We’re excited to open source Slsqp4j, a Java wrapper around the popular SLSQP nonlinear optimizer.
SLSQP is a nonlinear optimization algorithm, included as part of SciPy’s
optimize package. It was originally outlined by Dieter Kraft in  and implemented in . SLSQP uses a sequential-quadratic-programming approach to solve nonlinear optimization problems. It can solve constrained and unconstrained as well as bounded and unbounded problems. This makes it an attractive general-purpose solver.
One of the most beneficial ways blockchain technology could be used in traditional markets is by speeding up trade settlements — typically taking two days to complete through a cumbersome and expensive process. The efficiency gains could yield potentially tremendous savings — options on S&P500 alone traded on average $400bln+ notional daily in 2018. …
Q2 was a great quarter for cryptocurrency markets and derivatives in particular: this is our take on the main developments.
1/. General Performance
2/. Macro theme #1: Easing
3/. Macro theme #2: Facebook