- Devised quoting strategy for 3-year and 10-year Treasury Bond Futures- Implemented low-latency C++ arbitrage strategy targeting price inefficiencies between fungible products at open auction- Developed mean-reversion roll trading strategy for weekly options- Investigated open price momentum, identifying a 7 bps momentum signal in the first 10 minutes of trading when the overnight move exceeded 20 bps, enhancing intraday trading decisions- Conducted trade classification analysis on counterparties, successfully predicting expiry price movement based on market makers' aggregated positions.- Capitalized on market-moving news, generating AU$20,000 by buying KOSPI 200 puts during geopolitical events, profiting from a 1.5% market drop and a 7-point volatility spike- Automated trade reconciliation and cash management, ensuring 0 position breaks and preventing margin calls by using VBA to extract data from broker emails pre-market- Reduced 50% latency and improved 30% queue priority for multi-level quoting strategies- Validated trading strategy execution, reconciling live production trades with auto-backtests across 3 strategies to measure success and ensure consistency- Maintained and managed production risk for 10 high-frequency trading strategies, mitigating unexpected issues in a real-time trading environment- Designed and implemented a high-performance data processing pipeline normalizing and serializing millions of KRX and Eurex daily PCAP data into Parquet format, creating synthetic delta and roll order books across various products for the same underlying and expiry- Automated and visualized XML comparison between trading configuration vs. baselines

- Made 10,000 AUD over two-week trading in NK225 Index Options by manually adjusting the trading parameters based on signals such as other markets parameters, realized volatility, index level, and trading flows from the IDB and DCP market- Designed a trading strategy to buy and sell Ping An stock using order book signals and futures movement and generated 7,000 HKD per day over the backtest in 2020 and 2021- Built a regression model to predict implied vol based on historical returns and realized vol- Actively communicated and collaborated with 5 traders in the team on trading ideas

- Analyzed the precision and accuracy of TAIEX constituents’ dividend forecast from multiple data sources in the past two years and identified the source with the best quality- Investigated the statistical relationship between the futures rolls of TAIEX and TSMC- Developed an Excel sheet to display all options greeks across base prices and strike prices for user input structures during the 1-month global training program in Amsterdam

- Conducted holistic ESG analyses of the portfolio holdings against the MSCI ACWI Index via Sustainalytics risk scores, MSCI ESG ratings, and ISS ESG performance scores- Devised and maintained an automated system to watermark and send quarterly investor letters and monthly factsheets to 500+ prospects via Word Mail Merge and VBA programs- Assessed the portfolio’s monthly exposures and return attributions by asset classes, sectors, countries, market capitalizations, and liquidity from fund inception to Jun 2021 - Reduced 90% of the time for the operation managers to access and track trade records based on the date, broker, and counterparty with a customized email searching tool

- Conducted statistical analyses on intraday price movement in the major Asian markets and developed trading strategies accordingly- Executed 3 profitable market making strategies during the weekly mock trading activities