How One Trade Became ₹1.75 Cr in Just 1 Hour | Rakesh Pujara Made For Trade Story

Finance-focused summary of the subtitles

Key market/investing takeaways (from Rakesh Pujara)

• Survival > returns: The core message is that the biggest objective is to stay alive (avoid blowing up capital), because markets are “very unkind” and mistakes are punished via money loss.
• Risk + sensible leverage: Early failure is attributed to leveraged trades using borrowed capital. Later success comes from defined risk, sensible leverage, and strict risk management.
• All-weather / multi-strategy approach: He advocates multi-strategy systems that can work across market regimes—long + short (“play both sides”)—to smooth results and handle drawdowns.
• Time-and-regime awareness: Returns arrive in “patches” (easy-money periods vs difficult years). Emphasis is on waiting for favorable conditions rather than revenge trading.
• Discipline and process over emotion: Use structured rules, avoid trading in isolation, and calibrate positions when emotionally—or relative to risk appetite—is off.

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Notable numbers, timelines, and performance claims

• 1991: He says he “bl[ew] up entire capital around ₹2 lakh,” described as entirely borrowed capital, and it took ~a decade to pay it back with interest.
• 21 January 2008: Described as:
  • A day of big losses for many, but very profitable for his desk/company.
  • He claims: ₹1.75 crore made within ~1 hour, from an intraday cash–futures arbitrage opportunity.
• Rule-based automation timeline:
  • 2012 / 2012–13: Long/short model development (and implementing rules more strictly).
  • 2018: Formed company; also mentions complete automation/rule-driven products since 2018–19.
  • 2020 onward: He states returns improved after earlier flat/doubt period.
  • Smallcase product: says it has been running for “three years” at the time of the talk, with continued growth.
• Backtesting history used:
  • Some strategies: intraday data from 2010.
  • End-of-day data possibly from 2001 (depends on instrument).
  • Index option data:
    • Nifty from 2019
    • Bank Nifty from 2016 (when maximum data is available)
• Investment product cost example (Smallcase):
  • Mentions a smallcase fee of “₹100 fixed” in illustrative terms regardless of deposit size.
• Capacity / portfolio rules (CWA Two Sigma indicator strategy):
  • Universe: “₹1500 NSC listed stocks liquid” (as stated).
  • Weekly trigger: weekly close outside Bollinger Bands; buy on Monday morning.
  • Allocation: 2% per stock (example: ₹5 lakh → ₹10,000 per stock).
  • Max holdings: roughly 50 stocks; if a new signal arrives beyond capacity, skip until space opens.
  • Exit triggers include: stop loss / drawdown thresholds and trailing stop using either:
    • 100-week moving average, or
    • ATR (14) with setting ~1.8 (as stated).

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Mentioned instruments, sectors, indices, and tickers (explicitly or by examples)

Indices / market terms

• Sensex (mentioned as being ~4500–4600 during the downturn described)
• Futures vs cash market (arbitrage framing)
• Nifty, Bank Nifty
• Options on indices (including “Nifty data” and “Bank Nifty first”)
• Futures, options, and arbitrage / cash-futures spread concepts

Stocks / examples (examples and references)

• Infosys, Wipro (internet/new economy examples)
• Satyam (cycle/crisis narrative)
• ACC, Karnataka Ball Bearing (referenced in Harshad Mehta era-style examples)
• Silver Line, DK Software (internet/new economy examples)
• PSU banks (relative strength “PSUs based on what we follow”; claimed “long for last 8–10 months” with “no position in IT”)
• References like: Sun Pharma, TCS/Infosys (“If it is SPL or Sun Pharma or Infosys…”)

Note: Subtitles have many transcription errors; ticker/sector captures may be imperfect, but the entities above are clearly referenced.

Crypto / commodities

• No crypto tickers mentioned.
• “Silver and gold” appears only as a metaphor for discounted futures vs cash.

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Methodologies / frameworks and step-by-step processes

1) “Survival-first” risk management principles (repeated throughout)

• Preserve capital; don’t blow up even if it slows growth.
• Define risk and use sensible leverage (not maximum leverage).
• Avoid revenge trading after losses.
• Reduce risk / take risk-off when drawdowns or psychological strain appears.
• Scale gradually only after consistent profitability.

2) Long/short + multi-strategy “all-weather” approach

• Build multiple non-correlated strategies.
• Aim for risk-adjusted returns with all-weather behavior.
• Use both:
  • Long + short exposure to capture different regimes.
  • “Bouquet” style: some strategies remain stable while others may switch off during regime change.

3) “Mona Lisa framework” (ongoing multi-strategy framework)

• Goal: “minimize risk, maximum returns,” and deliver all-weather returns.
• Mechanism: combine multiple non-correlated strategies (long/short/options/equities) into a live system.
• Process controls:
  • Backtest each component strategy.
  • Review/turn off strategies when regime change causes breakdown.
  • Maintain strategies that are “ahead and behind” to adapt.

4) Backtesting methodology (data + regime stability focus)

• Backtest using as much historical data as available, e.g.:
  • intraday since 2010
  • end-of-day since 2001
  • Nifty options since 2019
  • Bank Nifty options since 2016
• Weight recent data more due to:
  • regulatory changes / margin changes altering price and option dynamics.
• If data is affected by regime shifts:
  • repeated backtesting cycles are required.
  • frequent regulatory shifts create operational pain.

5) “CWA Two Sigma” (Bollinger Bands) investment indicator: operational rules

A practical rule-set (as described):

• Universe selection: start from a list of NSE-registered/liquid stocks (stated as “₹1500 NSC listed stocks liquid”).
• Entry condition: on a weekly chart, if weekly close is outside Bollinger Bands:
  • Take the signal on Friday’s weekly close
  • Execute buy on Monday morning
• Position sizing: allocate 2% per stock
  • Example: ₹5 lakh portfolio → ₹10,000 per stock
• Portfolio constraint: max ~50 stocks
  • If capacity is reached, skip new signals until space opens
• Exit conditions (exit when any triggers first):
  1. Initial stop loss / trailing logic (subtitle mentions “more than 20% until Friday,” then exit next Monday)
  2. Trailing exit option 1: trailing stop using 100-week moving average
  3. Trailing exit option 2: trailing stop using ATR (14) with setting ~1.8
• He also notes the indicator is productized for retail investors (referenced through his description of access via TradingView/Google form).

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Explicit recommendations / cautions

• Do not scale until you are confident you can generate consistent profits.
• Avoid trading in isolation: build community/mentorship to speed learning.
• Don’t apply leverage recklessly: define risk and keep leverage sensible.
• Keep expenses/operating model lean (“lean and mean”): if cash burn rises too much, you may not survive.
• Regulatory stability matters: frequent changes break backtests and raise operational costs.
• AI caution (implied): use AI for coding/productivity/research drafting, but don’t delegate primary investing ideas to AI.

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Disclosures / disclaimers mentioned

• At the end: “Investments in the Securities Market are subject to market risk. Read all the related documents carefully before investing.”
• No explicit “not financial advice” line is included in the subtitles, but the standard market-risk disclaimer is present.

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Presenters / sources mentioned

• Presenter/Guest: Rakesh Pujara (Compounding Wealth Advisors; associated with prop desk / algo and rule-based strategies)
• Host/Interviewers (mentioned in closing): Sandesh and the Dhan team (roles not fully specified in subtitles)
• Notable authors/books discussed (sources):
  • Charlie Munger / Poor Charlie’s Almanack
  • Ray Dalio (mentioned)
  • Bollinger Bands (method)
  • Other names appear unclear due to transcription (e.g., possible “Jim Symes” / “Jim Cramer” style errors), and some Buffett/Graham/Lynch references are not clearly confirmed.
  • A Buffett/Munger-related title appears garbled: “About One Buffett and Charlie Mars… / All I Want to Know If I’m Going to Die” (likely referencing a Charlie Munger/Buffett compilation).