Modern Stock Markets: How To Cope With Information Overload
There was a time not too long ago, when as individual stock investors, we lamented the lack of information on the market and on specific stocks. Just 13 years or so ago, with the advent of the Browser, the Internet became an everyday technology for every man. Online trading, the instant transmission of information, the power of modern computers, the sophistication of new software for analyzing streams of financial data in real-time-all these became too much of a good thing. Soon we were deluged with too much information which confused us, and the noise clouded our decision-making process.
Modern stock markets are characterized by this excess of information. In this globalized, super-speed environment of modern financial markets the winners are those who adopt a quantitative, objective, independent and unemotional approach to investment that is able to filter out the noise. The best way to cope with information overload is to subscribe to the philosophy and methodology of Quantitative Analysis using the power of modern computers and software. For Baby Boomers, this is a good time for you to learn more about the new ways to filter out noise and capture the real information you need to make your investing decisions. Here then is a summary on computerized Quantitative Analysis, and its advantages:
Stock Analysis is often divided into two categories: Fundamental Analysis (FA) and Technical Analysis (TA). Quantitative Analysis can be said to be a combination of both FA and TA. Quantitatative Analysis (QA) can be defined as the analysis and presentation of financial data using the tools and techniques of mathematics and statistics.
Typical tools used in financial QA include Times Series Analysis, Regression and Correlation, Probability, Statistical Inference and Calculus. The quantitative aspects of FA and TA can also be part of QA. The keyword to emphasize in QA is “quantitative”. A quantitative item is one that can be represented in a measurable and finite form whether it be a data item based on fundamentals or technicals.
For example some aspects of FA e.g. Balance Sheet, Profit &Loss Statement, and the financial ratios, are quantitative because they have a numerically finite value. However some aspects of FA e.g. an analyst’s assessment of the caliber of a Company’s management or its competitiveness are not quantitative but qualitative. On the other hand if Analysts’ Estimates and Recommendations can be categorized by grades, ranked and counted and numerically analyzed (such as is done in our ValuEngine models), they are quantitative.
A lot of modern TA is quantifiable e.g. the various technical indicators which measure the level or rate of change in a stock’s Price and Volume. And derivatives of the basic Price/Volume information can measure momentum, relative strength and deviation from the Mean, volatility and liquidity. However older TA techniques for identifying chart patterns (Heads and Shoulders, Triangles, Double Tops etc) are not strictly quantitative as identification of these chart patterns is subjective. Similarly Candlesticks, Elliot Waves, Gann charts and other more esoteric forms of TA are non-quantitative.
The Quant (a person who does financial quantitative analysis) believes that in order for all financial analysis to be a viable decision-support tool it should be quantitative- leaving no gray areas and room for subjective interpretation. (To Quants, even if we live in a world of uncertainty and cannot reduce everything to a Yes or No, Black or White, Zero or One, uncertainty can be still be expressed in probabilistic terms).
Reasons for advocating a quantitative approach to stock and market analysis:
1. QA can cover more of the market because, being QA, it can be computerized, and the tasks of acquiring, compiling, analyzing, and presenting the information can be completed in a fraction of the time it would take to do it manually.
2. A very important corollary of (1) is that having a larger pool of quality stocks to choose from dramatically increases your chances of outperforming the market.
3. Without computerized QA and the power of today’s computers, attempts to build models that factor in the many variables that have an effect on the markets and their complex inter-relationships, would be futile.
4. QA goes by the numbers, is objective, measurable, and leaves no room for misinterpretation.
5. For today’s markets characterized by almost instantaneous communication and information on a global basis, QA is the key to quick response.
6. Even recognizing the fact that sometimes qualitative analysis by human analysts is necessary for the final judgment and decision, QA is still an invaluable aid to them for avoiding information overload. For example, QA can help scan and screen thousands of stocks to shortlist those with specified criteria. QA can help create, optimize and track portfolios.
7. One important factor often forgotten is that because of the ease with which we can represent, manipulate and present quantitative financial data, we are able to visualize their inter-relationships in ways not possible before, and this can generate new investment ideas
8. Humans are emotional and this can be a disadvantage when trading the market. Humans might prefer to have programmed trading i.e. after analyzing all the variables, setting the buy/sell price and volume and the take profit/cut loss points, leave it to a machine to execute the trades. QA is eminently suited to this kind of trading.
9. Above all, QA is able to help you filter out the noise. "Noise" is a relative term. Its defination depends on what you don't want to hear at a particular moment in time. Therefore you use the appropriate filter for that moment to take out the noise.
Typical tools used in financial QA include Times Series Analysis, Regression and Correlation, Probability, Statistical Inference and Calculus. The quantitative aspects of FA and TA can also be part of QA. The keyword to emphasize in QA is “quantitative”. A quantitative item is one that can be represented in a measurable and finite form whether it be a data item based on fundamentals or technicals.
For example some aspects of FA e.g. Balance Sheet, Profit &Loss Statement, and the financial ratios, are quantitative because they have a numerically finite value. However some aspects of FA e.g. an analyst’s assessment of the caliber of a Company’s management or its competitiveness are not quantitative but qualitative. On the other hand if Analysts’ Estimates and Recommendations can be categorized by grades, ranked and counted and numerically analyzed (such as is done in our ValuEngine models), they are quantitative.
A lot of modern TA is quantifiable e.g. the various technical indicators which measure the level or rate of change in a stock’s Price and Volume. And derivatives of the basic Price/Volume information can measure momentum, relative strength and deviation from the Mean, volatility and liquidity. However older TA techniques for identifying chart patterns (Heads and Shoulders, Triangles, Double Tops etc) are not strictly quantitative as identification of these chart patterns is subjective. Similarly Candlesticks, Elliot Waves, Gann charts and other more esoteric forms of TA are non-quantitative.
The Quant (a person who does financial quantitative analysis) believes that in order for all financial analysis to be a viable decision-support tool it should be quantitative- leaving no gray areas and room for subjective interpretation. (To Quants, even if we live in a world of uncertainty and cannot reduce everything to a Yes or No, Black or White, Zero or One, uncertainty can be still be expressed in probabilistic terms).
Reasons for advocating a quantitative approach to stock and market analysis:
1. QA can cover more of the market because, being QA, it can be computerized, and the tasks of acquiring, compiling, analyzing, and presenting the information can be completed in a fraction of the time it would take to do it manually.
2. A very important corollary of (1) is that having a larger pool of quality stocks to choose from dramatically increases your chances of outperforming the market.
3. Without computerized QA and the power of today’s computers, attempts to build models that factor in the many variables that have an effect on the markets and their complex inter-relationships, would be futile.
4. QA goes by the numbers, is objective, measurable, and leaves no room for misinterpretation.
5. For today’s markets characterized by almost instantaneous communication and information on a global basis, QA is the key to quick response.
6. Even recognizing the fact that sometimes qualitative analysis by human analysts is necessary for the final judgment and decision, QA is still an invaluable aid to them for avoiding information overload. For example, QA can help scan and screen thousands of stocks to shortlist those with specified criteria. QA can help create, optimize and track portfolios.
7. One important factor often forgotten is that because of the ease with which we can represent, manipulate and present quantitative financial data, we are able to visualize their inter-relationships in ways not possible before, and this can generate new investment ideas
8. Humans are emotional and this can be a disadvantage when trading the market. Humans might prefer to have programmed trading i.e. after analyzing all the variables, setting the buy/sell price and volume and the take profit/cut loss points, leave it to a machine to execute the trades. QA is eminently suited to this kind of trading.
9. Above all, QA is able to help you filter out the noise. "Noise" is a relative term. Its defination depends on what you don't want to hear at a particular moment in time. Therefore you use the appropriate filter for that moment to take out the noise.
You can explore Quantitative Analysis by taking a 14-Day No-Risk Free Trial at www.valuengine.com
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