Depth-at-Distance Profile

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export type JsonObject = Record<string, any>;

function numberValue(name: string, value: unknown, options: {positive?: boolean; nonnegative?: boolean} = {}): number {
  if (typeof value !== "number" || !Number.isFinite(value)) throw new TypeError(`${name} must be a finite number`);
  if (options.positive && value <= 0) throw new RangeError(`${name} must be positive`);
  if (options.nonnegative && value < 0) throw new RangeError(`${name} must be nonnegative`);
  return value;
}

function integerValue(name: string, value: unknown, positive = false): number {
  const result = numberValue(name, value);
  if (!Number.isInteger(result)) throw new RangeError(`${name} must be an integer`);
  if (positive && result <= 0) throw new RangeError(`${name} must be positive`);
  return result;
}

type Level = {price: number; quantity: number};

function levels(raw: unknown, side: "bid" | "ask"): Level[] {
  if (!Array.isArray(raw) || raw.length === 0) throw new RangeError(`${side}s must be a non-empty list`);
  const seen = new Set<number>();
  const result = raw.map((item, index) => {
    if (!item || typeof item !== "object") throw new TypeError(`${side}s[${index}] must be an object`);
    const row = item as JsonObject;
    const price = numberValue(`${side}s[${index}].price`, row.price, {positive: true});
    const quantity = numberValue(`${side}s[${index}].quantity`, row.quantity, {positive: true});
    if (seen.has(price)) throw new RangeError(`${side} prices must be unique aggregated levels`);
    seen.add(price);
    return {price, quantity};
  });
  for (let index = 1; index < result.length; index += 1) {
    if (side === "bid" && result[index - 1].price <= result[index].price) throw new RangeError("bids must be strictly descending from best price");
    if (side === "ask" && result[index - 1].price >= result[index].price) throw new RangeError("asks must be strictly ascending from best price");
  }
  return result;
}

function book(bidsRaw: unknown, asksRaw: unknown): [Level[], Level[]] {
  const bids = levels(bidsRaw, "bid"), asks = levels(asksRaw, "ask");
  if (bids[0].price >= asks[0].price) throw new RangeError("visible book must be uncrossed");
  return [bids, asks];
}

function tickDistance(price: number, best: number, tick: number, side: "bid" | "ask"): number {
  const raw = side === "bid" ? (best - price) / tick : (price - best) / tick;
  const rounded = Math.round(raw);
  if (Math.abs(raw - rounded) > 1e-7) throw new RangeError("price is not aligned to the declared tick grid");
  return rounded;
}

export function cumulativeDepth(bidsRaw: unknown, asksRaw: unknown, tickRaw: unknown): JsonObject {
  const [bids, asks] = book(bidsRaw, asksRaw);
  const tick = numberValue("tick_size", tickRaw, {positive: true});
  const rows = (sideLevels: Level[], side: "bid" | "ask") => {
    let cumulative = 0;
    const best = sideLevels[0].price;
    return sideLevels.map(level => {
      cumulative += level.quantity;
      return {price: level.price, quantity: level.quantity, distance_ticks: tickDistance(level.price, best, tick, side), cumulative_quantity: cumulative};
    });
  };
  const bidRows = rows(bids, "bid"), askRows = rows(asks, "ask");
  const spreadRaw = (asks[0].price - bids[0].price) / tick, spreadTicks = Math.round(spreadRaw);
  if (Math.abs(spreadRaw - spreadTicks) > 1e-7) throw new RangeError("spread is not aligned to the declared tick grid");
  const bidTotal = bidRows[bidRows.length - 1].cumulative_quantity, askTotal = askRows[askRows.length - 1].cumulative_quantity;
  return {model: "visible-cumulative-depth", best_bid: bids[0].price, best_ask: asks[0].price, tick_size: tick, spread_ticks: spreadTicks, bid_levels: bidRows, ask_levels: askRows, total_bid_depth: bidTotal, total_ask_depth: askTotal, state: bidTotal > askTotal ? "bid-deeper" : bidTotal < askTotal ? "ask-deeper" : "balanced"};
}

export function topNDepthImbalance(bidsRaw: unknown, asksRaw: unknown, nRaw: unknown, thresholdRaw: unknown = 0.1): JsonObject {
  const [bids, asks] = book(bidsRaw, asksRaw);
  const n = integerValue("n", nRaw, true), threshold = numberValue("threshold", thresholdRaw, {nonnegative: true});
  if (threshold > 1) throw new RangeError("threshold must not exceed one");
  if (bids.length < n || asks.length < n) throw new RangeError("both sides must contain at least n visible levels");
  const bidDepth = bids.slice(0, n).reduce((sum, row) => sum + row.quantity, 0);
  const askDepth = asks.slice(0, n).reduce((sum, row) => sum + row.quantity, 0);
  const total = bidDepth + askDepth, imbalance = (bidDepth - askDepth) / total;
  return {model: "top-n-visible-depth-imbalance", n, bid_depth: bidDepth, ask_depth: askDepth, total_depth: total, imbalance, threshold, state: imbalance > threshold ? "bid-heavy" : imbalance < -threshold ? "ask-heavy" : "balanced-band", complete_window: true};
}

export function depthAtDistanceProfile(bidsRaw: unknown, asksRaw: unknown, tickRaw: unknown, maxRaw: unknown): JsonObject {
  const [bids, asks] = book(bidsRaw, asksRaw);
  const tick = numberValue("tick_size", tickRaw, {positive: true}), maximum = integerValue("max_distance_ticks", maxRaw);
  if (maximum < 0) throw new RangeError("max_distance_ticks must be nonnegative");
  const profile = (sideLevels: Level[], side: "bid" | "ask") => {
    const best = sideLevels[0].price, byDistance = new Map<number, number>();
    sideLevels.forEach(level => byDistance.set(tickDistance(level.price, best, tick, side), level.quantity));
    let included = 0;
    for (let d = 0; d <= maximum; d += 1) included += byDistance.get(d) ?? 0;
    let cumulative = 0;
    return Array.from({length: maximum + 1}, (_, distance) => {
      const quantity = byDistance.get(distance) ?? 0; cumulative += quantity;
      return {distance_ticks: distance, quantity, cumulative_quantity: cumulative, depth_share: included ? quantity / included : 0};
    });
  };
  const bidProfile = profile(bids, "bid"), askProfile = profile(asks, "ask");
  const bidTotal = bidProfile[bidProfile.length - 1].cumulative_quantity, askTotal = askProfile[askProfile.length - 1].cumulative_quantity;
  return {model: "same-side-best-tick-distance-profile", tick_size: tick, max_distance_ticks: maximum, bid_profile: bidProfile, ask_profile: askProfile, included_bid_depth: bidTotal, included_ask_depth: askTotal, state: bidTotal > askTotal ? "bid-profile-heavier" : askTotal > bidTotal ? "ask-profile-heavier" : "profile-balanced"};
}

function sweep(bidsRaw: unknown, asksRaw: unknown, sideRaw: unknown, quantityRaw: unknown, limitRaw: unknown): JsonObject {
  const [bids, asks] = book(bidsRaw, asksRaw);
  if (sideRaw !== "buy" && sideRaw !== "sell") throw new RangeError("side must be buy or sell");
  const side = sideRaw, requested = numberValue("quantity", quantityRaw, {positive: true});
  const limit = limitRaw == null ? null : numberValue("limit_price", limitRaw, {positive: true});
  const sideLevels = side === "buy" ? asks : bids;
  let remaining = requested, notional = 0;
  const fills: JsonObject[] = [];
  for (let index = 0; index < sideLevels.length && remaining > 1e-12; index += 1) {
    const level = sideLevels[index];
    if (limit != null && (side === "buy" ? level.price > limit : level.price < limit)) break;
    const fillQuantity = Math.min(remaining, level.quantity);
    fills.push({level_index: index, price: level.price, quantity: fillQuantity, notional: fillQuantity * level.price});
    notional += fillQuantity * level.price; remaining -= fillQuantity;
  }
  if (remaining <= 1e-12) remaining = 0;
  const filled = requested - remaining, partialVwap = filled ? notional / filled : null;
  return {side, requested_quantity: requested, filled_quantity: filled, unfilled_quantity: remaining, full_fill: remaining === 0, fills, fill_notional: notional, partial_vwap: partialVwap, worst_fill_price: fills.length ? fills[fills.length - 1].price : null, best_bid: bids[0].price, best_ask: asks[0].price, midpoint: (bids[0].price + asks[0].price) / 2};
}

export function expectedFillPrice(bids: unknown, asks: unknown, side: unknown, quantity: unknown, limitPrice: unknown = null): JsonObject {
  const result = sweep(bids, asks, side, quantity, limitPrice);
  return {model: "deterministic-visible-book-fill-estimate", ...result, expected_fill_price: result.full_fill ? result.partial_vwap : null, state: result.full_fill ? "full-fill" : result.filled_quantity ? "partial-fill" : "unfilled"};
}

export function sweepCostAndSlippage(bids: unknown, asks: unknown, side: unknown, quantity: unknown, benchmarkRaw: unknown = "midpoint", benchmarkPriceRaw: unknown = null, limitPrice: unknown = null): JsonObject {
  const result = sweep(bids, asks, side, quantity, limitPrice);
  if (!["midpoint", "best-quote", "explicit"].includes(String(benchmarkRaw))) throw new RangeError("benchmark must be midpoint, best-quote, or explicit");
  const benchmark = String(benchmarkRaw);
  const reference = benchmark === "midpoint" ? result.midpoint : benchmark === "best-quote" ? (side === "buy" ? result.best_ask : result.best_bid) : numberValue("benchmark_price", benchmarkPriceRaw, {positive: true});
  const vwap = result.partial_vwap, direction = side === "buy" ? 1 : -1;
  const slippagePrice = vwap == null ? null : direction * (vwap - reference);
  const slippageBps = slippagePrice == null ? null : slippagePrice / reference * 10_000;
  return {model: "visible-book-sweep-cost", ...result, benchmark, benchmark_price: reference, sweep_vwap: vwap, signed_slippage_price: slippagePrice, signed_slippage_bps: slippageBps, total_slippage_cost: slippagePrice == null ? null : slippagePrice * result.filled_quantity, state: result.full_fill ? "full-sweep" : result.filled_quantity ? "partial-sweep" : "unfilled"};
}

function median(values: number[]): number {
  const sorted = [...values].sort((a, b) => a - b), middle = Math.floor(sorted.length / 2);
  return sorted.length % 2 ? sorted[middle] : (sorted[middle - 1] + sorted[middle]) / 2;
}

export function liquidityWallConcentration(levelsRaw: unknown, multipleRaw: unknown = 2, minShareRaw: unknown = 0.25, thresholdRaw: unknown = 0.30): JsonObject {
  const parsed = levels(levelsRaw, "ask");
  const multiple = numberValue("wall_multiple", multipleRaw, {positive: true});
  const minShare = numberValue("minimum_share", minShareRaw, {nonnegative: true});
  const threshold = numberValue("concentration_threshold", thresholdRaw, {nonnegative: true});
  if (minShare > 1 || threshold > 1) throw new RangeError("share thresholds must not exceed one");
  const quantities = parsed.map(row => row.quantity), total = quantities.reduce((a, b) => a + b, 0), med = median(quantities);
  const shares = quantities.map(value => value / total), hhi = shares.reduce((sum, value) => sum + value * value, 0);
  const walls = parsed.map((level, index) => ({level_index: index, price: level.price, quantity: level.quantity, depth_share: shares[index], median_multiple: level.quantity / med})).filter(row => row.quantity >= multiple * med && row.depth_share >= minShare);
  let largestIndex = 0; quantities.forEach((value, index) => { if (value > quantities[largestIndex]) largestIndex = index; });
  return {model: "level-share-concentration-and-wall-screen", level_count: parsed.length, total_depth: total, median_level_quantity: med, hhi_fraction: hhi, effective_level_count: 1 / hhi, largest_level_index: largestIndex, largest_level_share: shares[largestIndex], walls, wall_multiple: multiple, minimum_share: minShare, concentration_threshold: threshold, state: walls.length ? "wall-detected" : hhi >= threshold ? "concentrated" : "distributed"};
}

export function depthDepletionReplenishment(seriesRaw: unknown): JsonObject {
  if (!Array.isArray(seriesRaw) || seriesRaw.length < 2) throw new RangeError("series must contain at least two snapshots");
  const parsed = seriesRaw.map((item, index) => {
    if (!item || typeof item !== "object") throw new TypeError(`series[${index}] must be an object`);
    const row = item as JsonObject;
    return {timestamp_seconds: numberValue(`series[${index}].timestamp_seconds`, row.timestamp_seconds, {nonnegative: true}), quantity: numberValue(`series[${index}].quantity`, row.quantity, {nonnegative: true})};
  });
  for (let i = 1; i < parsed.length; i += 1) if (parsed[i - 1].timestamp_seconds >= parsed[i].timestamp_seconds) throw new RangeError("timestamps must be strictly increasing");
  let depletion = 0, replenishment = 0;
  const changes = parsed.slice(1).map((current, index) => {
    const previous = parsed[index], delta = current.quantity - previous.quantity;
    replenishment += Math.max(delta, 0); depletion += Math.max(-delta, 0);
    return {timestamp_seconds: current.timestamp_seconds, previous_quantity: previous.quantity, quantity: current.quantity, delta_quantity: delta, classification: delta > 0 ? "replenishment" : delta < 0 ? "depletion" : "unchanged"};
  });
  const net = replenishment - depletion;
  return {model: "snapshot-visible-depth-change-decomposition", snapshot_count: parsed.length, start_quantity: parsed[0].quantity, end_quantity: parsed[parsed.length - 1].quantity, gross_depletion: depletion, gross_replenishment: replenishment, net_depth_change: net, replenishment_to_depletion: depletion ? replenishment / depletion : null, changes, state: net > 0 ? "net-replenishing" : net < 0 ? "net-depleting" : "net-flat"};
}

export function marketDepthHeatmap(snapshotsRaw: unknown, tickRaw: unknown, binRaw: unknown, maxRaw: unknown): JsonObject {
  if (!Array.isArray(snapshotsRaw) || snapshotsRaw.length < 2) throw new RangeError("snapshots must contain at least two regular observations");
  const snapshots = snapshotsRaw as JsonObject[], tick = numberValue("tick_size", tickRaw, {positive: true}), binSize = numberValue("time_bin_seconds", binRaw, {positive: true}), maximum = integerValue("max_distance_ticks", maxRaw);
  if (maximum < 0) throw new RangeError("max_distance_ticks must be nonnegative");
  const times = snapshots.map((item, index) => {
    if (!item || typeof item !== "object") throw new TypeError("each snapshot must be an object");
    return numberValue(`snapshots[${index}].timestamp_seconds`, item.timestamp_seconds, {nonnegative: true});
  });
  for (let i = 1; i < times.length; i += 1) if (times[i - 1] >= times[i]) throw new RangeError("snapshot timestamps must be strictly increasing");
  const intervals = times.slice(1).map((time, index) => time - times[index]);
  if (intervals.slice(1).some(interval => Math.abs(interval - intervals[0]) > 1e-9)) throw new RangeError("canonical heatmap requires regularly sampled snapshots");
  const origin = times[0], buckets = new Map<string, number[]>(), binSet = new Set<number>();
  snapshots.forEach((snapshot, snapshotIndex) => {
    const [bids, asks] = book(snapshot.bids, snapshot.asks), binIndex = Math.floor((times[snapshotIndex] - origin) / binSize);
    binSet.add(binIndex);
    const observed = new Map<number, number>();
    bids.forEach(level => { const d = tickDistance(level.price, bids[0].price, tick, "bid"); if (d <= maximum) observed.set(-(d + 1), level.quantity); });
    asks.forEach(level => { const d = tickDistance(level.price, asks[0].price, tick, "ask"); if (d <= maximum) observed.set(d + 1, level.quantity); });
    const coordinates = [...Array.from({length: maximum + 1}, (_, i) => -(maximum + 1) + i), ...Array.from({length: maximum + 1}, (_, i) => i + 1)];
    coordinates.forEach(coordinate => { const key = `${binIndex}|${coordinate}`, values = buckets.get(key) ?? []; values.push(observed.get(coordinate) ?? 0); buckets.set(key, values); });
  });
  const cells = [...buckets.entries()].map(([key, values]) => {
    const [binIndex, coordinate] = key.split("|").map(Number);
    return {time_bin_index: binIndex, time_bin_start_seconds: origin + binIndex * binSize, book_coordinate: coordinate, mean_quantity: values.reduce((a, b) => a + b, 0) / values.length, max_quantity: Math.max(...values), observation_count: values.length};
  }).sort((a, b) => a.time_bin_index - b.time_bin_index || a.book_coordinate - b.book_coordinate);
  const peak = cells.reduce((best, cell) => cell.mean_quantity > best.mean_quantity ? cell : best);
  return {model: "regular-snapshot-inside-relative-depth-heatmap", snapshot_interval_seconds: intervals[0], time_bin_seconds: binSize, max_distance_ticks: maximum, time_bin_count: binSet.size, book_coordinates: [...Array.from({length: maximum + 1}, (_, i) => -(maximum + 1) + i), ...Array.from({length: maximum + 1}, (_, i) => i + 1)], cells, peak_cell: peak, state: peak.book_coordinate < 0 ? "bid-peak" : "ask-peak"};
}

export function calculate(topicId: string, inputs: JsonObject): JsonObject {
  if (!inputs || typeof inputs !== "object" || Array.isArray(inputs)) throw new TypeError("inputs must be an object");
  if (topicId === "D11-F05-A01") return cumulativeDepth(inputs.bids, inputs.asks, inputs.tick_size);
  if (topicId === "D11-F05-A02") return topNDepthImbalance(inputs.bids, inputs.asks, inputs.n, inputs.threshold ?? 0.1);
  if (topicId === "D11-F05-A03") return depthAtDistanceProfile(inputs.bids, inputs.asks, inputs.tick_size, inputs.max_distance_ticks);
  if (topicId === "D11-F05-A04") return expectedFillPrice(inputs.bids, inputs.asks, inputs.side, inputs.quantity, inputs.limit_price);
  if (topicId === "D11-F05-A05") return sweepCostAndSlippage(inputs.bids, inputs.asks, inputs.side, inputs.quantity, inputs.benchmark ?? "midpoint", inputs.benchmark_price, inputs.limit_price);
  if (topicId === "D11-F05-A06") return liquidityWallConcentration(inputs.levels, inputs.wall_multiple ?? 2, inputs.minimum_share ?? 0.25, inputs.concentration_threshold ?? 0.30);
  if (topicId === "D11-F05-A07") return depthDepletionReplenishment(inputs.series);
  if (topicId === "D11-F05-A08") return marketDepthHeatmap(inputs.snapshots, inputs.tick_size, inputs.time_bin_seconds, inputs.max_distance_ticks);
  throw new RangeError(`unsupported topic_id: ${topicId}`);
}