demonstrates better predictive abilities than a pure indicator. This idea has been used to improve the next release of TA software. The list of existing indicators in TA Technical Analysis module has been empowered by two new divergence-modified indicators - Relative Strength Index (RSI) and Moving Average Convergence/Divergence (MACD). These two indicators have been transformed to a slope of line and differentially-coupled with a price line slope. Indicators and price transformation to line slopes has been performed using Least Squares Linear Regression within a sliding 10-day period (moving window).
Try free fully-functional software during 30 days; it is available on Addaptron Software download page
Technical analysts know that it is better to select the best indicators for a particular case. Evidently, it can be a time-consuming process. One of the solutions is to allow a computer program to decide which indicator should be trusted more and another less for particular market conditions and a specific shares using back-testing. Such computer program could compose the forecast with weights accordingly to predictive ability of each technical indicator. The example of such program is Technical Analyzer TA-1 (TA).
The recent researches showed that predictive abilities of some classical indicators can be improved by additional transformations. In short, if an indicator is trend-differentially coupled with price - it demonstrates better predictive abilities than a pure indicator. This idea has been used to improve the next release of TA software. The list of existing indicators in TA Technical Analysis module has been empowered by two new divergence-modified indicators - Relative Strength Index (RSI) and Moving Average Convergence/Divergence (MACD). These two indicators have been transformed to a slope of line and differentially-coupled with a price line slope. Indicators and price transformation to line slopes has been performed using Least Squares Linear Regression within a sliding 10-day period (moving window).
Try free fully-functional software during 30 days; it is available on Addaptron Software download page
2011-06-10
June 2011: SP-500 Might Not Touch 1250, At Least For Now
One of the popular ideas now is that until S&P-500 index touch 1250 number, it is too early to buy or sell. However, on the assumption that currently many market participants are looking at charts and use technical analysis to make their buy-sell decisions, the index might not move down too much, at least for now.
If almost everyone is considering that it is not good time yet to sell (or go short) and waiting for this magic number, this move might not happen. The reason is that there will be no sellers but mostly holders that are waiting. It can be a typical situation when an expectation affects the market. The index might stall for a while and then move up. Also a statistical cycle analysis method based on action-reaction idea indicate that such reverse will happen after June 15-17 and before reaching 1250 value:
Chart has been calculated using cycles predictor
If almost everyone is considering that it is not good time yet to sell (or go short) and waiting for this magic number, this move might not happen. The reason is that there will be no sellers but mostly holders that are waiting. It can be a typical situation when an expectation affects the market. The index might stall for a while and then move up. Also a statistical cycle analysis method based on action-reaction idea indicate that such reverse will happen after June 15-17 and before reaching 1250 value:
Chart has been calculated using cycles predictor
2011-05-28
Are Technical Indicators Useful?
Yes and No. Evidently, there are periods when technical analysis works and the periods when it does not. The reasons can be many – fundamental changes, revised expectations, unexpected news, etc. During the periods when a majority of market participants make their decisions based on past market performance, as a rule, there would be some technical indicators that relatively work well.
Are there best ones? During some periods, some indicators might be the best winners, others – the worst losers. But all things are subject to change. Besides, indicators and markets are often a two-way system, i.e., markets can be affected when a huge number of investors use the same indicator(s). For example, the indicator predicts flat 2 days and then an uptrend for 3 days. If everybody follows, the forecast fails because price would be driven up first 2 days by buying volume and then 3 days flat or down-trending due to taking profit.
Other technical methods. In many cases, due to a semi-stochastic nature of the market, probabilistic statistical methods are able to predict well. Some of the systems that employed such methods is Neural Network (NN). NN often suffers from “over-fitting”. It is bad because over-fitting gives an exact but sometimes wrong result more often than an approximate but correct one. Cycle analysis, as another statistical method, has other advantages and disadvantages.
Are there best ones? During some periods, some indicators might be the best winners, others – the worst losers. But all things are subject to change. Besides, indicators and markets are often a two-way system, i.e., markets can be affected when a huge number of investors use the same indicator(s). For example, the indicator predicts flat 2 days and then an uptrend for 3 days. If everybody follows, the forecast fails because price would be driven up first 2 days by buying volume and then 3 days flat or down-trending due to taking profit.
Other technical methods. In many cases, due to a semi-stochastic nature of the market, probabilistic statistical methods are able to predict well. Some of the systems that employed such methods is Neural Network (NN). NN often suffers from “over-fitting”. It is bad because over-fitting gives an exact but sometimes wrong result more often than an approximate but correct one. Cycle analysis, as another statistical method, has other advantages and disadvantages.
2011-04-08
Market Crowd Factor: Why Trend Might Not Be Your Friend Sometimes
“An advertisement said, 'Send me $1 and I will let you know how it was easy for me to become a millionaire.'
A man who wants to be a millionaire sent $1 in an envelop.
After a while he received a reply: 'I became a millionaire by asking to send me $1'
The next day, the advertisement said, 'Send me $1 and I will let you know how it was easy for me to become a billionaire.'”
- Author unknown
A man who wants to be a millionaire sent $1 in an envelop.
After a while he received a reply: 'I became a millionaire by asking to send me $1'
The next day, the advertisement said, 'Send me $1 and I will let you know how it was easy for me to become a billionaire.'”
- Author unknown
An advanced and robust principle, idea, or system might help to win in the stock market. But what if it is used by almost all market participants? Would everyone be a winner? Read to find out about cases when stock investing can be successful or risky. Although a successful stock market investing or trading is complicated, in general, it consists of three major parts: analyzing data and possible future, making decision, and executing this decision. The same applies in case of automated trading - just these parts incorporated in the system and work in the same way. If we abstract from non-controllable external factors, we could clearly see that the quality of our decision and consequently the outcome depend on input data and their processing to make an optimal decision. What input data are the best and how to convert them into a meaningful information and finally into a right action?
Quality vs. quantity. First of all, apparently, too many data, especially, that are non-relevant to the searching result, might make the solution too noisy and with error ranges that exceed the accuracy of a certain solution. That is why most market participants use a limited but sufficient enough the set of input data in order to transform it further into a necessary information with a minimal uncertainty. The second important task is a processing with the highest quality of extracting worthy information. A good processing enables enriching the information while trying to avoid losing any value in the translation process.
Sometimes trend might be your friend. Is it possible to find and use the best universal principles and systems in stock trading? The second question - is it possible to make money using methods, systems, or ideas that are employed by many? It seems collective actions can be beneficial. For instance, if there is a uptrend - many would join the movement and add more pushing power up. Although a crowd behavior could be useful, sometimes, it can lead to unexpected results.
What if everyone does the same. Typical example - many thought that February could be a good month to invest because institutional funds' managers could increase their portfolios in March. Many converted cash into stocks in February pushing market up. Then when buying power exhausted and funds were unable to support this trend - the stock market collapsed. Another examples, several years ago October was a low month but since too many talked about this annual cycle, it is not the case anymore - everybody buys in October and pushes the market higher.
One more danger of crowd. Some classical books warn investors - when everyone is very bullish in the stock market - this is time when the market can crush because there is no one left who can invest more money to support the uptrend. It was in case of a hi-tech bubble in 2000. What factors influence our investing or trading decision? The opinion of most market participants? But their opinions link to their actions - that is why a trend might be built on sands and it can let you down anytime.
The benefit of using a new or rare approach. Let's imagine the situation - a group of people read the same book, for example, "How to Find Mushrooms" and all go to one forest. Evidently, then there would be more chances to find mushrooms in the places that are not recommended in this book. The conclusion - stock trading can be successful also in case of using something new or something that is used by limited number of traders.
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