Our Strategies
Over 16 years of expertise, most recognized and reliable business partnership in A-share marketplace.Market Neutral
Alpha portfolios superposition day trading and basis trading to increase absolute returns
1
Systematic Arbitrage
Select high-quality assets to obtain spreads and achieve returns by participating in non-public offerings
2
Enhanced Indexing
Based on tracking the index itself, while obtaining the growth dividend of the index, multiple strategies are used to achieve excess returns
3
HFT Stock Optimization
Unique quantitative multi-strategy superposition to build a factor combination, through in-depth research, AI algorithm to build specific quantitative models
4
IPO Allocation
High allocation rate of 93%+, provide offline subscription services for individual stocks according to various customer needs
5
Our Competitive ‘Edge’
We harness diverse data and advanced algorithms to optimize our investment strategies, delivering refined alpha portfolios while effectively managing risk exposure.Multi-Source, Heterogeneous Data Processing.
Volume and price data, fundamental data, sentiment data, consensus expectations, and other industry-related data.
Alpha Portfolio.
Machine learning, deep learning across full-frequency bands and multi-period optimisation combinations.
Multi-Modal Full-Frequency Factor Engineering.
Trading logic factors, genetic algorithm optimisation for factor discovery, deep learning factor engineering, covering frequencies from weeks to minutes.
Strategy Optimisation.
Risk exposure control based on proprietary style factors, historical long-term strategy testing to prevent overfitting due to hyper-parameter tuning.
Our Risk Control Philosophy
Standardised investment behaviour, ensure risks are measurable, controllable, and bearable. The company values risk control more than pursuing high-risk high returns in the balance between risk and return. Therefore, dedicating a significant amount of energy to studying the balance between risk and return.
Strategy Development
Internal and external testing and cross-data verification of 10-year historical data samples to prevent overfitting
MSCI Barra model controls risk factor exposure
Post-Trade Evaluation
Post-market tick-level back testing
Performance attribution, strategy effectiveness, deal execution review
Continuous iteration of strategies for different market environments
Real-Time Risk Monitoring
Real-time monitoring of PNL, volatility, risk exposure etc.
Macro events warning and risk control, with comprehensive system disaster recovery
Portfolio Risk Control
Portfolio exposure ratio
Margin ratio
Fund distribution
Allocation of funds among strategies
Operational Risk Control
Continuous market data review and risk tolerance alerts
Account statistics, performance feedback
Manual monitoring throughout the transaction