arXiv · arXiv q-fin · 2026
Transitioning a strategy from backtest to live trading is a common failure point for quantitative systems due to parameter overfitting, selection bias, and sensitivity to regime changes. This paper presents the AlgoXpert Alpha Research Framework, a standardized protocol that evaluates strategies across three stages: In Sample (IS), which focuses on stable parameter regions instead of single optima; Walk Forward Analy…
The Anh Pham, Bao Chan Nguyen, Nguyet Nguyen Thi
arXiv · arXiv q-fin · 2023
The prevention of rapidly and steeply falling market prices is vital to avoid financial crisis. To this end, some stock exchanges implement a price limit or a circuit breaker, and there has been intensive investigation into which regulation best prevents rapid and large variations in price. In this study, we examine this question using an artificial market model that is an agent-based model for a financial market. Ou…
Takanobu Mizuta, Isao Yagi
arXiv · arXiv q-fin · 2026
Portfolio replication, or the construction of a tradable basket of assets to match the risk-return profile of a target benchmark, is fundamentally an ill-posed inverse problem. When restricted to a subset of available assets, classical variance-minimizing models often yield unstable, over-leveraged portfolios highly vulnerable to market shocks. We propose a unified, two-stage methodology rooted in information theory …
Argimiro Arratia, Henryk Gzyl
arXiv · arXiv q-fin · 2021
The stock market is volatile and complicated, especially in 2020. Because of a series of global and regional "black swans," such as the COVID-19 pandemic, the U.S. stock market triggered the circuit breaker three times within one week of March 9 to 16, which is unprecedented throughout history. Affected by the whole circumstance, the stock prices of individual corporations also plummeted by rates that were never pred…
Jinlong Ruan, Wei Wu, Jiebo Luo
arXiv · arXiv · 2025
We study a \emph{QDisCoCirc}-inspired, chunked diagram-to-circuit quantum natural language processing (QNLP) model for three-class sentiment classification of financial texts. In our classical simulations, we keep the Hilbert-space dimension manageable by decomposing each sentence into short contiguous chunks. Each chunk is mapped to a shallow quantum circuit, and the resulting Bloch vectors are used as a sequence of…
Takayuki Sakuma
arXiv · arXiv · 2024
Quantum machine learning has demonstrated significant potential in solving practical problems, particularly in statistics-focused areas such as data science and finance. However, challenges remain in preparing and learning statistical models on a quantum processor due to issues with trainability and interpretability. In this letter, we utilize the maximum entropy principle to design a statistics-informed parameterize…
Xi-Ning Zhuang, Zhao-Yun Chen, Cheng Xue, Xiao-Fan Xu, Chao Wang
arXiv · arXiv · 2015
In quantum computation, series of quantum gates have to be arranged in a predefined sequence that led to a quantum circuit in order to solve a particular problem. What if the sequence of quantum gates is known but both the problem to be solved and the outcome of the so defined quantum circuit remain in the shadow? This is the situation of the stock market. The price time series of a portfolio of stocks are organized …
Ovidiu Racorean