MTS Mechanical Thinking Society mts.institute

MTS Mechanical Thinking Society: mentorship in mechanical trading systems

The bridge from retail thinking to institutional thinking.

Purvang Gandhi

Welcome, everyone. Let me walk you through a short journey: the problem in the market, the people who don’t face it, the solution, whether it has worked, a little about me and how I built my system, and finally how you can learn it from me.

The line on the right edge tracks your crossing as you scroll.

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MTS = Market Tension State

Let’s start with the problem. The market has three groups of people. Watch each graph, then tap the card beside it to see that group’s problem.

Externals70%slow, big swings of hope and fear
Externals70%Market tension: 100%Tap to see the problem
Externals: the problem
  • Fund investors Fear
    Stop SIPs and redeem when markets fall.
  • Portfolio holders Hope
    Hold losers hoping they come back. Sell winners too early.
  • Option gamblers Greed
    Buy cheap out of the money options. Revenge trade after a loss.
  • Pair speculators Doubt
    Abandon the spread at its widest, just before it converges.
Tap to turn back
Intermediaries20%constant pressure and fast, nervous reactions
Intermediaries20%Market tension: 100%Tap to see the problem
Intermediaries: the problem
  • Brokers & APs Pressure
    Push activity and leverage because brokerage depends on it.
  • Distributors & advisers Herd
    Recommend last year's top performer.
  • Dealers Fear
    Quote and hedge by gut feel when inventory moves against them.
  • Analysts Anchoring
    Defend old targets and rarely say sell.
  • Odd lot marketeers FOMO
    Trade on rumours and tip flow.
Tap to turn back
Internals10%sudden spikes when they override their own rules
Internals10%Market tension: 90%Tap to see the problem
Internals: the problem
  • Analytical Ego
    A strong view becomes a position they can't admit is wrong.
  • Discretionary Overconfidence
    Skip signals after losses. Double up after wins.
  • Systematic Doubt
    Switch the system off in a drawdown, often right before it recovers.
  • Algorithmic Rule based
    Rules run exactly as written. No override.
Tap to turn back
Up nextSo who doesn’t face this problem?

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Who stays calm?

First, look at what all that emotion costs.

So who makes the profit? Proprietary traders and foreign investors (FPIs). And almost all of their profit comes from algorithms.

Proprietary traders+₹33,000 cr
Foreign investors (FPIs)+₹28,000 cr
Individuals and others−₹61,000 cr

Source: SEBI study of the equity F&O segment, FY24. Gross trading profit and loss, before transaction costs.

Why do individuals lose? Algos follow rules. People follow feelings. Watch 100 people try to cross from retail thinking to institutional thinking.

Externals70%Waiting to cross
Intermediaries20%Waiting to cross
Internals10%Waiting to cross

Group sizes are the MTS model. One figure = one person in 100.

Up nextSo how is each problem solved?

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MTS = Mechanical Thinking Solution

Here are the same problems again. Flip each card to see how the problem is solved.

99%
Market tension
0 of 12 solved
ExternalsFund investors“Markets are crashing. Stop the SIP before I lose more.”Tap for the rule
Mechanical investors
  1. IF date = SIP date THEN INVEST, whatever the news
  2. IF equity > target + 5% THEN REBALANCE to target
  3. IF market falls 20% THEN ADD the planned top up
What changes: Buying continues when prices are lowest, which is exactly when an SIP does its best work.
ExternalsPortfolio holders“It will come back. Sell the winner, keep the loser.”Tap for the rule
Mechanical holders
  1. IF close < exit level THEN SELL
  2. IF position > 10% of portfolio THEN TRIM
  3. REVIEW every quarter on a fixed date
What changes: Losers are cut while small, and winners are allowed to keep growing.
ExternalsOption gamblers“This cheap option could go 10x. One more trade to win it back.”Tap for the rule
Mechanical option traders
  1. RISK per trade <= 1% of capital
  2. IF daily loss hits 2% THEN STOP for the day
  3. TRADE only setups with a tested probability
What changes: A lottery ticket becomes a position with a known risk and a tested edge.
ExternalsPair speculators“The spread is too wide. Something is broken. Get out!”Tap for the rule
Mechanical pair traders
  1. IF spread > 2 SD THEN ENTER
  2. IF spread returns to mean THEN EXIT
  3. IF spread > 3.5 SD THEN STOP: relationship broken
What changes: Entries and exits are decided before the spread moves, not while it hurts.
IntermediariesBrokers & APs“Clients need to trade more this month.”Tap for the rule
Mechanical brokers
  1. SUGGEST only pretested strategies
  2. IF client margin use > 50% THEN ALERT
  3. MEASURE success by client survival, not turnover
What changes: Clients last longer, so the relationship and the revenue last longer too.
IntermediariesDistributors & advisers“Everyone wants last year's top fund. Give it to them.”Tap for the rule
Mechanical advisers
  1. MATCH product to the client's risk score
  2. IF fund lags benchmark for 3 years THEN REVIEW
  3. REBALANCE every client on fixed dates
What changes: Advice follows a process clients can trust, not a headline.
IntermediariesDealers“Inventory is moving against me. Hedge everything now!”Tap for the rule
Mechanical dealers
  1. IF inventory > limit THEN HEDGE the excess
  2. QUOTE spreads from a volatility table
  3. IF loss > daily limit THEN FLATTEN
What changes: Risk is controlled by limits written in calm, not by decisions made in panic.
IntermediariesAnalysts“I said BUY at 500. I can't change my target now.”Tap for the rule
Mechanical analysts
  1. IF thesis condition fails THEN DOWNGRADE
  2. IF inputs change > 10% THEN UPDATE target
  3. PUBLISH a record of every call
What changes: Calls are judged by rules and track record, not by pride.
IntermediariesOdd lot marketeers“Everyone is talking about this stock. Get in now!”Tap for the rule
Mechanical marketeers
  1. NO entry on a tip alone
  2. ENTER only on a tested setup
  3. SIZE every trade from a fixed table
What changes: Rumours become filtered signals, or nothing at all.
InternalsAnalytical traders“My analysis says up. The market is wrong.”Tap for the rule
Mechanical analytical traders
  1. WRITE the exit before the entry
  2. IF price hits stop THEN EXIT, view or no view
  3. LOG every trade and its reason
What changes: A view becomes a hypothesis the market is allowed to reject.
InternalsDiscretionary traders“I don't feel good about this signal. I'll skip it.”Tap for the rule
Mechanical discretionary traders
  1. TAKE every signal the method gives
  2. SIZE from volatility, never from mood
  3. IF 3 losses in a row THEN HALVE size, never stop
What changes: Results become repeatable, so they can finally be measured and improved.
InternalsSystematic traders“The system is in a drawdown. Switch it off.”Tap for the rule
Mechanical systematic traders
  1. KNOW the tested maximum drawdown in advance
  2. IF drawdown < 1.5x tested max THEN KEEP running
  3. CHANGE the system only at a scheduled review
What changes: The system's recovery stays in your account instead of being missed.

Example rules for illustration only. They are not investment advice or recommendations.

Twelve problems, twelve simple rules. Easy to understand, right? But you may be asking: does it really work?

Up nextDoes thinking in rules really work?

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MTS = Mechanical Trading Strategy

Does it really work?

Fair question. These traders built fortunes thinking this way. Tap a theme, then tap any face to read their story.

What they have in common

Tap a theme to light up the traders who show it.

The traders

Tap a portrait to read the story. Their own words are kept on a separate tab.

Read all eight trader stories

Marty Schwartz: $40K → $20M

Account growth. 1984 U.S. Investing Champion

Originally a stock analyst, he grew tired of writing bullish advice on overpriced companies.

He developed and combined several technical indicators to find lower risk entry points, and found success when he shifted to technical analysis and focused on mathematical probabilities.

He ran his account from $40,000 to $20 million and won the U.S. Investing Championship in 1984. Asked whether technical analysis works, he said he used fundamentals for nine years and got rich as a technician.

A big advocate of moving averages, he identifies healthy stocks by looking for positive divergences in price action against the broad market.

Mark D. Cook: +563%

Return that won the 1992 U.S. Investing Championship

He lost all his capital several times while learning to trade, once more than his entire net worth. In 1982 he sold naked calls on Cities Service that expired deep in the money: his account fell from $165,000 to a deficit of $350,000 in days, a total loss of $815,000 including his family’s accounts.

Within five years he had fully recovered, and vowed never to sell another naked option. He credits the turnaround to his Cumulative Tick Indicator.

The NYSE ‘tick’ counts stocks on an uptick minus stocks on a downtick. When it moves outside a neutral band, his indicator adds or subtracts the ticks to a running total, which works as an overbought and oversold gauge: at extreme readings, the market tends to reverse.

In 1989 he finished second in the U.S. Investing Championship trading stocks. In 1992, after moving to options, he won it with a 563% return.

Victor Sperandeo: 18 years

Profitable in a row, averaging 72% a year

An options trader and technical analyst with 18 profitable years in a row and an average return of 72%. His first losing year was 1990.

He takes risk only when the odds are in his favour. After a two year study he identified ‘life expectancy’ profiles for market moves: an intermediate swing on the Dow in a bull market is typically about 20%, and once that is realised, the odds of further advance drop sharply.

Just as a life insurer prices an 80 year old differently from a 20 year old, he believes most technical analysts fail because they ignore the life expectancy of the move they are trading.

He later became President and CEO of Alpha Financial Technologies, known for its trend following, futures based indices.

Ed Seykota: +250,000%

One client account, by 1988

The pioneer of computerised trading systems. Inspired by Richard Donchian, he began building futures systems in the 1970s and tested them on an IBM 360 programmed with punch cards.

His systems followed trends, with pattern recognition and money management rules. By 1988 one client account was reported up 250,000% on a cash on cash basis.

His daily work is reported to take a few minutes: running his programs and generating the new signals. He credits money management, cutting losses and his technical systems, and calls fundamentals ‘funny mentals’.

James Simons (1938 to 2024): $11.0B

Net worth, Forbes 2012

The ‘Quant King’. He studied mathematics at MIT, earned a PhD at UC Berkeley, broke codes for the U.S. Department of Defense, and coauthored the Chern to Simons theory, later used in physics.

He founded Renaissance Technologies in 1982, a quantitative hedge fund that trades with computer models. A $10,000 investment in 1990 would reportedly have grown to over $4 million by 2007, and the Medallion Fund gained about 80% in 2008 after fees.

Renaissance hired scientists, not MBAs. About a third of its staff held PhDs, including code breakers, astrophysicists and speech recognition experts.

Jim Simons died in 2024.

Ray Dalio: $10B

Net worth, Forbes 2012

He placed his first trade at 12, earned an MBA from Harvard, and founded Bridgewater Associates in 1975 at age 25. From the start he kept a trading diary so his ideas could later be backtested.

Bridgewater became the world’s largest hedge fund, with about $130 billion under management in 2012. Its Pure Alpha fund averaged about 15% a year from 1992 to 2010.

He studies the cause and effect behind historical events and turns that understanding into computer algorithms. Every strategy is backtested and stress tested across periods and markets to make sure it is timeless and universal.

Well defined systems, processes and principles drive every decision, with relatively low leverage and many uncorrelated return streams.

Steven Cohen: $8.8B

Net worth, Forbes 2012

He started trading options in 1978 and made $8,000 on his first day. He founded SAC Capital in 1992 with $25 million; by 2012 it managed about $13 billion and had averaged a reported 36% net return a year.

His style is high volume, fast stock and options trading, at one point around 2% of daily NYSE volume.

Even at SAC, the best trader was profitable on about 63% of trades and most on 50 to 55%. About 5% of trades produced nearly all the profits: worth remembering the next time someone sells a ‘95% accurate’ trading robot.

He believes about 40% of a stock’s move comes from the market, 30% from its sector and 30% from the stock itself.

Paul Tudor Jones II: $3.6B

Net worth, Forbes 2012

Both a discretionary and a systems trader, he started in cotton futures under Eli Tullis, who taught him emotional control.

He started Tudor Investment Corp in 1983 with $300,000. By 2012 it managed an estimated $12 billion with a 24% average annual return.

He became famous for anticipating the 1987 crash, reportedly returning about 200% that year, because he understood how portfolio insurance would set off a chain reaction of selling.

He looks for trades where risk and reward are strongly skewed in his favour and uses little leverage. In his view, a good trader returns two to three times their largest drawdown.

Inside, they share six traits

Low emotional reactivityCalm, with neither major highs nor lows.
DetachedThe market does what it does. They don’t try to control it.
HumbleLittle ego, so taking losses and letting profits run is easy.
DecisiveThey decide quickly and act without second guessing.
ConscientiousDisciplined, consistent and plan driven. They persevere.
ConfidentFaith in their system and in their ability to follow it.

Rules, testing, discipline. Every time. Mechanical thinking works.

Up nextSo who am I, and why should you listen?

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MTS = Mad Trading Scientist

Purvang Gandhi, founder of MTS Institute and systematic trader with 30 years in the markets
Purvang Gandhi

After seeing all this, I decided to walk the same path. Thirty years in the market, through every role. Here is my trading story.

30years in the market
3roles: external, intermediary, internal
2approved SSRN papers
Up nextMy trading story

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MTS = My Trading Story

I built a system to trade for a living. Watch it grow: like splitting a molecule, I broke it into smaller parts, tested each, and rebuilt it stronger.

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    Read all ten stages of the system
    1. Detrended discretionary system. A discretionary system, tested by hand on detrended charts.
    2. The first continuous system. My first continuous system: the rules ran without a gap.
    3. Splitting the molecule. Like breaking a molecule, the system was split into separate buy and sell systems, each tested on its own.
    4. Split by time. Each side was broken down again by timeframe.
    5. System combinations. The parts were recombined into combinations of systems.
    6. Adding probabilities. Probabilities were added to every part.
    7. Trend into money management. Trend was added back, into the money management layer of the detrended systems.
    8. Profit excursions. Profit excursions were added to manage how trades move after entry.
    9. Extremes trading. A separate layer for trading extremes.
    10. Cross domain research. Ideas from other fields, brought in and tested in the market.
    The moment it clicked

    My thinking was mechanical.

    Rules, not feelings. Every single time.

    So I applied that thinking to my 10 years in each role, and started three services: Origio, iamb and MTS. Watch each part of my experience turn into a service.

    10 yearsas a market external
    GeneratedOrigio Researchfor market externals (70%)
    10 yearsas a market intermediary
    Generatediamb.clubfor market intermediaries (20%)
    10 yearsas a market internal
    Generatedmts.institutefor market internals (10%)
    Retail thinking Institutional thinking

    Together, this is my work: a bridge from retail thinking to institutional thinking.

    Up nextNot ready to commit? Explore first

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    Built for you to explore

    My work stands on four pillars. Each has a service and a product, so you can try a product first and see the result for yourself. Each one was generated mechanically.

    Pillar 2 · TrainingBuild ServiceMTS Institute: you are here ProductUdemy courses: mechanical systems in TradingView
    Pillar 4 · Technical researchAutomate ServiceMech Lab research (link coming soon) ProductRule based Expert Advisor on MQL5 ↗
    Community work · an achievement

    Published, approved academic research.

    Two of my papers are approved and published on SSRN. You can call me a serious researcher now.

    Up nextThis is me. Want my mentorship?

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    MTS Mentorship Programme

    If you want me to mentor you, here is how it works. In 25 weekends I take you from market basics to your own live, monitored mechanical system, thinking the way an institution thinks.

    mts.institute

    Mentorship Programme

    Taught directly by me. No prior market knowledge needed. You finish with a tested, sized and deployed system, and you stay part of the society for life.

    See how it works →
    50sessions, 2 hours each = 100 hours
    Sat + SunSat 7 to 9 pm · Sun 10 am to 12 noon IST
    25weekends, or 10 weeks on weekdays
    From $650founding seats, first 100 only

    Three ways to learn mechanical thinking