Vikas Agarwal, Georgia State University

Pulak Ghosh, Indian Institute of Management Bangalore

Nagpurnanand Prabhala, Johns Hopkins University

Haibei Zhao, Lehigh University

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CICF 2026

Animal Spirits on Steroids:

Evidence from Retail Options Trading in India

Outline of presentation

• Insights into the nature of retail options trading
• Panel of all retail investors in India, a large derivatives market
• Evidence from natural experiments
• One increases supply of short-term opportunities (weeklies)
• Two others increase costs of participation (lot size and delivery margin)
• Conclusions
• Speculative tastes once set, hard to undo
• Financial inclusion has benefits but is costly if premature

Indian Index Options Market in Global Context

Outsized options market

Data

• Trader-day-contract level daily aggregated data on the National Stock Exchange of India (99.6% volume)
• 6.8 million traders
• 14.5 years of data from 2007Q1-2021Q2
• Variables:
• Masked IDs for each individual/institution
• Number of contracts traded, and prices paid for purchases and sales of each contract each day
• Exclude extremely small traders (₹5,000 in 15 years) and large “protail” traders = top 1% volume over the last 6 months
• Median protail volume is 482X regular retail

Growth in retail participation

15X growth in number of traders (more inexperienced traders in recent years; dominated by middle aged and male)

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86X growth in premium turnover

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358X growth in notional amount

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Options trading losses

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Per trader loss ₹109,900 > Per capita GDP ₹98,000

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76% are low-income investors (SEBI report)

Other stylized facts

• Index dominance
• 75% premium and 93% notional volume
• Short-termism
• Day trading proportion growth: 30% to 90%
• TTM and moneyness: 87% of volume is 0-5DTE; ATM and slightly OTM
• Duration: Mean = 2.4 days; Median = 0
• Strong shift to 0DTEs
• Simple, directional strategies

0DTE skewness: 04/09/2025

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Realized skewness: BANKNIFTY

For each TTM sort all index options into quintiles by moneyness; assume buy and hold to maturity for each option; table shows skewness of each TTM+moneyness portfolio.

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Stocks: 0.219 (Boyer, Mitton, and Vorkink, 2010) to 1.35 (Bali, Cakici, and Whitelaw, 2011).

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Stock options: 0.7 to 2.7 for 7DTE ATM and OTM options (Boyer and Vorkink, 2014)

Natural Experiments

• A) Introduction of weekly options on BANKNIFTY index
• B) Increase in lot size
• C) Delivery margin tightening

1. Introduction of weekly BANKNIFTY

• Only 2 major indexes during our sample period (99.9% of all volume)
• NIFTY50 is a traditional index of 50 large cap stocks
• BANKNIFTY 12 large private and state-owned banks
• Pre-2016: One expiry per month for both indexes

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• In May 2016, NSE introduced
• Weekly expiries for BANKNIFTY
• Still one expiry for NIFTY50

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1. Introduction of weekly BANKNIFTY

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1. Introduction of weekly BANKNIFTY

• Extensive margin growth
• 68% of weekly traders had zero BANKNIFTY experience
• 46% of weekly traders had zero options experience
• Intensive margin growth (DiD)
• For the same trader, trading on BANKNIFTY as treated and trading on NIFTY50 as controls
• Parallel pre-trend in volume but profound increase in BANKNIFTY volume after introduction (next figure)

1. Introduction of weekly BANKNIFTY

• Extensive margin growth
• 68% of weekly traders had zero BANKNIFTY experience
• 46% of weekly traders had zero options experience
• Intensive margin growth (DiD)
• For the same trader, premium volume on BANKNIFTY increased by 91,020/month and notional by 65.56 million/month relative to NIFTY50.
• Dollar losses increase by 2,352/ month

Withdrawal from stock investments

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Less net investment into stocks

Extreme short term, leveraged bets while ERP rewards long term investors

2. Lot size increase

• Lot size: the multiplier which is NOT fixed (e.g. 100 in the US)
• In August 2015, SEBI
• Tripled the lot size for NIFTY from 25 to 75 contracts
• Doubled the lot size for BANKNIFTY from 15 to 30 contracts
• Consequences
• Overall retail volume decreases shortly after rule change, but reverses thereafter
• Systematic shift to 0DTE and OTM options

Aggregate retail volume

• Intended consequence: (short term) reduction in volume

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Aggregate retail volume

• Unintended consequence of volume shifting to OTM and 0DTE

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2. Lot size increase

• Next, a DID
• Treated Always below NEW lot sizes before the shock
• Control Slightly above NEW lot sizes before the shock
• [75, 250] for NIFTY50
• [30, 90] for BANKNIFTY
• Same message:
• Less volume but shift to cheaper options with lower moneyness and less maturity
• No net benefit

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3. Physical settlement margins

3. Physical Settlement (contd.)

• Treated Average horizon before rule change < 9 days (bottom 25%). These are likely constrained traders;
• Control: Other traders
• Results: Speculation Venue Shifting
• Treated investors reduce their short maturity option trading by ₹79.03 million and increase their long maturity option trading by ₹78.11 million after the shock
• Treated shifted to OTM (₹58.87 million increase) with a greater loss of ₹777 per month

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Addiction model

• Traders derive utility from trading which depends on instantaneous volume c and a “stock” level A
• Additional trading adds to the stock, which decays over time
• Leverage Ω helps increase effective volume
• Traders switch to higher leverage only if adjacent complementarity u(c,A) is large

Additional results

• 0DTE trading
• Same trader gets more into 0DTE over time
• Increases with cumulative profits and losses
• More volume from male, young traders
• Trader entry into options
• Less experience on stock trading
• After losing on stocks
• Had traded volatile/lottery stocks
• Trader exit
• Winners stay longer but suffer worse future returns (overconfidence or skill extrapolation)

Additional results

• Single stock options
• Prefer cheaper options (lower premium and volatility)
• Prefer options on stock with high share prices
• Fintech brokers (including switchers)
• Promote participation
• Induce more losses
• Institutions gain

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Contribution and conclusion

• Household finance
• Benefits of stock participation: diversification, gain equity risk premium
• Our study: Pathway to speculation; hard to undo even if investors lose
• Retail options trading
• de Silva, So, and Smith, 2022; Hendershott, Khan, and Riordan, 2022; Bryzgalova, Pavlova, and Sikorskaya, 2023; Beckmeyer, Branger, and Gayda, 2023; Hu et al., 2023; Eaton et al., 2024; Ernst and Spatt, 2023; Bogousslavsky and Muryayev, 2024; Naranjo, Nimalendran, and Wu, 2024
• Our study:
• Natural experiments, supply side shocks; addictive behavior at investor level

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Aftermath: Recent SEBI effort

https://www.fia.org/sites/default/files/2025-05/ETD%20Trends%20Q1%202025%20final.pdf

Faulty FIA data

• But the FIA data is about the number of LOTs (which mechanically shrinks by 2/3 as lot size goes from 25 to 75), not the actual volume!

Actual premium and notional volume around recent lot size change

Again, short term decline in volume and shift to cheaper options!