1 research outputs found
Designing a NISQ reservoir with maximal memory capacity for volatility forecasting
Forecasting the CBOE volatility index (VIX) is a highly non-linear and
memory-intensive task. In this paper, we use quantum reservoir computing to
forecast the VIX using S&P500 (SPX) time-series. Our reservoir is a hybrid
quantum-classical system executed on IBM's 53-qubit Rochester chip. We encode
the SPX values in the rotation angles and linearly combine the average spin of
the six-qubit register to predict the value of VIX at the next time step. Our
results demonstrate a potential application of noisy intermediate scale quantum
(NISQ) devices to complex, real world applications