7.1

🧮 Математика ризику

Розмір позиції, математика просідань, ризик/дохідність, Келлі та диверсифікація

1. Чому спочатку ризик?

🚀 New to Trading? Before digging into Kelly Criterion and volatility scaling here: first read Chapter 6.0 — The 1R Rule. It's the simplest risk rule and more than enough for your first 6 months.

Why Risk First?

The best strategy is worthless if you're out in round one. Three cases in which mathematical geniuses, stock market prodigies, and trading legends failed — not because of their strategy, but because of risk discipline they treated as a formality.

„Picking up nickels in front of a steamroller."

How two Nobel laureates and a dream team tried to double the world — and lost $4.6 billion in six weeks.

In 1994, John Meriwether, formerly a legendary bond trader at Salomon Brothers, founded a hedge fund unlike any before: Long-Term Capital Management. On board were finance academics Myron Scholes and Robert Merton — three years later both received the Nobel Prize for their options pricing theory. The strategy sounded elegant and safe: Convergence Trades. They searched for bond spreads that statistically had to converge again and pocketed the gap.

To turn tiny margins into real returns, LTCM needed leverage. And massive leverage at that. At times the fund operated at 30:1 on its own capital, with the notional of open positions at $1.25 trillion — with a "t", larger than Germany's GDP at the time. For four years LTCM delivered over 40% return per year. Wall Street puzzled over how. Banks fought to be counterparty on every trade.

In August 1998, Russia unexpectedly defaulted on its ruble bonds. What was a footnote in the normal distribution models of Scholes and Merton was, in reality, a wildfire. Panicking investors fled to safe assets — all convergence spreads widened simultaneously instead of converging. The leverage that had been a return machine for four years became a wrecking ball. Within a few weeks, LTCM burned through $4.6 billion. The Fed had to organize a consortium of 14 banks, each contributing around $300 million, just to prevent a systemic collapse.

The mathematics behind the trades was brilliant — but it was based on the assumption that returns are normally distributed. Fat Tails didn't fit the model. And anyone leveraged 30:1 has no buffer when the real world refuses to follow the bell curve.

The LessonA 30:1 lever makes you rich in 99 out of 100 weeks — and bankrupt in one. The Nobel Prize mathematics was correct; the position size was wrong. Risk management is not about how often you win, but about how large the worst possible loss may be.

„I'm sorry."

How a 28-year-old with a secret account wiped out the oldest investment bank in Britain.

Barings Bank, founded in 1762, had financed the Napoleonic Wars and enabled the Louisiana Purchase for the United States. 233 years old. Then came Nick Leeson. In 1992, the 25-year-old Briton was sent to Singapore to work as a derivatives trader on the SIMEX. Barings made a mistake that every compliance manual lists as a cardinal sin: Leeson was given both trading AND back-office settlement in one hand. Whoever settles their own trades can also make them disappear.

Officially, Leeson was supposed to arbitrage Nikkei futures between Singapore and Osaka — low risk, but little profit. He soon wanted more. He set up account "88888", ostensibly for booking errors by his clerks, and buried growing losses in it. By 1994 it was already $200 million, by early 1995 around $500 million. In London, Leeson was simultaneously regarded as the wonder boy of the Asian derivatives desk.

On 17 January 1995, the ground shook under Kobe. Leeson held gigantic short straddle positions on the Nikkei — i.e., short volatility. The Nikkei crashed 15%, volatility exploded, and margin calls came in series. Instead of closing, Leeson doubled down on the position hoping for a reversal. It never came.

On 26 February 1995, Barings filed for insolvency. Total losses stood at £827 million — more than the bank's entire equity. ING bought Barings for £1. Leeson fled, was arrested in Frankfurt, served four years in a Singapore prison and afterwards wrote a book.

The LessonDoubling down on losses is not risk management — it is its opposite. If your first impulse when a position moves against you is to "add more and hope," that is the first warning signal. Discipline on the first loss is what decides the outcome, not on the third.

„I made my money by sitting, not trading."

The greatest trader of all time knew everything about risk — and still couldn't sustain it.

Jesse Livermore was born in 1877 in Massachusetts, started as an office boy at a brokerage firm at age 14, and made his first own trades at 15 in the so-called Bucket Shops — semi-illegal betting parlors on stock prices. He read ticker tapes like others read novels. By age 30 he had $3 million in assets (roughly $100 million today) and a nickname: Boy Plunger.

Then came the moments that made him immortal. In 1907, during the notorious panic, he earned around $3 million with short positions in a single day — J.P. Morgan personally asked him to stop shorting to prevent Wall Street from collapsing further. In 1929, during the greatest crash of all time, Livermore made an estimated $100 million — he was one of the richest men in America. At a time when others were jumping out of office windows.

And yet: bankrupt four times. In 1915, 1922, 1934, 1940. Each time a comeback, each time with a little less discipline. Livermore was the man who popularized the concept of the trailing stop, who was one of the first to calculate position sizing methodically, and who devoted entire chapters of his book Reminiscences of a Stock Operator to waiting. His most famous quote — "I made my money by sitting, not trading" — became the most cited trader aphorism in history after his death.

In 1940 his third marriage failed. He wrote a farewell letter to his wife — "My life has been a failure" — and shot himself in the cloakroom of the Sherry-Netherland Hotel in New York. The man who had written the rules could not follow his own at the end.

The LessonKnowledge is not the same as execution. Livermore knew what to do — he had written it down, practiced it in offices in New York, preached it to others. Risk management is not a one-time decision and not a checkbox to tick. It is a daily discipline that you must summon anew every morning. Otherwise your own ego catches up with you.
$4.6 bn
LTCM · 1998
30:1 leverage + Fat Tails. Normal distribution in the model — reality had a tail the model had never seen.
£827 mn
Barings · 1995
One single trader, account "88888", doubling down. 233-year-old bank sold for £1.
Livermore · Bankruptcy
Wrote the rules found in every trading book today — and broke them every time. Knowledge ≠ execution.
To make money you must first make sure you don't lose money. Warren Buffett · Rule No. 1

🛠️ This Chapter's Toolkit

Four workshops, fifteen tools. First we build the risk framework (Position Sizing, Drawdown, Kelly). Then the infrastructure (Broker, Fees, Execution). Then the tax office (three countries, three rule sets). And finally the unexpected events that reshape your portfolio: splits, dividends, mergers.

I · Risk & Sizing

2. Розмір позиції

🖨️ Cheatsheet · A4
🛡️
Quick Reference · printable
Risk Management — Position Sizing & Kelly on One Page

Position sizing formula, R/R ratio, break-even win rate, Kelly/Half-Kelly, drawdown recovery table, daily & max drawdown limits, 4 psychological pitfalls and pre-trade checklist.

→ Save as PDF or pin next to your monitor 🖨️ Open Cheatsheet
I made my money by sitting, not trading. Jesse Livermore · 1877-1940

Position Sizing — the most important rule in trading

The most important variable in trading is not the win rate, but how much you risk per trade. The Fixed-Fractional method is the industry standard:

Position Size = (Capital × Risk%) ÷ (Entry Price − Stop-Loss Price)

Example: Capital $10,000 · Risk 1% · Apple Entry $180 · Stop-Loss $175
→ Risk Amount = $100 · Risk/Share = $5 → Position Size = 20 Shares ($3,600 capital deployed)

🧮 Position Size Calculator

Max. Risk Amount
Position Size (Shares)
Capital Deployed
Capital Percentage

3. Математика просідань та відновлення

Drawdown & Recovery Mathematics

A drawdown is the loss from the account's peak to its current low. The tricky part: the larger the loss, the more you need to gain to get back to zero.

Formula: Required Gain% = (1 ÷ (1 − Loss%)) − 1

DrawdownRequired GainAssessment
10%11.1%Manageable
20%25.0%Still OK
30%42.9%Critical
50%100.0%Very Dangerous
75%300.0%Almost Impossible

🧮 Drawdown Calculator

Loss
Required Gain
Assessment

4. Ризик/дохідність та критерій Келлі

Risk/Reward Ratio (R/R)

The R/R ratio (Risk/Reward) describes how much profit you aim for relative to what you risk. It is the most important quality criterion for a trade setup.

Formula: R/R = (Target Price − Entry) ÷ (Entry − Stop-Loss)

Example: Entry $180 · Stop-Loss $170 · Target $210
→ Risk = $10 · Reward = $30 → R/R = 3.0 (you risk $1 for $3 potential profit)

From the R/R ratio you can derive the break-even win rate — how often you need to be right to be profitable long-term:

Break-Even Win Rate = 1 ÷ (1 + R/R)

At R/R 2.0: at least 33.3% required. At R/R 1.0: at least 50%.

Kelly Criterion

The Kelly Criterion calculates the mathematically optimal position size based on R/R and win rate:

Kelly% = Win Rate − ((1 − Win Rate) ÷ R/R)

A positive result means: the setup has a positive expected value. A negative result means: you will lose money long-term no matter how disciplined you trade.

Evidence Edward Thorp, mathematician at MIT and later hedge fund manager, applied the Kelly Criterion first to Blackjack (1962) and later to the stock market. His fund Princeton Newport Partners delivered 19.1% annual return from 1969 to 1988 with only 3 losing quarters in 230. His practical lesson: in reality, Full-Kelly is too aggressive — the win rate is estimated, not known. Professionals use Half-Kelly or Quarter-Kelly to compensate for model errors.

🧮 R/R & Kelly Calculator

Risk / Reward
R/R Ratio
Break-Even Win Rate
Expected Value (at your win rate)
Kelly% (optimal position size)
Half-Kelly% (recommended)

Half-Kelly significantly reduces account volatility — at only ~25% less expected growth. Full Kelly is mathematically optimal but psychologically hard to sustain.

5. Диверсифікація та кореляція

Diversification & Correlation

5 tech stocks (Apple, Microsoft, Google, Meta, NVIDIA) are not diversification — they all fall together when the Nasdaq crashes. True diversification means: different asset classes, different sectors, different geographical regions.

This is what a poorly diversified portfolio (left) vs. a well diversified portfolio (right) looks like in sector view:

❌ Concentration Risk (52% Tech)
Technology · Finance · Industrials · Other
✅ Well Diversified
Technology · Finance · Healthcare · Industrials · Energy · Materials

💡 You can see your current sector allocation in sTraderZ.com under Portfolio → Sector Allocation. Make sure no single sector accounts for more than 30% of your portfolio.

Correlation measures how strongly two assets move together (+1 = perfectly positive, -1 = perfectly negative, 0 = none). Gold and bonds are typically negatively correlated with stocks → buffer in crises.

Asset PairTypical CorrelationMeaning
S&P 500 + NASDAQ~+0.95Almost always fall together
S&P 500 + Gold~−0.10 to −0.30Gold often rises when stocks fall
S&P 500 + Bonds (TLT)~−0.30 to −0.50Classic "Flight to Safety"
S&P 500 + Bitcoin~+0.40 to +0.60Risk-on asset, correlated in crises
🧠
Mindset Kills Accounts — Not Missing Strategy
Studies show: 80%+ of losses stem from emotional decisions, not bad setups.

You can have the best strategy in the world — if you abandon it during a drawdown, you lose. Trading psychology is not a soft-skill add-on, but the hardest technical part of trading.

🧠 Go to Mindset Chapter →