Contents/Data Tables
Data: EOD. Value Analytics Information for preparation for tomorrow's trading strategy
Table: Three days of reference points (Condition and market flow)
2 Overlays: Two days and 3 days (location of proto-balances)
3 Meta-Profiles: Last three days (details of market activity)
Yesterday total tick counts for all futures (identifies tradeability)
Market Information for Current market (new day)
Overlay + Current profile (current activity vs previous days)
Value area of combined Overlay + Current profile
CMaPS for Meta-profile value location, current reference points
Run Pause 1: Congestion detection, 15 minute basis
Run Pause 2: Congestion detection, 30 minute basis
Using Value Analytics Trading Data
Step 1. Yesterday's Data. Develop your trading strategy prior to Currrent open
You can do this anytime after 6 PM, using:
Report Table (3-Day)
Report Profiles (Last 3 Days)
Report Overlays (2 Day and 3 Day)
Step 2. Current Day: Use CMaPS to do the pre-open analysis as you choose
Step 3. Current Day: Use Todays AMVA Analysis to see the TPOs added
to the 3 day Overlay
Step 4. Current Day: Use CMaPS display to evaluate your trading strategy
for exit/entry
Step 5. Current day: Use Todays Run Pause to evaluate market condition
for exit/entry
Step 6. Anytime: Use Lookup Publications for profile information sources
Auction Market Value Analytics (tm)
Successful trading is easy to define when based on value. The breakout (initiative) trader enters on a change of
value (a breakout when the market has been balancing) and exits when value stops changing (trend end, start of congestion).
The trader of balances (responsive)
seeks to close out when value
begins changing (trend begins). The key, obviously, is to track value. Value, strictly defined, is constant only
in balanced markets. (Imagine a strongly trending market: value is constantly changing and hence is not defined in
a measurable way.)
Value Analytics(tm) is the quantification of profile and market condition variables, providing the data
for finding value The multi-day structure of Value Analytics is based on
the discovery that a single day's data is inadequate to define the development of a balanced market condition. The
minimum time is of the order of three days.
Overlay Demand Curve Background
Value Analytics views the market from a three day perspective. examining the flow of each profile variable over that
time frame.
The first step for the serious trader is to understand value. In auction markets, value is an
experimental measure: it is what the majority of traders think it is at that point in time.
They vote by trading. Often overlooked in profile literature is the fact that value can generally
only be found for a market in balance. Balance can be defined only in conjunction with a time frame: a 3 day
balance, a 9 day balance, etc. Further, a market can be in a 10 day balance while trending in the 4 day time frame.
Hence the beginning of market analysis must be an understanding of the market's condition (balance or imbalance).
Value Analytics
starts with a measure of market condition on a 2, 3, 5 and 10 day basis.
The CBOT Market Profile (1985) manual opened the door to single day value evaluation. Market Profile
methodology is propounded more clearly
in the CBOT Market Profile Manual (1991) (see CBOT site or CISCO Sitemap for free download
link). Auction Market Value Analytics) (AMVA) assumes that the user has at least a rudimentary knowledge
of profile concepts and methodology (i.e., form of a profile display (bell curve), point of control, value area,
initiative trading, responsive trading, etc.). AMVA integrates longer term Overlay measures, profile methodology
and general market principles to find value and other trading reference points as a guide to the development
of one's trading strategy (set-up).
Value is continuous and migratory, as one of our bright students noted.
Price undergoes constant change (ticks); value change is much more measured. Still, the local value (daily value area)
fluctuates even in bounded, balanced markets. If value changes slowly over a period of days
(migrates), the upper and lower limits of the balance are adjusted at the end of each day's recalculation
and balance is maintained. The balance boundaries may change somewhat. This is value 'creep'. A creeping market
remains the province of the responsive trader.
A rapid change in value
is evidenced by a price breakout from the established balance limits, with price continuing directionally. In this
case the end of day recalculation does not find a balanced market (a trend is underway). Initiative traders
work this arena. Obviously, the market's condition determines the appropriate method of attack.
Auction Market Value Analytics starts by identifying balanced market conditions, as stated. AMVA uses
timeframes of 1, 2, 3, 5 and 10 days for the
balance search. Balances, as they exist, give the information required for entry and exit decisions.
The initiative trader is constantly seeking the point where price breaks out (for entry) and once in, immediately
turns to looking for signs of congestion (for exit). The responsive trader is active in balanced conditions (selling
highs and buying lows). When a (breakout) trend begins, the responsive trader goes to the sidelines. Market
condition is thus the arbiter, the first level of analysis.
Your knowledge of market condition gives you a broad unbrella for your trading activities: the go, no go signals
of balance and imbalance.
As a trader (either responsive or initiative) continues with a trade, the market is changing (continuous and migratory,
remember?). Market behavior
reflects the collective intent of all participants; the problem lies in divining their intent from the
data flow (ticks for the most part) as quickly as possible. Here techniques introduced by Market Profile*, Meta-Profile**,
standard market analysis and CISCO research
come into play. This second level consists of e.g.: starting with market condition and then
comparing price with earlier value (value area or the
limits of a balance);
volatility change, initial balance behavior, profile value center and change, TPO analyses, etc. Each of
the 30 or so reference points in the Value Analytics table have the potential for contributing information about the
market's intent. Each profile variable, by itself, rarely dominates. It is the collective that counts. (This is the
reason that traders who concentrate on value area alone find a high variability in their trading results.)
Not all reference points are important in any one case. You must learn about each of them and how to
discriminate. This is called experience. In some profile teaching the operative word is 'holism', looking into
the pot with some 30 or so elements and somehow divining which control the taste today. Value Analytics goes the other way,
separating the elements, measuring them and their flow individually and eliminating those that do not apply to the
case at hand. Feedback is involved:
if your understanding of a particular item (say trade facilitation) is in error and you continually make that
error in your market strategy; your error will become apparent to you rather quickly. This illustrates the value
of isolating the reference points and examining them individually.
The job of Auction Market Value Analytics is to integrate the two information levels, market condition (Level 1)
and individual reference points (Level 2). This
provides the trader the most current information available
on value and the way it is changing. Both level 1 and level 2 informations are tabulated for the last
three days, so that any reference point may be traced and its trajectory determined. These
end-of-day data are available about six thirty PM, Chicago time. This gives you the time to do a
thorough pre-market analysis the night before (i.e. to develop a trading strategy for the new day). You are also prepared
for the after-market, should you wish to trade it.
The trader has two jobs; First is to integrate the latest information (last three days) into a strategy for
the coming day. This primarily draws on the Yesterday's Data on the Value Analytics pages. These data provide
the flow of the market, where it is headed. The result is a trading strategy for tomorrow. Second is
implementation of that strategy in trading tomorrow's market (Current Day on the AMVA page).
Starting about 2 AM, when some of the electronic markets begin generating substantial volume, the Current Day market Value
Analytics program offers a current analysis of the market, including it's interaction with the yesterday data list.
These data offer an answer to the trader's toughest question, "what is my market doing now (i.e. continuation or not)".
An additional tool,
'Run-Pause' analysis, examines congestion on the fly, on 15 and 30 minute scales. From midnight forward the trader
can be in touch with the market, including all the information required for trading decisions within his
(or her) trading strategy.
* Market Profile is a trademark of the CBOT.
** Meta-Profile is a trademark of CISCO. Meta-Profile methodology is copyrighted.
Information for Trading Analysis: Specifics/Benefits of the Value Analytics data package:
Last three days of auction market reference points:
1) This is enough history to find market direction and includes:
a) Four Overlays for finding market condition (2, 3, 5, 10 days)
b) Reference points for each day (value area, volume, volatility, etc.)
c) The Meta-Profiles for each of the three days
d) The 3 day Overlay and the 2 day Overlay graphics
e) 6 PM to midnight analysis via standard profile (CMaPS)
2) 3 day package minimizes rollover problems (2 days off at rollover,
once every three months)
3) Cost effective: additional data bases not required
4) Self training aid: Profile tutorial access via Lookup Tables for
Profile literature
5) Current day market tracking with the Value Analytics Current Day Programs
a) Current profile, value, etc., starting anytime after midnight
b) Display of 3 day Overlay + Current day TPOs
c) Run-Pause measure (2) for intra-day congestion
Value Analytics is the culmination of the Market Profile revolution begun by J.Peter
Steidlmayer and the Chicago Board of Trade in 1985. Their focus on day value and the dynamics
of profile formation had the stated goal of "giving the trader an edge". In the statistical universe
of an auction market, even a modest edge can lead to substantial profits in the long run (look
at what an 'edge' has done for the statistics based casino business).
As portrayed in the 1985 CBOT Market Profile Manual, Market Profile describes a market that
traces out a bell shaped (normal distribution) curve: little trading at the higher and
lower prices, with a lot of activity at the middle prices. Value is found as the central 70
percent of the cleared trading volume. Reference points such as day types, range extension
and tails are defined. These analyses are based on the CBOT Liquidity Data Bank of cleared
price, time and volume. This data bank is unique to the CBOT and the CBOT advertised a product, "The CBOT
Market Profile Service is a Detailed Breakdown of Pit Activity on the Exchange Floor. Volume
and Price Information...Measured Against Time." Market Profile parameters discussed below
were all defined in terms of the CBOT Liquidity Data Bank (LDB) data. Data from the LDB volumes
is used to find 'market condition', where 'trend' refers to intra-day behavior.
Liquidity Data/BuySell Background
Market Condition
in Value Analytics is based on multi-day (at least 3 days) behavior of the market; resulting in
a market that is either in balance (with a well defined upper and lower limit) or one with changing
value (a directional market). See e.g.
Overlay Demand Curve Background.
Within the LDB framework, the myriads of daily market profile shapes are parsed out and meaning is
inferred from their shapes and (cleared) volume. The process is primarily pattern recognition,
as is abundantly clear from the
many examples in the Manual and the various other Steidlmayer publications. And, of course, it is
an end of day process (clearing was completed around 9 PM).
A practical problem for most traders was the limitation of profile concepts to CBOT futures. e.g. Value
area is defined in terms of (cleared) volume and the CBOT LDB is the sole source. Indeed, all the
profile concepts required the LDB. Not everyone wanted to trade just CBOT futures and CISCO as
an information provider to traders quickly saw the need to be able to determine value for non-CBOT markets.
This resulted in the development of the Tick-TPO or Meta-Profile from tick data and CISCO published
on the concept in 1987 (twice).
Introduction to Day trading
Meta-Profile generalized the 'Market Profile' type analyses to all auction
markets, with ticks taking the place of cleared volume. The CISCO Overlay Demand Curve (tm) for locating
market condition (balance, imbalance) made the leap from day value to longer time-period value.
A follow-on book to the 1985 CBOT Market Profile Manual, by Dalton, Jones and Dalton (Mind Over Markets,
'MOM, 1990'), more clearly organizes the profile
field. Although their analyses were mostly on CBOT futures, they did follow the CISCO lead and applied
profile analyses to several non-CBOT futures. (MOM, Appendix 1, explains the 'TPO Value-Area Calculation',
without attribution to the source, CISCO.) 'MOM', too, is heavy on pattern recognition. And the same
is true to an extreme in the new book by the same authors (Markets in Profile, 2007) .
Enter Auction Market Value Analytics (AMVA):
There is much worthwhile in the market insights of the Market Profile publications. The
difficulty lies in the required pattern recognition methodology (holism) needed for
their application to real world market analysis. Value Analytics is designed to combine the older
Market Profile discoveries with the newer Meta-Profile and Market Condition
methodology into an analytical technique that results in objective market measurements.
Where pattern recognition provides inferences, Value Analytics offers more solid guideposts.
For instance, early termination of an auction (no tail at, say, the low) may tell
pattern recognitionists that buyers took over, with the resulting group of potential
consequences (e.g. the start of a trend). By comparison, data from Value Analytics fills in the blanks:
1) Is the market in balance?, If yes the Overlay Demand Curves provide
upper and lower limits
and the tail may have little meaning until and unless there is an upside
breakout.
2) Is the market growing (increasing range and volume) or slowing? The AMVA trader
can tell by following:
the track of TPO counts, tick counts, the trade facilitation factor, etc.
3) Is a tail incomplete? AMVA gives you quantitative measures of
subsequent behavior.
4) Is the market starting to become directional?, i.e. is price nearing a balance limit?
The Overlay for various timeframes provides an answer.
5) And a 'MOM' favorite, what is the attempted direction? AMVA calculates it.
Now let's examine some analytical results for emini SP 20070110 (data at the link):
Value Analytics Sample Data.
For the day and future posted there, the market is in balance for time frames of 2, 3, 5 and 10 days.
Volume is falling, value area is stable, TPO counts
are falling (slightly), the lower tail is incomplete (buyers took over at the low), the market showed little directionality
(Attempted Direction (2 of them) is both up and down) and TPO balances above and below the Point of Control are even. This is a
classically balanced market, waiting for something to start driving it.
In the holistic universe of profile pattern recognition a trader must have a very large
amount of 'inferential' information, putting together a number of clues into a final diagnosis.
If the market does not behave as expected, what part of the whole can be examined
to explain the failure? On the other hand, AMVA analysis is built from discrete elements as in the sample data.
These elements are put together only at the end of the study. If the analysis proves wrong it is easy to sort out
and examine the offending element(s). In fact, as markets change, as some do over time, AMVA data reflects these changes
and the trader can make adjustments.
The difference between the two disciplines (pattern recognition and AMVA) is most easy to understand by what is meant by
trader self-understanding. Self understanding to the pattern recognitionist includes
all the elements of the various patterns, how they interact and the trader's involvement
in the process. Self understanding to the
AMVA trader is simply a knowledge of the level of risk that trader is comfortable with.
What is Auction Market Value Analytics (AMVA)?
We have made some comparisons between pattern recognition and Value Analytics. In a larger sense
AMVA represents market concepts first beginning as ideas and qualitative evaluations being transformed
into more measurable, quantitative numbers. The move is from practical observational methodology
developed through the genius of Steidlmayer for his own benefit as a trader, to the more analytical format of AMVA that
can be applied by any educated trader. AMVA is not a formula, but it distills much of the
pattern recognition information into useable numbers for a trader's strategy.
AMVA is the confluence of the early work on profiles by Steidlmayer with the subsequent
analytical studies of CISCO. The insights of Steidlmayer broke new ground in the understanding
of auction markets. His contribution cannot be diminished. Without his perceptive understanding
of the markets from the perspective of being in the pits, there would possibly be no valid
auction market analyses today. His intuitive approach developed truths that we believe are better applied
by objective analyses to the (non-pit) markets of today. The bell shaped curve concept was critical
to the early description of the market. Today we know that a true bell shaped market curve
is a rarity. But the concept gave market profile it's original legs (value area). The field began rounding
out with the discovery by CISCO that TPOs are valid replacements for the cleared volume of
the original profile, for calculating value. That meant that all auction markets, not just the CBOT, could be
analyzed. As noted above, CISCO's development of the Overlay Demand Curve identifies
a market's condition (balance). Putting it all together has produced a trading tool, AMVA.
The AMVA trader can use objective measures to replace much of the intuitive, holistic
market profile teaching of today. One thing has not changed. AMVA methodology, like the original
CBOT Market Profile, gives the trader an edge, not a certainty.
The first goal of Value Analytics is to put the trader in postion to make a thorough analysis of a
market prior to open, to offer corrobrating (or not) pre-opening market behavior and finally,
to track and understand a market as it trades throughout the day. The ultimate goal, of course,
is to put the trader in position to generate more winning trades and to avoid more losers.
Heretofore, Market Profile has been the only candidate for market understanding, primarily,
for most, via the value area. Value area remains important if used properly, but it is
only one of the numerous elements needed to analyze a market. Typical questions answered
objectively by Value Analytics are:
Is the market in balance? Always the primary question.
Is volume increasing, decreasing?
Is the price range increasing, decreasing?
How well is the market facilitating trade?
Is the Initial Balance widening, narrowing?
Is the point of control rising, falling?
Is the value area increasing, decreasing?
Are the tails showing completed auctions?
Are the range extensions consistent?
What is the market 'attempting' to do?
4. Limitations on Analysis
Any measurement depends on the quality of the data. Statisticians are concerned with sample size, knowing
that a too small or poorly chosen sample will give unreliable results. In our analysis of market data, say
ticks, we are sampling a market. Value for a day, for instance, is the central 70 percent of the TPOs. How
many TPOs are needed? How many TPOs will make the cluster (quasi-bell) a reliable sample? TPOs come from
ticks and as a starting point we count ticks. Restated, how many ticks are required for an adequate sample?
A simple rule of thumb minimum is 200 ticks per day. In a four hour market this is about a tick per minute.
A 200 ticks per day market will have extended periods of inactivity. A more reasonable cutoff is in the
neighborhood of 500 ticks per day (about 2 ticks per minute average). Typically, there are about 60 deliveries
with 500 or more ticks per day. Extending down to 200 ticks brings in another 20 deliveries. Tradeables of 80 deliveries
contrasts with the some 250 contracts we cover. The Value_Analytics application has a listing of tick counts
for each future we carry (Tick Count under Yesterday's Data. The color codes are green (heavy trading,
above 500 ticks per day),
yelllow (adequate activity, 500 to 200) and red (below 200). Here tick meanS 'change in price', the actual definition
of ticks, not the transaction count (time and sales) so often carelessly called ticks. Two hundred ticks in a six hour
market is about one tick every two minutes. There are likely to be some fairly long periods with no trading
at all; so that market is not facilitating trade very well--you might get some ugly fills on a market order.
It is easy to be fooled by a bar chart of a thin market. For example, the grains often will trade heavily in
July and December (old crop, new crop) the October (e.g. soybean oil) may have little activity. However, the
the high - low price range will approximate the heavier traded deliveries. Why? Arbitrage. The exchange posts the
opening and closing prices to keep all deliveries in line. Even if there were no trades, a bar chart would show
a range for the day. For there to be a valid auction for you to trade, you must have volume, someone to take
the other side.
Value Analytics tools/data: see: Value Analytics Sample Data.
A) Post close of today: Value-Analytics Report
1. Market Condition Location of Value
10 Day Overlay
5 Day Overlay
3 Day Overlay
2 Day Overlay
2. Meta-Profile: Value, Reference Points (3 consecutive days)
General
Price range
Number price ticks
TPO count
Tick count
Trade Facilitation Factor
Volatility
Close as percent of high
Initial Balance
Price range
Number price ticks
TPO count
TPOs above/below
Value Area behavior
Price range
Price location
Point of Control
Point of Control half-hour symbols
TPOs above/below
Number price ticks
Tails
Location upper
Number price ticks upper
Completion or not upper
Location lower
Number price ticks lower
Completion or not lower
Range Extension
Price range upper
Price range lower
Attempted direction
Basis POC
Basis Rotation Factor
Multiple Distribution Days
Number distributions
For Each Distribution
Value area
POC
POC TPOs
3. Meta-Profiles: (3 consecutive days)
4. Overlay Demand Curves: 2 day and 3 day Overlays
There are some 30 entries in the Value-Analytics Table. That may seem a lot and it is.
But the market is complex and that is shown in a number of ways. At any time some of the
30 may apply, some may not. A problem with standard Market Profile analysis is that
you, the trader, are expected to recognize (holistically) the current pattern the market is
describing (day type). Then you are supposed to integrate the changes that are constantly occurring.
This can be a tall order. At end of day, of course, there are no dynamic changes. But
there will be as you trade on this information tomorrow.
In preparing for tomorrow with the value Analytics Report, the average trader can divine a
market's behavior in minutes. With that information under one's belt, setting up a
trading strategy is much, much simplified. It therefore becomes possible to analyze several
markets for the next day's trading. Diversified trading can be a reality, with all the benefits
that come with the risk reduction.
B) Tomorrow pre-open: for markets with overnight (electronic) trading
Currently, some markets begin actively trading after midnight. Within an hour or two a
comparison of current market behavior with the 3 day Overlay gives a graphic picture of
the market's follow-through of the previous day's movement. Adjustment of one's trading
strategy generated last night may be needed. If so, it will be clear what has changed
from the previous day.
C) Post open:
The same tool used for the pre-open, profile plus Overlay may be utilized throughout the day.
In addition, you may use:
a. CMaPS for Current day trading
b. Run-Pause analysis to measure balance on the 15 minute time scale
c. Run-Pause analysis to measure balance on the 30 minute time scale
D) Look-up Tables:
Any value trader has had occasion to wonder just how profile analysis applies to a particular situation.
Finding answers has been difficult because of the breadth of the coverage (yes, there
is a lot to it) and the fact that some of the expository materials (e.g. CBOT Market Profile Manual)
have no index. As a part of this product we offer a set of Look-up Tables. We have combed through
the primary references, listing index items or elements we feel can be helpful in finding answers
to questions of meaning or definition. Some of the earlier materials are free, some are still in print
and some are out of print.
The list:
C4 [203MMM.ASYMMETRY] Value_ANALYTICS_DIRECTORY.TXT
Primary References for Value_ANALYTICS
R1. Book: CBOT Market Profile 1985
Lookup Market Profile, 1985
Brief review: Market Profile (MP), Liquidity Data
R1A CBOT Market Profile 1985
Keywords Market Profile, 1985
Index/Keywords
R2. Book: Markets and Market Logic, Steidlmayer & Koy 1986
Lookup: Markets and Market Logic
Principles, Components, Market Generated Information
R3. Book: Mind Over Markets, Dalton, Jones, Dalton 1990
Lookup: Mind Over Markets
Application of R1 and R2, Directional Performance Relationships
R4. Book: CBOT Market Profile 1991
Lookup Market Profile, 1991
Brief review: Market Profile (MP), Liquidity Data
Free download on CBOT site
CBOT Market Profile Manual
(If link fails, check with CME)
R4A. CBOT Market Profile 1991
Keywords Market Profile, 1991
Index/Keywords
R5. Book: Value Based Power Trading, Jones 1993
Overlay Demand Curve, TPO Value Measure, Trader Control Package
See especially Ch. 4
R6. Book: Markets in Profile, Dalton, Dalton, Jones 2007
Markets in Profile, a Review
Review of MP, Timeframes, Long Term to Day Trading
R7. Reports: Research in Value, Auction Theory, Trading Tools, Articles
Lookup: CISCO References Page
R8. Reports: Profile Report, Dalton Capital Management/CISCO (1987 - 1991)
Lookup: Profile Report 1987 - 1991
Profile Research & Analysis
R9. Reports: Market Profile Society Intl. (1992 - 1994)
Lookup: Market Profile International
Professional Journal
