Jing Zhang
Wesleyan University’27 | Majoring in Economics and Mathematics | Developing skills & practical experience in Quant Finance
Middletown, Connecticut, United States of America
Artifacts
An earlier project of mine failed to find a working timing signal for US Treasury yields. I pre-registered 66 tests, locked the held-out window in code, and none passed. One signal looked strong at first (t = −4.62), but that came from overlapping returns. After correcting for serial correlation (Newey-West), it fell to −0.76. That failure taught me two things: lock tests before looking, and timing a single bond gives too few independent bets. So I redesigned the question. The question. Carry is one of the best-documented premiums in finance. Koijen, Moskowitz, Pedersen and Vrugt (2018) find it across asset classes, including government bonds. I tested whether Treasury carry across the yield curve is a real premium or just rate exposure under another name. The setup. I built monthly returns for the curve from the Fed's zero-coupon yields (Gürkaynak-Sack-Wright). I wrote down every test and pass/fail bar and tagged them in git before running anything. The 2019–2026 window stayed locked in code until a one-time reveal, and every data access was logged. Replication first. The paper's construction replicated on my data: Sharpe 0.28 before costs, against their 0.33. It also carried a duration beta of 0.45, meaning a large share of the return came from simply being long bonds. A design flaw, caught before the reveal. My first rate-neutral version ranked bonds on carry per dollar but held them in DV01-neutral (rate-neutral) sizes, so the ranking and the positions were in different units. I caught this in a pre-registered diagnostic, amended the design to rank on carry per unit of duration, recorded the change, and only then continued. The result. With rate exposure removed, the premium disappeared. The development-period Sharpe was 0.02 after costs (t = 0.20). On the locked 2019–2026 window it was −0.30 (93 months). Before costs (t = 0.29), random rankings did as well or better in 27.5% of 1,000 shuffles, so the signal can't be told apart from noise. What it means. In US Treasuries, the carry premium is mostly compensation for holding duration. Take that exposure away and the premium disappears.
Mint Finance · Quantitative Researcher · July 2026During my quant research internship at Mint Finance, I chose the Nasdaq-100 index enhancement track out of three fixed project options offered in week one. The mandate was explicit: build something that beats QQQ, prove the edge isn't just repackaged beta, and back every claim with 8-10 years of history. Beyond that starting brief, the actual mechanism was mine to design. I built a strategy that rotates a QQQ core into whichever Nasdaq-100 sector shows the strongest momentum, with two custom safety layers on top. A mega-cap override checks at every rebalance whether the top 5 stocks by market cap (deduplicated across dual-class shares like GOOG/GOOGL) already make up 45% or more of the cap-weighted universe and have beaten the equal-weighted index by 5% or more over the trailing 6 months — if both hold, the strategy stops ranking sectors and shifts to 40% QQQ plus 60% split across those five names directly. I also added two independent drawdown brakes: one watches QQQ's own trailing 63-day drawdown and cuts the book to 50% QQQ / 50% cash if it falls past -12% (releasing above -8% to avoid flapping), while a second watches the currently-held sector sleeve on the same logic and drops to 100% QQQ if that sleeve alone craters past -20%, since a single sector can collapse while the broader market is fine. I validated the whole system with a leak-free nested walk-forward test spanning 22 years, well beyond the 8-10 year minimum, plus separate parameter sensitivity and trading-cost analysis. After validation, the strategy earns about 6.3% annualized alpha over QQQ net of trading costs, with a higher Sharpe ratio (1.04 vs 0.73) and a smaller max drawdown (-37% vs -53%). It's now running on a dedicated live paper-trading account at Mint, separated from other interns' strategies so the risk brakes don't interfere with each other. I also prepared the research report, notebook, and one-page strategy card required for the program's Final Pitch, where external judges from hedge funds, investment-bank research desks, and wealth management firms evaluate the work and can extend referrals or direct hires.
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Leave a testimonialWork history
Jun 2026 - Jul 2026 · 2 months · Quantitative Researcher
Jul 2025 - Oct 2025 · 4 months · Quantitative Researcher Intern
Jan 2025 - Mar 2025 · 3 months · Private Equity Analyst Intern
Jan 2023 - Aug 2023 · 8 months · Rotational Summer Analyst
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