feat: order-book microstructure indicators (part 1 of 4) (#112)
* feat(core): add microstructure input types (OrderBook, Trade, TradeQuote) New non-OHLCV value types for the order-book / trade-flow indicator family: Level, OrderBook (sorted, uncrossed depth snapshot), Side, Trade (with aggressor side), and TradeQuote (trade paired with prevailing mid). Each has a validating constructor plus a new_unchecked hot-path constructor, with full unit coverage. Adds InvalidOrderBook / InvalidTrade error variants. * feat(core): add 5 order-book microstructure indicators OrderBookImbalanceTop1/TopN/Full (signed depth imbalance), Microprice (size-weighted fair value), and QuotedSpread (top-of-book spread in bps). All consume the OrderBook snapshot type, emit f64, are stateless and ready after the first snapshot, with full unit coverage. Registers a new Microstructure family in the taxonomy. * feat(bindings): expose order-book microstructure indicators Python, Node, and WASM bindings for OrderBookImbalanceTop1/TopN/Full, Microprice and QuotedSpread. Each takes a depth snapshot via four equal-length (bid_px, bid_sz, ask_px, ask_sz) arrays. Python and Node expose a batch over a list of snapshots; WASM exposes per-snapshot update (the streaming model that fits a browser book feed). Regenerates node index.d.ts/.js and registers the new InvalidOrderBook/InvalidTrade arms in the Python error mapping. * test(bindings,fuzz): cover order-book microstructure indicators Python: smoke, reference values, streaming-vs-batch, lifecycle/repr and input validation (mismatched lengths, crossed book, misordered levels, zero levels) for all five order-book indicators. Node: reference values, streaming-vs-batch, and rejection cases. Adds an indicator_update_orderbook fuzz target driving every order-book indicator over arbitrary (incl. degenerate) snapshots. * bench(microstructure): synthetic order-book benchmarks Add a bench_orderbook_input harness and synthesise a five-level book around each candle close (no order-book dataset ships with the repo). Benches the cheapest (top-of-book imbalance) and most-expensive (full-depth imbalance) plus microprice, matching the curated cheapest/expensive-per-family approach. * docs: add Microstructure family + bump indicator counter to 224 README gains the Microstructure family row (order-book imbalance, microprice, quoted spread) and the indicator counter goes 219 -> 224 across seventeen families; CHANGELOG records the new order-book indicators and value types.
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@@ -166,3 +166,28 @@ def test_family_10_ehlers_rejects_invalid_parameters():
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ta.MAMA(0.05, 0.5)
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with pytest.raises(ValueError):
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ta.EmpiricalModeDecomposition(20, 0.0)
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def test_orderbook_topn_zero_levels_raises():
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with pytest.raises(ValueError):
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ta.OrderBookImbalanceTopN(0)
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def test_orderbook_unequal_price_size_lengths_raise():
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# bid_px has 2 entries but bid_sz has 1 -> mismatched -> ValueError.
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with pytest.raises(ValueError):
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ta.OrderBookImbalanceTop1().update([100.0, 99.0], [1.0], [101.0], [1.0])
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with pytest.raises(ValueError):
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ta.Microprice().update([100.0], [1.0], [101.0, 102.0], [1.0])
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def test_orderbook_crossed_book_raises():
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# best_bid (102) >= best_ask (101) is a crossed book -> rejected.
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with pytest.raises(ValueError):
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ta.QuotedSpread().update([102.0], [1.0], [101.0], [1.0])
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def test_orderbook_misordered_levels_raise():
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# Bids must be strictly descending in price.
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with pytest.raises(ValueError):
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ta.OrderBookImbalanceFull().update([99.0, 100.0], [1.0, 1.0], [101.0], [1.0])
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