Tanishk Yadav
Resume

Projects / Regime-Aware Factor Strategy

Fundamental equity backtest

Regime-Aware Fundamental Factor Strategy

Tanishk Yadav, New York University

Code on GitHub

A walk-forward, regime-switching fundamental equity strategy on point-in-time data, 2008 to 2026, and an honest account of where its return came from.

Key facts

-39.7% vs -51.5%
maximum drawdown vs SPY, 2008 to 2026, net of 2/15 fees with a high-water mark
8.37%
Fama-French five-factor alpha in 2008 to 2017 (t = 2.73), net of fees
2.42%
the same alpha over the full period, not significant (t = 0.91)
0.85
market beta; the edge over SPY is beta and a small-cap tilt, not residual alpha

How it works

  • Four-state hidden Markov regime sizing over a composite of four fundamentals: ROIC, free-cash-flow margin, leverage aversion and revenue growth.
  • Point-in-time fundamentals from ChronoFund; delistings are penalized with a forced liquidation after 20 consecutive missing-price days, so dead firms cannot flatter the result.
  • Fama-French five-factor attribution on daily excess returns, split by sub-period to show the alpha decaying.

Built with

Python, hmmlearn, statsmodels, pandas, SEC EDGAR via ChronoFund

What it does not show

  • Sharpe is 0.61 vs 0.57 for SPY: the strategy survives crises through regime sizing, not stock selection.
  • The first-half alpha does not persist; it is reported as decay, not as an edge.

Tanishk Yadav

MS Financial Engineering at New York University, graduating May 2027, and looking for full-time quantitative research roles. My master's thesis measures, in real time, when US debt dynamics turn self-reinforcing.

See all my workThe thesisResume

Related

Related work

Point-in-time data engine

ChronoFund

SEC EDGAR, XBRL and Bloomberg fundamentals dated to the second the SEC accepted each filing. Four independent layers enforce the cutoff, and any violation fails at parse time rather than months later inside an inflated backtest. Survivorship-free, 65 tests.

See the project
SSRN preprintSeptember 2026

Calm Months, Crash Months

Built with only past data, capped leverage and trading costs, volatility management lifts momentum's Sharpe ratio from 0.43 to 0.94 and helps none of the other five factors. A closed-form formula for momentum's market beta explains why.

Read the paperPDF