Forex Investment Optimization Using Instantaneous Stochastic Gradient Ascent—Formulation of an Adaptive Machine Learning Approach

In the current complex financial world, paper currencies are vulnerable and unsustainable due to many factors such as account deficit, gold reserves, dollar political stability, security, presence of war in region, etc. The vulnerabilities not limited above, result fluctuation instability currency values. Considering devaluation some Asian countries Pakistan, Sri Lanka, Türkiye, Ukraine, there is a tendency look beyond SWIFT system. It feasible have reserves only one currency, thus, forex markets likely significant growth their volumes. this research, we consider challenge work on having sustainable multiple world currencies. This research aimed overcome and, instead, exploit volatile nature attain sustainability reserves. regard, formulate problem propose investment strategy inspired by gradient ascent optimization, robust iterative optimization algorithm. dynamic market led us formulation development instantaneous stochastic method. Contrary conventional which considers whole population or its sample, proposed (ISGA) next time instance update strategy. We employed data containing one-year currencies’ values, results quite profitable compared strategies.