Princeton AI-Quant Finance Faculty-SME: CFA-PRMIA-$Trillion Wall Street Hedge Funds SME: AI-Cyber-Crypto-Quantum-Risk Engineering Chief Scientist
Dr. Yogesh Malhotra, AI-ML-Cyber-Quant Finance Post-Doc
Silicon Valley VCs-Trillion $ Wall Street Hedge Funds-Pentagon Joint Chiefs-Boards-CEOs Leader: MIT-Princeton AI-Quant Finance Faculty-SME: R&D Impact among AI-Quant Finance Nobel Laureates: NSF-UN HQ Advisor
30-Years Leading AI-Quant Finance & Trading-Risk Management R&D and Practices: World's First Augmented-AI Generative Browser and MetaGenAI-MetaSearch Engine: We Create the Digital Future?. You Can Too! Let's Show You How!: New York State Government: "Join Dr. Yogi Malhotra to get up to speed on Cloud Technology." 2024: New York State Capitol Conference Presentation: "Beyond GenAI: HAI" : Save 99% Of Your Search-Learning Time-Costs With Our World-Leading "Generative AI Meta Search Engine"?, - Dr. Yogesh Malhotra "Yogi" :
"It is this?true uncertainty, and?not?risk, as has been argued, which forms the basis of a?valid theory of profit?and accounts for the divergence between?actual?and?theoretical?competition... It is a?world of change?in which we live, and a?world of uncertainty...If we are to understand the workings of the economic system we must examine the?meaning and significance of uncertainty; and to this end some?inquiry into the nature and function of knowledge?itself is necessary." - Dr. Yogesh Malhotra, Princeton Quant Trading & FinTech Crypto Conferences referencing Frank H. Knight in his classic Risk, Uncertainty & Profit.
"In the exponentially growing realms of the 'invisible' risks, those used to the pre-WWW era of 'visible' risks will be increasingly challenged to 'see' with their minds what they shall not be able to see with their eyes."
Future Of Risk: We Pioneered 30-Years Ago: Now It's the?ISO?Standard:?https://lnkd.in/d4rbE23y: #ISO31000?#Standard?#RiskManagement (2022 July)
AIMLExchange?: We create the Digital Future?. AIMLExchange.com: Join us!
Let's create the Digital Future together, we are doing so since the beginning of the WWW.
"Obsolete what you know before others obsolete it and profit by creating the challenges and opportunities others haven't even thought about."
"Yogesh Malhotra says his vision is to fill the gaps between business and technology, data and knowledge, and, theory and practice..."
"Future strategic advantage and competitive performance will not derive from simply adoption and use of new information and communication technologies. Rather, they will be determined by smart minds using smart technologies, with greater emphasis being on smart minds. In the new knowledge management paradigm, smart minds hold the key to the success or failure of business systems based upon even the smartest technologies. Some studies have even found an inverse correlation between IT investments and business performance. Apparently, spending more on information technology in itself does not translate into productivity or performance."?
"Hence, a key responsibility and challenge for corporate executives lies in cultivating and nurturing such smart minds that provide perhaps the only sustainable competitive edge. In a world characterised by continuous, radical and unpredictable change, there is hardly any competitive advantage or core competence that is sustainable. This applies as well to any competitive advantage based upon IT and information. Therefore, a viable competitive strategy seems to be one that is based upon making your own knowledge obsolete before it is obsolesced by the competition or the environment. As IT and information become more easily accessible and affordable global commodities, the real competitive advantage will rest with those who continuously devise and exploit knowledge-based advantages."?
"The synergy of 'smart minds' and 'smart technologies' provides a basis for defining agile and adaptable supply chain networks that can withstand the challenges of a radically changing business environment. Fundamental distinction between data and knowledge plays a major role in whether a system is designed for adaptation and quick response to change. Dynamically and radically changing environments overwhelm the deterministic logic of a structured model, resulting in a 70 percent failure rate of knowledge management models. The role of users' motivation, commitment, and sense making becomes all the more critical when information needs to be critiqued, renewed, reconsidered, and modified to account for changing contexts of business performance."
MIT Sloan Management Review on Partnering 'Smart Minds' with 'Smart Tools' (Winter 2018)
"Companies are succeeding with AI by partnering smart machines with smart people who are learning how to take advantage of what those machines can do. In short, AI implementation success depends on your ability to hire and develop problem-solvers, equip them with data (and potentially AI), and then empower them to actually solve problems."
Charting the Future of Finance-IT-Risk Management for Over Two Decades:
Future of Finance (https://lnkd.in/e3jZr5s FutureOfFinance.org): Within 3 weeks of our December 07, 2018 publication on SSRN of our National Association of Insurance Commissioners (NAIC) invited Expert Paper titled Advancing Cyber Risk Insurance Underwriting Model Risk Management beyond VaR to Pre-empt and Prevent the Forthcoming Global Cyber Insurance Crisis [noting potential catastrophic risks of cyber-attacks such as WannaCry], Financial Times of December 28, 2018 reported a major insurance company CEO's advice to governments for backstopping the potential catastrophic risks of such cyber-attacks in report titled: 'Swiss Re chief urges governments to back cyber insurers'. Earlier, two?months after our prognostication on LinkedIn about the Future of Hedge Funds in response to the August 25, 2017, Bloomberg reported 'The Hot New Hedge Fund Flavor Is 'Quantamental' ("Latest in Hedge Fund Flavors: Quantamental = [Quant + Fundamental]. Next expected advancements in DeepQuantum = [Deep Learning + Quantum Computing. Further on... QDQ = Quantamental * DeepQuantum"). About 4 years after our first invited presentation of Nov. 18, 2013 on Quantum Computing and Quantum Cryptography 15-miles from AFRL, the Financial Times of Nov. 1, 2017, reported that big Hedge Funds such as "Renaissance, DE Shaw look to quantum computing for edge." Prior to that on April 16, 2016, our invited presentation at the 2016 Princeton Quant Trading Conference held at the Princeton University specifically identified Amazon as the ultimate benchmark of monetization related to Digital Transformation on Slide 72. On November 24, 2017, Bloomberg reported that 'Jeff Bezos’s Net Worth Just Broke $100 Billion', Bezos being the first billionaire to build a 12-figure net worth since 1999, when Microsoft Corp. co-founder Bill Gates hit the mark. Earlier our public presentation of May 3, 2013,?15-miles from AFRL prognosticating the end of RSA-1024 was followed within 4 weeks by the first known related announcement of May 27, 2013, by Google that Google will be ditching 1024-bit RSA in favor of 2048-bit RSA. Prior to that our MidTown Manhattan presentation of January 26, 2012, on Measuring & Managing Financial Risks with Improved Alternatives Beyond Value-At-Risk (VaR) preceded the February 28, 2012 report by the Risk Magazine: "Goodbye VaR? Basel to Consider Other Risk Metrics." https://lnkd.in/e4SjjtE.
On the publication of: Renaissance, DE Shaw look to quantum computing for edge:
Fischer Black and the Revolutionary Idea of Finance?: Related excerpts at the end.
领英推荐
Following up on the conversation of 1995 with?Dr. John Holland, the pioneer of?Genetic Algorithms?(also described as?Neuroevolution)...
Reference:?Malhotra, Y., Expert Systems for Knowledge Management: Crossing the Chasm between Information Processing and Sense Making,?Expert Systems with Applications: An International Journal, 20(1), 7-16, 2001.
It seems paradoxical that despite its well-known 'cognitive biases', human 'mind' (software: versus hardware that is known as 'brain') still represents the?[yet] ultimate benchmark that Deep Learning initiatives of 'smartest' IT firms are hoping to emulate over the next several years. Just imagine the possibility of tapping the 'full potential' of human minds when they can 'self-learn' or are 'trained' to self-optimize their capabilities better such as by overcoming many such biases as substantive empirical research in diverse fields of human psychology already shows. Creating the 'smarter humans' that will not only 'design' and 'master' the 'smart tools' such as the latest Artificial Intelligence, Machine Learning, and, Deep Learning Technologies but will also 'outsmart them' on the most critical dimensions of 'sense making' (unstructured vs. structured, non-routine vs. routine, and, non-procedural vs. procedural - data and information processing, but most particularly, constructing meaning, such as in personal construct psychology, cognitive psychology, and, other fields related to human sense making) represents the utopian contrast to the dystopian views of AI?and Deep Learning in?current mainstream discussions as apparent in Henry David Thoreau's reflection that: "Men Have Become the Tools of Their Tools." More details on human-machine contrasts?critical to understanding how to design 'smart minds using smart tools' are available in our research published over the last two decades.
Here are some recent reports from the world of Hedge Funds Trading and Risk Management which seem to indicate that despite known cognitive biases of the human mind, 'smart' minds are being brought back in control at the greatest hedge funds in an environment of significant losses and draw-downs evident in the continuing stream of closures of large and small hedge funds that have been unable to survive despite the 'smart' algorithms given the wicked environments wherein the emerging future doesn't compute by simply looking in the 'rear view mirror': 1) Hedge Fund Bosses Make the Case for Humans; 2) Even the most cutting-edge quant funds rely on old-school human intuition; 3) A $96 billion fund firm created a AI hedge fund, but freaked out when it couldn't explain how it made money; 4) Human stock pickers at hedge funds are actually beating their computer competition so far this year; 5) Massive quant hedge funds run by AQR and Two Sigma are losing to humans; 6) Why Machine Learning Models Often Fail to Learn; 7) Wall Street’s Robots Still Have a Lot to Learn About Being a Human Trader.
At the same time, some other hedge funds are switching to AI-driven automated trading for specific strategies found to be missed by humans. Interestingly, Warren Buffet has already won his bet made 10 years ago with a hedge-fund manager that the S&P 500 index fund would beat over the subsequent 10 years the average of five fund-of-funds picked by that hedge-fund manager who has already conceded defeat even though the bet would have ended this December. Is it a matter of timing? Or, are most fooled by randomness? In any case, Ed Thorp, a pioneer and one of most successful practitioners of timing as well as outsmarting the Markets, whose successful real-world applications of option-pricing models [originally attributed to Louis Bachelier] preceded their publication by others awarded the Nobel Prize, would likely disagree with the randomness argument.
For someone who has any awareness of Thorp's contributions to real-world practices of Gaming and Quant Finance, Thorp's recently published autobiographical memoir, A Man for All Markets, should be an inspiring and riveting study. His story may remind some of the first name in what is likely the most famed Quantitative Finance model, namely, [Fischer] Black in the Black-Scholes Model, who did not receive the Nobel Prize awarded after his death as it isn't awarded posthumously. Interestingly, the speech delivered by Emanuel Derman, currently Director of Financial Engineering program at Columbia University and earlier Managing Director and Head Quant of Goldman Sachs, at Bloomberg New York City headquarters on November 24, 2009, 'On Fischer Black: Intuition is a Merging of the Understander with the Understood', shares interesting insights about what machines likely will still not be capable of doing in the near future as compared to humans such as Fischer Black who are well-endowed with pragmatic intuition, imagination, and inspiration.
Here is another look in the 'rear view mirror' about the core academic discipline of IT known as MIS that has been rapidly vanishing in the rear view mirror over the last two decades in the USA mainland academia despite exponential growth in all kinds of Information and Communication Technologies even though the "premier" journal of the field warned about 'driving forward while focused on the rear view mirror' in 1993. Around the same era, at the most "premier" conference of the academic discipline, the most senior academics compared the ongoing response of the discipline to the changing environment akin to 'shifting the deck chairs while the Titanic was going down'. Above events among others in the first year or two of the doctoral program inspired the emergence of an alternative hypothesis of a new PhD student, an inter-continental leader of global Banking & Finance IT practices who had originally traveled back to the USA from Asia en route to Australia leading global financial systems consulting projects spanning the world.
Having joined the PhD program, he was trying to make sense as a newbie about the normal science enterprise of academia while marveling about the pragmatic validity of mathematical models published in the most premier journals. He was also trying to reconcile their academic findings with empirical reality of strategic real-time execution and performance outcomes within the "messes" of dynamic change, complexity and uncertainty presented by the real world. He would discover that the metaphorical 'devil' isn't always necessarily in the intricacies of the mathematical models but in the most core fundamental assumptions and logic underlying the models as well as their applications that often depend upon pragmatic intuition, imagination, and, inspiration.
There may be some exceptions as in case of the Value-at-Risk (VaR) models developed and applied for financial and cyber insurance risk assessments. That being said, even when the devil is in the mathematical details, fundamental assumptions and logic, may still be critical for ensuring the 'system's credibility' [such as in the case of VaR]. Intuition of smart humans can be facilitated by smart machines even though Hegelian Dialectic seems to be of critical importance for survival of human-machine systems in increasingly indeterminate environments wherein model risk management may be as crucial as model development or use. Given quantitative measurement focus on machine learning, algorithmic, and, cryptographic models, when deploying the widely used precept 'What gets measured gets managed' [attributed to Peter Drucker, widely recognized as the Father of Modern Management], one may also need to consider that 'What gets mismeasured gets mismanaged' and 'What gets grossly mismeasured gets grossly mismanaged' - as evident from the first major Global Financial Crisis of this century.
For a Management classic on the related issue of misdirected "reward systems" [which is related to models at various levels and related mismeasurement issues noted above] written by the Chief Learning Officer of GE who later became Managing Director with Goldman Sachs: see "On the folly of rewarding A, while hoping for B": : PDF Download: https://lnkd.in/gWt9BSXt. For those with interest in Predictive Analytics and Risk Management, also accessible online is the revolutionary R&D program inspired by the same scholar-practitioner advancing the world Beyond Predictive Analytics to Anticipatory Risk Analytics since more than a decade before Wall Street CEOs, CFOs, and CROs said we need it as well as the CIO Magazine Interview of September 15, 1999 on the same program:
"I'd just caution you that?models are backward-looking.?The future isn’t the past."--?Jamie Dimon,?Chairman & CEO, JP Morgan Chase & Co., US Senate Banking Committee hearing,?June 13, 2012.
“The new business model of the Information Age, however, is marked by fundamental, not incremental, change. Businesses can't plan long-term; instead, they must shift to a more flexible "anticipation-of-surprise" model.”?--?Yogesh Malhotra,?Interview with the CIO Magazine,?September 15, 1999.?
References:
Emanuel Derman. Goldman Sachs: Quantitative Strategies Research Notes: Model Risk, April 1996. Goldman Sachs. URL: http://www.emanuelderman.com/media/gs-model_risk.pdf.
Emanuel Derman. On Fischer Black: Intuition is a Merging of the Understander with the Understood. Emanuel Derman Talk Delivered at Bloomberg, NYC. November 24 2009. URL: https://www.emanuelderman.com/media/Fischer_Black_by_Derman_Bloomberg_2009.pdf
Psychology Today. Einstein On Creative Thinking: Music and the Intuitive Art of Scientific Imagination. March 31, 2010. URL: https://www.psychologytoday.com/blog/imagine/201003/einstein-creative-thinking-music-and-the-intuitive-art-scientific-imagination.
Perry Mehrling and Aaron Brown. Fischer Black and the Revolutionary Idea of Finance. Dec 27, 2011. Wiley. URLs: https://www.richmondfed.org/~/media/richmondfedorg/publications/research/region_focus/2005/fall/pdf/book_review.pdf. https://www.amazon.com/s/ref=nb_sb_noss_2?url=search-alias%3Dstripbooks&field-keywords=%22Fischer+Black%22.
Fischer Black and the Revolutionary Idea of Finance : Related Excerpts
“The hope is that, in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today. . . .Those years should be intellectually the most creative and exciting in the history of mankind.” -J. C. R. Licklider, Man-Computer Symbiosis,??IRE Transactions on Human Factors in Electronics, 1960.
"Intuitive thinking, the training of hunches, is a much-neglected and essential feature of productive thinking not only in formal academic disciplines but also in everyday life. . . . Usually intuitive thinking rests on familiarity with the domain of knowledge involved and with its structure, which makes it possible for the thinker to leap about, skipping steps and employing shortcuts in a manner that requires a later rechecking of conclusions by more analytical means, whether deductive or inductive." - Jerome S. Bruner, The Process of Education, Harvard University Press, 1960.
“As you know, I like the idea of mixing basic and applied research. I think the best pure science grows out of efforts to solve applied problems; and sometimes the best applied science grows out of simple intellectual curiosity. . . .This award is unique. I’d rather have this than any other prize out there. I hope it helps to spread my enthusiasm for finding useful truths.”?- Fischer Black to Jon Corzine, John Cox, and Robert Merton, July 19, 1995.
"Practical experience is not merely the ultimate test of ideas; it is also the ultimate source. At their beginnings, most ideas are dimly perceived. Ideas are most clearly viewed when presented as abstractions, hence the common assumption that academics—who are proficient at presenting and discussing abstractions—are the source of most ideas. One of the dangers in our system of formal education, however, is that a student can go all the way through to an advanced degree in many fields without ever having seen an idea in the rough. An academic with this kind of background may even have trouble recognizing a new idea when he has one." - Jack Treynor, “Editor’s Comment,” Financial Analysts Journal (March/April 1973, p. 6).
"I start with the view that nothing is really constant. Volatilities themselves are not constant, and we can’t write down the process by which the volatilities change with any assurance that the process itself will stay fixed. We’ll have to keep updating our description of the process." - Fischer Black, “Studies of Stock Price Volatility Changes” (1976, p. 177).
"The totality of our so-called knowledge or beliefs, from the most casual matters of geography and history to the profoundest laws of atomic physics or even of pure mathematics and logic, is a man-made fabric which impinges on experience only along the edges. Or, to change the figure, total science is like a field of force whose boundary conditions are experience. A conflict with experience at the periphery occasions readjustments in the interior of the field.?But the total field is so underdetermined by its boundary conditions, experience, that there is much latitude of choice as to what statements to reevaluate in the light of any single contrary experience." - W.V. O. Quine,“Two Dogmas of Empiricism” (1953, p. 42)
"The machine is useful, the system in terms of which the machines gain their use is efficient, but what is man? The artist, the writer, and to a new degree the scientist seek an answer in the nature of their acts. They create or they seek to create, and this in itself endows the process with dignity. There is “creative” writing and “pure” science, each justifying the work of its producer in its own right. It is implied, I think, that the act of a man creating is the act of a whole man, that it is this rather than the product that makes it good and worthy." - Jerome S. Bruner, On Knowing (1962, p. 17)
"Preferring a search for objective reality over revelation is another way of satisfying religious hunger. . . . it follows a very different course--a stoic's creed, an acquired taste, a guidebook to adventure plotted across rough terrain. It aims to save the spirit, not by surrender but by liberation of the human mind. Its central tenet, as Einstein knew, is the unification of knowledge. When we have unified enough certain knowledge, we will understand who we are and why we are here." - Edward O.Wilson, Consilience.