...True Positive Technologies, which creates investment strategies for institutional investors with the use of machine learning, has been working with quantum computers since 2014 for portfolio optimization and scenario simulations....
It typically takes too many observations for an econometric model to gather enough information to conclude that a structural break has taken place. ML algorithms are better suited for recognizing change before it is too late...Read this newsletter
A machine learning algorithm learns patterns from data without us programming the answer. The learned patterns can be extremely complex and not representable as a small set of equations. Fortunately, we can interrogate the ML algorithm for the reasons behind a decision...Read this newletter
There are dozens of trillions of dollars allocated today using Markowitz-style portfolio optimization methods, despite all empirical and mathematical evidence that demonstrates how costly this mistake is...Read this newsletter
QUANTMINDS CONFERENCE - LISBON…Finance is perhaps the last remaining sector of the economy that is still virtually unaffected by these technologies. Here we are, in the 21st century, when cult-like activities such as technical analysis still have greater following or assets under management than ML-based funds. Part of the problem is that finance is a particularly difficult field for ML. Standard ML techniques tend to fail when applied to investments problem. Finance accounts for about 10%-20% of the GDP in the United States, depending on various definitions. That gives you an idea of the magnitude of the disruption that we are about to experience…
Most discoveries in empirical finance are false, as a consequence of selection bias under multiple testing. This may explain why so many hedge funds fail to perform as advertised or as expected. These false discoveries may have been prevented if academic journals and investors demanded that any reported investment performance incorporates the false positive probability, adjusted for selection bias under multiple testing. In this paper, we present a real example of how this adjusted false positive probability can be computed and reported for public consumption.
Financial firms today are the pharmaceutical companies of a century ago. As a result of promoting false strategies, every year financial firms defraud investors for tens of billions of dollars. The Madoff scandal is negligible in comparison. It is, perhaps, the greatest scam in financial history, and it will only worsen as more powerful computers allow for an ever-larger number of trials.