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Auction Market Value Theory

Foreword

Auction markets have long been the province of Capital Market Theory. Behavioral economists have demolished the concepts of 'rational investors', 'one price', 'expected return' and other foundations of CAPM. Econophysists have shown markets to complex, self regulating, driven by feedback and not stochastic. CAPM has provided a convenient framework for analysis. Neither behavioral economists nor econophysicists have offered a replacement for CAPM. In fact there is no one-to-one replacement possible since a closed form solution like the gaussian distribution of CAPM does not and probably can not exist. However, long before the concept of complex markets came into fashion, a method for reading market value was in use by futures traders. Market Profile will be shown to be the fundamental element in auction market analysis, finding local (day) value. Overlay Demand Curve identifies market condition, i.e. value, on a multi-day basis. These two methodologies permit calculation of the 'market unit', the primary structural element of the market itself.



Introduction

Capital Market Theory (CAPM), as reported by Sharpe [CX-1], starts with the assumption of a stochastic (gaussian) market with daily high-lows (returns) forming the distribution. Other assumptions for CAPM, explicit or implicit, are that investors are rational, markets are efficient, value is firmly grounded in expected return, the one-price rule (no arbitrage) holds and volatiltiy (risk) is the variance of the returns. These rules are admittedly imperfect, but it is often proposed that CAPM is correct because it has predictive value (much of this through econometric analyses).

Since 1970 economic researchers have disputed every assumption of CAPM. Thaler, Kahneman and others have shown that investors are not rational, price varies too fast and too much for an efficient market, at times arbitrage dominates the stock market (program trading) and common sense argues that the variance of returns cannot be solely risk since opportunity derives from the same source.

Most devastating to CAPM is the work of the econophysicists who prove the market is complex and non stochastic. This finding throws all results derived from CAPM into question. According to the econophysicists, financial markets are a complex, self regulating process driven by feedback. Further, there is probably no distribution function that can be found to describe market behavior in general [CX-5].

Auction Markets and Value
Complex processes are met everywhere in life. The climate, ocean movement, traffic flow, tornados, one's interaction with others, airflow over a finite wing, even the motion of coffee being stirred in a cup, are all complex. Often a process will have two phases: non-complex and then, under certain conditions, a transition to complex behavior at some point. For example, airflow over a wing at low velocities (laminar flow) is well understood and easily modeled. At high velocities turbulent flow sets in. Financial markets similarly display quiet periods that are straightforward to analyze and project (econometrics works), followed by agitated periods that are not. The quiet periods are characterized by balance, where the high-low price range of the period is constrained within limits. Active periods are normally, but not always, associated with the directional phase of price movement.

A key to analyzing complex financial markets involves a change of variable. Price, the obvious choice, must be transformed into value. The catalyst is time. Price over time translates into value. A seller wants the highest price possible, a buyer, the least. Jockeying for the best deals in an auction market produces a range of prices over time. The highest prices will have few buyers. The lowest prices will have few sellers. In between prices have more activity, with most trading occurring around the middle. A price-volume plot of a day's trading will show a quasi-bell shape, thickest around the middle prices, tapering down to the small volumes at the highs and lows. Assuming that price over time defines value, the price-activity display shows the preferred prices; those prices that market participants perceive as revealing value. A price-volume (or price- activity) plot is a raw picture of market feedback.

The concept of measuring market feedback to determine value was proposed by Steidlmayer in 1985 [CX-2]. He defined value as the price range of the middle seventy percent of volume in a trading day. This definition was limited to Chicago Board of Trade futures since the CBOT Liquidity Data Bank (LDB) was the only source of volume at price. This methodology can be called LDB - Volume Jones, [CX-4], devised a methodology using price - time occurrences (TPOs) as a surrogate for volume, thus making value calculations available for all futures. The new methodology (Tick - TPO) relied on quoter or tick data and thus is available in real time. In 1988 Jones [CX-3] extended the day model to multiple days via the Overlay Demand Curve, identifying the market's condition (balancing or directional). A balancing market has unchanging value (value is a range, not a single price). Directional markets are those in which value is changing. The value approach is inductive; mesurements are made, data is analyzed and sorted and conclusions are drawn. The methodology offers an understanding of markets and market dynamics. There is no general formulation, e.g. the gaussian distribution of CAPM is not applied and there is thus less opportunity for prediction. The value approach depends on actual market measurement, effectively bringing financial economics onto a scientific basis.

Market Profiles were originally applied to one day's market, but any representative time period may be chosen. For most purposes one day is adequate, and will be used in this report. There are two types of profile: Market Profile comes from the CBOT Liquidity Data Bank and Meta-Profile is built from tick data. Both find value and for purposes of this discussion, are equivalent. Market Profile/Meta-Profile is the fundamental method of auction market analysis, the basic building block. Overlay Demand Curves use a collection of Profiles, linearly adding activity for the number of days chosen. A market will be in balance so long as the market feedback decrees. When the balance phase gives way to directional movement, that too may last an arbitrarily long time; from a part of a day to many days. If the Overlay covers enough profiles the entire cycle from balance to directionality and back to balance is displayed. Thus market condition is an observable directly connected to market activity and its feedback.

Overlay Demand Curve integrates Profiles to analyze the longer term market, revealing market condition.

Market condition developed by the overlays rely on no preconditions; no assumptions are made about fundamentals (e.g. interest rate change). Market activity, what is observed, rules in auction value analysis. The same is true in most physical experiments.

Basic Elements of Markets
The Profile is the fundamental element of auction market analysis, measuring local demand (short term value). Overlays integrate profiles to find longer term demand. The market unit is the basic element of market structure, found from Overlays. The foundation of auction market value theory lies in the set of Profile, Overlay Demand Curve and market unit.

Profiles, Overlays and market units provide a powerful platform for investigating markets. Items as diverse as market equilibrium, volatility and market opportunity will be studied as applications of value theory.

This report on Auction Market Value Theory is broken into sections. Each can be studied separately or in order.


Market Profile History



The Market Profile/Meta-Profile



Overlay Demand Curve ****put in webserver


Link: Market Unit
The Market Unit






Link: Noise
Noise Traders


Link: Pulse
Pulse


Link: Opportunity
Opportunity **** no writeup found


Link: Profit
Taking Short Term Profits Link: Volatility
Volatility and Stops for Daytrading


Link: References
Auction Market References


CX-1 Sharpe, W. (1970) (2000). Portfolio Theory and Capital Markets, MCGraw Hill
CX-2 Steidlmayer, J. (1985). CBOT Market Profile Manual
CX-3 Jones, D. (1988). Overlay Detection of Long Term Market Condition, The Profile Report, Vol 2, Oct. 1988
CX-4 Jones, D. (1987). Determining the TPO Value Area, Market Logic School, Al. Ltr. V1-#3, Apr 13
Jones, D. (1987). Estimating the Market Profile Value Area for Intra-day Trading, S&C Sep.
CX-5 Sornette, D. (2003). Why Stock Markets Crash, Princeton
Johnson, N., P. Jeffries, P. Hui (2003). Financial Market Complexity, Oxford

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