API Error: Your account can't receive replies from Claude right now. You can find the next step in the Anthropic Verification Portal: https://portal.anthropic.com/verify?org=51aecaa4-3870-434f-a220-d88f16e622c2

I cannot establish whether fixed stakes, uncertainty-aware Kelly, or conditional sizing improves this strategy. The dataset could not be retrieved, so no files passed SHA-256 verification and no empirical analysis was performed. A sizing recommendation would be unsupported.

The web tool returned access errors for all six requested URLs; direct Python retrieval failed with a DNS resolution error. These are access failures, not evidence that the dataset is defective.

The following is an unexecuted research specification, with mathematical calculations explicitly distinguished from dataset findings.

Coverage and missingness audit

Those five document links identify attempted sources; they are not supporting citations. I cannot honestly supply five verified citations or verbatim quotations from inaccessible material. The final citation array is therefore empty.

Once verified, construct the audit around all observed rounds, reporting both counts and denominators for:

• Valid target, outcome, forecast, index history and actionable book availability.
• Recorded unavailable/no-order states, order submission, rejection, cancellation, partial fill, full fill and unknown execution status.
• Missing or conflicting source, receive, forecast, decision, exchange-fill and label timestamps.
• Missing collateral, fee schedule, lot size, minimum notional, depth, settlement and inventory reconciliation.
• Configuration cohorts, especially the current $15 ceiling versus older limits.

Preserve explicit states separately from absent records. Missing orders establish neither deliberate abstention nor zero exposure. Multiple executions in one round must aggregate into net inventory without losing their individual costs and timestamps.

Competing explanations

These are hypotheses to test, not findings:

Volatility belongs among conditioning variables; it should not be presumed to explain losses.

Three exact candidate sizing rules

Proposed assumptions: preserve the existing entry signal, timing gates, half-edge transformation, protected-depth checks and positive-net expected-log exit policy. Their exact implementation must first be recovered from verified material. Evaluate sizing changes separately from signal changes.

Let:

• (q) be additional purchased shares, respecting actual lot and minimum-notional rules.
• (C(q)) be all-in incremental acquisition cost from executable depth and supported fees.
• (W) be known available collateral; unknown collateral blocks Kelly evaluation.
• (I) be existing inventory.
• (G(q,p)) be expected terminal log wealth under probability (p), accounting for (I), acquisition costs and supported terminal cash flows.
• (\mathcal Q(B)) be feasible quantities with (C(q)\le B), including zero.

The $15 ceiling applies to incremental all-in spending in these proposals. If verified documentation defines it as total round exposure, enforce that stricter definition instead; this remains unresolved.

1. Fixed-stake control

Use (B=$5); choose the largest feasible (q\in\mathcal Q(5)) that passes the unchanged entry gates. If minimum notional exceeds $5, record “infeasible,” not a hypothetical fill.

This is an assumed control budget, not an empirical optimum. Compare it directly with fixed $15 and with the current policy using the same opportunities.

2. Uncertainty-aware quarter-Kelly

Construct a probability interval ([p_L,p_U]) using only chronologically prior observations. Its construction and tuning must be frozen before any future holdout; an interval with unverified coverage must be labeled a sensitivity assumption.

Compute:

[ q_K=\arg\max_{q\in\mathcal Q(15)} \min_{p\in[p_L,p_U]}{G(q,p)-G(0,p)}. ]

Trade the largest feasible lot no greater than (q_K/4), only if its worst-case incremental expected log wealth is positive. Recheck costs after rounding.

This uses the existing half-edge forecast convention before uncertainty adjustment; its exact probability transformation must not be guessed. Unknown (W), inventory or required costs means not evaluable, not zero collateral.

3. Conditional fixed sizing

Using the same conservative probability interval, define net edge per dollar:

[ r(q)=\min_p\frac{\mathbb E_p[\text{incremental terminal proceeds}]-C(q)}{C(q)}. ]

Evaluate executable quantities at budgets $5 and $10:

• Use $10 if its quantity is feasible and (r(q_{10})\ge 0.10).
• Otherwise use $5 if feasible and (r(q_5)\ge 0.05).
• Otherwise choose zero.

The thresholds are assumed candidate parameters, not measured findings. They deliberately form one frozen candidate, not a grid from which to select the best historical result.

For all candidates, prohibit additional exposure when known joint inventory violates the applicable cap. Any new portfolio exposure limit is a separate proposed intervention and must be tested separately.

UNEXECUTED PSEUDOCODE

verify manifest structure
for every file listed in manifest:
    fetch exact bytes
    require SHA256(bytes) == listed digest
require every analysis input is manifest-listed
stop on mismatch, absent file, or ambiguous manifest entry

parse verified dictionary and cohort configurations
reconcile raw and CSV records; retain disagreement flags

for round in all_observed_rounds ordered chronologically:
    retain recorded unavailable/no-order/unfilled/unknown states

    for decision opportunity supported by records:
        context = information received by decision_time only
        require source_time <= receive_time <= decision_time
        keep forecast and label availability clocks separate
        do not replace exchange_fill_time with intent/state time

        reconstruct trailing volatility using eligible prior ticks
        reconstruct existing inventory from supported fills
        evaluate unchanged entry gates under original cohort rules

        for sizing_policy in [fixed_5, robust_quarter_kelly, conditional]:
            compute feasible quantity using lots, fees and depth
            retain unknown/infeasible/no-order separately
            simulate execution under declared fill assumptions
            apply unchanged supported exit policy

    reconcile settlements, cash flows, fees and ending inventory
    append chronological results, coverage and unresolved fields

A historical book replay cannot establish that an unsubmitted order would have filled. Report such results as simulated, with fill assumptions, rather than measured trading performance.

Matched baseline, exposure and stress comparisons

Report observed baseline accounting separately from replayed baseline and candidate simulations. First establish whether the observed baseline is profitable after supported costs; do not assume it is.

Run two complementary comparisons:

1. Sizing-only: identical reconstructable entry opportunities and the same exit algorithm for every policy. Differences isolate sizing and its inventory-dependent consequences.
2. Full-policy: retain abstentions caused by each rule, with results over all observed rounds. This captures the combined sizing/selection effect.

For both, present:

Normalize using prior calibration data or clearly label an ex-post normalization as descriptive. Report overlap-only results alongside whole-window results so unmatched opportunities remain visible.

Derived illustration, not dataset evidence: if a $5 trade earns $0.10 net per dollar, expected profit is $0.50. A $15 trade at the identical edge earns $1.50. The extra dollar profit demonstrates exposure, not improved edge.

Report net profit, profit per dollar spent, maximum concurrent capital, terminal log-wealth change where wealth is known, drawdown and worst chronological loss cluster. Unknown starting collateral precludes measured Kelly fractions and account-level log growth.

Proposed stress grid; unexecuted:

• Supported fee schedule, then incremental cost penalties of 1 and 2 cents per share.
• Visible executable depth at 100%, 50% and 25%.
• Additional execution delays of 0, 250 and 1,000 milliseconds.
• No fill versus feasible partial fill for unsupported counterfactual execution.
• Settlement-only valuation where no supported contract exit quote exists.

Recompute quantities under every stress: costs and reduced depth can change feasibility. Never use BTC index prices as contract liquidation proceeds.

Downside, concentration and falsification

Measure chronological account exposure and overlapping inventory before calculating portfolio losses. Preserve dependence across related rounds; do not treat 237 executions as 237 independent observations.

Report the worst round, worst hour, longest loss run, peak concurrent exposure, and the contribution of the largest one, three and five gains and losses. Define session boundaries before examining outcomes; show both hourly and broader contiguous blocks. The single supplied 24-hour window cannot by itself establish repeatability across days.

Missing collateral prevents an observed ruin probability or reliable account-level drawdown percentage. Missing fills or exits should produce explicit accounting bounds where possible, otherwise “unresolved.”

Strongest falsification: freeze the uncertainty method and all three rules, then compare against the unchanged baseline on a local, fixed future holdout. Use identical clocks, execution assumptions, capital and costs. Reject the sizing-improvement claim if its advantage disappears under equal-risk/equal-capital comparison, depends on unsupported fills, or comes chiefly from one concentrated episode. Passing this check would still require reporting uncertainty; no significance claim is justified here.

Ranked missing-data requests

1. Retrievable immutable manifest and all listed bytes, including the four introductory documents. This is the prerequisite for any dataset finding.
2. Exchange execution evidence: order IDs, fills, partial fills, cancellations, exchange timestamps, quantities, prices, fees and settlement cash flows.
3. Collateral and inventory ledger: available funds, commitments, existing positions, and the precise scope of the $15 cap.
4. Decision-time information: source/receive/forecast/decision clocks, clock offsets, book availability and recorded no-order/unavailable reasons.
5. Exact strategy and cohort configuration: half-edge transformation, Kelly computation, timing semantics, depth protection, fees, lot/notional rules and exit implementation.
6. Chronologically prior calibration data and a sealed local future holdout, with fixed boundaries and evaluation rules.

No measured sizing winner, profitability estimate, stress result or statistical test is available from this attempt. No orders, installs or live changes were made.

There is no verified basis here to conclude that changing stake size improves Madame Gila’s returns—or that its baseline has positive net edge. Under the $15 ceiling, the useful comparison is fixed stakes versus uncertainty-aware Kelly versus conditional sizing, with capital and risk matched so larger bets cannot masquerade as better predictions.

Access limitation: I attempted the four requested documents, dataset root and manifest through the web tool; none was retrievable. Direct HTTPS requests also failed with a DNS-resolution error. Consequently, zero files were downloaded or hash-verified, and no dataset analysis or simulation was executed.

The counts and model description below are user-reported, unverified. All proposed rules, thresholds and tests are assumptions or unexecuted specifications. I cannot provide five verified citations or verbatim source quotations without accessing the sources; the final citation list is deliberately empty.

Coverage and missingness audit

Do not divide 237 by 289 and call the result a trading or fill rate. Executions and rounds are different units; a round can contain multiple fills, and execution records may need reconciliation.

A completed audit should start from every observed round, then distinguish:

• Explicitly unavailable opportunities, with recorded reasons.
• Available opportunities with an explicit no-order decision.
• Orders attempted but rejected, canceled, expired or unfilled.
• Partial and complete fills.
• Missing decision/order telemetry: unknown, not a deliberate skip.
• Open inventory, settled inventory and unresolved outcomes.

Report field missingness and join failures by round, policy cohort, side and time block. Missing labels must remain visible in denominators; unresolved inventory must not silently receive zero P&L.

For integrity, hash the original bytes of every manifest-listed file, including both raw and flattened representations, before parsing for analysis. Audit raw/CSV agreement afterward; they are alternate representations, not independent observations. The manifest supplies the requested checksum reference; without an independently pinned manifest hash, it does not independently authenticate itself.

Competing explanations to test

These are hypotheses, not findings.

Volatility is only one candidate explanation. A forecast can improve without becoming tradable, and sizing can improve dollar profit while worsening risk-adjusted performance.

Three exact candidate rules

These are proposed research rules, not recommended live changes. Apply them only to the current $15 cohort; preserve the existing side-selection, timing and protected execution checks. Preserve the actual implementation’s clock convention for “earliest entry 45s”; that wording alone is insufficient to reconstruct its predicate.

Let:

• (p_0): existing forecast for the selected side.
• (q): a supported quantity, respecting actual lot and minimum-notional constraints.
• (C(q)): all-in entry cash outlay from eligible ask depth, including fees.
• (P(q)): net winning payout after applicable settlement charges.
• (W): recorded available collateral.
• (R(q)=P(q)-C(q)) on a win and (-C(q)) on a loss.

For known (W), expected incremental log wealth is

[ G(q,p)=p\log!\left(1+\frac{P(q)-C(q)}{W}\right) +(1-p)\log!\left(1-\frac{C(q)}{W}\right). ]

Exclude quantities with undefined logarithms, unsupported depth or (C(q)>$15). This assumes the loss on that position is limited to its entry outlay; actual contract accounting must confirm that assumption.

1. Fixed $5 control.
On each baseline-qualified opportunity, choose the largest supported quantity with (C(q)\le $5). If the minimum order exceeds the budget, record “minimum-size infeasible.” This provides a probability-independent sizing control. Treat $1, $10 and $15 as prespecified sensitivity budgets within this same rule family.

2. Uncertainty-aware quarter Kelly.
Construct a lower probability bound (p_L) from a calibration procedure frozen before the evaluation period. For example: fixed forecast bins of width 0.10, calibration restricted to prior labeled observations, and a 10th-percentile lower bound from resampling contiguous one-hour blocks. Require at least 100 observations in the relevant bin; otherwise mark the rule unavailable.

Find the feasible quantity maximizing (G(q,p_L)). If its maximum is nonpositive, assign zero. Otherwise allocate one quarter of that optimum’s all-in outlay and round down to a supported quantity. The bin width, confidence percentile, block length and minimum count are assumed research settings, not validated choices.

Missing (W) makes this Kelly calculation unresolved. A hypothetical bankroll can be used only in a separately labeled simulation.

3. Conditional fixed stakes.
Using the same frozen (p_L), find the feasible $5 quantity and calculate robust expected net return per entry dollar:

[ e_L=\frac{p_LP(q)-C(q)}{C(q)}. ]

Assign a target budget of:

• $0 when (e_L\le0);
• $5 when (0<e_L<0.03);
• $10 when (0.03\le e_L<0.06);
• $15 when (e_L\ge0.06).

Recompute depth and fees at the assigned size. Reduce the budget through $15, $10, $5, $0 until the larger quantity satisfies its corresponding edge threshold. The 3% and 6% thresholds are assumed, and must not be chosen after seeing this window’s outcomes.

Common pseudocode:

for round in all_observed_rounds:
    retain round even if decision, order, quote or label is missing
    cohort = policy_version_effective_at_decision

    for recorded decision in chronological availability order:
        inputs = records received no later than decision time
        require forecast inputs available before forecast creation
        never use future labels in features or calibration

        classify observed availability/order/fill state
        if baseline opportunity cannot be reconstructed:
            record UNKNOWN; continue

        if cohort != CURRENT_15_DOLLAR_COHORT:
            analyze separately; continue

        if baseline timing/side/protection checks fail:
            record explicit reason; continue

        q = candidate_rule(inputs, recorded_collateral)
        check actual lots, minimum notional, depth, fees and capital

        if counterfactual execution cannot be supported:
            record EXECUTION_UNRESOLVED
        else:
            simulate under declared fill assumptions

    reconcile actual fills, exits, settlements and remaining inventory

“Recorded decision” is intentional: do not invent a complete decision grid or interpret absent orders as deliberate skips.

Matched baseline, capital and risk comparisons

No results were computed. A valid replay needs four complementary comparisons:

1. Matched opportunities: identical decision timestamps, sides, eligibility and exit logic; vary sizing only. Report both the common reconstructable subset and how much of the full round universe it excludes.
2. Equal committed dollars: fit candidate stake multipliers on a prior development period to match baseline mean all-in outlay, then freeze them. On evaluation data, report realized exposure differences.
3. Equal downside budget: separately match a prespecified loss-risk measure on development data, such as empirical one-hour expected shortfall. Freeze scaling before evaluation.
4. Equal capital: same starting bankroll and collateral availability path. Charge open positions against available capital until proceeds become available; model overlapping positions jointly.

Matching committed dollars does not necessarily match loss risk. Neither retrospective rescaling nor a hypothetical bankroll should be presented as an executable historical result.

Separate the effects using:

• Selection: constant stake on each strategy’s selected opportunities.
• Sizing: different stakes on the same opportunities.
• Total policy: selection and sizing together.

Report gross payoff, fees, slippage, net P&L, net return per entry dollar, peak committed capital and log wealth only where collateral supports it. Describe the existing “half-edge quarter-Kelly” baseline from its actual code or recorded sizing fields; the phrase alone is insufficient to reproduce it.

Cost, depth, inventory and downside stress

The following are assumed sensitivity scenarios, not estimates of actual execution costs:

• Observed fees, then fees multiplied by 1.25 and 1.50.
• Additional adverse price movement of one and two actual contract ticks.
• Available displayed depth reduced to 75% and 50%.
• Execution delayed by 250 ms and 1 second, using the next eligible observed book. Missing coverage becomes unresolved rather than an assumed fill.
• Settlement-only results alongside faithfully reconstructed baseline early exits.

An intent timestamp or state update is not an exchange fill timestamp. A larger counterfactual order cannot inherit the recorded small order’s fill automatically.

Maintain inventory by contract and side from confirmed fills. Apply partial fills, entry/exit fees and settlement proceeds to the remaining quantity. Opposite-side holdings can be netted economically only where contract settlement mechanics support it.

BTC index prices cannot price contract exits. Simulated exits need eligible prediction-contract bids and depth; preserve the baseline’s positive-net expected-log exit requirement. If exit quotes are unavailable, report settlement-only simulation and mark baseline-exit replay unresolved.

Downside reporting should include:

• Chronological drawdown, worst loss streak and peak concurrent capital.
• Worst one-hour and four-hour losses; tail averages labeled descriptive when samples are small.
• Profit and exposure concentration in the largest five rounds and each hour.
• Side concentration, adjacent-round exposure and overlapping inventory.
• Leave-one-contiguous-four-hour-block-out results and removal of the five largest positive contributors.
• Joint losses under common forecast error; do not assume individual Kelly positions are independent.

Resampling must preserve temporal dependence. A single reported 24-hour window cannot establish stability across market regimes; no significance claim is justified here.

Strongest falsification and missing-data priorities

Strongest proposed falsification: freeze calibration, thresholds, sizing and cost assumptions locally before a future fixed holdout. Compare the candidates with the existing baseline and fixed stakes at matched capital and prespecified downside risk. The sizing hypothesis is undermined if:

• Its gain disappears when exposure is matched;
• Larger prescribed stakes do not correspond to better subsequent net returns;
• Its advantage depends on one short time block;
• Plausible cost/depth stress removes the advantage.

Failure would challenge the sizing claim; it would not identify volatility as the cause.

Ranked requests:

1. Accessible immutable dataset and manifest, preferably with an independently supplied manifest checksum. This is the immediate prerequisite for any measured answer.
2. Clock and identity linkage: source/receive/forecast/decision timestamps, feature provenance, order IDs, exchange acknowledgments, partial fills and settlement IDs.
3. Collateral and policy history: available balance, reserved capital, concurrent inventory, cap changes and exact sizing implementation.
4. Executable contract data: both sides’ books, fees/rebates, lot sizes, minimum notionals, tick sizes and exit depth.
5. All-round decision telemetry: explicit unavailable/no-order reasons, attempts, rejections, cancellations, unfilled states and missing-label reasons.
6. Prior calibration data and a fixed future holdout protocol, retained locally, with sufficient history to assess uncertainty and temporal dependence.

The present deliverable is an unexecuted research specification. Dataset coverage, baseline profitability, equal-risk performance and the preferred sizing rule all remain unresolved.