AI/ML for Stock Market Forensics

INTRODUCTION
My idea is related to the application of machine learning, based on rudimentary pattern analysis and matching, onto the field of forensic analysis of the financial markets.

I hope to raise money to support the creation of a body of work in software and machine learning that
(1) performs forensic analysis of financial markets via the application of my concepts, theories, and findings on what I refer to market consensus
(2) while at the same time, create the opportunity to rebuild my credentials to allow me to return to work.




TO LEARN MORE:
To learn about my ideas, you can visit these links:
* http://twitter.com/@market_patterns 
* http://instagram.com/market_consensus 
* http://marketconsensus.wordpress.com 




INTERNATIONAL ATTENTION AND INTEREST
This work has WORLDWIDE public interest as well as international value. Specifically, in the forensic mode, anomalies can be detected and understood whereas in the predictive mode, they can be used to help understand market behavior and evaluate hedges.

The work is not limited to forensic analysis but also predictive modeling but at this time, I prefer to focus not its predictive power. Nevertheless, the software base outcome is a project that has both forensic as well as predictive applications and I welcome approaches of others seeking to support this work into a formal startup. I have all the necessary skills to deliver this prototype but I am agreeable with partnership and other funding options.




INTELLECTUAL PROPERTY
I am versed in intellectual property and ought to be able to use several tricks and innovations to make the work patentable.

Specifically, I am the author of eight highly cited/referenced patents in various fields ranging from scalable cloud computing to anti-malware data pipelines.




CREDENTIALS
To review my credentials, see my blog:
http://nelsonmanohar.wordpress.com 

There you will find descriptions and links to my patents, and a summary of my education and work experience.




EDUCATION
UNIVERSITY OF MICHIGAN AT ANN ARBOR
Post-Doc
Information Science and Library Sciences
2008 – 2009

UNIVERSITY OF MICHIGAN AT ANN ARBOR
Ph.D
Computer Science and Engineering
1992 – 1997

UNIVERSITY OF MICHIGAN AT ANN ARBOR
M.S.E
Industrial and Operations Engineering
1991 – 1992

UNIVERSITY OF WISCONSIN – MADISON
M.S.E.E.
Computer Engineering,
1987 - 1988

UNIVERSIDAD DE PUERTO RICO – MAYAGUEZ
B.S.E.E.
Computer and Electrical Engineering
1982 – 1987




KEYWORDS:
Machine learning, artificial intelligence, fuzzy pattern analysis, python, lisp, R, data science, forensic analysis, stock markets, predictive modeling, market consensus, market patterns, feature engineering, software systems, prototypes, intellectual property, patents, research, market modeling, market behavior, etc




DISCLAIMERS:
(1) This text is tentative text. 

(2) I reserve the right to update the description, for example, to clarify any issues later on.

(3) No contractual terms are to be derived from this text.

(4) My work is fully owned by me, and my research has neither been sponsored nor funded by the U.S. government, its agencies or foreign governments -- even though it had been incompetently plagiarized by others during past twenty years.




OUTCOMES:
To be discussed later but related to a software system, data pipeline, capable of
(1) automatically generating market consensus annotation charts,
(2) comparative pattern analysis between market consensus charts,
(3) and identification of intraday market consensus interactions between/within North American indices.



A patent filing for this system may be pursued. A website documenting this system may be pursued. A press release for the outcomes may be pursued. 




HOW DID I ENDED UP HERE?
Very long and complicated story. Extensive malfeasances, related to greed and misguided retaliatory obstruction and discredit, have left me penniless, in ignominy, in debt and without resources --- due to some parties engaged in reckless implementation of virtual slavery conditions onto me to appropriate years of my findings and work. According to officials, this is now, allegedly, being investigated by the Inspector General of the USDOJ.










FIGURES AND ILLUSTRATIONS

FIGURE 1: MY ROSSETTA STONE DECODING ANALYSIS OF MARKET CONSENSUS SIGNALING (2005-2018)
















FIGURE 1B: COMMODITIES




















FIGURE 1C: COMPONENTS












FIGURE 2: ILLUSTRATIONS OF THE PREVALENCE OF MARKET CONSENSUS SIGNALING



















































FIGURE 3: ILLUSTRATIONS OF INTRADAY MARKET CONSENSUS ACTIVITY
























FIGURE 4: DYNAMICS OF MARKET CONSENSUS


















FIGURE 5: ENCODED HIDDEN (MARKOV) STATE MODELS OF MARKET DYNAMICS USING MY LINEAR TRANSFORMATIONS































FIGURE 6: GUIDING PRINCIPLES IN MY COMPARATIVE PATTERN ANALYSIS