Tokenization Hype vs Reality: Kya ye ETF se bhi bada revolution hoga?

TECHNOLOGY
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AuthorAnanya Iyer|Published at:
Tokenization Hype vs Reality: Kya ye ETF se bhi bada revolution hoga?
Overview

Log keh rahe hain ki tokenization se stock market mein ETF jaisa bada revolution aayega, par abhi bhi kuch bade issues hain. Liquidity kam hai, regulations alag alag hain, aur custody mein bhi risks hain. Sabse badi baat, costs bahut zyada hain aur 24/7 market mein dikkatein aa sakti hain.

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Mechanism vs Market Ki Haqeeqat

Blockchain par tokenization ko ETF creation-redemption cycle jaisa banane ki koshish ho rahi hai. Lekin iske liye on-chain liquidity ko us efficiency tak pahunchna hoga jo abhi ke established exchanges par hai. Traditional finance mein ETFs isliye successful hain kyunki unke paas Authorized Participants (APs) ka bada network hai jo kam profit par bhi kaam karte hain. Iske bilkul opposite, tokenized assets mein transaction costs bahut high hain aur clearing house integration bhi theek se nahi hai. Smart contracts se assets ko mint ya burn karne mein ek bada risk hai: agar code mein koi technical problem aa gayi, toh arbitrage band ho jayega aur price discovery atak jayegi.

Fragmentation Ka Nuksaan

Global ETF market ke opposite, jahan liquidity concentrated hai, tokenized assets abhi fragmented hain. Investors ko alag alag liquidity pools mein asset trade karne padte hain, aur ek protocol ya chain par bane assets ko dusre par trade karne ke liye costly bridge mechanisms use karne padte hain. Isse kafi slippage hota hai. Jabki kuch log kahte hain ki off-market hours mein continuous trading se price discovery behtar hoti hai, reality iske opposite hai. Kam participation hone ki wajah se cost of carry badh jati hai, jisse bid-ask spreads bade ho jate hain aur institutional participants ke liye off-hour trading bahut mehengi pad jati hai. Isko currency market se compare karna galat hai; FX markets ke paas decades se established credit lines hain jo abhi tokenized asset sector mein nahi hain.

Bear Case: Asliyat Kya Hai?

Tokenization thesis ki sabse badi kamzori custody aur insolvency ko lekar regulatory ambiguity hai. Agar koi tokenized equity issuer bankruptcy mein chala jata hai, toh bahut si jurisdictions mein token holder ka legal status tested nahi hai. ETF share ke opposite, jismein regulated trust mein rakhe underlying securities par legal claim hota hai, token contract aur property right ke beech ambiguous position mein ho sakta hai. Iske alawa, key management ka operational risk ek silent killer hai; private keys kho dene se ya smart contract exploits se principal ka total loss ho sakta hai, jo traditional ETF custodians ke saath kam hota hai. Aur haan, regulators bhi synthetic securities ke representation ko lekar zyada scrutiny dikha rahe hain. Agar kisi bade regulator ne specific tokenized wrappers ko unregistered securities ya derivatives declare kar diya, toh poori liquidity model ko existential threat ho jayega, jismein forced delisting ya compliance restructuring ho sakti hai.

Institutional Challenges

Tokenization ko ETF market ($10 trillion) ka ek chhota sa hissa bhi achieve karne ke liye, legacy settlement systems ke friction ko overcome karna hoga. Asli adoption ke liye ye tokens central securities depositories aur current clearing infrastructure ke saath interoperable hone chahiye. Jab tak ye systems modern nahi ho jate, tokenized assets core market utility ki jagah ek peripheral experiment bane rahenge. Abhi jo institutional adoption ho raha hai, woh mostly private ledger solutions par focus kar raha hai, jo ironically us public, transparent, aur democratic market structure ke premise ke khilaaf hai jisne decentralized finance mein interest jagaya tha.

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Disclaimer:This content is for educational and informational purposes only and does not constitute investment, financial, or trading advice, nor a recommendation to buy or sell any securities. Readers should consult a SEBI-registered advisor before making investment decisions, as markets involve risk and past performance does not guarantee future results. The publisher and authors accept no liability for any losses. Some content may be AI-generated and may contain errors; accuracy and completeness are not guaranteed. Views expressed do not reflect the publication’s editorial stance.