Quarterly momentum. Before the crowd.

from valuein_sdk import ValueinClient, ValueinError sql = """WITH quarterly_rev AS (    SELECT        r.symbol, r.name, r.sector,        f.fiscal_year,        f.fiscal_period,        f.period_end,        f.numeric_value AS revenue    FROM fact f    JOIN references r        ON f.entity_id = r.cik    JOIN index_membership im ON im.cik = r.cik    WHERE f.form_type = '10-Q'      AND f.standard_concept = 'Revenues'      AND im.index_name = 'SP500'      AND im.removal_date IS NULL      AND f.fiscal_year >= 2022    QUALIFY ROW_NUMBER() OVER (        PARTITION BY r.symbol, f.fiscal_year, f.fiscal_period        ORDER BY f.accepted_at DESC    ) = 1),with_growth AS (    SELECT *,        LAG(revenue, 1) OVER (PARTITION BY symbol ORDER BY period_end) AS prev_qtr_rev,        LAG(revenue, 4) OVER (PARTITION BY symbol ORDER BY period_end) AS same_qtr_prior_yr    FROM quarterly_rev)SELECT    symbol, name, sector,    fiscal_year, fiscal_period,    ROUND(revenue / 1e6, 1)                                               AS revenue_m,    ROUND((revenue / NULLIF(prev_qtr_rev, 0) - 1) * 100, 1)              AS qoq_growth_pct,    ROUND((revenue / NULLIF(same_qtr_prior_yr, 0) - 1) * 100, 1)         AS yoy_growth_pctFROM with_growthWHERE fiscal_year = 2024  AND yoy_growth_pct > 10  AND qoq_growth_pct > 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 eps_qtrs AS (    SELECT        r.symbol, r.name,        f.fiscal_year,        f.fiscal_period,        f.period_end,        f.numeric_value AS eps_diluted    FROM fact f    JOIN references r        ON f.entity_id = r.cik    JOIN index_membership im ON im.cik = r.cik    WHERE f.form_type = '10-Q'      AND f.standard_concept = 'EarningsPerShareDiluted'      AND im.index_name = 'SP500'      AND im.removal_date IS NULL      AND f.fiscal_year >= 2023    QUALIFY ROW_NUMBER() OVER (        PARTITION BY r.symbol, f.fiscal_year, f.fiscal_period        ORDER BY f.accepted_at DESC    ) = 1),consecutive AS (    SELECT *,        LAG(eps_diluted, 1) OVER (PARTITION BY symbol ORDER BY period_end) AS eps_q1_ago,        LAG(eps_diluted, 2) OVER (PARTITION BY symbol ORDER BY period_end) AS eps_q2_ago,        LAG(eps_diluted, 3) OVER (PARTITION BY symbol ORDER BY period_end) AS eps_q3_ago    FROM eps_qtrs)SELECT symbol, name,    ROUND(eps_diluted, 2) AS eps_latest,    ROUND(eps_q1_ago, 2)  AS eps_q1_ago,    ROUND(eps_q2_ago, 2)  AS eps_q2_ago,    ROUND(eps_q3_ago, 2)  AS eps_q3_agoFROM consecutiveWHERE fiscal_year = 2024  AND eps_diluted > eps_q1_ago  AND eps_q1_ago  > eps_q2_ago  AND eps_q2_ago  > eps_q3_ago  AND eps_diluted > 0ORDER BY eps_diluted 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 wc_qtrs AS (    SELECT        r.symbol, r.name,        f.fiscal_year, f.fiscal_period, f.period_end,        MAX(CASE WHEN standard_concept = 'AssetsCurrent'      THEN numeric_value END) AS current_assets,        MAX(CASE WHEN standard_concept = 'LiabilitiesCurrent' THEN numeric_value END) AS current_liab    FROM fact f    JOIN references r        ON f.entity_id = r.cik    JOIN index_membership im ON im.cik = r.cik    WHERE f.form_type = '10-Q'      AND f.standard_concept IN ('AssetsCurrent', 'LiabilitiesCurrent')      AND im.index_name = 'SP500'      AND im.removal_date IS NULL      AND f.fiscal_year >= 2023    GROUP BY r.symbol, r.name, f.fiscal_year, f.fiscal_period, f.period_end),with_wc AS (    SELECT *,        current_assets - current_liab AS working_capital,        LAG(current_assets - current_liab, 1) OVER (PARTITION BY symbol ORDER BY period_end) AS wc_q1_ago,        LAG(current_assets - current_liab, 2) OVER (PARTITION BY symbol ORDER BY period_end) AS wc_q2_ago    FROM wc_qtrs)SELECT symbol, name,    ROUND(working_capital / 1e6, 0) AS wc_latest_m,    ROUND(wc_q1_ago       / 1e6, 0) AS wc_q1_ago_m,    ROUND(wc_q2_ago       / 1e6, 0) AS wc_q2_ago_mFROM with_wcWHERE fiscal_year = 2024  AND working_capital < wc_q1_ago  AND wc_q1_ago < wc_q2_agoORDER BY working_capital 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 = """SELECT    r.sector,    f.fiscal_year,    f.fiscal_period,    ROUND(        AVG(            MAX(CASE WHEN standard_concept = 'GrossProfit' THEN numeric_value END) /            NULLIF(MAX(CASE WHEN standard_concept = 'Revenues' THEN numeric_value END), 0)        ) * 100, 1    ) AS avg_gross_margin_pct,    COUNT(DISTINCT r.symbol) AS companiesFROM fact fJOIN references r        ON f.entity_id = r.cikJOIN index_membership im ON im.cik = r.cikWHERE f.form_type = '10-Q'  AND f.standard_concept IN ('GrossProfit', 'Revenues')  AND im.index_name = 'SP500'  AND im.removal_date IS NULL  AND f.fiscal_year >= 2023GROUP BY r.sector, f.fiscal_year, f.fiscal_periodORDER BY r.sector, f.fiscal_year, f.fiscal_period""" try:    with ValueinClient() as client:        df = client.run_query(sql)    print(df.pivot_table(        index="sector",        columns=["fiscal_year", "fiscal_period"],        values="avg_gross_margin_pct"    ))except ValueinError as e:    print(f"Valuein error: {e}")