Scientific Principles
Market Guidance Systems Inc. (MGS) is a unique R&D company that continuously develops cutting edge market analysis software. This software provides active traders, hedge funds and money managers with state-of-the-art decision support tools. Unlike any other company, MGS's approach to interpreting market data is based on Mathematical Psychology and Collective Behavior Pattern Recognition. This approach has been developed through extensive market research over the last 15 years and in summary, can be called the Sentiment Analysis of The Market.
The relationship between traderssentiment and price movement is a complex phenomenon. However, there are many fundamental principles underlying the design of MGS's software that enable it to follow a number of stable patterns in tradersbehavior to ensure its reliability. These patterns, in turn, are reflected in price movements that could be used to profit from. Below is a brief description of the major underlying scientific principles discovered and implemented by MGS's scientists through various software packages.
Principle of Price Representation in the Units of its Volatility
The collective behavior of a large amount of people has been studied for several years and it is a widely known fact that neither logic nor the experience of individuals plays any role in the overall behavioral patterns observed in their common activities. The same holds true for trading collectives where large amounts of traders, dispersed all over the world, are performing simultaneous betting on the price movements of any given security. Tradersactivities form a combined behavioral pattern that is completely irrelevant to the level of knowledge that each of the individual traders possesses or their prior trading experience. This phenomenon has a reflection on the price behavior of securities. In order to prove this fact, extensive research has been undertaken by MGS's scientists. To acquire an idea of the results achieved through this research, please refer to the 45-year-long daily price chart of the S&P 500 Index below.
It is not difficult to see that the daily price distribution is far from being normal Gaussian distribution. However, this picture is dramatically different if the same price movement is presented in the price volatility units measured daily. Below is the same price chart represented in what MGS's scientists call Volatility Quantum Units (VQU).
This representation of the price movement accurately depicts the collective behavior that traders exhibited over the time span of 45 years. Taking the above price pattern and measuring the distribution of price changes over their mean value gives us the almost perfect Gaussian distribution presented in the picture below.
Similar results have been identified in more than 200 different securities, including currencies, stocks, futures etc., and MGS's scientists have also been able to prove that the same pattern exists in time frames ranging from seconds to weeks, from hundreds of ticks to thousands of ticks etc. In addition, it has also been established that for each time frame, there is a permanent relationship between the length of the price time window and its VQU value.
Principle of Price Representation Through its Mean Value Measured in VQU Units
Establishing the nature of the price patterns governed by traderscollective behavior clearly proved that the Price/VQU distribution over its mean value is Gaussian. In turn, this presented a necessity to accurately predict the future value of the mean. Based on prior experience, MGS's scientists were able to define the Cubic Spline Interpolation as one of the best, and most accurate, methods in predicting future values of the mean. This was one of the primary discoveries that led to several more accurate distribution curves established on price behavior patterns. Below is a graph depicting the price distribution over the mean, calculated using 5 knot splines.
Principle of Significant Event and Reaction Time
In order to assess the significance of any market event and to estimate the upcoming price movement, the difference in reaction time between various groups of traders needs to be measured. The diversity in reaction times to an event is inherent in any collective of people. The idea of dividing a large group of people with a common goal into subdivisions is an important concept derived from spectrum analysis. Because there could be thousands of traders involved in trading at any instance, we grouped our information by dividing all the traders currently involved in trading into a large amount of distinct groups. All of the traders in each group exhibited similar reaction times to any event that happened in the market. Categorizing traders by their reaction time, analyzing the sentiment of each of these groups of traders, then displaying the tradersconfidence in the present trend in a specific security gives an accurate estimate of the upcoming price movement. It has also been determined that the significance of an event falls exponentially as time elapses.
Principle of Sliding Time Windows
Identifying the relative significance of an event and the subsequent reaction of traders is the cornerstone of MGS's software. The moving relative scale uses tradersreaction to recent events to assess their sentiment to the current event. The significance of an event and its impact on the price movement is calculated relative to a passed event and subsequent price movement. The narrower the history, the more relevant or accurate the predicted price movement is to the current event. Our propriety sentiment spectrum visually displays the relative associative real time analysis of market activity.
Principle of Price Movement
Price movement is difficult to assess since there is no record of the intentions of 'at market' traders. However, our research team has devised a formula that correlates an unknown price movement with the known values of tradersactions to assess the future price movement. We have discovered that there is an exceptionally high correlation between tradersactions (buying and selling) over a given period of time and the price movement over the same time frame. By taking the difference of the total number of asks minus the total number of bids (both weighted by the distance to the current price level) in any given time frame, it is possible to assess an upcoming price movement with reasonable accuracy. Our scientists have established the relationship between price distribution and its volatility using this approach.
Principle of Mapping using the Market Elasticity Theory
Using innovative interpolation techniques, MGS's software relates the changes in Bid and Ask sizes to the changes in price over a sliding window. We can calculate the elasticity of the market by measuring the behavior of the average trading group compared to the extreme trading group. This approach enables us to assess the amount of pullback necessary to restore equilibrium to the market and the effect this pullback has on the price movement.
Principle of Kinetic Energy
Our research team has applied the principles of kinetic energy to market situations. Kinetic energy, the energy of motion, is directly proportional to the square of the speed of an object times its mass. If you know the amount of kinetic energy stored in an object, you can calculate the amount of force required to stop this object. Price movement exhibits kinetic energy where the mass is the number of shares traded and the speed is the price movement in a given time frame. By continuously assessing the kinetic energy stored in any price movement, MGS's software can calculate the probability of an event in the market having enough force to stop the current price movement.
Conclusion
Market Guidance Systems Inc.'s main goal is to bring various elements of scientific computing, bioengineering, neuroscience, finance and software development together into a unified framework. Our 15 years of research and development demonstrates an established track record as problem-solvers in the scientific, bionic and financial fields.
MGS's software is derived from a new, interdisciplinary scientific field called Bionics. Stemming from the words biology and technology, bionics is at the intersection of psychology, engineering and mathematics. For our development team, the main goal of bionics is to transfer decision-making and problem-solving strategies developed by active traders into the technological realm. This, in turn, requires new and innovative solutions for active traders in financial markets.
MGS's software has been designed using biological and human-computer design principles. The advanced human-computer interface creates a cyclical interaction in which the computer automatically handles all raw data analysis while subsequent acts are essentially manual with the trader interpreting the display, taking the appropriate course of action and then executing the trade. It is essential for traders to execute orders at the right time and at the right price. To accomplish this, the computer must work intimately with the trader.
An essential part of MGS's software is a direct access execution platform with a state-of-the-art order placement technique that is unique to the industry. The fundamentals of ergonomics and bionics govern the design of this execution platform. The single screen interface allows the trader to execute trades with a minimum amount of effort.