Quarterly momentum. Before the crowd.

from valuein_sdk import ValueinClient, ValueinError sql = """WITH members AS (    SELECT r.cik, r.symbol, r.name, r.sector    FROM "references" r    JOIN index_membership im ON im.cik = r.cik    WHERE im.index_name = 'SP500'      AND im.removal_date IS NULL      AND r.is_active      AND r.is_primary_ticker),quarters AS (    -- Quarter-only revenue: Q2/Q3 may be filed year-to-date and the FY row    -- carries Q4, so read derived_quarterly_value first.    SELECT entity_id, period_end,           COALESCE(derived_quarterly_value, numeric_value) AS revenue    FROM fact    WHERE standard_concept = 'TotalRevenue'      AND fiscal_period IN ('Q1', 'Q2', 'Q3', 'FY')      AND (fiscal_period <> 'FY' OR derived_quarterly_value IS NOT NULL)  -- FY only for its Q4    QUALIFY ROW_NUMBER() OVER (        PARTITION BY entity_id, period_end ORDER BY accepted_at DESC    ) = 1),growth AS (    SELECT *,        LAG(revenue, 1) OVER (PARTITION BY entity_id ORDER BY period_end) AS prev_qtr_rev,        LAG(revenue, 4) OVER (PARTITION BY entity_id ORDER BY period_end) AS same_qtr_prior_yr,        -- gaps in the history would compare the wrong quarters: keep only clean runs        period_end - LAG(period_end, 1) OVER (PARTITION BY entity_id ORDER BY period_end) AS days_to_prev,        period_end - LAG(period_end, 4) OVER (PARTITION BY entity_id ORDER BY period_end) AS days_to_year_ago    FROM quarters    QUALIFY ROW_NUMBER() OVER (PARTITION BY entity_id ORDER BY period_end DESC) = 1)SELECT    m.symbol, m.name, m.sector,    g.period_end,    ROUND(g.revenue / 1e6, 1)                                  AS revenue_m,    ROUND((g.revenue / NULLIF(g.prev_qtr_rev, 0) - 1) * 100, 1)      AS qoq_growth_pct,    ROUND((g.revenue / NULLIF(g.same_qtr_prior_yr, 0) - 1) * 100, 1) AS yoy_growth_pctFROM growth gJOIN members m ON m.cik = g.entity_idWHERE g.days_to_prev BETWEEN 80 AND 100  AND g.days_to_year_ago BETWEEN 350 AND 380  AND g.revenue / NULLIF(g.same_qtr_prior_yr, 0) > 1.10  AND g.revenue / NULLIF(g.prev_qtr_rev, 0) > 1.0ORDER BY yoy_growth_pct DESCLIMIT 25""" try:    with ValueinClient() as client:        df = client.run_query(sql)        print(df)except ValueinError as e:    print(f"Valuein error: {e}")

from valuein_sdk import ValueinClient, ValueinError sql = """WITH members AS (    SELECT r.cik, r.symbol, r.name, r.sector    FROM "references" r    JOIN index_membership im ON im.cik = r.cik    WHERE im.index_name = 'SP500'      AND im.removal_date IS NULL      AND r.is_active      AND r.is_primary_ticker),eps_qtrs AS (    -- Diluted EPS as filed in 10-Qs. EPS is not additive, so there is no    -- derived Q4: compare each fiscal quarter with the same quarter a year earlier.    SELECT entity_id, period_end, fiscal_period, numeric_value AS eps_diluted    FROM fact    WHERE standard_concept = 'EPSDiluted'      AND fiscal_period IN ('Q1', 'Q2', 'Q3')      AND period_span_days BETWEEN 80 AND 100        -- three-month figures only    QUALIFY ROW_NUMBER() OVER (        PARTITION BY entity_id, period_end ORDER BY accepted_at DESC    ) = 1),yoy AS (    SELECT *,        LAG(eps_diluted) OVER (PARTITION BY entity_id, fiscal_period ORDER BY period_end) AS eps_year_ago,        ROW_NUMBER() OVER (PARTITION BY entity_id ORDER BY period_end DESC)               AS recency    FROM eps_qtrs),streak AS (    SELECT entity_id,        MAX(period_end)                               AS latest_quarter,        ARG_MAX(eps_diluted, period_end)              AS eps_latest,        ARG_MAX(eps_year_ago, period_end)             AS eps_year_ago    FROM yoy    WHERE recency <= 3    GROUP BY entity_id    HAVING COUNT(*) = 3       AND BOOL_AND(eps_diluted > eps_year_ago)       -- up year over year, three quarters running)SELECT m.symbol, m.name,    s.latest_quarter,    ROUND(s.eps_latest, 2)   AS eps_latest,    ROUND(s.eps_year_ago, 2) AS eps_year_ago,    ROUND((s.eps_latest / NULLIF(s.eps_year_ago, 0) - 1) * 100, 1) AS yoy_growth_pctFROM streak sJOIN members m ON m.cik = s.entity_idWHERE s.eps_year_ago > 0ORDER BY yoy_growth_pct DESCLIMIT 20""" try:    with ValueinClient() as client:        df = client.run_query(sql)        print(df)except ValueinError as e:    print(f"Valuein error: {e}")

from valuein_sdk import ValueinClient, ValueinError sql = """WITH members AS (    SELECT r.cik, r.symbol, r.name, r.sector    FROM "references" r    JOIN index_membership im ON im.cik = r.cik    WHERE im.index_name = 'SP500'      AND im.removal_date IS NULL      AND r.is_active      AND r.is_primary_ticker),balances AS (    -- Balance-sheet values are point-in-time, so every quarter-end row counts.    SELECT entity_id, period_end, standard_concept, numeric_value    FROM fact    WHERE standard_concept IN ('CurrentAssets', 'TotalCurrentLiabilities')    QUALIFY ROW_NUMBER() OVER (        PARTITION BY entity_id, standard_concept, period_end ORDER BY accepted_at DESC    ) = 1),wc AS (    SELECT        entity_id,        period_end,        MAX(CASE WHEN standard_concept = 'CurrentAssets'           THEN numeric_value END)          - MAX(CASE WHEN standard_concept = 'TotalCurrentLiabilities' THEN numeric_value END) AS working_capital    FROM balances    GROUP BY entity_id, period_end    HAVING working_capital IS NOT NULL),trend AS (    SELECT *,        LAG(working_capital, 1) OVER (PARTITION BY entity_id ORDER BY period_end) AS wc_q1_ago,        LAG(working_capital, 2) OVER (PARTITION BY entity_id ORDER BY period_end) AS wc_q2_ago    FROM wc    QUALIFY ROW_NUMBER() OVER (PARTITION BY entity_id ORDER BY period_end DESC) = 1)SELECT m.symbol, m.name,    t.period_end,    ROUND(t.working_capital / 1e6, 0) AS wc_latest_m,    ROUND(t.wc_q1_ago       / 1e6, 0) AS wc_q1_ago_m,    ROUND(t.wc_q2_ago       / 1e6, 0) AS wc_q2_ago_mFROM trend tJOIN members m ON m.cik = t.entity_idWHERE t.working_capital < t.wc_q1_ago  AND t.wc_q1_ago < t.wc_q2_agoORDER BY wc_latest_m ASCLIMIT 20""" try:    with ValueinClient() as client:        df = client.run_query(sql)        print(df)except ValueinError as e:    print(f"Valuein error: {e}")

from valuein_sdk import ValueinClient, ValueinError sql = """WITH members AS (    SELECT r.cik, r.symbol, r.name, r.sector    FROM "references" r    JOIN index_membership im ON im.cik = r.cik    WHERE im.index_name = 'SP500'      AND im.removal_date IS NULL      AND r.is_active      AND r.is_primary_ticker),quarters AS (    SELECT entity_id, period_end, standard_concept,           COALESCE(derived_quarterly_value, numeric_value) AS quarter_value    FROM fact    WHERE standard_concept IN ('GrossProfit', 'TotalRevenue')      AND fiscal_period IN ('Q1', 'Q2', 'Q3', 'FY')      AND (fiscal_period <> 'FY' OR derived_quarterly_value IS NOT NULL)  -- FY only for its Q4      AND period_end >= current_date - INTERVAL 18 MONTH    QUALIFY ROW_NUMBER() OVER (        PARTITION BY entity_id, standard_concept, period_end ORDER BY accepted_at DESC    ) = 1),per_company AS (    SELECT        entity_id,        period_end,        MAX(CASE WHEN standard_concept = 'GrossProfit'  THEN quarter_value END)          / NULLIF(MAX(CASE WHEN standard_concept = 'TotalRevenue' THEN quarter_value END), 0) AS gross_margin    FROM quarters    GROUP BY entity_id, period_end)SELECT    m.sector,    date_trunc('quarter', p.period_end)   AS calendar_quarter,    ROUND(AVG(p.gross_margin) * 100, 1)   AS avg_gross_margin_pct,    COUNT(*)                              AS companiesFROM per_company pJOIN members m ON m.cik = p.entity_idWHERE p.gross_margin BETWEEN 0 AND 1   -- banks and REITs have no meaningful gross marginGROUP BY m.sector, calendar_quarterORDER BY m.sector, calendar_quarter""" try:    with ValueinClient() as client:        df = client.run_query(sql)    print(df.pivot_table(index="sector", columns="calendar_quarter", values="avg_gross_margin_pct"))except ValueinError as e:    print(f"Valuein error: {e}")