Cognitive Radio Optimization

By Arman Zaribafiyan & Jaspreet Oberoi

This research proposes a new approach for tackling cognitive radio asset allocation optimization problems. The cognitive radio optimization problem is generally an NP-hard mixed-integer programming problem due to its convoluted constraints. In contrast to conventional methods of using meta-heuristics and evolutionary algorithms, we implement non-linear constraints as polynomial penalty functions of binary variables and build a new objective function in a quadratic unconstrained binary optimization (QUBO) format.

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Most Recent Papers

CME Market Sentiment Meter Historical Market Analyses – Gold – 2019 Federal Funds Rate Cuts

Periods of Anxious market states for COMEX Gold futures (GC1) tended to be either short-lived or long-lived in the eight-year period ending in December 2019. In 2018, the U.S. saw economic growth and the Federal Reserve hiked rates four times during the year. The year was dominated primarily by Balanced market states, and GC consistently fell once the rate hikes were announced. The year 2019 saw slowed economic growth and increased tensions with China, Iran, and Russia. This led to a large rise in GC from July to November, and GC remained at a high relative to the beginning of the year. In 2019, the Federal Reserve made three rate cuts. During this time, the Market Sentiment Meter (MSM) indicated an extended period of Anxious market states from July to November.

Market Reactions to COVID-19

A review of Q1 2020 as seen in the CME Market Sentiment Meter By Anish R. Verma, Andrew Milne The COVID-19 pandemic had a notable effect on the eight futures and options products tracked by 1QBit’s CME Market Sentiment Meter. In some markets, such as U.S. equity index...