Equational

 My previously shared bookshelf picture got a hit peak and this got me thinking:  Most of my books are more than 20 year old. Some are from my dad and his older brothers. That means they are sixty+ years old! (FYI my dad, Socrates Litsios , recently passed away, had a PhD from MIT (operational research in EE department)). I have never been a linear student (except with audio books). I tend not to read books but to read publications. And even then, I skim the publications, I do not read them. However, I do a lot: I program prototype on prototype during my spare time. I implement software for real professionally, mostly in rocket science areas that rely on math. Therefore most of these books still resonate with me, having used much what is in them. That is why I keep them. Once a year I throw out the books that no longer resonate. A month ago I put 30 of these books on a chair on the sidewalk, including my Collected Algorithms from ACM books (mostly Fortran in print). At th...

At least eight dimensions can be used qualify the way financial participants trade: Transaction speed from slow to quasi-instantaneous. Transaction rate from rare/infrequent to quasi-continuous. Selection of transactions from disorganized to very organized (e.g. backed by mathematics and research). Transaction's future obligations from no future obligations to with future obligations (e.g. backed by personal wealth). Time scope of transaction's obligation from immediate (e.g. transfer cash) to long term (e.g. payout bond coupon after 30y). Number of participants on "same side of transaction" from small to large Size of single transaction from small to large. Influence of fundamental/"real world" properties of traded contract from none to very important. In the context of the GameStop event we note the following:  Traditionally,  retail investors execute transactions: Slowly Infrequently In a disorganized way With no future obligation With only immediate obli...

In 1996, my team adopted a tensor view of its application parameter space. Credit must be given to one of my partners at QT Optec/Actant, who presented the following view of the world: each client could "tie" each parameter to any point/slice in "high-dimensional" cartesian space of primary and secondary keys. It was an advanced concept which took me many years to fully master. The simple statement is: "it ain't easy"! Higher dimensional data views are "all the rage" now, but not in 1996. I'll try to illustrate the concept as follows: Imagine we have a parameter P1 used in formula F that goes from X to Y. Imagine that X can be queried with keys kx0 and kx1 (it is two dimensional) and Y is three dimensional with "axis" ky0, ky1, and ky2. P1 is a parameter, which means that it is a "given value". The question is then: is P1 just one value? Should we use a different P1 for the different values of X tied to its 2d mapping ...