A bit past the midway point and MM1 & MM2 are 29% & 36% of an Average days trade. The world is full of counters but few know accounting. Free floats enable accounting, whereas other measures of counting are self serving vehicles for extrapolating rationalizations.
If Supply and demand were actually connected, there would be serious problems in mudville. Lots of buying, by dip stalkers but it is obviously getting the Stock Out treatment by the trade. Mostly our complex is just sold out.
Remember 8.4 billion short in May, that is mighty big deficit especially those applied to our share, which is best characterized by Spending on Obfuscation.
Here is a partial list of books that were designed to skirt the issue of supply and demand; may have other intents as well, like no human traders etc..
a full reading list was added to the thread header all designed to skirt what are the laws of stock issuance.
decades of planning
@book{AIWS95,
title = "AI Applications on Wall Street",
editor = "R. Freedman",
publisher = "Software Engineering Press",
year = "1995"
}
@article{Abu95,
author = "Y. Abu-Mostafa",
title = "Hints",
journal = "Neural Computation",
year = "1995",
volume = "7",
pages = "639--671"
}
@article{Aka74,
author = "H.~Akaike",
title = "A New Look at the Statistical Model Identification",
journal = "IEEE Trans.~Auto.~Control",
year = "1974",
volume = "19",
pages = "716--723"
}
@TechReport{AleKerMurSch98,
author = "S. D'Alessio and A. Kershenbaum and K. Murray and
R. Schiaffino",
title = "Hierarchical Text Categorization",
institution = "Department of Computer Science, Polytechnic
University",
address = {Brooklyn, NY},
year = "1998"
}
@Article{AlsGavKov94,
author = "P.~M.~Alsing and A.~Gavrielides and V.~Kovanis",
title = "Using Neural Networks for Controlling Chaos",
journal = "Physical Review E",
year = "94",
volume = "49",
number = "2",
pages = "1225-1231"
}
@inproceedings{AmaCicYan96,
AUTHOR = {S.~Amari and A.~Cichocki and H. H. Yang},
TITLE = {A new learning algorithm for blind signal
separation},
BOOKTITLE = {Advances in Neural Information Processing Systems 8
(NIPS*95)},
YEAR = {1996},
ORGANIZATION = {MIT Press},
ADDRESS = {Cambridge, MA},
PAGES = {757--763},
EDITOR = {D. S. Touretzky and M. C. Mozer and M. E. Hasselmo}
}
@Book{And71,
author = "T.~W.~Anderson",
title = "The Statistical Analysis of Time Series",
publisher = "John Wiley and Sons",
year = "1971",
address = "New York"
}
@Article{AndBol97,
Author = {Torben G. Andersen and Tim Bollerslev},
Title = {Heterogeneous Information Arrivals and Return
Volatility Dynamics: Uncovering the Long-Run in High
Frequency Returns},
Journal = {Journal of Finance},
Pages = {975--1005},
Volume = {52},
Year = { 1997 }
}
@techreport{AndBol97:ARCH,
author = {Torben G. Andersen and Tim Bollerslev},
title = {Answering the Critics: Yes, {ARCH} Models Do Provide
Good Volatility Forecasts},
month = {April},
year = {1997},
institution = {NBER Working Paper},
number = { 6023}
}
@BOOK{Aok90,
AUTHOR = {Masanao Aoki},
ADDRESS = {New York},
PUBLISHER = {Springer-Verlag},
TITLE = {State Space Modeling of Time Series},
YEAR = {1990}
}
@BOOK{AstWit89,
AUTHOR = "K.~J.~Astrom and B.~Wittenmark",
TITLE = "Adaptive Control",
YEAR = "1989",
ADDRESS = "Reading, MA",
PUBLISHER = "Addison-Wesley"
}
@book {Azo94,
author = {E. Michael Azoff},
title = {Neural {N}etwork {T}ime {S}eries {F}orecasting of
{F}inancial {M}arkets},
publisher = {John {W}iley and {S}ons},
address = {Chichester},
year = {1994}
}
@article{BacWei97,
author = {A. D. Back and A. S. Weigend},
title = {A First Application of Independent Component
Analysis to Extracting Structure from Stock Returns},
year = {1997},
journal = "International Journal of Neural Systems",
volume = "8",
PAGES = {473-484}
}
@techreport{BacWei98,
author = {Andrew D. Back and Andreas S. Weigend},
title = {Discovering Structure in Finance Using Independent
Component Analysis},
year = {1998},
note = {Proceedings of {\em Computational Finance 97.}}
}
@Article{BaiBolMik96,
Author = {R. T. Baille and T. Bollerslev and H. O. Mikkelsen },
Title = {Fractionally Integrated Generalized Autoregressive
Conditional Heteroscedasticity},
Journal = { Journal of Econometrics },
Volume = {74},
Pages = { 3-30 },
Year = { 1996 }
}
@Article{BalCha94,
author = "P.~Baldi and Y.~Chauvin",
title = "Smooth Online Learning Algorithms for Hidden
{M}arkov Models",
journal = "Neural Computation",
year = "1994",
volume = "6",
pages = "307-318"
}
@article{BalHor89,
author = "P. Baldi and K. Hornik",
title = "Neural Networks and Principal Component Analysis:
{L}earning from Examples Without Local Minima",
pages = "53--58",
journal = {Neural Networks},
volume = 2,
year = 1989
}
@INPROCEEDINGS{BaldiHornik:92,
AUTHOR = "Pierre Baldi and Kurt Hornik",
TITLE = "Back-propagation and Unsupervised Learning in Linear
Networks",
BOOKTITLE = "Backpropagation: Theory, Architectures and
Applications",
YEAR = "1992",
EDITOR = "Y. Chauvin and D. E. Rumelhart",
ASWPAGES = "?",
EXTRAADDR = "Hillsdale, N.J.",
PUBLISHER = "Lawrence Erlbaum"
}
@ARTICLE{BanRaf92, |
