Plan smarter. Invest better. Build freedom.

Think in today’s money. Enter contributions, portfolio and spending as rupees you feel now. The planner converts your nominal return assumptions to “real” purchasing power after inflation, fees and tax drag. You’re deciding lifestyle, not guessing inflation.

Compounding + drawdowns = your flywheel. Two elements keep the flywheel going: (1) grow a base that throws off reliable cash flows; (2) protect that base so losses don’t set you back years. A deep early hit with withdrawals can permanently reduce the capital that future gains compound. If you must take risk, avoid taking it when you’re most fragile.

Sequence‑of‑returns risk: same returns, different order

Start with ₹ 1.00 Cr, withdraw a flat ₹ 4.0 L at the end of each year (ignore inflation here to keep the idea clear). Two five‑year paths use the same set of annual returns (four years of +10%, one year −30%) but in different order.

Why order matters

• Withdrawals after a loss sell more units at low prices; the pot then has less capital to recover.
• Big losses need outsized rebounds (+50% after −33%, +100% after −50%).
• Costs and taxes are small but relentless headwinds; lower what you can control.

Practical ways to manage sequence risk (no formulas)

• Hold a near‑term buffer for essentials (roughly 2–4 years if retired). This trims forced selling in a crash.
• Split essentials vs flexible spending. Label must‑have items (housing, food, insurance, basic healthcare). In rough years, automatically trim the flexible layer by a step (e.g., −10%).
• Guardrails policy: start from a sensible spend; nudge up/down if your withdrawal rate drifts outside a band.
• Diversify & rebalance across assets/geographies/styles; rebalancing buys what fell and sells what ran.
• Use the delay lever: a later retirement date or slightly lower starting spend has outsized impact.

How to use the planner thoughtfully

• Model your spending (today’s money), add one‑offs and incomes. Set conservative volatility and a return floor.
• Check success probability at your planned date and the required nest egg.
• Watch percentiles: if 10th‑percentile wealth looks uncomfortably low in key years, strengthen the plan (bigger buffer, lower spend, later date, or more contributions).

Principles to remember

• Compounding loves time and hates big losses — guard the downside first.
• Flexible precision beats rigid targets — a living plan outperforms a “perfect” static number.
• Small, consistent actions with low fees and periodic checks beat heroic market calls.

Educational content only — not financial advice.

The mission isn’t to avoid red days; it’s to avoid ruin. Big losses slow your compounding engine and steal years you can’t get back. A −50% crash needs +100% to recover — meanwhile the bills still arrive. Hedging is about building a plan that can absorb shocks while keeping you invested.

What “hedging” really means

• Diversifiers that don’t move together (quality bonds, some gold, global exposure).
• Insurance for catastrophic risks (health/term/disability) — feels “wasted” when unused, priceless in crises.
• Buffers & design — cash/short bonds for 1–2 years of essentials; position sizes that respect uncertainty.

Case study 1 — Buffer vs no buffer

Setup: portfolio ₹1.50 Cr, annual spend ₹12.0 L (essentials ₹7.2 L), asset mix 60/40. Year‑1 shock −30% in equities. No buffer: you sell more units at low prices to fund the year; recovery starts from a smaller base. With buffer: you fund essentials from cash/short bonds, trim flexible spending by a step (10%), and let the portfolio rebound. Small differences early snowball over a decade.

Case study 2 — Rebalancing as a built‑in hedge

Rule: rebalance to 60/40 on schedule (no predictions). After a shock, some bonds go up — you sell a slice and buy equities low. Over many years this dampens drawdowns and nudges long‑run returns without stock‑picking.

Practical hedge toolkit (with examples)

• Runway: 6–24 months of essentials in cash/short bonds (pre‑retirees lean shorter; retirees longer).
• Rebalancing: annual/quarterly, or bands (e.g., ±20% around targets).
• Diversification: mix domestic & international; currency adds another diversifier.
• Position sizing: a single idea must not sink the plan; cap exposure to any one asset/sector/manager.
• Spending guardrail: cap withdrawal rate; raise/trim by steps when outside band.

Black Swan thinking (Taleb, paraphrased)

• Rare, extreme events drive outcomes; models that ignore fat tails are fragile.
• Barbell: keep most capital ultra‑robust (cash/treasuries), place small, limited‑downside, high‑upside bets.
• Avoid ruin: never risk what you need for what you don’t.

Beyond markets: personal hedges

• Don’t let fixed costs dominate cash‑flows; lower fragility.
• Insurance (health, term, disability) prevents single‑event wipe‑outs.
• Skills & AI: keep learning; more adaptable skills = more optionality.

What hedging is not

• Not “calling tops.” It’s designing so that a single outcome can’t knock you out.
• Not free — like insurance, you pay a small cost to avoid catastrophic costs.

Bottom line: build a portfolio that can take a punch — and a life that doesn’t require perfection to thrive. First survive — then optimize.

Educational content only — not financial advice.

Screens narrow the field; they don’t guarantee winners. Use them to find candidates, then read deeply and think independently.

Signals that travel well

• Quality: ROCE/ROE multi‑year, consistent OPM, cash conversion, prudent leverage.
• Value: EVEBITDA, PE relative to growth/quality, PB vs reinvestment economics.
• Resilience: interest cover, working‑capital discipline, drawdown history.

Example checks

• OPM 5Y trending ≥ 15%; ROCE 5Y ≥ 15%; Debt/Equity ≤ 0.5.
• Growth that pays: Sales/Profit growth 5Y ≥ 12%; EVEBITDA < peer median.
• Owner behavior: sensible dilution, conservative pledging, coherent capital allocation.

Pair this with the Screener presets to build the initial list.

Kiran is a chemical engineer from National Institute of Technology Tiruchirappalli (NIT Trichy). He builds simple, private, client‑side tools that help people make disciplined, calm, better decisions.

His philosophy is straightforward: learn small, do consistently, and do it passionately — every day. Small improvements, repeated, beat grand plans that never get executed.

Interests include clear mental models, increasing optionality and resilience, practical hedging against big surprises, the study of “black swans,” and continuous learning — especially in AI.

Contact: kiranmenon84@gmail.com