MBA Dissertation: What Markets Actually Reward in Funded Indian Startups

Saloni started her MBA dissertation with a doubt rather than a hypothesis. Everyone around her was measuring startup success by valuation, unicorn status, and funding rounds raised. But she kept watching heavily funded companies stumble after listing while modestly funded ones compounded quietly. The question she wanted to answer was whether valuation was even the right measure of success, and what the market actually rewarded once companies faced public scrutiny.

Sharpening that into something researchable took deliberate work. She narrowed the question to a measurable one: how do listed PE and VC-backed Indian companies perform in terms of risk and volatility, and what characteristics separate the ones the market treats well from the ones it punishes?

Data collection was the first major constraint. Private company financials are not publicly available, so she used her college's access to the Venture Intelligence platform to pull data on private firms, and S&P data for listed companies. She gathered financials from pre-funding through post-funding stages across ten companies, including Akko, MyGram, Cred, and Cardico.

Building the Analytical Framework

She computed profitability, growth, and solvency ratios, then layered in volatility analysis using GARCH and eGARCH models to capture how corporate events affected stock behavior. She also ran sentiment analysis, tagging news events as positive or negative based on funding rounds, sales trends, and macroeconomic signals, to understand what drove volatility spikes.

Her professor reviewed her work weekly, which forced her to defend her methodology at each stage. When feedback came back that her sentiment categorization needed more rigor, she refined the framework to more precisely define what constituted a positive or negative investor event.

What the Data Actually Showed

One finding surprised her. A company she expected to be performing well based on its funding narrative turned out to have persistently negative revenue growth when she went deeper into the financials. The funding story said one thing; the cash flow said another. She included that gap in her findings rather than smoothing it over.

The core conclusion held up across the sample: capital efficiency and governance quality mattered more to market outcomes than how much a company had raised. The market punished governance failures far more severely than it rewarded positive news. Yes Bank demonstrated how governance deterioration leads to extreme volatility and prolonged investor uncertainty. IDFC Bank, by contrast, showed how institutional transformation with improving asset quality can stabilize investor sentiment over time.

Lenskart emerged as a positive case: initially cash-negative, it deployed capital into expansion and is now approaching IPO readiness. Companies like MyGlance, with multiple in-house brands but persistent negative EBITDA, illustrated the opposite pattern.