【Company Profile】
HIGGS HK TECHNOLOGY LIMITED is a leading provider of AI solutions in the financial trading industry. In today’s rapidly changing capital markets, one of the greatest challenges lies in accurately predicting market movements. Traditional models often fail to capture the complexity of financial markets, leading to missed trading opportunities and elevated risks. We are committed to delivering high-performance, AI-driven infrastructure for the Chinese financial sector, enabling rigorous traders to efficiently manage diverse models and datasets within regulatory frameworks so they can focus on deeper analysis and make better-informed decisions. Ultimately, this fosters exceptional returns. Our core values are “Uphold Integrity with Ingenuity; Maintain Simplicity and Benefit Others.” We have international development teams located in Kuala Lumpur and Ho Chi Minh City.
【Position Overview】
We are seeking an engineer well-versed in ARIMA-GARCH time series modeling to be deeply involved in financial market data modeling and forecasting. This position requires a thorough understanding of ARIMA (including ARMA, ARIMA, Seasonal ARIMA) and GARCH (including ARCH, GARCH, and extended variants) theoretical frameworks, combined with expertise in statistical testing, parameter estimation, and model diagnostics, to deliver highly reliable models that support quantitative trading and risk management. You will employ advanced mathematical and programming skills to preprocess, model, evaluate, and deploy large-scale market data (e.g., stock indices, commodities), thereby providing essential backing for strategy research and risk control within our organization.
【Key Responsibilities】
ARIMA-GARCH Model Development & Optimization
Build ARIMA (or ARMA) models based on historical price or return data, using differencing, ACF, PACF, EACF, etc. for preliminary model selection and order determination.
Perform ARCH effect tests on residuals and employ GARCH (or its extensions) to refine volatility forecasting and support risk measurement.
Leverage AIC, BIC, and statistical tests (e.g., JB Test, Ljung-Box Test) for model selection, comparison, and enhancement.
Use Maximum Likelihood (ML), CSS, or CSS-ML methods to robustly estimate key parameters.
Model Diagnostics & Risk Assessment
Conduct normality checks on residuals (e.g., Q-Q plots, JB tests) to identify and remediate potential issues.
Monitor autocorrelation and heteroskedasticity within residuals, ensuring stability and reliability in forecast outcomes.
Utilize metrics like VaR and confidence intervals for volatility to quantify market risk and propose improvements.
Integrate models such as GARCH(1,1) to delve into volatile market fluctuations and extreme risk scenarios.
Data Preprocessing & Feature Engineering
Develop a thorough understanding of financial time series characteristics, including stationarity checks, differencing, log transformations, and outlier detection.
Clean, normalize, select features, and visualize large-scale market data (e.g., S&P 500, commodities, foreign exchange).
Skillfully use R, Python, MATLAB, or similar tools to improve efficiency in data handling and model training.
Technical Innovation & Algorithm Enhancement
Stay abreast of academic and industry advancements; combine neural networks (e.g., NAR, RNN) with traditional time series models to achieve superior predictive performance.
Explore Seasonal ARIMA, T-distributed GARCH, EGARCH, APARCH, and other derivatives to strengthen volatility modeling and risk management.
Continuously optimize computation processes and hyperparameter tuning, enhancing model robustness and generalizability.
Cross-Team Collaboration & Technical Support
Collaborate closely with quantitative analysts, data scientists, and trading strategy teams to integrate ARIMA-GARCH models into the company’s core trading and risk-control systems.
Draft comprehensive technical documentation and provide training and support to both internal teams and external partners.
Offer ongoing feedback to improve model performance, enabling real-time support for risk monitoring, strategy development, and other critical business areas.
【Qualifications】
Education & Background
Bachelor’s degree or higher in Statistics, Mathematics, Financial Engineering, Computer Science, or related fields.
Prior experience in time series modeling within finance or quantitative trading is highly desirable.
Technical & Modeling Expertise
Proficiency with ARMA, ARIMA, and Seasonal ARIMA linear time series models, including parameter estimation and diagnostic methods.
In-depth understanding of ARCH, GARCH, and other nonlinear volatility models, capable of addressing market volatility clustering and heavy-tailed distributions.
Familiarity with AIC, BIC, ADF tests, Ljung-Box tests, JB tests, and other standard model evaluation and statistical techniques.
Skilled in R, Python, or MATLAB for data processing, visualization, model development, and forecasting.
Programming & Tools
Competent in using popular data analysis libraries (e.g., Pandas, NumPy, Scikit-learn) and time series libraries (e.g., statsmodels, TSA packages).
Able to write clean, reproducible code; familiar with Git or similar version control platforms.
Knowledge of Docker, cloud deployment, and other DevOps practices is a plus.
General Skills
Excellent mathematical and statistical reasoning, able to rapidly identify and troubleshoot complexities in data and modeling.
Strong teamwork and communication capabilities for close collaboration with quant, risk, and other cross-functional teams.
Enthusiasm for financial markets and risk management, staying current with the latest academic and industry developments.
Experience in analyzing large-scale financial datasets, with keen awareness of emerging tools and technologies.
【Compensation & Benefits】
Competitive base salary and annual performance bonuses.
Flat organizational structure with a positive, high-energy atmosphere.
Flexible work options, up to 100% remote, plus opportunities for overseas workdays each year.
Multiple company-sponsored international trips annually, along with diverse recreational activities (sports, board games, etc.).
Broad career development prospects, continuously engaging with the cutting edge of finance and AI.
【Work Locations】
Kuala Lumpur, Malaysia & Ho Chi Minh City, Vietnam