Dhruv Mandavkar.

Research and advisory layer of Third Rock Wealth (TRW), the firm's mutual fund distribution arm. Deep-dive equity fund research across large-, mid-, and flexi-cap, client-facing recommendation reports, and systematic fund-evaluation frameworks.

• Built a systematic screening model across the full SEBI active fund universe on a 3-layer method (pass/fail gates, category-adapted scoring, qualitative overlay): 177 equity funds across 8 categories, 96 hybrid (benchmark-distortion-aware), 134 sector and thematic, 64 solution-oriented and FoFs.
• Produced client-facing fund recommendation reports combining quantitative metrics (Sharpe, beta, rolling alpha) with qualitative manager and mandate assessment
• Conducting coverage of Angel One Ltd (NSE: ANGELONE), 6-tab institutional valuation model including 3-statement model, DCF, EV/EBITDA comparables, scenario and sensitivity analysis
• Analysing AUM trends, inflow/outflow dynamics, and category rotation across India's ₹73+ Lakh Cr mutual fund industry (March 2026)

A competitive research post embedded in the faculty's active research agenda. Worked alongside academic researchers on empirical financial research using econometric methods.

• Built a 15-year daily price dataset (5,372 observations) across BTC, ETH, S&P 500, FTSE 100, Nikkei 225, and crypto indices on Bloomberg Terminal, the foundation for my dissertation's event study and EGARCH analysis
• Applied EGARCH(1,1) volatility modelling, Granger causality testing, and event-study methodology under faculty supervision, directly in the dissertation that earned First Class
• Produced two original findings: the regulatory asymmetry paradox (regulation stabilises traditional securities while amplifying crypto volatility) and the sentiment contagion mechanism (Reddit negativity Granger-causes crypto vol at a single lag)
• Supervised by Dr. Malgorzata Sulimierska; direct faculty access shaped my approach to empirical research design

Self-funded discretionary portfolio on a macro-first selection framework. 65% cumulative money-weighted return since inception (2019), ~45% annual profit on deployed capital. Concentrated long/short across Indian equities, sector and timing decisions driven by physical-economy signals before stock analysis.

• Benchmark context: the Nifty 50 returned ~95% over the same period. This is concentrated L/S, higher volatility and drawdown than a passive index, not a like-for-like comparison.
• Selection framework: physical-economy signals (BDI, copper, credit spreads) drive sector and timing calls before individual stock analysis
• Risk management: position sizing tied to conviction × signal confirmation; trimmed into strength when macro regime indicators flipped
• Currently building equity baskets across sectors surfaced by macro signal tracking and fundamental screening