Wednesday, March 27, 2013
Monday, March 25, 2013
Understanding the Mechanics of Quantitative Trading
MetaStock SPRS Series - Week 111 - TechniTrader® Stock Discussion for MetaStock Users - Understanding the Mechanics of Quantitative Trading - March 25, 2013
By: Martha Stokes C.M.T.
One of the areas of professional trading that is least understood is how quantitative analysis actually works. Many retail traders assume wrongly that quantitative analysis is a form of stock chart analysis. It is not. One book that is circulating around the Quants is "Antifragile" by Nassim Taleb. I do not agree with all of his summations and theories, but what I find fascinating is how Quants are reacting to the book. By comparing his work to quantitative analysis, we can begin to dissect how the institutions derive and use quantitative analysis for their buying and selling on any financial market—stocks, bonds, futures, forex, index, ETFs, whatever. This is the key to figuring out what goes on in the HFT and Dark Pool back rooms.
The argument stems from the use of either a professional style momentum strategy, or choosing a mean reversal strategy which is what retail traders call “SAR” strategies. Please remember that your strategies are very simple and basic compared to Quant algorithms that trigger billions of orders in a very complex set of instructions. Often this code is many pages long with mathematical equations. The basis for all Quant work is mathematics, not technical analysis. What Quants are debating is whether a momentum strategy often used by HFTs or a mean reversal, actually lowers the risk when a "Black Swan" occurs. A Black Swan is an event that is totally unexpected and sends a shock wave through the market. This is something the professional side is hoping to minimize in terms of risk, something that they have not considered as much in the past few years, often with irreversible consequences. What the Quants are trying to determine is whether their formulas and strategies are fragile or "anti-fragile" based on the risk of a Black Swan. The problem is that if the true standard deviation is higher than estimated by a mere 5%, the probability of a catastrophic event will be increased by 5 times the original estimate. Their conclusions were fascinating and exposed the underlying problems of purely mathematical trading formulations.
The Quants are using a formula theory based on a standard bell curve, with 3 standard deviations as the mathematical premise. Recent data was tested to evaluate a negative left tail movement past 3 standard deviations to see the impact on a portfolio or trading. At 3 standard deviations beyond the norm, the losses would be catastrophic in some instances. Quants are currently of the opinion, being mathematically oriented, that Black Swans are utterly unpredictable events. I don’t agree that the markets are completely blindsided by Black Swan events. In every instance that a market-induced event turned into a Black Swan there was ample warning something was wrong, but the reality was that it is not the mathematical equations that failed but the human factor that is still present even with automated orders. Greed is the catalyst of every Black Swan market-induced event. True, non-market generated Black Swans are extremely rare events, such as the Tsunami of Japan. Most market driven events have ample warning that most traders ignore. As an example, it was blatantly obvious in 2007 that a recession of significant magnitude was coming. Every economic indicator pointed to a recession. People in the investment banks were warning it was way over the top, that the real estate market bubble was extreme, and that banks were over-leveraged. The extent of the stupidity was not known to anyone but insiders, but there were warnings.
At any rate, the goal for this year’s strategies for Quantitative Analysis is to minimize the downside risk of a Black Swan. The calculations are based on the left tail negative movement past 3 standard deviations, which would cause a devastating loss similar to what JPM experienced a while ago. Mean reversal strategies are often employed during trading range or range bound markets; however left tail risk rises significantly while profits are capped sharply. This is similar to the straddles and strangles of option trading with similar results. Although the mean reversal would be construed to be the safer strategy, market conditions in the past 3-4 months have proven that the momentum Quant strategies outperformed significantly with less risk. Therefore the argument is that the momentum strategies are less fragile and less prone to left tail risk factors. Applying this to HFT strategies for the current market provides a fascinating result. What the results showed was that although HFTs do not apply margin leveraging due to their speed of execution, HFTs do not benefit from the right tail profits, meaning they don’t receive the benefits of riding the run as a swing trader would. The HFT has lower risk because of their brief holding periods, which provide for cumulative profits quickly with minimal downside risk. This is how the HFT strategy which has a 51/49 ratio of profits to losing trades, is able to make tiny percentage penny profits on millions of dollars in trades. The results proved a couple of things:
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
The argument stems from the use of either a professional style momentum strategy, or choosing a mean reversal strategy which is what retail traders call “SAR” strategies. Please remember that your strategies are very simple and basic compared to Quant algorithms that trigger billions of orders in a very complex set of instructions. Often this code is many pages long with mathematical equations. The basis for all Quant work is mathematics, not technical analysis. What Quants are debating is whether a momentum strategy often used by HFTs or a mean reversal, actually lowers the risk when a "Black Swan" occurs. A Black Swan is an event that is totally unexpected and sends a shock wave through the market. This is something the professional side is hoping to minimize in terms of risk, something that they have not considered as much in the past few years, often with irreversible consequences. What the Quants are trying to determine is whether their formulas and strategies are fragile or "anti-fragile" based on the risk of a Black Swan. The problem is that if the true standard deviation is higher than estimated by a mere 5%, the probability of a catastrophic event will be increased by 5 times the original estimate. Their conclusions were fascinating and exposed the underlying problems of purely mathematical trading formulations.
The Quants are using a formula theory based on a standard bell curve, with 3 standard deviations as the mathematical premise. Recent data was tested to evaluate a negative left tail movement past 3 standard deviations to see the impact on a portfolio or trading. At 3 standard deviations beyond the norm, the losses would be catastrophic in some instances. Quants are currently of the opinion, being mathematically oriented, that Black Swans are utterly unpredictable events. I don’t agree that the markets are completely blindsided by Black Swan events. In every instance that a market-induced event turned into a Black Swan there was ample warning something was wrong, but the reality was that it is not the mathematical equations that failed but the human factor that is still present even with automated orders. Greed is the catalyst of every Black Swan market-induced event. True, non-market generated Black Swans are extremely rare events, such as the Tsunami of Japan. Most market driven events have ample warning that most traders ignore. As an example, it was blatantly obvious in 2007 that a recession of significant magnitude was coming. Every economic indicator pointed to a recession. People in the investment banks were warning it was way over the top, that the real estate market bubble was extreme, and that banks were over-leveraged. The extent of the stupidity was not known to anyone but insiders, but there were warnings.
At any rate, the goal for this year’s strategies for Quantitative Analysis is to minimize the downside risk of a Black Swan. The calculations are based on the left tail negative movement past 3 standard deviations, which would cause a devastating loss similar to what JPM experienced a while ago. Mean reversal strategies are often employed during trading range or range bound markets; however left tail risk rises significantly while profits are capped sharply. This is similar to the straddles and strangles of option trading with similar results. Although the mean reversal would be construed to be the safer strategy, market conditions in the past 3-4 months have proven that the momentum Quant strategies outperformed significantly with less risk. Therefore the argument is that the momentum strategies are less fragile and less prone to left tail risk factors. Applying this to HFT strategies for the current market provides a fascinating result. What the results showed was that although HFTs do not apply margin leveraging due to their speed of execution, HFTs do not benefit from the right tail profits, meaning they don’t receive the benefits of riding the run as a swing trader would. The HFT has lower risk because of their brief holding periods, which provide for cumulative profits quickly with minimal downside risk. This is how the HFT strategy which has a 51/49 ratio of profits to losing trades, is able to make tiny percentage penny profits on millions of dollars in trades. The results proved a couple of things:
- Using a mean reversal did not lower risk but rather increased risk and also cut profitability even further. This is never a good strategy.
- Momentum strategies offered lower risk as long as both sides of the market were traded and stop losses were used religiously. This is another reason why you as a retail trader, should be extremely proficient trading both the long trade position and the sell short trade position.
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
Friday, March 22, 2013
Main Article: MetaStock Monitor MARCH - APRIL 13
A Simple, Powerful Method for Trading Different Market Environments
Contributed by the Dynamic Market Lab, LLC
In 2004, the Dynamic Market Lab, LLC (our, us, we) introduced John Ehlers’ signal processing applications for the markets to the MetaStock community through introduction of the Adaptive Cycle Toolkit (ACT). The intent was clear; demystify powerful, but complex concepts and mathematics for immediate application to trading in the easily understandable MetaStock formula format. As time passed, it became apparent the real insight behind his pioneering work lay not in bringing these engineering tools to bear for market analysis, but in recognizing how these tools should be combined for maximum effectiveness.
In this article, we present one of the best approaches revealed by our extensive work with ACT. The approach is simple, powerful, and allows a trader to quickly, confidently identify different market environments, and execute a logical approach to capitalize on them, or stand down. The approach is described in the ensuing paragraphs, and all code is available from MetaStock with purchase of ACT. Discussion of the approach may appear complex, but we want you to understand the concepts, and feel comfortable with them. Fret not, application of the tools is very simple.
Three ACT or ACT modified functions are used to a) identify trend, b) measure trend strength and noise, and c) identify low risk entry points within a trend. A multi-faceted trading approach across different market modes (trending, drifting) is then suggested. The discussion below may appear complex, but the application of the tools is simple.
This approach is based on the Laguerre Transform, a modified version of David Sepiashvilli’s Trend Quality Indicator (TQI) (the ACT TQI), and a fisher transformed version of the Laguerre Stochastic.
Trend Following:
Use crossovers of price against the Laguerre Filter as the earliest warning of a trend change. Compare these crossovers to the ACT TQI. If prices are above the Laguerre Filter and the ACT TQI is > 1, a strong uptrend is likely in place, and do not trade against it. If prices are below the Laguerre Filter and the ACT TQI is < -1, a strong downtrend is likely in place, and do not trade against it. If you are trend follower, you can use these confirmed signals to initiate a trend position. We leave this to the viewer to examine the charts presented. We believe the confirmation points of the two indicators, and the trend direction to trade, are straightforward.
Mean Reversion Trading: (i.e., buy dips in an uptrend, sell peaks in a downtrend)
Mean reversion trading is based on the simple principle that when prices move far away from their average price they tend to move back to their average. This may be true in both trending and drifting markets. However, we should not employ this approach without a sound method. A strongly trending market can move prices farther from their average than expected.
Use the position of prices relative to the Laguerre Filter, and the ACT TQI to determine the market’s state. If prices are above the Laguerre Filter, and the ACT TQI is > 1, enter long trades only when the fisher transformed Laguerre Stochastic is below -2.5 standard deviations (oversold). If the price “hooks” down near the Laguerre Filter, this is even more desirable for entering long trades. If prices are below the Laguerre Filter, and the ACT TQI is < - 1, enter short trades only when the fisher transformed Laguerre Stochastic is above +2.5 standard deviations (overbought). If the price “hooks” up near the Laguerre Filter, this is even more desirable for entering short trades.
This allows us to buy dips in an uptrend, and sell peaks in a downtrend. We are capitalizing on both trend and price extremes, and using both to raise our odds of success. It is not recommended to use the oscillator values alone to take trades in the opposite direction of a strong trend. At this point, our examination of the market’s state indicates a strong trend exists, and we should not trade against it.
Range Bound or Drifting Markets:
If prices are above the Laguerre Filter, and the ACT TQI is -1< ACT TQI <1, enter long trades only when the fisher transformed Laguerre Stochastic is below -2.5 standard deviations. If prices are below the Laguerre Filter, and the ACT TQI is -1< ACT TQI <1, enter short trades only when the fisher transformed Laguerre Stochastic is above +2.5 standard deviations. During very noisy, drifting scenarios, prices tend to “hang on” to the Laguerre Filter, they are not above it (uptrends) or below it (downtrends.) In such cases, this may not be worth trading, unless the trader is selling options or option spreads to collect premium decay. These are lower probability trades because we do not have the benefit of a strong trend. These trades are strictly “range bound” trades. They may be very profitable during extensive periods of market drift. At the first sign of a price crossover of the Laguerre Filter or ACT TQI value moving beyond the +1/-1 limits, and in directions against your trade, exit immediately.
Please refer to the attached slides, and vertical lines indicating examples of these trade setups based on the rules explained above.
Conclusion:
Three carefully designed tools allow a trader to operate a simple, powerful approach across a spectrum of market conditions. Although the concepts behind the indicators we have discussed may be complex, applying them is not.
Trading is often the most successful when it is simple, and based on sound principles of market behavior. We hope that we have provided a more powerful perspective on market behavior© for you, and that you will take a look at the powerful tools and concepts in the Adaptive Cycle Toolkit (ACT).
ACT is available from MetaStock’s site in a convenient downloadable format on a risk free trial.
Disclaimer:
The Adaptive Cycle Toolkit (ACT) is a product of the Dynamic Market Lab, LLC. The techniques described in this article, and the software and related manuals, are based on approaches some consider to be experimental. As a result, this information is offered for educational purposes only. Concepts or techniques presented are not guaranteed or warranted to be profitable.
Users apply the product strictly at their own risk. They must understand that trading in stocks, commodities or other instruments has significant risks, and substantial losses may occur.
The creators of this product or authors of this article are not acting in a capacity as investment or trading advisers. Readers of this article or users of the product must accept full responsibility for their investment or trading decisions, and should seek professional investment counsel before beginning a trading/investment program.
About the ACT Developers:
Michael Burgess
Contributed by the Dynamic Market Lab, LLC
In 2004, the Dynamic Market Lab, LLC (our, us, we) introduced John Ehlers’ signal processing applications for the markets to the MetaStock community through introduction of the Adaptive Cycle Toolkit (ACT). The intent was clear; demystify powerful, but complex concepts and mathematics for immediate application to trading in the easily understandable MetaStock formula format. As time passed, it became apparent the real insight behind his pioneering work lay not in bringing these engineering tools to bear for market analysis, but in recognizing how these tools should be combined for maximum effectiveness.
In this article, we present one of the best approaches revealed by our extensive work with ACT. The approach is simple, powerful, and allows a trader to quickly, confidently identify different market environments, and execute a logical approach to capitalize on them, or stand down. The approach is described in the ensuing paragraphs, and all code is available from MetaStock with purchase of ACT. Discussion of the approach may appear complex, but we want you to understand the concepts, and feel comfortable with them. Fret not, application of the tools is very simple.
Three ACT or ACT modified functions are used to a) identify trend, b) measure trend strength and noise, and c) identify low risk entry points within a trend. A multi-faceted trading approach across different market modes (trending, drifting) is then suggested. The discussion below may appear complex, but the application of the tools is simple.
This approach is based on the Laguerre Transform, a modified version of David Sepiashvilli’s Trend Quality Indicator (TQI) (the ACT TQI), and a fisher transformed version of the Laguerre Stochastic.
- The Laguerre Transform is an average of prices derived from a mathematically “warped” cross-combination of only three current and past data points at each time interval (based on trader’s selected chart interval for trading). The three data points ensure rapid response to change; the “warped” cross-combination ensures smoothness. Prices tend to rapidly cross and “ride” above (below) the average during uptrends (downtrends), and “hang” on the average during drifting markets. This average is plotted as an overlay on prices in the chart window.
- The original TQI measures trend direction, trend strength, and market drift. It is powerful in its own right, but requires explanation to understand, and understand why we modified it.
- David Sepiashvilli introduced the TQI in a Stocks and Commodities (S&C) article, Trend Quality Indicator, as a technique to measure trend strength and noise. Copies of the article may be purchased online from S&C for $2.95.
- Sepiashvilli uses a difference between seven (7) and fifteen (15) period exponential averages to identify changes from an uptrend to a downtrend, and back again. At each crossover point, he resets his computations. He then performs the following steps: 1) measures cumulative bar to bar price change since the crossover point, 2) averages this change to compute the trend, 3) subtracts the trend from the cumulative change to compute the noise, 4) computes the square root of the moving average of the squared noise over time and multiplies this by 2. This multiplication is done so that when trend is compared to noise, if the ratio is 1 (uptrend) or -1 (downtrend), it means the trend is as strong as twice the noise. This “factor of 2 times noise” is a benchmark often used for distinguishing the onset of a trend from noise, 5) finally, he computes the ratio between the trend and noise. If the ratio is > 1, an uptrend is in force. If it is <-1, a downtrend is in force. If the result is – 1 < ratio < 1, the market is considered to be drifting. According to Sepiashvilli, the higher (lower) the ratio, the greater the strength of the uptrend (downtrend).
- We originally plotted the MetaStock version of this indicator from Stocks and Commodities Trader’s Tips code, but observed the code had an error. This was evident from the fact the indicator was not centered around zero. Since the indicator is reset at every crossover point (see above), it must by definition move back and forth across the zero line. Based upon discussion with a contact on the MetaStock forum, we were able to get corrected code that plots correctly for Sepiashvilli’s original formulation. We can supply this corrected code.
- A basic premise behind using adaptive tools is that markets are dynamic. Fixed period lengths do not always timely identify shifts in markets between trends, cycles and noise. Although the logic behind the TQI is very sound, we thought we might be able improve it a bit by replacing the fixed period lengths with ACT functions.
- Enter the ACT indicators named Mama/Fama (Cybernetic). These are nonlinear averages that speed up / slow down based on how fast the measured cycle is changing. Fama is set to follow behind the rate of change of Mama. The relationship between these two adaptive averages means it is hard for the two to cross, or cross by very much, unless a meaningful move has occurred. If Mama and Fama are substituted for the seven (7) and fifteen (15) period values in the TQI, this means it will be very difficult for the two to cross enough to exceed the noise thresholds of 1 or -1, unless a meaningful move has occurred. Furthermore, these two averages are adaptive and should rapidly change as market conditions change. Thus, there is little need to continue to optimize fixed values (such as 7, 15) for moving averages. In trading systems, the fewer the optimized parameters, the more robust the system tends to be.
- In constructing the inputs for Mama/Fama, we drew upon another concept from Ehlers’ work - ACT’s Signal to Noise function. We set a variable equal to this ratio, and used it to accelerate or slow down Mama/Fama’s cycle based computations. In other words, we would let both market cycles, and market noise, tell us what is happening.
- In daily plots of IBM (2000 through early 2007) (not shown to save space, available upon request), Sepiashvilli’s choice of parameters was quite robust, and tracked our ACT TQI quite closely. However, there were six periods during this time, ranging from a few weeks to a month, the ACT TQI identified range bound markets (-1 < ACT TQI < 1) much better than the original TQI. In candor, there was one time the original TQI was superior. The original TQI registered a slight uptick in value a few days before there was a price up gap…luck, maybe, but it did nonetheless. However, it is interesting to note the other six periods where the ACT TQI performed better, the markets made a more continuous transition from one price to another, and did not exhibit an abrupt gap.
- Thus, there is reason over a substantial span of years for a market which fell heavily, rose heavily, and drifted to believe the ACT TQI improved the traditional TQI, and thus we will use this modified version (i.e., the ACT TQI.)
- The ACT TQI is plotted in the first indicator pane. The red horizontal lines are placed at +1 (weak uptrend = 2* noise) and -1 (weak downtrend = 2* noise). If the ACT TQI > 1, an uptrend is in force. If the ACT TQI < -1, a downtrend is in force. If the -1 < ACT TQI < 1, the market is drifting. Divergences between the ACT TQI and price are, like other traditional divergences, a warning sign of possible, imminent change.
- Lastly, the fisher transformed version of the Laguerre Stochastic (FLS) is a statistically transformed version of a stochastic indicator, except the stochastic is computed from three prices first “warped” through application of the Laguerre mathematics. The three data points ensure rapid response to change; the “warped” cross-combination ensures a smooth stochastic. The fisher transform is then applied to the Laguerre Stochastic to ensure it is properly distributed according to the normal distribution function (i.e., bell curve in statistics). Many market price variations do not fit the normal distribution, and the fisher transform is one statistical technique that can be applied to help ensure computations based on such prices are normally distributed. The FLS is plotted in the second indicator pane. The red horizontal lines are placed at +2.5 standard deviations (potentially overbought) and -2.5 (potentially oversold).
Trend Following:
Use crossovers of price against the Laguerre Filter as the earliest warning of a trend change. Compare these crossovers to the ACT TQI. If prices are above the Laguerre Filter and the ACT TQI is > 1, a strong uptrend is likely in place, and do not trade against it. If prices are below the Laguerre Filter and the ACT TQI is < -1, a strong downtrend is likely in place, and do not trade against it. If you are trend follower, you can use these confirmed signals to initiate a trend position. We leave this to the viewer to examine the charts presented. We believe the confirmation points of the two indicators, and the trend direction to trade, are straightforward.
Mean Reversion Trading: (i.e., buy dips in an uptrend, sell peaks in a downtrend)
Mean reversion trading is based on the simple principle that when prices move far away from their average price they tend to move back to their average. This may be true in both trending and drifting markets. However, we should not employ this approach without a sound method. A strongly trending market can move prices farther from their average than expected.
Use the position of prices relative to the Laguerre Filter, and the ACT TQI to determine the market’s state. If prices are above the Laguerre Filter, and the ACT TQI is > 1, enter long trades only when the fisher transformed Laguerre Stochastic is below -2.5 standard deviations (oversold). If the price “hooks” down near the Laguerre Filter, this is even more desirable for entering long trades. If prices are below the Laguerre Filter, and the ACT TQI is < - 1, enter short trades only when the fisher transformed Laguerre Stochastic is above +2.5 standard deviations (overbought). If the price “hooks” up near the Laguerre Filter, this is even more desirable for entering short trades.
This allows us to buy dips in an uptrend, and sell peaks in a downtrend. We are capitalizing on both trend and price extremes, and using both to raise our odds of success. It is not recommended to use the oscillator values alone to take trades in the opposite direction of a strong trend. At this point, our examination of the market’s state indicates a strong trend exists, and we should not trade against it.
Range Bound or Drifting Markets:
If prices are above the Laguerre Filter, and the ACT TQI is -1< ACT TQI <1, enter long trades only when the fisher transformed Laguerre Stochastic is below -2.5 standard deviations. If prices are below the Laguerre Filter, and the ACT TQI is -1< ACT TQI <1, enter short trades only when the fisher transformed Laguerre Stochastic is above +2.5 standard deviations. During very noisy, drifting scenarios, prices tend to “hang on” to the Laguerre Filter, they are not above it (uptrends) or below it (downtrends.) In such cases, this may not be worth trading, unless the trader is selling options or option spreads to collect premium decay. These are lower probability trades because we do not have the benefit of a strong trend. These trades are strictly “range bound” trades. They may be very profitable during extensive periods of market drift. At the first sign of a price crossover of the Laguerre Filter or ACT TQI value moving beyond the +1/-1 limits, and in directions against your trade, exit immediately.
Please refer to the attached slides, and vertical lines indicating examples of these trade setups based on the rules explained above.
Conclusion:
Three carefully designed tools allow a trader to operate a simple, powerful approach across a spectrum of market conditions. Although the concepts behind the indicators we have discussed may be complex, applying them is not.
Trading is often the most successful when it is simple, and based on sound principles of market behavior. We hope that we have provided a more powerful perspective on market behavior© for you, and that you will take a look at the powerful tools and concepts in the Adaptive Cycle Toolkit (ACT).
ACT is available from MetaStock’s site in a convenient downloadable format on a risk free trial.
Disclaimer:
The Adaptive Cycle Toolkit (ACT) is a product of the Dynamic Market Lab, LLC. The techniques described in this article, and the software and related manuals, are based on approaches some consider to be experimental. As a result, this information is offered for educational purposes only. Concepts or techniques presented are not guaranteed or warranted to be profitable.
Users apply the product strictly at their own risk. They must understand that trading in stocks, commodities or other instruments has significant risks, and substantial losses may occur.
The creators of this product or authors of this article are not acting in a capacity as investment or trading advisers. Readers of this article or users of the product must accept full responsibility for their investment or trading decisions, and should seek professional investment counsel before beginning a trading/investment program.
About the ACT Developers:
Michael Burgess
- Co-founder of The Dynamic Market Lab, LLC. Conceptualized the ACT product.
- He received published credit for his editorial contributions to Cybernetic Analysis for Stocks and Futures, and has a unique perspective on John Ehlers work.
- He has over twenty (20) years of experience as a consultant with domestic and international corporations dealing with complex issues such as derivatives and other financial issues.
- He holds a BA from Duke University, and a Masters in Taxation from the University of Denver's Graduate Tax Program.
- Co-founder, and developer for The Dynamic Market Lab, LLC.
- He has been a C++ application developer for a healthcare software company, a mobile application developer, a technology coordinator in the ethanol industry, and currently provides litigation support work in the software and technology fields to several leading companies.
- He holds BS degrees in computer science and mathematics from Vanderbilt University with a background in algorithm design, signal processing, statistics, and numerical analysis. His academic experience includes the design and implementation of algorithms for recent mathematical theory on irregular sampling and reconstruction of digital signals in shift-invariant and wavelet spaces.
Support Tip: MetaStock Monitor MARCH - APRIL 13
How do I create a custom list?
Contributed by MetaStock Support
The Custom List Manager lets you create your own lists. The lists chan contain as many instruments from as many groups as you want. You can use these lists in the Power Console to view charts, run explorations, and run system tests. Here's how you can create your own custom lists:
1) To create a new custom list, click on either the "Tools" menu or click the "Manage Custom Lists" button at the bottom of the power console.
OR
2) After the Custom List Manager opens, click "New."
3) Enter a name for the list.
4) Enter symbols, one at a time, in the "Select Instrument(s)" field, clicking "Add" after each one.
OR look the instruments up (if you don't know the ticker symbol).
Search by the instrument name or symbol and options will auto populate below. Select the appropriate instrument name and click "OK."
5) Click "Save" to return to the Custom List Manager.
6) You can access your newly created Custom List by clicking on "Tools", then "Custom List Manager" or the Power Console.
OR
Contributed by MetaStock Support
The Custom List Manager lets you create your own lists. The lists chan contain as many instruments from as many groups as you want. You can use these lists in the Power Console to view charts, run explorations, and run system tests. Here's how you can create your own custom lists:
1) To create a new custom list, click on either the "Tools" menu or click the "Manage Custom Lists" button at the bottom of the power console.
OR
2) After the Custom List Manager opens, click "New."
3) Enter a name for the list.
4) Enter symbols, one at a time, in the "Select Instrument(s)" field, clicking "Add" after each one.
OR look the instruments up (if you don't know the ticker symbol).
Search by the instrument name or symbol and options will auto populate below. Select the appropriate instrument name and click "OK."
5) Click "Save" to return to the Custom List Manager.
6) You can access your newly created Custom List by clicking on "Tools", then "Custom List Manager" or the Power Console.
OR
Power User Tip: MetaStock Monitor MARCH - APRIL 13
Bollinger Bands - Part 1
Contributed by Breakaway Training Solutions
Bollinger Bands are one of the most popular and well known indicators in the world of technical analysis. Most traders use Bollinger Bands as a way to determine market volatility. In this first video of a three part video series on Bollinger Bands, Kevin will show you how to use Bollinger Bands inside of MetaStock. He’ll cover the basics of how they’re calculated, how to interpret them and discuss some of the different types of patterns to watch for. Have a look!
For more MetaStock training, make sure to visit Breakaway Training Solutions at www.learnmetastock.com or email Breakaway Training Solutions at admin@breakawayts.com.
About Kevin Nelson
Kevin Nelson is the founder of Breakaway Training Solutions, Inc. He has spent the last 17 years becoming an expert on MetaStock software and a serious student of technical analysis while working for MetaStock. Prior to joining MetaStock in 1993, Kevin was a stockbroker for a well-known NYSE firm. In his role as Sales Manager at MetaStock, Kevin interacted extensively with MetaStock customers via phone, webinars, and public appearances. His experiences while working at MetaStock have enabled him to gain a keen understanding of the needs of technical analysts worldwide. While with MetaStock, Mr. Nelson was a featured presenter for four years. During this time, he traveled the U.S. introducing the MetaStock program to thousands of people and teaching them how to use its many features. His easy-to-understand approach is considered by many to be the best in the industry.
©Breakaway Training Solutions, Inc. 2013
Contributed by Breakaway Training Solutions
Bollinger Bands are one of the most popular and well known indicators in the world of technical analysis. Most traders use Bollinger Bands as a way to determine market volatility. In this first video of a three part video series on Bollinger Bands, Kevin will show you how to use Bollinger Bands inside of MetaStock. He’ll cover the basics of how they’re calculated, how to interpret them and discuss some of the different types of patterns to watch for. Have a look!
For more MetaStock training, make sure to visit Breakaway Training Solutions at www.learnmetastock.com or email Breakaway Training Solutions at admin@breakawayts.com.
About Kevin Nelson
Kevin Nelson is the founder of Breakaway Training Solutions, Inc. He has spent the last 17 years becoming an expert on MetaStock software and a serious student of technical analysis while working for MetaStock. Prior to joining MetaStock in 1993, Kevin was a stockbroker for a well-known NYSE firm. In his role as Sales Manager at MetaStock, Kevin interacted extensively with MetaStock customers via phone, webinars, and public appearances. His experiences while working at MetaStock have enabled him to gain a keen understanding of the needs of technical analysts worldwide. While with MetaStock, Mr. Nelson was a featured presenter for four years. During this time, he traveled the U.S. introducing the MetaStock program to thousands of people and teaching them how to use its many features. His easy-to-understand approach is considered by many to be the best in the industry.
©Breakaway Training Solutions, Inc. 2013
Monday, March 18, 2013
Declining Volume in the Stock Market
MetaStock SPRS Series - Week 110 - TechniTrader® Stock Discussion for MetaStock Users - Declining Volume in the Stock Market - March 18, 2013
By: Martha Stokes C.M.T.
By: Martha Stokes C.M.T.
There are innumerable commentary and articles about how the US Stock Market is seeing a huge decline in volume in recent years. Certainly when you study a chart of the DJ-30 or SP-500 it is obvious that volumes are far below what they were earlier in this decade. Below is a chart of the declining volume in the Dow:
Chart 1
There is always cause and effect so the question is, “Why?” Are fewer people investing and trading, or are there fewer financial companies, or are the US financial markets in serious jeopardy? Even the Options Markets have had a huge decline in volumes. What is causing this steady decline? The real culprit is not that investors are not buying stocks. They are just not investing in Dow or S&P500 stocks as much as they did earlier. Keep in mind that 80% of the market activity is institutional. One huge factor is the fact that the financial markets are far more interwoven, complex, and there are far more Derivatives professionals and retail traders can trade. ETFs have been in huge demand, and have been on the rise as trading instruments for short term profits by the professional side.
Volumes traded in ETFs have been on the rise for more than 3 years now. Many funds are using ETFs or ETNs rather than investing in Dow or S&P500 stocks. Yes, mutual funds and pension funds must adhere to certain charter requirements but since the elimination of the “Rule of 3” (see the TechniTrader® Methodology ME10 course for a full explanation) the funds now can trade and move monies around with far less restrictions. More and more Hedge Funds and sell side institutions are buying and holding Dow and SP-500 stocks in trusts to create ETFs. Hedge Funds have become far more intricate, sophisticated, and unique. What we are seeing is that the big blue chip companies are being held more for charter or in trusts and less for short term trading activity, with fewer retail traders so volumes are declining. High Frequency Traders started rising exponentially in 2004 and peaked in 2009. HFT activity has steadily been declining as HFT firms reinvent and shift gears to other opportunities.
What is NOT causing the decline is Dark Pool activity aka OTC Giant Lot transactions. These companies are required to have all transactions recorded and documented through the National Clearinghouse just like the exchange transactions. Another area that is adding to the decline of volume in both Big Blue chip indexed stocks and stock Options, is the shift of retail traders from stock and options trading to Forex trading. It is not that the stock market is in decline or that there is less investing, what has happened is that the vast pools of American investments are spread out across a much broader array of investing and trading instruments. If you compare the Dj-30 or SP-500 to the COMPQX (Nasdaq) you will see that the COMPQX has had minimal decline in its volumes. Below is a chart image of the COMPQX:
Chart 2
Always rely upon empirical evidence such as stock charts to confirm what you read. There is no decline in the US stock market. It is busier than ever with far more opportunities for every market participant.
Trade wisely,
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
Chart 1
There is always cause and effect so the question is, “Why?” Are fewer people investing and trading, or are there fewer financial companies, or are the US financial markets in serious jeopardy? Even the Options Markets have had a huge decline in volumes. What is causing this steady decline? The real culprit is not that investors are not buying stocks. They are just not investing in Dow or S&P500 stocks as much as they did earlier. Keep in mind that 80% of the market activity is institutional. One huge factor is the fact that the financial markets are far more interwoven, complex, and there are far more Derivatives professionals and retail traders can trade. ETFs have been in huge demand, and have been on the rise as trading instruments for short term profits by the professional side.
Volumes traded in ETFs have been on the rise for more than 3 years now. Many funds are using ETFs or ETNs rather than investing in Dow or S&P500 stocks. Yes, mutual funds and pension funds must adhere to certain charter requirements but since the elimination of the “Rule of 3” (see the TechniTrader® Methodology ME10 course for a full explanation) the funds now can trade and move monies around with far less restrictions. More and more Hedge Funds and sell side institutions are buying and holding Dow and SP-500 stocks in trusts to create ETFs. Hedge Funds have become far more intricate, sophisticated, and unique. What we are seeing is that the big blue chip companies are being held more for charter or in trusts and less for short term trading activity, with fewer retail traders so volumes are declining. High Frequency Traders started rising exponentially in 2004 and peaked in 2009. HFT activity has steadily been declining as HFT firms reinvent and shift gears to other opportunities.
What is NOT causing the decline is Dark Pool activity aka OTC Giant Lot transactions. These companies are required to have all transactions recorded and documented through the National Clearinghouse just like the exchange transactions. Another area that is adding to the decline of volume in both Big Blue chip indexed stocks and stock Options, is the shift of retail traders from stock and options trading to Forex trading. It is not that the stock market is in decline or that there is less investing, what has happened is that the vast pools of American investments are spread out across a much broader array of investing and trading instruments. If you compare the Dj-30 or SP-500 to the COMPQX (Nasdaq) you will see that the COMPQX has had minimal decline in its volumes. Below is a chart image of the COMPQX:
Chart 2
Always rely upon empirical evidence such as stock charts to confirm what you read. There is no decline in the US stock market. It is busier than ever with far more opportunities for every market participant.
Trade wisely,
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
Friday, March 15, 2013
Monday, March 11, 2013
Who Is Controlling Price?
MetaStock SPRS Series - Week 109 - TechniTrader® Stock Discussion for MetaStock Users - Who Is Controlling Price? - March 11, 2013
By: Martha Stokes C.M.T.
By: Martha Stokes C.M.T.
Understanding why price is behaving the way it is at any point in a trading week is dependent upon seeing the broader scope of the market beyond the limited view of retail trading. Who has been controlling price lately? It has been retail traders, small lots, and HFTs. Recognizing their footprints is the first step, knowing how they trade habitually is the second step, and combining volume and quantity analysis with price analysis as confirmation is the third step. Once you have this information, trading becomes significantly easier, simpler, and faster. What many retail traders do not realize is that the largest lot traders and investors do not move price. When price is moving speculatively, the largest price action is often HFTs or retail, and NOT Dark Pools as many assume. As a retail trader, being able to first determine who is in control of price is a huge help because it defines quickly how price is likely to behave, what volume patterns you are likely to see, and how long the run or rally will sustain.
We are in a range bound market regardless of what news reports claim about the Dow. The Dow is a mere 30 stocks, which the giant buy side funds hold as charter stocks, and the giant sell side holds as trust fund stocks to create trading instruments to sell to small funds, retail, and the general market participants. The Dow moves on the retail side buying or selling. So those stocks seldom will move with huge gains like the underlying stocks will when news gets out that Dark Pools have accumulated. Quiet accumulation is often misused or misunderstood. It does track large lots, but there are numerous patterns within TTQA. It is not just that red bars indicates large lots distributing and green bars indicate large lots accumulating. TTQA is a sophisticated, highly sensitive indicator and it is a relational indicator to Volume and to Price. You have to use all 3 together to interpret and analyze what TTQA is saying to you, and it is always telling you more than Price and Volume alone. But it is a professional indicator and sublimely capable of revealing far more than most retail traders realize.
The professional side of the market makes great profits and most professionals are highly successful. Otherwise, they are gone quickly. The retail side has a dismal success rate. Part of the reason for this is because retail traders prefer to use what every other retail trader is using. They prefer to run with the retail crowd and use retail indicators that do not expose who is in control of price. So more often than not, they are trading against the large lots rather than with them. The ratio of pros to retail is 80/20. You need to be with the 80% and stop trading with the 20%.
Trade wisely,
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
We are in a range bound market regardless of what news reports claim about the Dow. The Dow is a mere 30 stocks, which the giant buy side funds hold as charter stocks, and the giant sell side holds as trust fund stocks to create trading instruments to sell to small funds, retail, and the general market participants. The Dow moves on the retail side buying or selling. So those stocks seldom will move with huge gains like the underlying stocks will when news gets out that Dark Pools have accumulated. Quiet accumulation is often misused or misunderstood. It does track large lots, but there are numerous patterns within TTQA. It is not just that red bars indicates large lots distributing and green bars indicate large lots accumulating. TTQA is a sophisticated, highly sensitive indicator and it is a relational indicator to Volume and to Price. You have to use all 3 together to interpret and analyze what TTQA is saying to you, and it is always telling you more than Price and Volume alone. But it is a professional indicator and sublimely capable of revealing far more than most retail traders realize.
The professional side of the market makes great profits and most professionals are highly successful. Otherwise, they are gone quickly. The retail side has a dismal success rate. Part of the reason for this is because retail traders prefer to use what every other retail trader is using. They prefer to run with the retail crowd and use retail indicators that do not expose who is in control of price. So more often than not, they are trading against the large lots rather than with them. The ratio of pros to retail is 80/20. You need to be with the 80% and stop trading with the 20%.
Trade wisely,
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
Friday, March 8, 2013
Monday, March 4, 2013
Dodd Frank Act & OTC Swaps
MetaStock SPRS Series - Week 108 - TechniTrader® Stock Discussion for MetaStock Users - Dodd Frank Act & OTC Swaps - March 4, 2013
By: Martha Stokes C.M.T.
By: Martha Stokes C.M.T.
What the professionals worry about and discuss in their news feeds is totally different than what the retail side worries about and discusses incessantly in their news. The pros are currently focused on the new regulations being set in place with the Dodd Frank Act. The discussions have gone way beyond whether that is a good or bad law to how to cope with the regulations and what it means for the financial markets’ capital structures, individual professional traders’ profits, and dealers’ profits and risk. Right now, Swaps are up for some major regulation. The OTC Swap market is gargantuan. The outstanding contracts are estimated to be $600 trillion in notional value which is 40 times the US GDP. The market turnover is approximately 2.5 times a year which means there is an estimated $1,800 trillion notional value traded annually. That is a staggering amount. Swaps are a major part of profitability, risk management, hedging, and growth of the financial industry. Pros have many concerns as the OTC Swaps have been mandated to have clearing houses just as stocks and other instruments are cleared, as a means of full transparency and full documentation of the risk inherent in the financial system.
As an example, the international Banks have been holding a vast number of Interest Rate OTC Swaps. This was a hugely profitable trading strategy for them while the Feds suppressed interest rates. But without knowing exactly how many of these Swaps were out there, the risk is high that there may not be sufficient collateral in the event something started to unravel. Another big discussion is whether dealers can still make the huge profits as these OTC markets convert to more traditional and standardized systems. These are the worries of the professional side at this time. Certainly transparency in such a massive market as OTC Swaps is necessary, but margin to cover losses is a key issue.
What you need to worry about as a retail trader are those firms that are vested in Swaps and the risk these changes and mandates will create for those firms. Certainly GS, C, BAC, JPM, and other big banks, dealers, and market makers are going to see major structural changes to their Swaps trading activity and this will have a ripple effect in stocks, options, indexes, ETFs that are associated with financial services, and big banks. The retail side news is telling everyone banks are a great bargain. The Professional side is watching and waiting to see what the OTC Swap regulations truly mean for these industries’ future profitability.
Trade wisely,
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
As an example, the international Banks have been holding a vast number of Interest Rate OTC Swaps. This was a hugely profitable trading strategy for them while the Feds suppressed interest rates. But without knowing exactly how many of these Swaps were out there, the risk is high that there may not be sufficient collateral in the event something started to unravel. Another big discussion is whether dealers can still make the huge profits as these OTC markets convert to more traditional and standardized systems. These are the worries of the professional side at this time. Certainly transparency in such a massive market as OTC Swaps is necessary, but margin to cover losses is a key issue.
What you need to worry about as a retail trader are those firms that are vested in Swaps and the risk these changes and mandates will create for those firms. Certainly GS, C, BAC, JPM, and other big banks, dealers, and market makers are going to see major structural changes to their Swaps trading activity and this will have a ripple effect in stocks, options, indexes, ETFs that are associated with financial services, and big banks. The retail side news is telling everyone banks are a great bargain. The Professional side is watching and waiting to see what the OTC Swap regulations truly mean for these industries’ future profitability.
Trade wisely,
Martha Stokes, C.M.T.
Member of Market Technicians Association
Master Rated Technical Analyst: Decisions Unlimited, Inc.
Instructor and Developer of TechniTrader® Stock Market Courses
http://technitrader.com
MetaStock Partner
©2013 Decisions Unlimited, Inc.
Disclaimer: All statements, whether expressed verbally or in writing are the opinions of TechniTrader, its instructors and or employees, and are not to be construed as anything more than an opinion. Student/subscribers are responsible for making their own choices and decisions regarding all purchases or sales of stocks or issues. At no time is any stock or issue on any list written or sent to a student/subscriber by TechniTrader and its employees to be construed as a recommendation to buy or sell any stock or issue. TechniTrader is not a broker or an investment advisor it is strictly an educational service.
Subscribe to:
Posts (Atom)