Auction Market Value Theory & Analytics

Any one who can help configuring mp-mt4. I only get csv for 1,5,10,15 not for 3,20

Replace all the "." with ","

Nice to hear from you. It works fine. Thank you.

By the way, Linking csv enables you to work with the data in ms access. Linking external data establish direct connection so that any change made in the csv file will be visible immediate in the table in real time. Is there any reason why we have to work with macro in spread sheet and then import into database while we can directly do the work in a database itself in real time without the hassle of going around for further computation? Does access database alone not capable of doing the business of what we are looking for?

Hey JP,

how are you? Very interesting idea.

I think you can do that. Its only important that you can read and understand the refs meaning. The rest is upon you (creation of data tables). You already know that there are some important data tables and as long as they are correct...Or in other words updating the data should not be a problem. Because you have the tables. (The data changes every day, calculation not.)

Greetings
C

Chris,
I am doing fine, thank you. If we get the tables update in real time in database I was wondering why around. I know libre base is limited to read in real time unless it is backed by calc, but Access does in real time. Since our calculations are basic "+ - x div > < = true false yes no," just wondering if I miss something of the benefit of the turning around of going to spread sheet, macro and then into database while it could be directly dealt in "database" all at all. JP

Hi

I tried with Access a couple of years back and the problem i hit when linking to external "changing" information was the write lock issue kept glitching the data set

I tried all sorts, I am not sure if I still have the workings as it was on an old laptop. I remember doing all sorts of mirroring, copying files and then went to the time delay reading of the tables, this worked 90%+ of time and only glitched if the timings of the write and access read occurred simultaneously, which was rare

I own up to being self taught access, and never got my head into the vba side, so my experience may not be relevant to what you are thinkingh

Please disregard if this is old info and you have a way to deal with this

But dont forget that Jones method uses day closing data. So if you want to stick with the rules, you "cant use" todays developing data.

If you like you can share your list of interesting pairs for the next days here, if you want some advise/test how good you are now after some months of training. I have done that and it realy helped me, because Mzvega always had some good advise/tipps to share. And the thread comes to alive.
Share the pairs with screenshot and why you would consider a trade please.

Greetings
C

This thread has peaked my interest for some time now. Definitely I'm a beginning to intermediate student when attempting successfully to trade using profiles and the super profile. I understand the basic theory but haven't quite developed that next level experience or feel. My ultimate goal is automation. but I still need to add a Rotation Profile and learn to use the analytical data objectively. Based on trade, I would bet the EurUsd will test the 1.1330 level next. Significant Naked POC and a brush past the upper octant, which will also setup another responsive short since the 20 Day is bracketing.

Hey Trader Krw,

so you are a "beginning to intermediate" student. I dont know what you mean by that, since I dont know you or your skills. So let me ask you some questions, that we can make sure that we know what you want and what your targets are with the market profiling.

do you know the differences between profile trading and auction market theory? Or in other words do you know what auction market theory makes so special?
What is your goal with the auction market theory? You are speaking of "automation", what you mean by that?

greetings
C

References are not used for their "absolute numeric values" as trade locations on the chart. The thread is not about the "holistic" pattern recognition used in market profile. This thread is about quantitative analysis.

If you would take the time to read the thread, you would realize that "prediction" is not a permitted practice. Trade entry is based on a change in market condition not price.

References are not used for their "absolute numeric values" as trade locations on the chart. Nor do we chase price from one reference location to another.
Thats called market profile or at least what the misinformed think is MP...

Until you have read VBPT and have read through the thread learning to use analytical data, can you please refrain from posting charts with what you seem to call "basic theory". Your charts have no useful utility. We use daily profiles for their information/data content, not for there relative locations on the chart.

Your ideas about automation lead me to believe this thread would be of no interest to you.
AMVA requires "critical" thinking, and all trading is discretionary.

You posts and analysis are better suited for the market profile thread

Could you please read the content of the thread, before posting anymore of your charts

Thank You

Yes I think so. AMT in the case of markets is considered a dual auction where participants move the price both directions. Value of that price also moves and that is where profile traders focus their trade entries on. Super profile traders consider the market condition first, rotating or trending, and create trade entries based on that. Regarding automation I was hoping to create an EA that constantly asked the computer math based questions to create trade signals based on calculations of Time, Price, Volume.

Understood. Okay so I'm reduced to total rookie but I must ask, wouldn't quantitative values from AMVA be eligible for automation? What is the difference between discerning market condition manually and teaching a computer to establish its bias? Decision making in trading is essentially based on probabilities anyways.

Hey Krw,

first of all I dont know where you got your wisdom from, but we dont use the term "super profile" here. I think you mean composite profile. We want to stick with the terms Jones uses, because we are refering to his method. Jones invented composite profiles.

Yes you are right, the two way auctions and value are points to know about. There are some excelent books, published by Dalton about two way auctions and how they work.
Have you read some articles published by Jones? Why do you think the method could give you an edge?

Creating an EA might be possible - but I think thats only possible if you understand the method. And that is a lot of work and not attainable in some hours or conversations. I personaly stick with the data and chart analysis doing by my own thinking, because I dont know how a PC could do that. Jones already developed computer based tools, but I dont know anything about an EA with automatic trading.

I've read as much as I can get my hands on and watched free Dalton videos. I've traded FX since 2008 and started trading Futures this year. In that time I've had large swings up and down but am certainly a net loser. The past few years results have been positive though. The way of the present and future is autonomous tasking. This is my goal for trading. I've come to this thread to learn and improve my knowledge and own tools that I'm developing, and I hope with time I can contribute. To start, my plan was to create and run Scripts to discover probabilities based on the different setups.

Ok, but for that "different setups" you need to know how the method works. And that can only be accomplished by reading Jones articles, checking with the data and charts the same time + asking detailed questions in this thread and/or posting entries. Start by downloading the composite indi and reading the articles...

Why is it not possible that Iam just tell you the setups?
Because there is no such thing. There are no typical/mechanical entries. Forget about all that oscillator stuff (buying selling cross, divergences...) and the websites telling you how to use them. (They dont work if you dont know the condition of the market - condition is key. Every successful oscillator trader that I know dont use his indi in a mechanical way.) Auction market value theory is about understanding how the market works. Its about market conditions and how they develope and much more. I would tell you the setups, because I might also profit from your EA, but I cant show you mechanical setups, if there is no such thing.

You have studied the Dalton videos? Ok then you know that he also mentioned that fact.

My advice is, if you realy think you can handle all the important points and write an EA, then first learn everything about the method or read some articles, that you might see if it is a waste of time for your goal.

Back in the early 1980s, J. Peter Steidimayer talked the Chicago Board of Trade into collecting and releasing the Liquidity Data Bank/Market Profile. These data signaled a new era in futures analysis. For the first time we could see how much volume took place at each traded price and which class of member on the floor was doing the trading. Further, by breaking the trading day into half-hour mini-days, it became possible to see how trading was distributed within the day. The half-hourly data could be shown as standard half-hour bar charts; when the bars were collapsed onto the price axis, they formed a distribution. i.e.. the Market Profile.

These new data came with an analytical methodology. Based on Steidimayer's experience as a floor trader, Market Profile analysis described daily market behavior to an unparalleled degree. The market came alive with initial balances, range extensions, day types, price rotation, initiating activity, responsive activity, and much more. Many traders, for the first time ever, began to understand the dynamics of the marketplace in which they risked their money.

The stated aim of Market Profile analysis was to find "free exposure", "market created opportunity", a trading edge based on market understanding. Many students attended courses on Market Profile analysis taught by Steidimayer and his group, by James F. Dalton, and by others. Few of these attendees were floor traders; most were longer-term position traders. Few became successful profile traders. In retrospect, it appears that many expected too much. They wanted more than just an edge, they wanted a model to trade. Another dynamic governed day and position trader alike, a dynamic that makes it hard to become a winner on the basis of Market Profile analysis alone. That dynamic is the fact that markets are not day-to-day serially correlated. Today's results are poor predictors of tomorrow's action. There is a missing link.

Market understanding can come only from first understanding the market. And the market does not consist of one day's trading. It consists of a number of days and depends on its condition. If the market is trending, its description will include all those days since the trend began. If it is in a trading range (bracketing), it can be described only by taking into account the activity since the trend ended. The missing link to market understanding is found within the data itself. All the relevant data must be used.

The Overlay Demand Curve integrates the data into a super profile that determines the market structure and identifies the market condition. The Overlay is the missing link.

VBPT Preface p.xiii-xiv

Futures trading remains one of the few places where an individual of modest means can attain riches, as Jack Schwager (1989) shows in his book Market Wizards. The secret is leverage. The leverage factor of a futures trade is 10 to 20; under current practice less than $1,000 can control a 5,000-bushel wheat contract worth $15,000 to $20,000. A price movement of 10 cents per bushel for the trader can result in a 50 percent profit. If the price moves that amount against the trader, the loss is also 50 percent.

It is not unusual for the wheat market to move 10 cents within a few days, or even in a single day. Clearly, the large leverage can create extremely large profits quickly for the trader who is right, but most traders have found that it is not easy to be consistently right on the markets. In fact, most surveys show that up to 85 percent of traders are net losers.

It is not as surprising as it might seem that only 15 percent of traders are winners. Except for commissions, trading is a zero-sum game with 50 percent winners; add in commissions, and maybe the expectation is 40 percent winning. Then. skill also plays a role. Many public traders are ill prepared to compete with the professionals. They do not have access to the inside information and they do not have the market understanding that comes with years of experience. This book levels the playing field. Information directly from the markets, properly interpreted, can bring the public's market knowledge up to par with the professionals. Now the public can compete head-to-head with the establishment and win its share of the time.

This book shows you how to understand the condition of a futures market to use the markets inherent leverage for trading at low risk. Value Based Power Trading will teach you how to determine a market's structure and condition, who the principal players are, and what they are doing. From market structure and condition you can find value, that group of prices that most market participants perceive as fair. Then you can readily identify prices that are too high or too low, prices that ate away from value. You will know what market behavior is expected and quickly be able to detect the unexpected when it occurs. If you follow value and changes in value, you can control trading risk.

So the first part of this book's title is clear: value based market analysis is that form of technical market analysis that identifies value and value change. Risk control puts the power in Value Based Power Trading.

Your key to trading futures markets is knowing the important reference points. what is a reference point? It is a price, volume, or other variable that carries important information about a market or about a trading decision. Bracket limits, the Prices that define a trading-range market (support and resistance levels) are reference points. If we are trading a 5-10-day moving average crossover model (as we do in an example in Chapter 2), the crossover price is the most important reference point for the model. A trader who is following a model that tells him or her to go long at 9527, with a stop-loss price of 9521 and a target of 9607, has three reference points for that trade. Reference points are an underlying theme throughout this book. If you know value, you can know the most important reference points. Then you understand your market and you know what to do at turning points.

This book integrates the earlier day-based Market Profile analysis into a comprehensive, short-term through long-term methodology. Value Based Power Trading is a radical departure from price-based technical analysis. The approach of this book in locating value in futures is in many ways a counterpart of Edwards and Magees (1966) work on technical analysis of value in the stock market.

If the rise of technical market analysis in the 1970s represented a revolution in the thinking of futures traders, the conversion from price based to value-based analysis is truly the second revolution.

History
Over the past 25 years, futures analysis has gone from Primarily fundamental (long-term value) to technical (price-based), and, since 1984 (see CBOT 1984), to value-based (price-time). In the early 1970s, markets were slow-moving, risk was low, and the trader had time to get a gut feel for value. Grain analysts like Chester Keltner in Kansas City would tour the fields during the growing season and report on the crop in Progress. These reports were eagerly awaited by the fundamentalist traders, as were the U.S. Department of Agriculture crop reports and the large traders commitments.

Starting about the third quarter of 1972, and covering the next several years, world events began affecting the sleepy U.S. grains and metals markets. A civil war in Zaire and strikes in Chile put copper in short supply. An El Nio weather condition in the Pacific damaged the already overfished and depleted anchovy crop, the world's largest source of low-cost protein. The Russians had (another) crop failure and the Nixon administration sold them our surplus wheat (and some that was not surplus). Our wheat prices soared. Newspapers had a field day, reporting the Russian people eating $0.25-per-loaf bread while ours ran up to s1.00 or more. A coffee cartel became effective and another cartel, OPEC, began to affect oil and many other prices. And a fellow named Bunker Hunt began accumulating silver.

Technical Analysis: The Markets of 1972 and Later
The markets exploded. Fundamentals changed rapidly. Gut feel for fundamental value could not keep pace. Computers were becoming available, and Dunn and Hargitt had developed a futures database (from about 1963 forward, this was the original source for many others databases).. These data were newspaper daily summary data; open, high, low, close, volume, and open interest.

Dunn and Hargitt published a slim volume called Trader's Notebook (19r0) in which several technical methods wete examined and, in today's parlance, optimized. They tested moving averages, reaction methods, the Keltner Minor Trend, and Donchian's Four-Week Method. Thus began modern technical analysis, primarily as an examination of price behavior. Unlike earlier, fundamental analysis, it was quick to measure price change. Market price levels were (implicitly) equated to value (price = value). A measure of the pace of the markets of the times, Dunn and Hargitt found that the best model used a four-week moving average and the second-best one used seven weeks.

Technical analysis with daily data continued to increase in popularity. Many successful trading techniques were found and reported. The Major Price Trend Directional Indicator, a linearly weighted moving average model, appeared in the second issue of Commodities Magazine (now Futures) in April 1972. It actually worked for most of the fourteen commodities listed in the report! Technical analysis still retains a large following. (The April 1993 Futures magazine featured a comprehensive list of providers of open, high, low, and close data, reproduced herein as Appendix c.) Anyone with a personal computer can collect daily summary data electronically for a few dollars per month and do their own research. Commercially available programs allow the individual to optimize trading methods over entire databases many years long.

Technical Analysis Today
Price-based methodology is not paying off as it once did. Market conditions have changed. The long price runs of past years are fewer and farther between. Governments are regularly intervening in the currency and interest-rate markets, sometimes almost daily. Other governments intervene in the oil markets, coffee, copper, etc. There is more smart money traded by money-center banks and other financial institutions. Futures funds are large, sometimes swinging the markets. It is widely believed that outside trading money is now larger than the floor traders capitalization, removing much of the floor's buffering capability. Information of all sorts is more readily available and disseminated faster. Local markets have worldwide impact and futures markets are Popping up everywhere. All this shortens the mean time between value changes, making markets harder to track by price alone. As value changes come faster, the time frame for decisions becomes increasingly shorter.

The need for price-based technical analysis arose because of a speed up of price change in the markets. Fundamental analysis could not keep pace with the changes. The then-recent availability to the public of main-frame computers accelerated the process. Today, much of price-based technical analysis is becoming obsolete because of still faster markets. Today, everyone has access to powerful computers; but, in a zero-sum game, not everyone can win. So the stage is set for the next advance, for value-based market analysis.

Value Based Power Trading: A Detective Story
Successful trading today requires more than just price analysis. The increasing complexity of the market argues for deeper analysis. Open, high, low, and close data give little detail within the day: one cannot even tell whether the days high occurred before or after its low.
One way to increase the information is to break the day into parts; using half-hour mini-days isolates the trading into shorter time frames and narrower price ranges. Increasing the detail Permits an analyst to identify the most popular prices, the ones the market trades most often.
Value can be understood as price over time. That is, value is located by volume: it is the price region to which the market continues to return over a period of time. Looking inside the day with half-hour samples facilitates the location of the popular price regions. Later on, we will examine various time frames, coming to the conclusion that half-hour Periods are pretty good. The added detail (relative to daily data) permits an examination of price action at the price extremes. Price-based research treats all prices equally: value-based research identifies those prices that are more important to the market.

A start toward value-based analysis was made in 1984 when the Chicago Board of Trade began compiling the Market Profile and the Liquidity Data Bank (LDB). Market Profiles are built by taking a day's half-hour bar chart and collapsing the trading onto the price axis. The result is a graphic, a curve that often "looks like" the familiar bell-shaped, or Gaussian, distribution*. This form of graphic provides a picture of market structure, in one or more distributions, and how the distributions are interacting. Under stable market conditions, the distribution chart will show an upper price limit beyond which there are no more buyers, a lower limit beyond which there are no more sellers, and a heavily traded central region where most participants consider the price to be fair. Such a situation is shown in Figure 1-1.

VBPT introduction p. xv-xix

*….."looks like" does not imply, that it "is"

Market Profile, A Trading Approach
The Market Profile was introduced in the CBOT Market Profile Manual (CBOT 1984), and augmented with analytical detail in Markets and Market Logic (Steidlmayer and Koy 1986), and Taking the Data Forward (Steidimayer and Buyer 1986). From the beginning, the Market Profile was treated more as trading methodology than as merely a half-hour database with a novel and useful way of presenting a day's data, i.e., as a distribution. The concept was to use the profile, as it developed throughout the trading day, to find the markets emerging structure and to identify value. Profiles were interpreted by comparing them to a normal statistical distribution, the bell-shaped curve present in so many data situations.

Market Profile theory defined value (via the value area, the central 70 percent of trading volume) and explored the auction process as a way to understand futures markets. A series of concepts was developed to help measure and define the market's structure. There are balance areas, continuation, day types, price/value divergence, range extension, initial balances, responsive buying/selling, initiating buying/selling, time frame markets, and much more.

Day types were of particular interest to many traders; they defined market structure. Normal days had a very well defined bell shape, showing a balanced market; trend days had two or more distributions (e.g., a double distribution down day); and so forth, for each of five defined day types. CBOT (1984), Steidlmayer and Koy (1986), and Steidlmayer and Buyer (1986) each treated certain areas, but none of the publications had an index, so following ideas from text to text was difficult. The present author tied the three texts together in a review and applications guide (Jones 1988), which incorporated an index for all three, as well as definitions of terms and a collection of rules and observations.

The basic concept in Market Profile analysis is to observe the trading early in a day and then to try to fit the data into an analytical picture (e.g., day type, any price rejection at the extremes). As the trading day proceeded,, the trader is supposed to see which trading path to follow, whether responsive or initiating. Responsive buying/selling is a much-used concept throughout this text: It refers to the action taken when trading near price extremes in balanced markets. The responsive seller is active near the top of the (balanced) market, the responsive buyer, near the bottom. Initiating action is taken when the market becomes unbalanced, as when a trend starts.

Initially, Market Profile courses developed by J. Peter Steidlmayer were given at the Chicago Board of Trade. The trading rules and systematic analysis became increasingly apparent to the CBOT. This caused concern that the CBOT might be perceived as promoting a trading approach instead of just generating data. Subsequently, the trading method Part of the Market Profile was turned over to Steidimayer, with the CBOT continued to generate the data. Steidimayer and a Partner started Market Logic School. A system of market analysis based on profiles was taught by Market Logic School, and separately by Dalton capital Management (Dalton, Jones, and Dalton 1990).

Hundreds of traders were drawn to these courses by the Promise of learning how futures markets could be understood and mastered. The Dalton Group initiated a biweekly research report under the editorship of Eric T. Jones. These Profile Reports investigated all aspects of the Market Profile/ Liquidity Data Bank, Providing an unparalleled breadth and depth of information on this database.

Students of Market Logic School and the Dalton group demonstrated a willingness to do the requisite homework and study to understand profile theory. Many students continued to have difficulty in applying it to the market. Our company, CISCO, had the impetus to encourage and help traders because we were a source of the CBOT data. We interviewed many traders who stopped buying our data because they could not make profile theory work satisfactorily. They reported two main problems: within the day, they were unable to project the day's action from the developing profile to its final form; and they were unsuccessful in predicting the next day's action from the previous day's profiles.

Liquidity Data Bank, Volume Detail without Peer
An adjunct to the Market Profile is the Liquidity Data Bank, or LDB, an end-of-day report of cleared volume. A most important aspect of the LDB is its allocation of the traded volume at each price to the four classes of trader (floor member, commercial member, off-floor member, and the rest, the public). Profiles could be built in real time from a quote machine, while the LDB was available only well after the end of trading. Consequently, the Market Profile got most of the attention, although, as data vendors, we noted considerable interest in the LDB from Professional traders.

While the Market Profile and the LDB gave a much clearer picture of each day's market activity than ever before, there was poor coupling to the next day's markets. That is, profile analysis did not do a good job of predicting continuation. Something was missing. There was all this comprehensive data, a well-developed theory and poor results. Very frustrating for the student.

The Watershed: No Day-to day Serial Correlation
At CISCO,we felt that a database with 10 or 20 times the information in the daily summary had to be useful for market analysis. We also believed in the utility of the Market Profile approach. Consequently, we developed an algorithm to calculate day types. Profile theory argued for the significance of day types in predicting continuation. We felt that, once we could generate day types under computer control, we could develop enough information to find statistically the conditions under which the day type(s) could predict continuation.

Our study was negative. Surprisingly, we found little or no correlation between day type and continuation. This Point was the watershed in our research. It forced us to look outside Market Profile theory in our attempt to understand markets of longer time frame. It has long been known in futures research that markets have no day-to-day serial correlation (Labys and Granger 1970). That is to say, even in trending markets, the probability that the next day will be either up or down is about fifty-fifty. On a day basis, the market's normal fluctuation, the daily trading range, is much larger than any underlying trend, and hence hides it. Thus, it is clear that longer time frames are necessary to define the market's condition. This was the catalyst that led us to develop Value Based Power Trading.

VBPT p. xix- xxii

The Missing Link, The Overlay Demand Curve
Lacking day-to-day serial correlation, yesterdays profile should not be expected to predict today's market direction or its condition. But each day is a part of the greater whole. Whether a market is bracketing, i.e., in a trading range, or if it is trending, a number of days are required to define its condition. Within the bracket framework there can be considerable variability from day to day: but taken as a whole, a certain group of days defines the market. The individual profiles, or half-hour bars for one day, show how the market is valued by the traders on that day, reflecting the current conditions. The next day will have different local conditions, and hence the traders will value the market somewhat differently. In a non-trending market, the summation, i.e., the Overlay, of market activity over the period of stability defines the market. This gives the context of the market, the overall Picture within which each days activity can be interpreted. The Overlay Demand Curve is a graphic of longer-term market distribution, just as the Market Profile shows the distribution for one day. Without the overall picture, it is no wonder that students of the profile have had trouble using profile theory for their longer-term, position trading.

Value Based Power Trading: The Trader Controls Risk
Overlay Demand Curves form the foundation of value Based Power Trading. The Overlay Provides the longer-term distribution, the market structure. Structure can be a single, well-developed, bell-shaped curve, several separate distributions more or less interfering, or a shape so chaotic that no sense can be made of it whatsoever. Understanding the structure leads to finding the market's condition (trending or bracketing or too volatile to read). The bell case denotes a bracketing market, which, it will be shown later, leads to locating value. In such a market, the reference points are unambiguous and the traders way is clear.

Adding to the Overlay information are reference points from commercial traders, from the Publics trading behavior, from the previous day's distribution, and from a variety of sources, detailed below. Once the market condition, value, and other reference points are found, the trader is in position to make low-risk trading decisions.

Traders and Their Reliance on Value
There are four general classes of traders. Floor traders make their living by going with the flow of orders on the floor. They provide liquidity, the grease that helps keep the market moving freely. Few floor traders pay much attention to value. They are go with" people who typically use very short-term technical analyses to calculate reference points. A danger of being a go with trader lies in getting with the flow just before a major top or bottom. An understanding of value and the associated reference points could help the floor trader avoid the daily bear and bull traps.

Commercials are the businesspeople on the floor. They work for financial institutions, grain companies and the like. Each day they have business to transact on the floor, which they try to do at value. Because of their insight, they understand value better than anyone else on the floor. (For example, grain commercials know the Prices for which their firms are buying and selling grain, and hence current value.) when prices deviate from value, the commercial can become a speculator, selling at high prices, buying if price is too low. Commercial traders are closely watched by the others on the floor. Commercial volume on the Liquidity Data Bank provides a second source, a second opinion to augment the information we get from the Overlays.

Off-floor members are those who trade from offices in the exchange or from the poolside in Florida or wherever they may be.They pay higher commissions than members on the floor and they lose the closeness to the action enjoyed on the floor. They need value for their trading because they must make more per trade than those on the floor.
The public is composed of three classes with differing time outlooks. Day traders, like those on the floor, trade on market action within the day.Unlike the scalper, the public day trader pays high commissions, and like the off-floor member suffers from time delay. This trader must know value to be able to trade effectively.

Position traders look to the longer term for larger profits. This class seeks to find breakouts from balanced markets. They must know value to avoid within-bracket trades that have little potential.
Swing traders are an amalgam of day and position traders. This group will take a short-term, low-risk position. If the trade works out, it may be held for several days. Like the public day traders, this group needs value in initiating their trades and in making hold/exit decisions.

The Chapters in Brief
This book develops value Based Power Trading from the basic concept of value (price over time) to the final reference points that permit the reader to trade futures with minimum risk (the Power).

The beginning point in Chapter 1 is the data available. An understanding of this most basic of trading information, the data, is critical, if often unappreciated. Many market participants use data of various sorts from several sources without questioning applicability or validity. Even seasoned traders are often naive about data. Few realize that there are often disagreements between prices released by the exchangeCiSCO prepares a daily report of mismatches between the daily summary highs and lows (newspaper data) and the Market Profile highs and lows from the exchange clearing house.

Chapter 2 provides an analysis of the Liquidity Data Bank volume and volume distribution. while LDB reports are for one day only and do not provide market continuation information, they are invaluable for showing what the commercial and other traders are doing. These data have many, many potential uses. we will detail three ways of calculating the commercial activity and explore the utility of each. Examples will be given of commercial capping creating resistance and support levels. Also, a case of commercial trend following is examined.
Hourly LDB data are covered in Chapter 3. They provide a cross link between the standard LDB analysis and the Overlay. By having the
volume data in real time, it is possible to make very short-term corrections, even for long-term trades. Market control by commercials is contrasted with market control by the public. Breakout analysis is made for (1) a case of public and commercial support, (2) public support only, and (3) an aborted breakout without either public or commercial support.

The next step, explored in Chapter 4, is to incorporate all the data into usable analytical tools: the Overlay Demand Curve, commercial trader activity reports, daily profile analyses, and the like. The fundamental building block is the Overlay Demand Curve. It gives the condition of the market, the starting place for all trading decisions: entry, management of a trade, and exit. If the market is bracketing, the day trader is prepared to trade responsively and the position trader is waiting for a breakout. If trending, the position trader will locate stop points, the day trader looks for pulibacks, and so on. Commercial trading can alter the interpretation of the Overlay when value changes suddenly. this can be monitored on an hourly basis for CBOT trading, using the hourly Liquidity Data Bank updates.

Chapter 5 is devoted to using Value Based Power Trading methodology, the application of Overlay information to real market trade selection. A screen of bracketing markets gives the bracket size and potential for the day trader. In trending markets, Overlay theory is used to limit risk and/or protect profits. Once potential trades are identified, they can be validated from commercial traders reference points; the Rotation Index for breakout alerts; Market Profile economic activity the previous day: technical analysis for potential turning points on moving averages, oscillators, and cycles; and any other methods or models the trader normally uses.

Chapter 6 addresses trade monitoring, the tracking of a trade underway Again, reference points are the guide. They are developed as in Chapter 3 for the Overlay Demand Curve, the commercials, etc. In addition, there are considerations of money management and real-time trade monitoring. Availability permitting, the hourly LDB reports can play an integral Part in trade monitoring.

Chapter 7 discusses the future of futures analyses. while this book is breaking new ground in market analysis, it is really just scratching the surface of what can be learned. we see an increasing reliance on sophisticated technical analysis. value determination, 24-hour trading, pattern recognition, and money-flows analysis are the wave of the future.

VBPT p. xxii-xxv