How Much Money You Suppose Risk Per One Trade

How much you suppose risk per trade? Di answer wey dey hold water for small account na fixed fraction: pick one small percent of your account, like 1%, and make dat amount be di most wey you ready lose if di trade turn against you. After you pick am, position size no be feeling again. You divide di money you ready lose by di distance between your entry and your stop, and di arithmetic go tell you how many share to buy.

Di arithmetic: how much you suppose risk per trade

Two line, nothing pass dat.

• Risk per trade = account balance x r, where r na di percent you choose.
• Position size = risk per trade / (entry price minus stop price).

Di first line concern your money alone. Di second one concern di chart. Stop na di price wey you don decide before you even enter say if market reach there, you comot, no argument. If stop no dey, di second line no get bottom, and "how much I dey risk" quietly turn to "everything I get".

Notice say two different thing dey inside here. Di money you RISK dey small. Di money wey ENTER di trade fit big. Plenty beginner mix di two, and na there confusion dey start.

Make we do am for naira

Say your broker app account carry ₦450,000. You pick r = 1%, so your risk per trade na ₦4,500. For di arithmetic we go use ₦1,500 to one dollar as round example figure, no be quote, use wetin your own app show you. ₦4,500 na about $3.

You see one US share wey dey trade for $50, and you decide say your stop go sit for $48. Distance na $2 for every share. $3 divided by $2 na 1.5 share. Di whole position na 1.5 x $50 = $75, wey be ₦112,500. So you risk 1% of di account, but 25% of di account enter di trade. Dat gap na normal, and e worth watching: too much money inside one name na different risk from di stop risk.

Second run, smaller account. ₦180,000, still 1% risk, so ₦1,800, wey be $1.20. Dis time di share dey $120 and your stop dey $117.60, 2% away, so di distance na $2.40. $1.20 divided by $2.40 na 0.5 share. Position value na $60, about ₦90,000, half of di account inside one trade. Same 1% risk, completely different position weight, and di only thing wey change na how far di stop sit from entry.

Now do di same thing with 5%. ₦450,000 x 5% = ₦22,500, about $15. With di same $2 stop distance, size na 7.5 share, and 7.5 x $50 = $375, wey be ₦562,500. Di account na ₦450,000. Di arithmetic dey ask you for money wey no dey there. To squeeze di 5% inside, you go either drag di stop far far away from entry or borrow, and either one turn di trade into another trade entirely.

Wetin one ordinary session dey cost

Before you argue about r, look wetin one plain day dey do to one liquid name. Di panel below bucket five years of AAPL daily moves by size, no direction, just how far di close waka from di day before.

SELECT
    multiIf(move_pct < 0.5, '1. under 0.5%',
            move_pct < 1.0, '2. 0.5% to 1%',
            move_pct < 2.0, '3. 1% to 2%',
            move_pct < 3.0, '4. 2% to 3%',
            move_pct < 5.0, '5. 3% to 5%',
                            '6. over 5%')          AS move_bucket,
    count()                                        AS sessions,
    round(100 * count() / sum(count()) OVER (), 1)  AS share_pct
FROM
(
    SELECT abs(100 * (c / prev_c - 1)) AS move_pct
    FROM
    (
        SELECT
            toFloat64(close) AS c,
            lagInFrame(toFloat64(close)) OVER (ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_c
        FROM global_markets.stocks_daily_aggs
        WHERE ticker = 'AAPL'
          AND date >= '2021-09-01'
          AND date <  '2026-09-01'
    )
    WHERE prev_c > 0
)
GROUP BY move_bucket
ORDER BY move_bucket

Most session quiet: 30.4% of di days move under 0.5%. Di big ones no too common, but dem dey show face. 16 session, 1.3% of di five years, waka pass 5% in one day. Any stop wey you place tighter than di everyday noise go get touched by noise alone, not by your idea being wrong.

So how tight na too tight? Di next panel give di middle daily move and di 90th percentile move for five names people dey trade.

SELECT
    ticker,
    round(quantileDeterministic(0.5)(move_pct, day_key), 2) AS median_move_pct,
    round(quantileDeterministic(0.9)(move_pct, day_key), 2) AS p90_move_pct
FROM
(
    SELECT
        ticker,
        toUInt32(date)                                            AS day_key,
        abs(100 * (toFloat64(close) / toFloat64(prev_close) - 1))  AS move_pct
    FROM
    (
        SELECT
            ticker,
            date,
            close,
            lagInFrame(close) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO')
          AND date >= '2021-09-01'
          AND date <  '2026-09-01'
    )
    WHERE toFloat64(prev_close) > 0
)
GROUP BY ticker
ORDER BY median_move_pct DESC

NVDA carry di widest middle move for di group, 1.85% on a typical day, and one day out of ten e waka 5.12% or more. SPY sit for di other end with 0.57%. Same 1% rule, same account, but di share count wey come out for each name go differ well well, since di distance to a sensible stop no be di same for both. For calmer names, see di quietest big US stocks.

1% versus 5% wen loss dey follow each other

Loss no dey line up one by one for orderly queue. Dem dey cluster. Di panel below count di longest run of back to back down days for each name over ten years, plus how many run of four or more dem get.

SELECT
    ticker,
    max(run_len)          AS longest_losing_run,
    countIf(run_len >= 4) AS runs_of_4_or_more
FROM
(
    SELECT
        ticker,
        grp,
        count() AS run_len
    FROM
    (
        SELECT
            ticker,
            down,
            sum(if(down = 0, 1, 0)) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS grp
        FROM
        (
            SELECT
                ticker,
                date,
                if(toFloat64(close) < toFloat64(prev_close), 1, 0) AS down
            FROM
            (
                SELECT
                    ticker,
                    date,
                    close,
                    lagInFrame(close) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close
                FROM global_markets.stocks_daily_aggs
                WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO')
                  AND date >= '2016-09-01'
                  AND date <  '2026-09-01'
            )
            WHERE toFloat64(prev_close) > 0
        )
    )
    WHERE down = 1
    GROUP BY ticker, grp
)
GROUP BY ticker
ORDER BY longest_losing_run DESC

KO carry di longest run for di group: 8 down days back to back, with 69 separate runs of four or more inside di ten years. Down day no be di same thing as losing trade, your entry and your stop dey settle dat. Wetin di panel dey show na di shape: runs dey happen, and dem dey happen often enough for you to plan for dem.

Chain am with di r you pick. Eight losses back to back, each one full r, na plain compounding.

• At 1%: 0.99 to power 8 na 0.923, so di account dey down about 7.7%. Annoying, still alive.
• At 5%: 0.95 to power 8 na 0.663, so di account dey down about 34%. To climb back from 34% down, you need about 51% gain on wetin remain.

Dat na di whole argument in one place. Eight losses in a row no be rare event for any strategy wey win about half di time, and maximum drawdown na di number wey dey tell you whether your plan fit sit through am.

Wetin di option market dey price for di next move

Past days no be di only guide. Implied volatility, IV for short, na di yearly movement wey option prices dey imply for a stock. Divide am by di square root of 252, di number of trading days in one year, and you get di one day move di option market dey carry. Di panel track near di money AAPL contracts wey still get 20 to 45 days before expiry.

SELECT
    toString(month_start)                                   AS month,
    formatDateTime(month_start, '%b %Y')                    AS month_label,
    round(100 * avg(implied_volatility), 1)                 AS atm_iv_pct,
    round(100 * avg(implied_volatility) / sqrt(252), 2)     AS one_day_move_pct
FROM
(
    SELECT
        toStartOfMonth(date) AS month_start,
        implied_volatility
    FROM global_markets.options_greeks
    WHERE underlying_symbol = 'AAPL'
      AND date >= '2024-09-01'
      AND date <  '2026-09-01'
      AND iv_converged = 1
      AND volume > 0
      AND days_to_expiry BETWEEN 20 AND 45
      AND abs(toFloat64(strike_price) / toFloat64(underlying_close) - 1) < 0.05
)
GROUP BY month_start
ORDER BY month_start

For Aug 2026, di average near di money IV land 24.7%, wey work out to about 1.56% for a single day. If your stop sit inside dat figure, di option market dey already price say one ordinary session fit touch am.

Two thing wey concern account wey naira dey fund

First, FX. Your broker account dey count dollar, but your head dey count naira, and di naira value of your risk budget dey move even wen di trade no move at all. Di $300 account wey be ₦450,000 at ₦1,500 na ₦495,000 at ₦1,650, and di ₦4,500 wey you first call 1% na $2.73 now instead of $3. Cleanest way: set r for di currency wey di account dey hold, then convert for your own record. If you fix r in naira, your rule dey shift every time di rate shift.

Second, fractional share. Di 1% rule dey ask you to buy part of a share plenty times at small size. Without fractional share, di smallest thing you fit buy na one whole share, and one $120 share na ₦180,000, di entire small account. Fractional share na wetin make dis arithmetic possible at all for dis size. Confirm say your app support am before you plan around am, some no support.

Wen you go want pass fixed percent

Fixed fraction na di entry level, and e dey serve plenty people fine. Two next step dey. Kelly criterion position sizing dey work r out from your edge and win rate instead of you picking am by hand. Volatility targeting dey move your size up and down as di name calm down or wild. Each one get im own post.

FAQ

How much money I suppose risk per trade as beginner?

Di common entry level range na 0.5% to 2% of di account for one trade, with 1% as di popular middle. Wetin matter pass di exact number na say you pick one, write am down, and make every position size come out of am.

Na 1% of di whole account or 1% of di trade?

1% of di whole account. Di money wey enter di trade fit reach 25% or even 50% of di account. Di 1% na how much of di account go disappear if price reach your stop.

Wetin happen if I no put stop loss?

Di position size formula lose im bottom. Without a stop, di distance to your exit no dey known, so "risk per trade" no fit be calculated at all, and di real risk na di full position value.

How many losing trade 5% risk fit survive?

Eight straight losses at 5% each leave di account about 34% down, and e need about 51% gain on di remainder to return. Di same eight at 1% leave am about 7.7% down.

Fractional share dey compulsory for di 1% rule?

For small account wey dey trade US shares, e near compulsory. One whole share of a $120 name fit swallow a ₦180,000 account by itself, while 0.25 share fit sit inside a 1% budget.

Every panel here carry di exact SQL under am, open any one and check how we count. To run di same count for di ticker wey you dey watch, ask am in plain English on di Strasmore terminal.