1.11 Case studies

Case 1: What SEBI's loss studies say about who wins#

Context SEBI has published a series of studies of individual traders' P&L using exchange and broker data. They are the best base rates available for Indian retail trading. This case is the course's single full treatment of the studies; other modules cite "(SEBI FY26 study; M01 · 1.11 Case 1)" and quote only the number they use.

Timeline and numbers

Study (release)	Period	Findings	Source
Jan 2023	FY22	89% of individual F&O traders lost money; average loss ₹1.1 lakh	Business Standard, 25 Jan 2023
PR 13/2024, 24 Jul 2024	FY23, intraday equity cash	71% of individual intraday traders made net losses (65% in FY19, 69% in FY22); 80% among those with more than 500 trades a year; average loss of loss-makers ₹5,371, average profit of profit-makers ₹5,989; loss-makers' trading costs equalled a further 57% of their trading losses (average cost ₹1,956 against an average trading loss of ₹3,415); profit-makers' costs took 19% of trading profits; participants rose from 14.9 lakh (FY19) to 68.9 lakh (FY23); under-30s rose from 18% to 48% of traders	SEBI PR 13/2024 (https://www.sebi.gov.in/media-and-notifications/press-releases/jul-2024/sebi-study-finds-that-7-out-of-10-individual-intraday-traders-in-equity-cash-segment-make-losses_84948.html); detailed figures as reproduced by Taxguru and Business Standard, 24 Jul 2024
PR 22/2024, 23 Sep 2024	FY22–FY24, F&O	93% of more than 1 crore individual traders lost money; aggregate losses ₹1.81 lakh crore over three years; only about 7.2% were profitable	SEBI press release (https://www.sebi.gov.in/media-and-notifications/press-releases/sep-2024/updated-sebi-study-reveals-93-of-individual-traders-incurred-losses-in-equity-fando-between-fy22-and-fy24-aggregate-losses-exceed-1-8-lakh-crores-over-three-years_86906.html)
7 Jul 2025	FY25	91% lost money; net losses ₹1,05,603 crore (FY24: ₹74,812 crore)	SEBI, Comparative study of growth in trading in Equity Derivatives Segment vis-à-vis Cash Market after recent measures (press release, Jul 2025: https://www.sebi.gov.in/media-and-notifications/press-releases/jul-2025/comparative-study-of-growth-in-trading-in-equity-derivatives-segment-eds-vis-vis-cash-market-after-recent-measures_95106.html); figures as reported by Business Standard, 7 Jul 2025
PR 50/2026, 20 Aug 2026	FY25–FY26, F&O	87.7% of individuals lost money in FY26 after costs (82.1% before costs); FY25 revised to 90.9%; aggregate net loss ₹91,685 crore in FY26 (FY25 revised to ₹1,11,788 crore on wider broker coverage); average net loss about ₹1.17 lakh per individual trader, about ₹1.47 lakh per loss-maker, and average profit about ₹1.22 lakh per profit-maker; options were about 92% of losses; about 97% of individual traders bought options; 59% of index-option turnover was in contracts expiring the same day (0DTE); transaction costs about ₹25,000 crore; prop traders made about +₹44,000 crore and FPIs about +₹14,000 crore gross while individuals lost about ₹72,000 crore gross, and about 99% of the prop and FPI gross profit came from algorithmic entities	SEBI PR 50/2026 (https://www.sebi.gov.in/media-and-notifications/press-releases/aug-2026/sebi-studies-indicate-key-trends-in-retail-participation-trading-behaviour-and-profitability-in-the-equity-derivatives_103838.html) and the study Profitability of Individual Traders in the Equity Derivatives Segment (FY25–FY26) (SEBI Department of Economic and Policy Analysis, Aug 2026: https://www.sebi.gov.in/sebi_data/attachdocs/aug-2026/1787233506209.pdf). Both PDFs were downloaded on 6 Nov 2026 but their text could not be machine-extracted, so the figures are as reported by summaries (CorpLawUpdates, Finnovate); check them against the PDF tables before relying on any one number

The FY26 participation figures conflict between summaries (98.1 lakh → 78.6 lakh in one, 106.2 → 87.5 lakh in another); the direction (a fall of about one-fifth) is consistent.

Mechanism Apply this module's tools.

1. Costs turn a zero-sum game negative-sum. Before costs, F&O is zero-sum across all participants. The FY26 numbers show 82.1% of individuals losing before costs and 87.7% after. Costs move roughly 5.6% of the population from small gains to losses. In the intraday study, costs added 57% to the losses of loss-makers. Formula (1.4) shows why: a trader whose average gross edge per trade is a few basis points cannot clear a 7–8 bp break-even, and an option buyer paying ₹47 fixed costs on a ₹6,500 premium needs a 0.7% move in the option to cover the fixed costs alone, and about 1% once STT and exchange charges are included.
2. Adverse selection in the order book. Individuals' gross loss of about ₹72,000 crore was mirrored by gains of prop desks and FPIs, nearly all of them algorithmic. In a CLOB with price-time priority (1.4), faster participants update quotes before slower ones can trade on stale prices. M05 · 5.3–5.4 models this.
3. Product design. Most individual losses came from buying cheap, short-dated options. The payoff is lottery-like: a small probability of a large gain. The tendency to overpay for such payoffs is documented behaviourally (M14).

Case 2: The 2024–2026 SEBI derivatives rules as market design#

Context By 2024 more than one crore individuals had traded equity F&O over three years (SEBI PR 22/2024), driven by weekly expiries on several indices and small contract sizes. SEBI's response is a sequence of design changes. Each one acts on a term in this module's algebra.

Timeline (SEBI circular SEBI/HO/MRD/TPD-1/P/CIR/2024/132 of 1 Oct 2024, https://www.sebi.gov.in/legal/circulars/oct-2024/measures-to-strengthen-equity-index-derivatives-framework-for-increased-investor-protection-and-market-stability_87208.html ; later items from the SEBI and NSE circulars named in the rows, all fetched 6 Nov 2026):

Date effective	Measure	Lever
20 Nov 2024	Minimum index-derivative contract value ₹15 lakh (band ₹15–20 lakh at review); Nifty lot 25 → 75, Bank Nifty 15 → 30	Raises the minimum ticket, so the fixed-cost term $K/(PQ)$ shrinks but capital at risk per trade rises
20 Nov 2024	Weekly expiry on one benchmark index per exchange	Reduces the number of 0DTE lottery tickets
20 Nov 2024	Extra 2% extreme-loss margin on short index options on expiry day	Raises the cost of selling 0DTE options
1 Feb 2025	Upfront collection of option premium; calendar-spread margin benefit removed on expiry day	Removes intraday leverage on long options
1 Apr 2025	Intraday monitoring of position limits	Institutions
1 Sep 2025	NSE expiries moved to Tuesday, BSE to Thursday (SEBI circular SEBI/HO/MRD/MRD-TPD-1/P/CIR/2025/76 of 26 May 2025; NSE/FAOP/68589 of 17 Jun 2025)	Separates the two exchanges' expiries
Contracts after the 30 Dec 2025 expiry	Lot sizes cut (Nifty 75 → 65, Bank Nifty 35 → 30) to stay in the ₹15–20 lakh band (NSE/FAOP/70616 of 3 Oct 2025)	Keeps contract value in the band as the index rose; confirmed in the NSE F&O bhavcopy of 5 Nov 2026
1 Apr 2026	STT on futures 0.02% → 0.05%, on option premium 0.1% → 0.15% (Finance Act, 2026, not SEBI; NSE/FATAX/73524)	Raises $\beta$ in (1.3)
1 Apr 2026	Retail algo framework applies to all brokers (SEBI circulars of 4 Feb 2025 and 30 Sep 2025)	Access to automation
3 Aug 2026; 7 Dec 2026	Closing auction session (SEBI, 16 Jan 2026); expiry settlement on last-30-minute VWAP (SEBI, 15 Oct 2026)	Close-price manipulation resistance

As of 6 Nov 2026 SEBI's circulars list contains no circular abolishing weekly expiries; the 26 May 2025 circular (para 3.2) still allows one weekly benchmark index option per exchange.

Mechanism and outcome The measures raise the per-trade cost of short-dated speculation (STT, margins, minimum size) and reduce the number of available 0DTE contracts. The FY26 study reports fewer active individuals (down about one-fifth), fewer new entrants (down about 40%), lower aggregate losses (₹91,685 crore, down about 18% from the revised FY25 figure) and a lower loss rate (87.7% versus 90.9%). SEBI's study credits the STT increase with keeping aggregate transaction costs roughly flat while turnover fell. The loss rate barely moved; the intensive margin (how much each trader lost) and the extensive margin (how many traded) moved more.

Case 3: The 1992 securities scam as a settlement-system failure#

Context In 1991–92 Indian banks traded government securities among themselves through ready-forward (repo) deals: a sale with an agreement to buy back at a fixed price, which is economically a secured loan. Settlement was often not through the RBI's Subsidiary General Ledger (SGL) accounts, which would have moved securities and cash together, but through bank receipts (BRs): a paper receipt from the selling bank promising that it held the securities for the buyer and would deliver them. Brokers intermediated these deals.

Timeline and numbers

• 1991–early 1992: bank funds routed through brokers, of whom Harshad Mehta was the most prominent, flowed into equities. ACC's share price was reported to rise from about ₹200 to nearly ₹9,000 (Dalal & Basu, The Scam, as cited by Wikipedia).
• 23 Apr 1992: Sucheta Dalal's column in The Times of India exposed the use of bank funds (Wikipedia, "Harshad Mehta").
• The State Bank of India found itself holding BRs that were not backed by securities. The RBI-appointed Janakiraman Committee estimated the size of the irregularities at about ₹4,000 crore; reported figures from its reports range from ₹4,024 crore to ₹4,300 crore (The Quint; secondary summaries), and other popular figures of ₹5,000 crore or more are not from the committee.
• Bank losses tabulated by Narayanan (2004) include National Housing Bank ₹1,199.39 crore, Standard Chartered ₹300 crore, State Bank of Saurashtra ₹175.04 crore and SBI Capital Markets ₹121.23 crore (as cited by Wikipedia).
• The BSE index fell from about 4,500 to about 2,500, a loss of about ₹1,00,000 crore of market value (Barua & Varma, Vikalpa, 1993, as cited by Wikipedia).
• 9 Nov 1992: Mehta arrested by the CBI. He was convicted by the Bombay High Court in Sep 1999; he died on 31 Dec 2001.

Mechanism The fraud worked because the settlement system lacked delivery-versus-payment (1.6). A BR is an unsecured promise if the issuing bank does not actually hold the securities. Some smaller banks issued BRs without backing; the receiving bank paid cash against them, and the cash went to the broker's account, not to the counterparty bank. The securities leg could be deferred indefinitely as long as new deals rolled the old ones. In this module's language: there was no central counterparty, no novation, no margin, and no atomic exchange of cash and securities. A clearing corporation with DvP settlement through a depository makes this specific fraud impossible, because cash moves only when securities move in the same book.

Case 4: Election-result day, 4 June 2024#

Context Exit polls published after voting ended on 1 Jun 2024 pointed to a large majority for the ruling coalition, and the Nifty and Sensex closed at record highs on 3 Jun 2024. Counting on 4 Jun showed a much narrower result. This is the course's reference timeline for the day; M02 · 2.10.3 (the move in standard deviations) and M04A Case 2 (stops and sizing) refer here.

Timeline (Nifty 50 and India VIX from NSE's daily index files ind_close_all_DDMMYYYY.csv, https://nsearchives.nseindia.com/content/indices/ind_close_all_04062024.csv and the files for the adjacent days, fetched 6 Nov 2026; Sensex from Moneylife and Business Standard, 4 Jun 2024):

Date	Event	Nifty 50 (open / high / low / close, change)	India VIX close
Fri 31 May 2024	Last session before the exit polls	close 22,530.70	24.60
Sat 1 Jun	Voting ends; exit polls published	–	–
Mon 3 Jun	Exit-poll rally to a record close	23,337.90 / 23,338.70 / 23,062.30 / 23,263.90, +733.20 (+3.25%)	20.94 (−14.9%)
Tue 4 Jun	Counting day	23,179.50 / 23,179.50 / 21,281.45 / 21,884.50, −1,379.40 (−5.93%)	26.75 (+27.8%; intraday high 31.71)
Wed 5 Jun	Rebound once the result was known	22,128.35 / 22,670.40 / 21,791.95 / 22,620.35, +735.85 (+3.36%)	18.89 (−29.4%)

The 4 Jun fall was the Nifty's largest one-day fall since March 2020; the Sensex closed at 72,079.05, down 4,389.73 points (−5.74%), and was down more than 5,000 points intraday (Business Standard). The open equalled the day's high: the gap was only −0.36%, and the whole fall, up to 8.2% from the open (8.5% from the previous close), happened during the continuous session as counting progressed.

Analysis with this module's tools

• Circuit breakers. The 10% MWCB trigger was about 20,937.5 (1.5 worked example). The intraday low, 21,281.45, was 8.5% below the previous close, so no halt. A 10% fall before 13:00 would have stopped trading for 45 minutes and reopened through a call auction.
• Price bands. F&O stocks, with dynamic bands, could fall further than non-F&O stocks with fixed 5% or 10% bands. PSU and Adani-group stocks were among the largest fallers (Business Today, 4 Jun 2024). For any stock locked at its lower band, the close understates the price at which a seller could actually have exited.
• Execution cost. On such a day spreads widen and displayed depth thins. A stop-loss market order fills well below its trigger; an SL limit order may not fill at all (1.4).