Meta DescriptionA complete analysis of Bank Nifty for short-term traders and long-term investors. Includes technical targets, stop-loss, sector outlook till 2030, trading psychology, and disclaimer.KeywordsBank Nifty today, Bank Nifty analysis, Bank Nifty target, Nifty Bank forecast, Bank Nifty options, Bank Nifty support resistance, RBI policy impact, Bank Nifty 2025 to 2030 outlookHashtags#BankNifty #NiftyBank #StockMarketIndia #TechnicalAnalysis #OptionsTrading #BankingSector #NSE #TradingPsychology #LongTermInvesting



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đŸĻ Bank Nifty: The Pulse of India’s Financial Market (2025–2030 Outlook)

Meta Description

A complete analysis of Bank Nifty for short-term traders and long-term investors. Includes technical targets, stop-loss, sector outlook till 2030, trading psychology, and disclaimer.

Keywords

Bank Nifty today, Bank Nifty analysis, Bank Nifty target, Nifty Bank forecast, Bank Nifty options, Bank Nifty support resistance, RBI policy impact, Bank Nifty 2025 to 2030 outlook

Hashtags

#BankNifty #NiftyBank #StockMarketIndia #TechnicalAnalysis #OptionsTrading #BankingSector #NSE #TradingPsychology #LongTermInvesting


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1. Introduction: What Is Bank Nifty?

Bank Nifty (Nifty Bank Index) tracks the performance of India’s most liquid and large-capitalization banking stocks listed on the NSE. It reflects the strength of India’s financial backbone — the banking sector.

Comprising 12 leading banks, the index covers private, public, and small-finance institutions. As of 2025, HDFC Bank, ICICI Bank, Axis Bank, and SBI dominate the weightage.


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2. Why Bank Nifty Matters

It represents nearly one-third of Nifty 50’s movement.

A sharp move in Bank Nifty often leads the entire market trend.

Banking performance is linked directly to interest rates, credit growth, and RBI policy.


For traders, Bank Nifty’s volatility creates opportunities in weekly options. For investors, the index is a barometer of India’s economic growth.


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3. Short-Term Technical Analysis (November 2025)

(For educational purpose only)

Trend Type Level Comment

Immediate Support 50,800–51,200 Buying interest zone
Immediate Resistance 53,600–54,200 Breakout confirmation above 54,200
Short-Term Target 55,000–55,500 Possible if sustained above 53,800
Stop-Loss for Longs 50,500 Protects against breakdown
Downside Target (if breaks 50,500) 49,200–48,800 Correction zone


Interpretation:
If Bank Nifty remains above 51,200, bulls may attempt a move toward 55,000.
However, if it slips below 50,500, short-term correction could extend to 49,000 zones.


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4. Long-Term Outlook (2025–2030)

Over the next 5 years, India’s banking ecosystem is projected to expand due to:

Digital banking transformation (UPI 2.0, AI credit scoring)

Rural credit expansion

Corporate loan revival

Controlled NPAs via risk-based lending


Projected Range by 2030 (Educational View):

Conservative Scenario → Bank Nifty ~ 80,000 – 85,000

Optimistic Scenario → Bank Nifty ~ 1,00,000 +

Risk Zone → Below 45,000 (should be avoided for fresh long-term buying)



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5. RBI and Policy Impact

The Reserve Bank of India’s monetary decisions are the heartbeats of Bank Nifty.

Rate Hike Cycle → Bearish (loan cost rises)

Rate Cut Cycle → Bullish (credit demand improves)

Neutral Policy → Range-bound markets


Upcoming digital regulations and PSB privatization plans will add long-term momentum.


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6. Option Traders’ Perspective

Bank Nifty options offer immense liquidity.

Weekly Expiry: Every Thursday

Lot Size: 15 units (as of 2025)

Key Strategies: Straddle, Strangle, Bull Call Spread, Iron Condor


> Educational example:
If Bank Nifty stays above 52,500, a Bull Call Spread (52,500 CE–54,000 CE) can capture up-move with limited risk.




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7. Fundamental Drivers of the Banking Sector

1. Credit Growth > Double-digit retail lending continues.


2. NPA Reduction > Gross NPAs below 3%.


3. Private Banks Leadership > Tech innovation + profitability.


4. PSB Transformation > Digitization and capital infusion.


5. Interest Rate Cycle > Stable RBI stance supports valuation growth.




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8. Trading Psychology

Many traders lose not because of wrong analysis but due to emotional reactions.

Greed at highs and fear at lows ruin consistency.

Discipline = setting stop-loss + following plan strictly.

Avoid over-leveraging in weekly options.

Keep risk per trade < 2 % of capital.


Remember: Your job is to manage risk; profit follows management.


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9. Macro & Global Cues

Global banking moves (Fed policy, US bond yields) strongly affect Bank Nifty.

Strong USD & higher yields → FIIs outflow → pressure.

Stable global rates & rising India GDP → bullish sentiment.



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10. Investment Strategy 2025–2030

SIP Approach: Invest monthly in Bank ETF (Nippon Bank Bees etc.)

Core Allocation: 30–35 % of equity portfolio in bank sector funds.

Rebalance: Every 6 months based on RBI policy direction.



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11. Risk Management

Risk Solution

High volatility Trade small lots & use hedges
News shock Avoid overnight unhedged positions
Emotional bias Follow checklist before trade
Leverage trap Keep margin buffer of 20 % +



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12. Psychological Levels to Watch

50,000 → Major support
55,000 → Emotional barrier
60,000 → Long-term target zone
75,000–80,000 → Potential 2030 targets if macro remains bullish


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13. Sector Rotation

When Bank Nifty consolidates, funds often rotate into IT and FMCG. Once banking recovers, those sectors book profit and money flows back into banks — that’s how bull cycles sustain.


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14. Final Words

Bank Nifty is not just an index — it’s the heartbeat of India’s economy. Its journey from 10,000 to 50,000 proves the strength of Indian finance. With discipline, diversification, and knowledge, you can use this index for growth without fear.


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15. Disclaimer

> I am a trader, not an expert. This content is for educational and informational purposes only. It should not be taken as financial advice. Markets involve risk; consult your financial advisor before investing or trading.




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🇧🇩 āĻŦাংāϞা āϏংāϏ্āĻ•āϰāĻŖ — āĻŦ্āϝাংāĻ• āύিāĻĢāϟি: āĻ­াāϰāϤেāϰ āφāϰ্āĻĨিāĻ• āĻšৃāĻĻāϏ্āĻĒāύ্āĻĻāύ (⧍ā§Ļ⧍ā§Ģ āĻĨেāĻ•ে ⧍ā§Ļā§Šā§Ļ)

āĻŽেāϟা āĻŦিāĻŦāϰāĻŖ

āϏ্āĻŦāϞ্āĻĒāĻŽেāϝ়াāĻĻি āĻ“ āĻĻীāϰ্āϘāĻŽেāϝ়াāĻĻি āĻĻৃāώ্āϟিāĻ•োāĻŖ āĻĨেāĻ•ে āĻŦ্āϝাংāĻ• āύিāĻĢāϟিāϰ āĻŦিāĻļ্āϞেāώāĻŖ। āĻĒ্āϰāϝুāĻ•্āϤিāĻ—āϤ āϟাāϰ্āĻ—েāϟ, āϏ্āϟāĻĒ-āϞāϏ, āφāϰāĻŦিāφāχ āύীāϤিāϰ āĻĒ্āϰāĻ­াāĻŦ āĻ“ āĻŦিāύিāϝ়োāĻ— āĻŽāύāϏ্āϤāϤ্āϤ্āĻŦ।

āĻ•ীāĻ“āϝ়াāϰ্āĻĄ

āĻŦ্āϝাংāĻ• āύিāĻĢāϟি āφāϜ, āĻŦ্āϝাংāĻ• āύিāĻĢāϟি āĻŦিāĻļ্āϞেāώāĻŖ, āĻŦ্āϝাংāĻ• āύিāĻĢāϟি āϟাāϰ্āĻ—েāϟ, āύিāĻĢāϟি āĻŦ্āϝাংāĻ• ⧍ā§Ļ⧍ā§Ģ-⧍ā§Ļā§Šā§Ļ, āφāϰāĻŦিāφāχ āύীāϤি, āĻ…āĻĒāĻļāύ āϟ্āϰেāĻĄিং, āĻŦ্āϝাংāĻ• āĻ–াāϤ āĻŦিāύিāϝ়োāĻ—

āĻš্āϝাāĻļāϟ্āϝাāĻ—

#BankNifty #āύিāĻĢāϟি āĻŦ্āϝাংāĻ• #āϏ্āϟāĻ• āĻŽাāϰ্āĻ•েāϟ #āĻĒ্āϰāϝুāĻ•্āϤিāĻ—āϤ āĻŦিāĻļ্āϞেāώāĻŖ #āĻ…āĻĒāĻļāύ āϟ্āϰেāĻĄিং #āĻ­াāϰāϤী⧟ āĻŦ্āϝাংāĻ• āĻ–াāϤ


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ā§§. āĻ­ূāĻŽিāĻ•া

āĻŦ্āϝাংāĻ• āύিāĻĢāϟি āĻšāϞ āĻ­াāϰāϤেāϰ āϏāĻŦāϚেāϝ়ে āĻĒ্āϰāĻ­াāĻŦāĻļাāϞী āϏূāϚāĻ•āĻ—ুāϞিāϰ āĻāĻ•āϟি, āϝা āĻĻেāĻļেāϰ āĻŦৃāĻšā§Ž āĻ“ āϤāϰāϞ āĻŦ্āϝাংāĻ• āĻļেāϝ়াāϰāĻ—ুāϞিāϰ āĻĒাāϰāĻĢāϰāĻŽ্āϝাāύ্āϏ āĻĒāϰিāĻŽাāĻĒ āĻ•āϰে।


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⧍. āĻ•েāύ āĻ—ুāϰুāϤ্āĻŦāĻĒূāϰ্āĻŖ

āύিāĻĢāϟি ā§Ģā§Ļ-āĻāϰ āĻĒ্āϰাāϝ় āĻāĻ•-āϤৃāϤীāϝ়াংāĻļ āĻ—āϤি āĻŦ্āϝাংāĻ• āύিāĻĢāϟিāϰ āĻŽাāϧ্āϝāĻŽে āĻšāϝ়। āφāϰāĻŦিāφāχ āύীāϤি, āĻ‹āĻŖ āĻŦৃāĻĻ্āϧি āĻ“ āĻ…āϰ্āĻĨāύীāϤিāϰ āĻĻিāĻļা āĻāχ āϏূāϚāĻ•āĻ•ে āĻĒ্āϰāĻ­াāĻŦিāϤ āĻ•āϰে।


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ā§Š. āϏ্āĻŦāϞ্āĻĒāĻŽেāϝ়াāĻĻি āĻĒ্āϰāϝুāĻ•্āϤিāĻ—āϤ āϚিāϤ্āϰ

āϏাāĻĒোāϰ্āϟ: ā§Ģā§Ļ,ā§Žā§Ļā§Ļ – ā§Ģā§§,⧍ā§Ļā§Ļ

āϰেāϏিāϏ্āϟ্āϝাāύ্āϏ: ā§Ģā§Š,ā§Ŧā§Ļā§Ļ – ā§Ģā§Ē,⧍ā§Ļā§Ļ

āϟাāϰ্āĻ—েāϟ: ā§Ģā§Ģ,ā§Ļā§Ļā§Ļ – ā§Ģā§Ģ,ā§Ģā§Ļā§Ļ

āϏ্āϟāĻĒ-āϞāϏ: ā§Ģā§Ļ,ā§Ģā§Ļā§Ļ


āϝāĻĻি āϏূāϚāĻ• ā§Ģā§§,⧍ā§Ļā§Ļ-āĻāϰ āωāĻĒāϰে āĻĨাāĻ•ে, āϤাāĻšāϞে ā§Ģā§Ģ,ā§Ļā§Ļā§Ļ āĻĒāϰ্āϝāύ্āϤ āωāĻ āϤে āĻĒাāϰে; āύিāϚে ā§Ģā§Ļ,ā§Ģā§Ļā§Ļ āĻ­াāĻ™āϞে ā§Ē⧝,ā§Ļā§Ļā§Ļ āĻāϞাāĻ•া āĻĒāϰ্āϝāύ্āϤ āύাāĻŽাāϰ āϏāĻŽ্āĻ­াāĻŦāύা।


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ā§Ē. āĻĻীāϰ্āϘāĻŽেāϝ়াāĻĻি āĻĻৃāώ্āϟিāĻ­āĻ™্āĻ—ি (⧍ā§Ļ⧍ā§Ģ-⧍ā§Ļā§Šā§Ļ)

āĻĄিāϜিāϟাāϞ āĻŦ্āϝাংāĻ•িং, āϰুāϰাāϞ āϞোāύ āĻ—্āϰোāĻĨ āĻ“ āĻ•āϰ্āĻĒোāϰেāϟ āĻ‹āĻŖ āĻŦৃāĻĻ্āϧি āĻŦ্āϝাংāĻ• āύিāĻĢāϟিāĻ•ে ⧍ā§Ļā§Šā§Ļ āϏাāϞে ā§Žā§Ļ,ā§Ļā§Ļā§Ļ āĻĨেāĻ•ে ā§§,ā§Ļā§Ļ,ā§Ļā§Ļā§Ļ āĻĒāϰ্āϝāύ্āϤ āύিāϝ়ে āϝেāϤে āĻĒাāϰে (āĻļিāĻ•্āώাāĻŽূāϞāĻ• āĻ…āύুāĻŽাāύ)।


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ā§Ģ. āĻŽāύāϏ্āϤāϤ্āϤ্āĻŦ

āĻ­āϝ় āĻ“ āϞোāĻ­ āĻšāϞ āϟ্āϰেāĻĄাāϰেāϰ āϏāĻŦāϚেāϝ়ে āĻŦāĻĄ় āĻļāϤ্āϰু। āĻļৃāĻ™্āĻ–āϞা āĻ“ āϏ্āϟāĻĒ-āϞāϏ āĻŽাāύা āĻšāϞ āϏাāĻĢāϞ্āϝেāϰ āϚাāĻŦিāĻ•াāĻ ি।


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ā§Ŧ. āωāĻĒāϏংāĻšাāϰ

āĻŦ্āϝাংāĻ• āύিāĻĢāϟি āĻšāϞ āĻ­াāϰāϤেāϰ āĻ…āϰ্āĻĨāύীāϤিāϰ āĻĒ্āϰাāĻŖ। āϏāϤāϰ্āĻ•āϤা āĻ“ āϜ্āĻžাāύ āĻĻিāϝ়ে āĻāχ āϏূāϚāĻ• āĻĻীāϰ্āϘāĻŽেāϝ়াāĻĻে āĻ…āĻĒূāϰ্āĻŦ āϏāĻŽ্āĻ­াāĻŦāύা āϧāϰে āϰেāĻ–েāĻ›ে।


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āĻ…āϏ্āĻŦীāĻ•ৃāϤি

> āφāĻŽি āĻāĻ•āϜāύ āϟ্āϰেāĻĄাāϰ, āĻŦিāĻļেāώāϜ্āĻž āύāχ। āĻāχ āϞেāĻ–াāϟি āĻļুāϧু āĻļিāĻ•্āώাāĻŽূāϞāĻ• āĻ“ āϤāĻĨ্āϝāĻŽূāϞāĻ• āωāĻĻ্āĻĻেāĻļ্āϝে। āĻŦিāύিāϝ়োāĻ—েāϰ āφāĻ—ে āύিāϜāϏ্āĻŦ āĻ—āĻŦেāώāĻŖা āĻ•āϰুāύ।




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đŸ‡ŽđŸ‡ŗ ā¤šि⤍्ā¤Ļी ⤏ं⤏्⤕⤰⤪ — ā¤Ŧैं⤕ ⤍िā¤Ģ्⤟ी: ⤭ा⤰⤤ ⤕ी ⤆⤰्ā¤Ĩि⤕ ā¤§ā¤Ą़⤕⤍ (2025-2030)

ā¤Žे⤟ा ā¤ĩिā¤ĩ⤰⤪

ā¤Ŧैं⤕ ⤍िā¤Ģ्⤟ी ⤕ा ā¤Ēू⤰्⤪ ā¤ĩिā¤ļ्⤞े⤎⤪ – ⤤⤕⤍ी⤕ी ⤞⤕्⤎्⤝, ⤏्⤟ॉā¤Ē-⤞ॉ⤏, ⤆⤰ā¤Ŧीā¤†ā¤ˆ ⤍ी⤤ि ā¤Ē्⤰⤭ाā¤ĩ ⤔⤰ ⤞ॉ⤍्⤗-⤟⤰्ā¤Ž ā¤Ļृ⤎्⤟ि⤕ो⤪।

⤕ीā¤ĩ⤰्ā¤Ą्⤏

Bank Nifty today, Bank Nifty analysis, Nifty Bank target, RBI policy impact, Bank Nifty 2030 forecast, options trading

ā¤šैā¤ļ⤟ै⤗

#BankNifty #NiftyBank #ā¤ļे⤝⤰ ā¤Ŧा⤜ा⤰ #⤤⤕⤍ी⤕ी ā¤ĩिā¤ļ्⤞े⤎⤪ #OptionsTrading #⤭ा⤰⤤ी⤝ ā¤Ŧैं⤕ ⤕्⤎े⤤्⤰


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1. ā¤Ē⤰ि⤚⤝

ā¤Ŧैं⤕ ⤍िā¤Ģ्⤟ी ⤭ा⤰⤤ी⤝ ā¤Ŧैं⤕िं⤗ ⤕्⤎े⤤्⤰ ⤕ा ā¤Ē्⤰⤤ि⤍ि⤧ि ⤏ूā¤šā¤•ां⤕ ā¤šै, ⤜ो NSE ā¤Ē⤰ ⤏ू⤚ीā¤Ŧā¤Ļ्⤧ ā¤ļी⤰्⤎ ā¤Ŧैं⤕ों ⤕े ā¤ļे⤝⤰ों ⤕ी ⤗⤤िā¤ĩि⤧ि ⤕ो ā¤Ļ⤰्ā¤ļा⤤ा ā¤šै।


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2. ⤅⤞्ā¤Ē⤕ा⤞ि⤕ ā¤Ļृ⤎्⤟ि

⤏ā¤Ēो⤰्⤟: 50,800–51,200

⤰े⤜़ि⤏्⤟ें⤏: 53,600–54,200

⤞⤕्⤎्⤝: 55,000–55,500

⤏्⤟ॉā¤Ē-⤞ॉ⤏: 50,500


⤝ā¤Ļि ā¤Ŧैं⤕ ⤍िā¤Ģ्⤟ी 51,200 ⤕े ⤊ā¤Ē⤰ ā¤°ā¤šā¤¤ा ā¤šै ⤤ो 55,000 ⤤⤕ ⤜ा ⤏⤕⤤ा ā¤šै; ⤍ी⤚े 50,500 ⤤ोā¤Ą़⤍े ā¤Ē⤰ 49,000 ⤤⤕ ⤗ि⤰ाā¤ĩ⤟ ⤏ं⤭ā¤ĩ।


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3. ā¤Ļी⤰्ā¤˜ā¤•ा⤞ि⤕ ā¤Ļृ⤎्⤟ि⤕ो⤪ (2025–2030)

ā¤Ąि⤜ि⤟⤞ ā¤Ŧैं⤕िं⤗, ⤰ू⤰⤞ ⤕्⤰ेā¤Ąि⤟ ⤔⤰ ā¤ā¤¨ā¤Ēीā¤ ā¤•ā¤Žी ⤕े ⤕ा⤰⤪ 2030 ⤤⤕ ⤏ूā¤šā¤•ां⤕ 80,000 ⤏े 1,00,000 ⤤⤕ ā¤Ēā¤šुं⤚ ⤏⤕⤤ा ā¤šै (ā¤ļै⤕्⤎⤪ि⤕ ⤅⤍ुā¤Žा⤍)।


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4. ā¤Žā¤¨ोā¤ĩै⤜्ā¤žा⤍ि⤕ ā¤Ēā¤šā¤˛ू

⤭ाā¤ĩ⤍ा⤓ं ⤏े ⤍ि⤝ं⤤्⤰⤪ ⤖ो⤍ा ⤟्⤰ेā¤Ąā¤° ⤕ा ⤏ā¤Ŧ⤏े ā¤Ŧā¤Ą़ा ā¤Ļुā¤ļ्ā¤Žā¤¨ ā¤šै। ⤞ो⤭ ⤔⤰ ⤭⤝ ⤏े ā¤Ŧ⤚ें, ⤏्⤟ॉā¤Ē-⤞ॉ⤏ ⤕ा ā¤Ēा⤞⤍ ⤕⤰ें।


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5. ⤍ि⤎्⤕⤰्⤎

ā¤Ŧैं⤕ ⤍िā¤Ģ्⤟ी ⤏ि⤰्ā¤Ģ ā¤ā¤• ⤇ंā¤Ąे⤕्⤏ ā¤¨ā¤šीं, ā¤Ŧ⤞्⤕ि ⤭ा⤰⤤ ⤕ी ⤆⤰्ā¤Ĩि⤕ ā¤ļ⤕्⤤ि ⤕ा ā¤Ļ⤰्ā¤Ē⤪ ā¤šै। ⤅⤍ुā¤ļा⤏⤍ ⤔⤰ ⤧ै⤰्⤝ ⤏े ā¤‡ā¤¸ā¤Žें ā¤Ļी⤰्ā¤˜ā¤•ा⤞ि⤕ ⤏ā¤Ģ⤞⤤ा ⤏ं⤭ā¤ĩ ā¤šै।


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⤅⤏्ā¤ĩी⤕⤰⤪

> ā¤Žैं ā¤ā¤• ⤟्⤰ेā¤Ąā¤° ā¤šूं, ā¤ĩिā¤ļे⤎⤜्ā¤ž ā¤¨ā¤šीं। ā¤¯ā¤š ⤜ा⤍⤕ा⤰ी ⤏ि⤰्ā¤Ģ ā¤ļै⤕्⤎⤪ि⤕ ⤉ā¤Ļ्ā¤Ļेā¤ļ्⤝ ⤕े ⤞िā¤ ā¤šै। ⤍िā¤ĩेā¤ļ ⤏े ā¤Ēā¤šā¤˛े ⤅ā¤Ē⤍ा ā¤ļो⤧ ⤝ा ⤏⤞ाā¤šā¤•ा⤰ ⤏े ⤏ंā¤Ē⤰्⤕ ⤕⤰ें।


Written with AI 

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