activity
20232026
collaborators

6 papers

q-fin.PM2026

Relief-Gated Relative Rotation for QQQ-DIA Allocation: Globally Screened Relative States, Fixed Position Mapping, Incremental Interaction Admission, and Walk-Forward Validation

Zheli Xiong

This paper studies Relief-Gated Relative Rotation (RGRR), a two-ETF rule that allocates between QQQ and DIA by mapping screened relative and macro states into a continuous QQQ weig…

q-fin.PM2026

Continuous Cash-Overlay Filters for a Static Growth--Defensive Risk Sleeve: Slow-Tail Compensation, V-Shape Crash Brakes, Walk-Forward Validation, and Max-Cash Combination

Zheli Xiong

This paper studies a modular cash-overlay rule for allocating between a fixed growth-defensive risky sleeve R and interest-bearing cash C. The risky sleeve is a static 50/50 combin…

q-fin.PM2026

Continuous Timing Signals for Growth-Defensive Style Allocation: Factor Attribution, Risk Matching, and Out-of-Sample Evidence

Zheli Xiong

This paper studies conditional allocation between a growth/technology ETF basket, denoted by , and a defensive income/value-oriented ETF basket, denoted by . The objective is…

cs.LG2025

Ensemble RL through Classifier Models: Enhancing Risk-Return Trade-offs in Trading Strategies

Zheli Xiong

This paper presents a comprehensive study on the use of ensemble Reinforcement Learning (RL) models in financial trading strategies, leveraging classifier models to enhance perform…

cs.AI2023

Large-Scale OD Matrix Estimation with A Deep Learning Method

Zheli Xiong, Defu Lian, Enhong Chen +2

The estimation of origin-destination (OD) matrices is a crucial aspect of Intelligent Transport Systems (ITS). It involves adjusting an initial OD matrix by regressing the current…

cs.LG2023

A DeepLearning Framework for Dynamic Estimation of Origin-Destination Sequence

Zheli Xiong, Defu Lian, Enhong Chen +2

OD matrix estimation is a critical problem in the transportation domain. The principle method uses the traffic sensor measured information such as traffic counts to estimate the tr…