17.6868° N · 83.2185° E — VIZAG, INDIA
NEELAKANTA ADIMULAM
Finance · Trading · Analytics
I build financial models, trade real capital, and write about Indian markets. DCF frameworks, M&A analysis, systematic trading strategies — built from scratch, applied in the real world. Currently at SP Jain Global, open to equity research and IB internships for 2026–27.
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[01]
About
Open to Work
·
IB & Equity Research · 2026
NA
Neelakanta Adimulam
Finance · Research · Analytics
6+
Projects
15
Editions
3
Deals Built
Financial Modeling92%
M&A Analysis87%
Equity Research84%
Quant / Python75%
Finance Student · Trader · Writer
I didn't wait for
permission to
start building.
I'm Neelakanta Adimulam, from Vizag — currently studying Finance at SP Jain School of Global Management. The DCF models came before any class assigned them. I pulled 10-K filings, built valuation frameworks from scratch, broke them repeatedly, and rebuilt them. Curiosity, not curriculum.
Then came trading — real money, real losses. There's a gap between understanding a concept and being right when it costs you. That gap is enormous. Most of what I know about risk management came from being wrong in expensive ways.
The newsletter closed the loop: analysis I could defend clearly enough to write about. Fifteen editions in. Currently targeting equity research and IB internships for Summer / Fall 2026.
DCF & Valuation
M&A Analysis
Live Trading — NSE
Backtesting · Python
Prop Firm Evaluations
15 Research Editions
SP Jain Global
Equity Research
17.6868° N · 83.2185° E · VIZAG, INDIA
[02]
Selected Work
01Quantitative Analysis
Buy / Sell Stock Tracker
JavaScriptNSE APIChart.jsReal-time
Real-time portfolio tracker for Indian markets. Generates buy/sell signals using momentum and moving average crossovers, computes P&L, and runs performance analytics across 10 NSE-listed equities. Built to stop guessing and start measuring.
10 stocks · NSE data · Live signalsView Project →
02Valuation Modeling
Three-Statement DCF Model
ExcelWACC/CAPMSensitivity3-Statement
Integrated DCF valuation with full income statement, balance sheet, and cash flow linkages. Interactive WACC and TGR sliders with an 11×9 sensitivity matrix. Applied to Reliance and TCS — the model interrogates assumptions, not just outputs numbers.
Reliance · TCS · 11×9 matrixView Project →
03Deal Analysis
M&A Deal Analysis Suite
Due DiligenceSynergy ModelAcc/Dil
In-depth analysis of three landmark Indian M&A transactions — Zomato×Blinkit, the HDFC Bank merger, and Tata×Air India. Covers synergy decomposition, strategic rationale, accretion/dilution modeling, and deal thesis stress-testing across combined value exceeding ₹2 trillion.
3 deals · ₹2T+ combined valueView Project →
04Algorithmic Systems
Backtesting & Strategy Engine
PythonPandasWalk-ForwardNSE Data
Systematic backtesting framework for evaluating momentum and mean-reversion strategies on NSE data. Includes parameter optimization across lookback windows, position sizing rules, and drawdown controls. Designed to separate edge from noise.
NSE · Python · Strategy validationView System →
05Market Intelligence
The Market Lens
ResearchWritingMacro15 Editions
Weekly financial newsletter covering macro trends, sector rotation, and equity analysis. 15 full-length editions with original research perspectives on Indian and global market dynamics. The challenge: making someone else see exactly what you see.
15 editions · 2000+ words eachRead Editions →
06Research Framework
Equity Research Workflow
ScreeningValuationInvestment Memo
A structured end-to-end equity research framework — from initial sector screening and business quality assessment through valuation modeling and investment memo writing. Built on Coca-Cola analysis and refined across multiple Indian equities.
Multi-stock · Full workflowSee Framework →
07Quantitative Analysis
Quantitative Lab
Monte CarloKellyVaRDCFMarkov
four mathematical tools built to stress-test strategy, portfolio risk, and valuation. not outputs — the actual distributions. 10,000 simulations running live in the browser.
4 modules · Client-side computeOpen Lab →
[04]
The Market Lens
Producing an insight is one thing. Getting someone else to see exactly what you're seeing is a completely different challenge — and honestly, a more useful skill. These are pieces I've written on things I was thinking about.
May 2025 · Edition 01
Market Structure
Retail vs Institutional: The One Edge Worth Having
Retail traders are at a structural disadvantage in speed, data, and access. That's just true. But there's one thing institutions genuinely can't do: sit still. A fund manager with ₹5,000 crore has a mandate, a benchmark, and quarterly reports to justify. They cannot sit in cash for six months waiting for the right setup. A retail trader can. That patience — the ability to simply not trade until conditions are right — is a real, exploitable edge. Most people never use it because the urge to do something feels like the same thing as being productive.
Read Edition →5 min read
November 2025 · Edition 07
Central Banks
Why Central Banks Are in a Harder Spot Than They Admit
Rate decisions used to feel like a dial — turn it one way to cool inflation, the other to stimulate growth. That story is getting complicated. The Fed and RBI are both dealing with the same problem: inflation is still sticky where it matters to real people, but growth is clearly slowing. Markets keep expecting cuts that don't come — and then getting surprised when they finally do. What I've been watching: the gap between what central banks say and what the bond market prices in. That spread tells you how much trust is actually in the room.
Read Edition →6 min read
[05]
Capabilities
Financial Modeling
Integrated three-statement models with full linkages, scenario analysis, and sensitivity tables. Built for interrogating assumptions, not just computing outputs.
DCFLBOCompsM&A
Valuation
Multiples analysis, intrinsic value estimation, and sensitivity modeling across macro scenarios. Applied to Indian large-cap equities with real market data.
EV/EBITDAP/EWACCNAV
Trading Systems
Systematic strategy development with backtesting validation. Technical analysis, risk framework design, and prop firm evaluation protocol adherence.
BacktestingPrice ActionRisk Mgmt
Data & Quantitative Analysis
Quantitative methods, financial data processing, signal generation, and performance analytics. Python for automation, Excel for structured analysis.
PythonExcelStatistics
Market Research
Equity research, sector rotation analysis, and macro-to-micro signal synthesis across Indian markets. Communicating what I find in language that actually lands.
EquityMacroSectorsNewsletters
Deal Structuring & M&A
Transaction analysis, synergy assessment frameworks, and due diligence across landmark Indian M&A activity. Accretion/dilution modeling and strategic rationale mapping.
SynergiesDue DiligenceAcc/Dil
[06]
Analytical Frameworks
These are the actual frameworks I use — not theory, not decoration. Each one is something I've built, applied, and refined. The structure below reflects how I actually think through problems.
01
DCF Valuation Framework
How I estimate what a business is actually worth — not just what the market says it is.
Discount Rate
WACC via CAPM
Terminal Growth
3–5% tested
Sensitivity
11×9 matrix
01
Revenue Projection
Segment-level growth rates based on historical CAGR, analyst consensus, and macro overlay. Not one number — a range with a base case and bear/bull scenarios.
02
Three-Statement Build
Full income statement → balance sheet → cash flow linkages. Every line is connected. Changes in working capital flow through properly. No standalone P&L.
03
WACC Construction
Cost of equity via CAPM (risk-free + beta × ERP). Cost of debt from interest expense / total debt. Weight by market-value capital structure.
04
Sensitivity Matrix Output
The valuation isn't a single number. It's a range across WACC (±200bps) and terminal growth rate combinations. The matrix shows which assumptions the valuation is most sensitive to.
02
Market Structure Analysis
How I read a chart before I read a balance sheet. Structure first, then direction.
Uptrend: HH + HL
Downtrend: LH + LL
Range: No clear sequence
01
Trend Identification
Weekly chart first to determine the dominant trend. I look at the sequence of swing highs and lows — not moving average crossovers. Price structure is the source; indicators are a check.
02
Key Levels
Support = previous swing low where buyers stepped in. Resistance = previous swing high where sellers appeared. Level is valid if it's been tested at least twice.
03
Liquidity Zones
Areas where a large number of stop-losses are likely sitting — just above prior highs in an uptrend, just below prior lows in a downtrend. Price tends to reach for these zones before reversing.
04
Context Filter
I only take trades that align with the higher-timeframe structure. A bearish setup on the daily chart in a weekly uptrend gets significantly less weight. Confluence across timeframes is a hard requirement.
03
Risk Management Model
The rules I follow before I know what I'll make. Risk is calculated, not felt.
Risk / Trade
≤ 1–2%
Daily Loss Limit
–4% hard stop
Min R:R
1 : 2
01
Position Sizing
Formula: Position size = (Capital × Risk%) ÷ (Entry price − Stop price). Calculated before every entry. Never estimated or adjusted by feel after the trade is open.
02
Stop Placement
ATR-based stops to account for normal market noise. Stop is placed beyond a structural level — not at an arbitrary distance. If the stop placement makes the position too large, I skip the trade.
03
Daily Drawdown Protocol
If I hit –4% on the day, I stop. No exceptions. Trying to recover the same day is how small losses become large ones. The market is open tomorrow.
04
Drawdown Recovery Rule
After a losing streak (3+ consecutive losses), I reduce position size by 50% until I have two consecutive winners. Size only returns to normal after confidence and conditions both improve.
04
Trade Decision Framework
The exact conditions I need before I enter. Fewer trades, better trades.
Trend aligned
Setup confirmed
R:R ≥ 1:2
Risk sized
01
Entry Conditions (All must be met)
Higher-timeframe trend is clear. Price is at a defined structure level. There is a clear invalidation level for the stop. Reward-to-risk is at least 1:2 before entry — not after.
02
Confirmation Signals
I wait for a trigger candle — a rejection wick, an engulfing candle, or a break-and-close through a key level. I don't enter in anticipation. I enter on evidence.
03
Exit Strategy
Target 1: 1:1 R:R — take partial profits, move stop to breakeven. Target 2: next structural level. Trail remaining position using ATR. Never hold through a major news event without a plan.
04
The No-Trade Rule
If I can't clearly explain the trade in one sentence — the setup, the stop, the target — I don't take it. Confusion at the entry stage is a sign the setup isn't clean. Clean setups are rare. That's fine.
[07]
Journey
2023 · Foundation
Graduated High School — IGCSE
Finished secondary school in Vizag having studied the International General Certificate of Secondary Education. My first real exposure to economics — the subject that made me want to understand how capital moves through the world.
2024 · First Signal
First Equity Analysis — Coca-Cola
Pulled Coca-Cola's 10-K and spent three weeks building my first real valuation model from scratch. Revenue projections, margin analysis, a rudimentary DCF. The output was imperfect, but the process changed how I read companies. That report is still on my desk.
2024 · Build
Stock Tracker + Integrated DCF Suite + First Live Trades
Built the Buy/Sell Stock Tracker and expanded the DCF into a full three-statement model with interactive sensitivity analysis. Simultaneously entered the market with real capital for the first time — learned more in those first few trades than in months of reading.
2025 · Threshold
Graduated International Baccalaureate
Completed the IB Diploma Programme. The Extended Essay and Theory of Knowledge pushed me toward structured argumentation. Mathematics, economics, and systems thinking under pressure — it translated directly into how I approach analysis.
2025 · Systems
Prop Firm Evaluations + M&A Analysis
Started working toward funded prop firm accounts (FundedNext). Simultaneously completed M&A analysis across three landmark Indian deals. The discipline required for prop trading and the rigor required for deal analysis turned out to reinforce each other.
Present · Active
SP Jain School of Global Management — Finance
Pursuing a Finance degree at SP Jain Global, where academic rigour is finally catching up with the models I've been building independently. Trading continues. Research continues. The newsletter continues. This portfolio is part of that work — and the next chapter is an internship in equity research or investment banking.
"The hard thing isn't setting up the interview. The hard thing isn't designing the framework. The hard thing is waking up in the morning realizing that the thing you were building no longer makes sense — and deciding to keep going anyway."
— Ben Horowitz, The Hard Thing About Hard Things
[08]
What I'm Reading
Currently Reading
The Hard Thing About Hard Things
The reason this site sounds the way it does. No book has shaped how I think about honesty in work more than this one.
Completed
Trading in the Zone
Changed my understanding of why I was losing money. It wasn't strategy — it was the wrong mental framework.
Completed
The Intelligent Investor
The margin of safety concept is the most useful idea in finance. Everything else is decoration.
Currently Reading
Thinking, Fast and Slow
Understanding System 1 vs System 2 explains most of my early trading mistakes. The biases chapter is worth the whole book.
[09]
Contact
Open to internships — equity research & investment banking, 2026–27
Let's
talk.
If you're hiring for equity research, IB, or trading roles — I'd like to hear about it. If you want to discuss markets, analysis, or a project — that works too. Either way I'll respond.
iamneelakanta.edu@gmail.com ↓ Download Resume Updated May 2026
Find me elsewhere