Quantum portfolio value forecasting
- URL: http://arxiv.org/abs/2111.14970v1
- Date: Mon, 29 Nov 2021 21:29:15 GMT
- Title: Quantum portfolio value forecasting
- Authors: Cristina Sanz-Fernandez, Rodrigo Hernandez, Christian D. Marciniak,
Ivan Pogorelov, Thomas Monz, Francesco Benfenati, Samuel Mugel, Roman Orus
- Abstract summary: We present an algorithm which efficiently estimates the intrinsic long-term value of a portfolio of assets on a quantum computer.
The choice of loading and readout algorithms makes it possible to price a five-asset portfolio on present day quantum computers.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present an algorithm which efficiently estimates the intrinsic long-term
value of a portfolio of assets on a quantum computer. The method relies on
quantum amplitude estimation to estimate the mean of a novel implementation of
the Gordon-Shapiro formula. The choice of loading and readout algorithms makes
it possible to price a five-asset portfolio on present day quantum computers, a
feat which has not been realised using quantum computing to date. We compare
results from two available trapped ion quantum computers. Our results are
consistent with classical benchmarks, but result in smaller statistical errors
for the same computational cost.
Related papers
- Theoretical and experimental analysis of adaptive quantum computers [0.0]
Fault-tolerant quantum computations require alternating quantum and classical computations.<n>We look at the advantages of adaptive quantum algorithms in realistic scenarios.<n>We find that despite their potential, adaptive quantum algorithms currently do not outperform full quantum algorithms.
arXiv Detail & Related papers (2025-09-08T09:00:09Z) - Understanding and Estimating the Execution Time of Quantum Programs [7.972186774307552]
We study the characteristics of quantum programs' runtime on simulators and real quantum computers.
We introduce an innovative method that employs a graph transformer-based model to estimate their execution time.
Our approach can be integrated into quantum computing platforms to provide an accurate estimation of quantum execution time.
arXiv Detail & Related papers (2024-11-23T19:02:10Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Adiabatic Quantum Support Vector Machines [0.8445084028034932]
We describe an adiabatic quantum approach for training support vector machines.
We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach.
arXiv Detail & Related papers (2024-01-23T04:50:13Z) - QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum
Circuits [82.50620782471485]
QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits.
It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness.
Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
arXiv Detail & Related papers (2024-01-10T22:33:00Z) - Quantum Financial Modeling on Noisy Intermediate-Scale Quantum Hardware:
Random Walks using Approximate Quantum Counting [0.054390204258189995]
We introduce quantum approximate counting circuits that use far fewer 2-qubit entangling gates than traditional quantum counting.
We compare the results to price change distributions from stock indices, and compare the behavior of quantum circuits with and without mid-measurement to trends in the housing market.
arXiv Detail & Related papers (2023-10-17T16:54:31Z) - Enhancing Quantum Annealing in Digital-Analog Quantum Computing [0.0]
Digital-analog quantum computing (DAQC) offers a promising approach to addressing the challenges of building a practical quantum computer.
We propose an algorithm designed to enhance the performance of quantum annealing.
This study provides an example of how processing quantum data using a quantum circuit can outperform classical data processing, which discards quantum information.
arXiv Detail & Related papers (2023-06-03T09:16:15Z) - Quantum Clustering with k-Means: a Hybrid Approach [117.4705494502186]
We design, implement, and evaluate three hybrid quantum k-Means algorithms.
We exploit quantum phenomena to speed up the computation of distances.
We show that our hybrid quantum k-Means algorithms can be more efficient than the classical version.
arXiv Detail & Related papers (2022-12-13T16:04:16Z) - Anticipative measurements in hybrid quantum-classical computation [68.8204255655161]
We present an approach where the quantum computation is supplemented by a classical result.
Taking advantage of its anticipation also leads to a new type of quantum measurements, which we call anticipative.
In an anticipative quantum measurement the combination of the results from classical and quantum computations happens only in the end.
arXiv Detail & Related papers (2022-09-12T15:47:44Z) - Reducing the cost of energy estimation in the variational quantum
eigensolver algorithm with robust amplitude estimation [50.591267188664666]
Quantum chemistry and materials is one of the most promising applications of quantum computing.
Much work is still to be done in matching industry-relevant problems in these areas with quantum algorithms that can solve them.
arXiv Detail & Related papers (2022-03-14T16:51:36Z) - Quantum computed moments correction to variational estimates [0.0]
We present an approach in which problem complexity is transferred to dynamic quantities computed on the quantum processor.
With system dynamics encoded in the moments the burden on the trial-state quantum circuit depth is eased.
arXiv Detail & Related papers (2020-09-28T08:39:05Z) - Boundaries of quantum supremacy via random circuit sampling [69.16452769334367]
Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling.
We examine the constraints of the observed quantum runtime advantage in a larger number of qubits and gates.
arXiv Detail & Related papers (2020-05-05T20:11:53Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.