Part XI · Swing trading · Chapter 11N

How swing trades fail

Common failures and their remedies

Where we are

Chapters 11A to 11M built the swing-trading machinery: the regime read, the instruments, the setups, the vehicle and the expiry. This chapter catalogs how that machinery fails in use. Across the five swing setups, the four trend-based archetypes plus pre-earnings momentum, the same failure modes recur, each with a specific remedy.

What you need first

1 · Ten failures at a glance

The source numbers its ten failure modes, each with a symptom you can see, a mechanism that explains it and a remedy:

No.FailureSymptomRemedy
1Setup creepTrades that miss a required conditionCheck every condition in writing; skip if one is missing
2Holding through the time stopHolding a flat trade "to see if it works"Close at the time stop, whatever the P&L
3Stop migrationMoving the stop away "to give it room"Move stops only toward profit
4Sizing inconsistencyBigger after wins, smaller after lossesSize by the loss-budget rule, at a fixed percentage
5Skipping the exit before earningsHolding a winner into the reportClose on T-1 at the latest
6Correlated overconcentrationSeveral Mag-7 longs sized as independentOne budget for correlated positions
7Regime obliviousnessA setup taken in a regime that does not support itCheck the composite first
8Indicator stacking"Five indicators confirm this trade"One indicator per function
9A horizon mismatchAn expiry that does not fit the thesisExpiry at least 2 to 3 trading days past the horizon
10No written setup cardA trade taken from memoryReference the card and write the entry down

The rest of the chapter takes them in three groups: taking trades the framework would refuse, failing to leave when it says leave, and getting the size or the vehicle wrong. Beneath all ten sits one meta-failure, the belief that discipline appears by itself under stress.

2 · Taking trades the framework would refuse

Setup creep

Symptom, failure mode 1: taking trades that do not meet all of the setup's required conditions, because "it's close enough" or because slow weeks make you impatient. This is setup creep.

Mechanism: the framework is designed for selectivity, with each required condition added because the strategy's edge depends on it. Dropping one turns the setup from a "high-probability conditional edge" into a "weak directional bet".

Remedy: make the check physical and written, and accept that most days offer nothing.

  • The setup card must be physically present, printed, taped or copied, before you consider the trade.
  • Every required condition must be checked and confirmed in writing.
  • If checking reveals that one condition is "not quite there", skip, with no exceptions.
  • Accept that 70% to 80% of days have no qualifying setup, which is the framework working, not failing. Chapter 13C, drawn from another part of the same source, puts the share at 60% to 70% of days.
Familiar ground

A setup's conditions work like the criteria of a diagnostic rule, which setup creep loosens. Suppose 20% of the days on which a pattern appears carry a real edge. The full rule catches 80% of those days, a sensitivity of 80%, and passes 5% of the others, a specificity of 95%. Of the days it flags, 0.16/(0.16+0.04)=80%0.16/(0.16 + 0.04) = 80\% are real, its positive predictive value. Now drop one condition, supposing that sensitivity rises to 90% while specificity falls to 75%. The rule then flags 0.18+0.20=0.380.18 + 0.20 = 0.38 of days, of which only 0.18/0.38=47%0.18/0.38 = 47\% are real.

Worked example: What the loosened rule costs

Step 1: two kinds of trade. Give a trade on a real edge an expected value of +0.5R, and a trade on a false signal −0.2R. Here R is the loss planned at the stop, the unit of an R-multiple (Chapter 11H).

Step 2: the full rule. With 80% of its trades real, a trade is worth 0.8×0.5+0.2×(−0.2)=+0.360.8 \times 0.5 + 0.2 \times (-0.2) = +0.36R.

Step 3: the loosened rule. With 47% real, a trade is worth 0.47×0.5+0.53×(−0.2)=+0.130.47 \times 0.5 + 0.53 \times (-0.2) = +0.13R. Nearly twice as many trades then earn less in total, 0.38×0.13=0.050.38 \times 0.13 = 0.05R per candidate day against 0.20×0.36=0.070.20 \times 0.36 = 0.07R, before the extra trades' costs.

Regime obliviousness

Symptom, failure mode 7: taking a setup in a regime that does not support it, such as a Trend Pullback during a Stage 3 to Stage 4 transition, or pre-earnings momentum when the composite signal is +5.

Mechanism: the technical pattern looks similar regardless of regime, so without an explicit regime check the trader sees only the local geometry.

Remedy: read the regime first, and stop there if it fails.

  • The composite signal is layer 1 of the hierarchy (Chapter 11B), so check it before any setup-specific analysis.
  • Each archetype has an explicit composite threshold: +30 or more for the Trend Pullback, +20 or more for pre-earnings momentum, and so on (Chapters 11H and 11I).
  • If the composite is below the threshold, do not run the rest of the analysis, because the answer is no trade.

The conviction score of Chapter 13B shows how hard the regime bites. Its worked Trend Pullback on SPX scores 0.527, high conviction, in a calm regime with the composite at +50. The same setup scores 0.040 in a stress regime with the composite at −30, where the regime factor falls to 0.20 and execution and sizing weaken with it.

Indicator stacking

Symptom, failure mode 8: "Five indicators confirm this trade!", when the five all measure the same thing. This is multicollinearity in practice.

Mechanism: RSI(2), IBS, Bollinger %B, Williams %R and the stochastic oscillator all measure how stretched the price is relative to its recent range. When the underlying is stretched, their confluence is mathematically guaranteed, as Chapter 11C derives. The worked example below computes all five on one set of bars.

Worked example: Five readings from one down day

Step 1: the bars. Five hypothetical daily bars close at 101, 100.5, 102, 101 and 97.5. The last bar's high is 101.4 and its low 97.2, while the five bars' highest high is 102.6 and lowest low 97.2. The lookbacks are shortened to 5 bars so that the arithmetic fits on a page, where the standard ones are 14 bars for the stochastic and Williams %R and 20 for Bollinger Bands.

Step 2: the five formulas. Each indicator's formula, with its value on the last bar:

IndicatorFormulaValue
Internal bar strength(C−L)/(H−L)=0.3/4.2(C - L)/(H - L) = 0.3/4.20.07
Stochastic oscillator, 5 bars100 (C−LL)/(HH−LL)=100×0.3/5.4100\,(C - \text{LL})/(\text{HH} - \text{LL}) = 100 \times 0.3/5.45.6
Williams %R, 5 barsthe stochastic minus 100−94.4
Bollinger Bands %B, 5 bars, 2 standard deviations12+z/4\tfrac12 + z/4, with z=(97.5−100.4)/1.53=−1.90z = (97.5 - 100.4)/1.53 = -1.900.03
Relative strength index, 2 bars100 Uˉ/(Uˉ+Dˉ)100\,\bar U/(\bar U + \bar D), with Wilder smoothing8.3

Step 3: the RSI. From the four changes, −0.5, +1.5, −1 and −3.5, Wilder's 2-bar average starts with a gain of 0.75 and a loss of 0.25 from the first two, then moves halfway toward each new change. After −1 the averages are 0.375 and 0.625. After −3.5 they are 0.1875 and 2.0625, so RSI(2) is 100×0.1875/2.25=8.3100 \times 0.1875/2.25 = 8.3.

Step 4: the count. Five "oversold" readings have appeared, every one of them the position of the 97.5 close within a recent range. Williams %R is the stochastic shifted by 100, exactly.

Remedy: count functions, not readings.

  • Use one indicator per pedagogical function, as Chapter 11C sets out: one each for momentum, trend, volatility and range.
  • If you cannot say what feature of the data each indicator uniquely measures, drop the duplicates.
  • Genuine confluence is across different functions, such as momentum, trend, volatility and volume, not across reparameterizations of one.

The source is not consistent about one pair. Its setup chapter calls IBS with RSI(2) genuine confluence, while this failure mode lists the two among five measures of one quantity (Chapters 11C and 11H). Chapter 11C suggests settling it on your own data, by measuring how closely the two move together.

Trading without a written setup card

Symptom, failure mode 10: "I see a setup forming", and a trade taken without explicit reference to the setup's definition.

Mechanism: the criteria you match against are the criteria you can remember. Without an external reference, those become the criteria that conveniently match the current chart.

Remedy: read the card, then write the entry down before sending it.

  • Setup cards (Chapter 13F) must be physically referenced before every trade.
  • Write a confirmation: "Conditions A, B, C, D met: entering at $X with stop at $Y, time stop at day Z".
  • The act of writing slows the decision by 20 to 30 seconds, which is exactly long enough to catch impulse trades.
Worked example: A written entry

Step 1: the conditions. The Trend Pullback card asks for a composite of +30 or more, a confirmed Stage 2, positive dealer gamma, the VIX below 22 and below the VIX3M, and a trigger (Chapter 11H). Today the composite reads +42. Stage 2 holds, with the 30-bar SMA's ATR-normalized slope at +0.08 against the +0.05 threshold, the price above that SMA and the ADX at 23, inside the card's 20 to 30. GEX is positive, with the VIX at 15, below the VIX3M. RSI(2) is 7, below 10, on a touch of the 21-day EMA.

Step 2: the size. On a $300,000 account, 1% risk is $3,000. SPY enters at $598.40 with a stop at $594.90, so the loss-budget rule gives ⌊3,000/3.50⌋=857\lfloor 3{,}000/3.50 \rfloor = 857 shares, a notional of $512,829 or 171% of the account. That is leveraged, so check margin and gap risk before sending the order.

Step 3: the line. "Trend Pullback conditions met: entering 857 SPY at $598.40, stop $594.90, time stop at day 5."

3 · Failing to leave when the rules say leave

Holding through the time stop

Symptom, failure mode 2: the setup's time stop arrives without the profit target being hit. With the position at a small profit or a small loss, you hold "to see if it works".

Mechanism: time stops exist because, in the source's account, empirical work shows that swing setups which do not pay within their typical horizon have low forward expected value. The probability distribution of "this is a delayed winner" against "this is a slow loser" is heavily weighted toward the latter.

Bayes' rule shows why the weighting shifts: a trade still open at the time stop has already told you something about itself.

Worked example: Who is still open at the time stop

Step 1: the base rate. Suppose 60% of a setup's trades are eventually winners, and 85% of those winners have hit their target by the time stop. Of the 40% that are losers, half are still open at the time stop, the rest having hit their stops.

Step 2: the survivors. Delayed winners make 0.60×0.15=0.090.60 \times 0.15 = 0.09 of all trades, and slow losers 0.40×0.5=0.200.40 \times 0.5 = 0.20.

Step 3: the update. A trade open at the time stop is a winner with probability 0.09/(0.09+0.20)=31%0.09/(0.09 + 0.20) = 31\%. The base rate of 60% has halved, which is why the source calls the delayed winner the less likely story.

Remedy: make the time stop mechanical, and treat a new thesis as a new trade.

  • Time stops are mechanical: close at the specified day's close, regardless of P&L.
  • If you genuinely have a new thesis, such as "this is becoming a multi-week trade, not a 5-day swing", close the original position and re-enter under the new framework. Never roll the same trade forward without resetting the analysis.

Drag the share of winners paid in time toward 100% and watch the bar on the right. The green share, the chance that a trade still open is a delayed winner, falls far below the base rate.

60%
85%
50%
delayed winners = 0.60 × 0.15 = 0.090
slow losers = 0.40 × 0.50 = 0.200
P(winner | open) = 31%

More likely a slow loser. A trade open at the time stop is a winner 31% of the time, against a base rate of 60%: the wait itself is evidence against it.

What a trade still open at the time stop says about itself. The square is all of a setup's trades, split by width into eventual winners and losers, and within each column into trades resolved by the time stop and trades still open. The bar on the right takes only the open trades, the delayed winners and the slow losers, and sets the winners' share against the base rate. The two cases load the worked example and the first check question; when most winners pay early, an open trade is far less likely a winner than the base rate says.

Stop migration

Symptom, failure mode 3: the position is approaching its pre-committed stop, and you move the stop further away "to give it room". This is stop migration.

Mechanism: Loss aversion, the central finding of prospect theory, is at work. At the stop, you are psychologically drawn to avoid the realized loss by deferring it. A form of the disposition effect (Chapter 13A), stop migration converts small losses into large ones systematically.

Chapter 13D's Example 9 prices one migration: you are long 100 SPY at $580 with a stop at $575, and the price is $576.50. Kept, the stop triggers and fills at $574.20, a loss of $580. Moved to $572, it fills at $570.50, a loss of $950, which is 64% more than the plan.

Remedy: stops move one way only, and repeated migration triggers the cool-off.

  • Stops, once set, can only be moved toward profit, trailed up on winners as a trailing stop (Chapter 11E), and never away from it.
  • If you genuinely have new information, close the existing position at market and re-enter with a new analysis, rather than migrating the stop.
  • The 25% drawdown and 30-day cool-off of Chapter 13C is the structural defense when stop migration has happened repeatedly. A drawdown of 25% from peak to trough (PTP) halts all discretionary tactical trading for 30 days.

Skipping the exit before earnings

Symptom, failure mode 5: a pre-earnings momentum trade is going well and earnings approach. "Just hold through; the momentum is strong."

Mechanism: Confirmation bias combined with sunk-cost framing. The position has been profitable, so the trader projects its continuation through the binary event.

Remedy: the exit is the trade, so take it on schedule.

  • The exit-before-earnings rule is the defining discipline of the pre-earnings momentum trade (Chapter 11I).
  • Close mechanically on T-1 at the latest, the last trading day before the report, regardless of how good the trade looks.
  • Single-stock event risk requires defined-risk options, not naked equity, if the position is held through, which makes it a structurally different trade.

The arithmetic is short: a stock with an implied move of ±9% and a stop 3.5% below entry can gap through the stop on a move of ordinary size. A 9% gap against the position costs 9/3.5=2.69/3.5 = 2.6R, where the plan allowed 1R.

4 · Getting the size or the vehicle wrong

Sizing inconsistency

Symptom, failure mode 4: a larger position size after winning streaks and a smaller one after losing streaks.

Mechanism: Overconfidence after wins and loss aversion after losses push sizing in the wrong direction. The first adds risk when conditions have not changed, while the second removes it when nothing about the setup's edge has changed. If the trades are independent, a trade after three wins has the same win rate as any other, so extra size buys variance, not edge.

Remedy: size by formula, at the same percentage, whatever the recent results.

  • Position sizing is mechanical: n≤⌊Bexp/Lmax⁡⌋n \le \lfloor B_{\text{exp}}/L_{\max} \rfloor, where BexpB_{\text{exp}} is the dollar loss budget for the trade and Lmax⁡L_{\max} the loss per unit at the stop (Chapter 13C).
  • The loss budget BexpB_{\text{exp}} is the same percentage of the portfolio regardless of recent P&L.
  • Recent wins do not permit larger sizing, just as recent losses do not require smaller sizing.
  • The only legitimate changes to sizing are regime-based reductions, when the composite weakens, and the drawdown rule's kill switches.
Worked example: A fixed percentage, moving dollars

Step 1: the plan. A $300,000 account risks 1%, $3,000, with a $3 stop on SPY, so it buys ⌊3,000/3⌋=1,000\lfloor 3{,}000/3 \rfloor = 1{,}000 shares.

Step 2: after a loss and after a gain. At $270,000 the same 1% is $2,700, or 900 shares, while after a gain to $330,000 it is $3,300, or 1,100 shares.

Step 3: the point. The dollars follow the account by themselves, so there is never a reason to change the percentage by hand.

Correlated overconcentration

Symptom, failure mode 6: three Mag-7 longs running at once, sized as if independent, or three Compression Breakouts in growth stocks.

Mechanism: the setups are nominally different, but the underlying risk factor, Mag-7 momentum or growth-stock dispersion, is the same: pairwise correlations during stress can hit 0.9 or more. Three positions of equal risk at a correlation of 0.9 have a combined standard deviation of 3+6×0.9=2.9\sqrt{3 + 6 \times 0.9} = 2.9 times one position's, against 3=1.7\sqrt{3} = 1.7 times if they were independent (Chapter 11L).

Remedy: budget the factor, not the ticket.

  • Treat correlated positions as one position for risk-budget purposes.
  • The portfolio-level loss budget bounds the total, not the per-trade budget times the number of positions.
  • Cap simultaneous correlated positions, for example at two long Mag-7 swing positions at any time.

A horizon mismatch

Symptom, failure mode 9: an expiry that does not fit the thesis. Buying 7 DTE options for a 14-day swing thesis is one form, and buying 90 DTE options or LEAPS for a 3-day pivot trade is the other.

Mechanism: the option's expiry does not match the thesis horizon. Either it expires before the thesis develops, or it carries unnecessary cost for a fast resolution.

Remedy: date the vehicle from the thesis.

  • Apply the DTE matching principle of Chapter 11M, which sets each setup's expiry from its holding period.
  • Option expiration should be at least the thesis horizon plus a buffer of 2 to 3 trading days.

5 · The meta-failure: assuming discipline appears under stress

The deepest failure mode is implicit: assuming that you behave more carefully in stress than in calm. Most retail traders believe this about themselves, a belief that the source says the data systematically refute. Chapter 13A sets out the behavioral evidence behind the claim.

Discipline exists only when it is binding under stress. It is binding only when it was written down in calm. The setup cards, the kill rules, the time stops and the pre-committed exits exist as external constraints on your behavior, not as suggestions for it. The professional bias is to design the framework so that, even under maximum behavioral stress, it defaults you toward the right action. That is what discipline is: not willpower, but structural design.

Familiar ground

A trial's statistical analysis plan is written and registered before the data are unblinded. The reason is not a lack of character in the investigators: once the data are visible, everyone involved is the least reliable judge of which analysis to run. So the choice is made in advance and bound in writing. A setup card is the protocol, the time stop the prespecified endpoint, and stop migration is outcome switching.

Most swing-trade failures come not from misreading the setup but from failing to honor the framework's exits, sizing, and skip rules. The setups themselves are the easy part. The discipline to apply them is the entire game. The Dealer Mechanics Lab

In practice
  • Keep the card beside the order ticket, and write the entry line before sending the order.
  • Review every closed trade against the ten failures, tallying which ones occurred each month. A failure that recurs needs a structural fix, such as a pre-set order for the time-stop day, not a resolution to try harder.
  • After a planned loss, stop for the session, as Chapter 13F's card against revenge trading asks.
  • Put the exits in the platform. A stop order and a closing order for the time-stop day, entered with the trade, leave nothing to decide under stress.
When it fails
  • The remedies cost something. A mechanical time stop closes some delayed winners, just as a strict card skips some trades that would have worked. The worked Bayes example says why that is the right trade-off, but it is still a cost.
  • A card can go stale. Written rules encode a regime, so Chapter 13F asks for the cards to be updated on a regime change and reviewed quarterly.
  • Discipline does not create edge. The remedies only keep the framework from being undone, so if the setups have no edge, perfect discipline loses money in an orderly way.
Decision rule

Before any swing trade, in writing:

  • The regime: the composite above the setup's threshold, or no further analysis.
  • The card: every required condition checked and confirmed, with no "close enough".
  • The size: n≤⌊Bexp/Lmax⁡⌋n \le \lfloor B_{\text{exp}}/L_{\max} \rfloor at the usual percentage, and one budget for correlated positions.
  • The vehicle: shares, or an expiry at least 2 to 3 trading days past the horizon.
  • The exits: the stop, the time stop and, for pre-earnings trades, the T-1 close, all entered with the trade.

During the trade, stops move only toward profit, and a new thesis means a new trade.

Common mistake: counting confirmations

Five indicators agreeing is not five times the evidence. When they all measure how stretched the price is, they agree by construction, and the trade has one confirmation. Ask what each one measures that the others do not.

What to carry forward
  • Most swing failures are failures to honor exits, sizing and skip rules, not failures to read the setup.
  • The entry fails through setup creep, regime obliviousness, stacked indicators and trading from memory. The exit fails through ignored time stops, migrated stops and holding through earnings. The size fails through streak-driven sizing, correlated positions and mismatched expiries.
  • A trade still open at its time stop is more likely a slow loser than a delayed winner, by Bayes' rule.
  • Discipline is structural: rules written in calm that bind under stress.

6 · Check yourself

Question 1

A setup's trades win 55% of the time, and 90% of the winners pay by the time stop. At the time stop, 60% of the losers are still open. How likely is an open trade to be a delayed winner?

Answer

Delayed winners make 0.55×0.10=0.0550.55 \times 0.10 = 0.055 of all trades, and open losers 0.45×0.60=0.270.45 \times 0.60 = 0.27. An open trade is therefore a winner with probability 0.055/(0.055+0.27)=17%0.055/(0.055 + 0.27) = 17\%, against a base rate of 55%.

Question 2

You are long 200 shares at $50 with a stop at $48.50, and you move the stop to $47. What does the move do to the planned loss, if each stop fills at its level?

Answer

The planned loss is 200×1.50=$300200 \times 1.50 = \$300, while the migrated stop risks 200×3.00=$600200 \times 3.00 = \$600, double the plan. A fast market fills below either.

Question 3

After a 10% drawdown, a trader cuts the risk per trade from 1% to 0.5% "until confidence returns". Is that a legitimate change?

Answer

No: the source allows only regime-based reductions and drawdown-rule kill switches. The 1% rule already cuts the dollar size by 10% as the account falls, so the manual cut is loss aversion at work.

Question 4

Three single-stock positions each risk 1% at a pairwise correlation of 0.9. What is their combined risk as a standard deviation, and what should each risk in a 2% budget?

Answer

The combined standard deviation is 3+6×0.9=2.9\sqrt{3 + 6 \times 0.9} = 2.9 times one position's, close to the 3 of perfect correlation. Treated as one position, they share the 2% budget at 0.67% each.

Question 5

RSI(2) reads 8, IBS 0.07 and Williams %R −94 on the same day. How many independent confirmations is that?

Answer

Close to one, since all three measure where the close sits in a recent range and so move together. Chapter 11C's effective number, k/[1+(k−1)ρ]k/[1 + (k-1)\rho], gives 3/(1+2×0.9)=1.073/(1 + 2 \times 0.9) = 1.07 at a correlation of 0.9.