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金融

FinanceAgentToolSpec #

基础: BaseToolSpec

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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class FinanceAgentToolSpec(BaseToolSpec):
    spec_functions = [
        "find_similar_companies",
        "get_earnings_history",
        "get_stocks_with_upcoming_earnings",
        "get_current_gainer_stocks",
        "get_current_loser_stocks",
        "get_current_undervalued_growth_stocks",
        "get_current_technology_growth_stocks",
        "get_current_most_traded_stocks",
        "get_current_undervalued_large_cap_stocks",
        "get_current_aggressive_small_cap_stocks",
        "get_trending_finance_news",
        "get_google_trending_searches",
        "get_google_trends_for_query",
        "get_latest_news_for_stock",
        "get_current_stock_price_info",
    ]

    def __init__(
        self,
        polygon_api_key: str,
        finnhub_api_key: str,
        alpha_vantage_api_key: str,
        newsapi_api_key: str,
    ):
        self._api_key = {
            "ALPHA_VANTAGE": alpha_vantage_api_key,
            "POLYGON": polygon_api_key,
            "FINNHUB": finnhub_api_key,
            "NEWSAPI": newsapi_api_key,
        }

    def find_similar_companies(self, symbol: str) -> List[str]:
        """Given a stock's ticker symbol, returns a list of similar companies."""
        return comparisons.find_similar_companies(self._api_key, symbol)

    def get_earnings_history(self, symbol: str) -> pd.DataFrame:
        """Given a stock's ticker symbol, returns a dataframe storing actual and estimated earnings over past K quarterly reports."""
        return earnings.get_earnings_history(self._api_key, symbol)

    def get_latest_earning_estimate(self, symbol: str) -> float:
        """Given a stock's ticker symbol, returns it's earnings estimate for the upcoming quarterly report."""
        return earnings.get_latest_earning_estimate(symbol)

    def get_stocks_with_upcoming_earnings(
        self, num_days_from_now: int, only_sp500: bool
    ) -> pd.DataFrame:
        """
        Returns a pandas dataframe containing all stocks which are announcing earnings in upcoming days.

        Arguments:
         num_days_from_now: only returns stocks which announcing earnings from today's date to num_days_from_now.
         only_sp500: only returns sp500 stocks.

        """
        start_date = datetime.now().strftime("%Y-%m-%d")
        end_date = (datetime.now() + timedelta(num_days_from_now)).strftime("%Y-%m-%d")
        return earnings.get_upcoming_earnings(
            self._api_key,
            start_date=start_date,
            end_date=end_date,
            country="USD",
            only_sp500=only_sp500,
        )

    def get_current_gainer_stocks(self) -> pd.DataFrame:
        """
        Return US stocks which are classified as day gainers as per Yahoo Finance.

        A US stock is classified as day gainer if %change in price > 3, price >=5, volume > 15_000

        """
        return news.get_current_gainer_stocks()

    def get_current_loser_stocks(self) -> pd.DataFrame:
        """
        Returns US stocks which are classified as day losers as per Yahoo Finance.

        A US stock is classified as day loser if %change in price < -2.5, price >=5, volume > 20_000

        """
        return news.get_current_loser_stocks()

    def get_current_undervalued_growth_stocks(self) -> pd.DataFrame:
        """
        Get list of undervalued growth stocks in US market as per Yahoo Finance.

        A stock with Price to Earnings ratio between 0-20, Price / Earnings to Growth < 1

        """
        return news.get_current_undervalued_growth_stocks()

    def get_current_technology_growth_stocks(self) -> pd.DataFrame:
        """
        Returns a data frame of growth stocks in technology sector in US market.

        If a stocks's quarterly revenue growth YoY% > 25%.

        """
        return news.get_current_technology_growth_stocks()

    def get_current_most_traded_stocks(self) -> pd.DataFrame:
        """
        Returns a dataframe storing stocks which were traded the most in current market.

        Stocks are ordered in decreasing order of activity i.e stock traded the most on top.

        """
        return news.get_current_most_traded_stocks()

    def get_current_undervalued_large_cap_stocks(self) -> pd.DataFrame:
        """Returns a dataframe storing US market large cap stocks with P/E < 20."""
        return news.get_current_undervalued_large_cap_stocks()

    def get_current_aggressive_small_cap_stocks(self) -> pd.DataFrame:
        """Returns a dataframe storing US market small cap stocks with 1 yr % change in earnings per share > 25."""
        return news.get_current_aggressive_small_cap_stocks()

    def get_trending_finance_news(self) -> List[str]:
        """Returns a list of top 10 trending news in financial market as per seekingalpha."""
        trends = news.get_topk_trending_news()
        return [t["title"] for t in trends]

    def get_google_trending_searches(self) -> Optional[pd.DataFrame]:
        """
        Returns trending searches in US as per google trends.

        If unable to find any trends, returns None.

        """
        return news.get_google_trending_searches(region="united_states")

    def get_google_trends_for_query(self, query: str) -> Optional[pd.DataFrame]:
        """
        Finds google search trends for a given query in United States.

        Returns None if unable to find any trends.

        """
        return news.get_google_trends_for_query(query=query, region="united_states")

    def get_latest_news_for_stock(self, stock_id: str) -> List[str]:
        """Given a stock_id representing the name of a company or the stock ticker symbol, Returns a list of news published related to top business articles in US in last 7 days from now."""
        articles = news.get_latest_news_for_stock(self._api_key, stock_id=stock_id)
        return [a["title"] for a in articles]

    def get_current_stock_price_info(
        self, stock_ticker_symbol: str
    ) -> Optional[Dict[str, Any]]:
        """
        Given a stock's ticker symbol, returns current price information of the stock.

        Returns None if the provided stock ticker symbol is invalid.
        """
        price_info = news.get_current_stock_price_info(
            self._api_key, stock_ticker_symbol
        )
        if price_info is not None:
            return {
                "Current Price": price_info["c"],
                "High Price of the day": price_info["h"],
                "Low Price of the day": price_info["l"],
                "Open Price of the day": price_info["o"],
                "Percentage change": price_info["dp"],
            }
        return None

查找相似公司 #

find_similar_companies(symbol: str) -> List[str]

给定股票代码，返回相似公司列表。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def find_similar_companies(self, symbol: str) -> List[str]:
    """Given a stock's ticker symbol, returns a list of similar companies."""
    return comparisons.find_similar_companies(self._api_key, symbol)

获取财报历史 #

get_earnings_history(symbol: str) -> DataFrame

给定股票代码，返回一个数据框，其中存储了过去 K 个季度的实际和预计收益。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_earnings_history(self, symbol: str) -> pd.DataFrame:
    """Given a stock's ticker symbol, returns a dataframe storing actual and estimated earnings over past K quarterly reports."""
    return earnings.get_earnings_history(self._api_key, symbol)

获取最新财报预期 #

get_latest_earning_estimate(symbol: str) -> float

给定股票代码，返回其即将发布的季度报告的收益预期。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_latest_earning_estimate(self, symbol: str) -> float:
    """Given a stock's ticker symbol, returns it's earnings estimate for the upcoming quarterly report."""
    return earnings.get_latest_earning_estimate(symbol)

获取即将发布财报的股票 #

get_stocks_with_upcoming_earnings(num_days_from_now: int, only_sp500: bool) -> DataFrame

返回一个包含所有即将在未来几天宣布财报的股票的 pandas 数据框。

参数

名称 类型 描述 默认值
num_days_from_now int

只返回从今天起到 num_days_from_now 天内宣布财报的股票。

 必需
only_sp500 bool

只返回标普 500 指数的股票。

 必需
源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_stocks_with_upcoming_earnings(
    self, num_days_from_now: int, only_sp500: bool
) -> pd.DataFrame:
    """
    Returns a pandas dataframe containing all stocks which are announcing earnings in upcoming days.

    Arguments:
     num_days_from_now: only returns stocks which announcing earnings from today's date to num_days_from_now.
     only_sp500: only returns sp500 stocks.

    """
    start_date = datetime.now().strftime("%Y-%m-%d")
    end_date = (datetime.now() + timedelta(num_days_from_now)).strftime("%Y-%m-%d")
    return earnings.get_upcoming_earnings(
        self._api_key,
        start_date=start_date,
        end_date=end_date,
        country="USD",
        only_sp500=only_sp500,
    )

获取当前上涨股票 #

get_current_gainer_stocks() -> DataFrame

根据 Yahoo Finance 返回被归类为日内上涨股的美国股票。

如果价格变化百分比 > 3%，价格 >= 5，交易量 > 15,000，则将美国股票归类为日内上涨股。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_gainer_stocks(self) -> pd.DataFrame:
    """
    Return US stocks which are classified as day gainers as per Yahoo Finance.

    A US stock is classified as day gainer if %change in price > 3, price >=5, volume > 15_000

    """
    return news.get_current_gainer_stocks()

获取当前下跌股票 #

get_current_loser_stocks() -> DataFrame

根据 Yahoo Finance 返回被归类为日内下跌股的美国股票。

如果价格变化百分比 < -2.5%，价格 >= 5，交易量 > 20,000，则将美国股票归类为日内下跌股。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_loser_stocks(self) -> pd.DataFrame:
    """
    Returns US stocks which are classified as day losers as per Yahoo Finance.

    A US stock is classified as day loser if %change in price < -2.5, price >=5, volume > 20_000

    """
    return news.get_current_loser_stocks()

获取当前被低估的成长股 #

get_current_undervalued_growth_stocks() -> DataFrame

根据 Yahoo Finance 获取美国市场的被低估成长股列表。

市盈率在 0-20 之间，市盈增长比 < 1 的股票。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_undervalued_growth_stocks(self) -> pd.DataFrame:
    """
    Get list of undervalued growth stocks in US market as per Yahoo Finance.

    A stock with Price to Earnings ratio between 0-20, Price / Earnings to Growth < 1

    """
    return news.get_current_undervalued_growth_stocks()

获取当前科技成长股 #

get_current_technology_growth_stocks() -> DataFrame

返回美国市场科技板块的成长股数据框。

如果股票的季度收入同比增长率 > 25%。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_technology_growth_stocks(self) -> pd.DataFrame:
    """
    Returns a data frame of growth stocks in technology sector in US market.

    If a stocks's quarterly revenue growth YoY% > 25%.

    """
    return news.get_current_technology_growth_stocks()

获取当前交易最活跃股票 #

get_current_most_traded_stocks() -> DataFrame

返回一个数据框，其中包含当前市场中交易最活跃的股票。

股票按活跃度降序排列，即交易最活跃的股票排在最前面。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_most_traded_stocks(self) -> pd.DataFrame:
    """
    Returns a dataframe storing stocks which were traded the most in current market.

    Stocks are ordered in decreasing order of activity i.e stock traded the most on top.

    """
    return news.get_current_most_traded_stocks()

获取当前被低估的大盘股 #

get_current_undervalued_large_cap_stocks() -> DataFrame

返回一个数据框，其中包含市盈率 < 20 的美国市场大盘股。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_undervalued_large_cap_stocks(self) -> pd.DataFrame:
    """Returns a dataframe storing US market large cap stocks with P/E < 20."""
    return news.get_current_undervalued_large_cap_stocks()

获取当前激进型小盘股 #

get_current_aggressive_small_cap_stocks() -> DataFrame

返回一个数据框，其中包含一年内每股收益变化百分比 > 25 的美国市场小盘股。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_aggressive_small_cap_stocks(self) -> pd.DataFrame:
    """Returns a dataframe storing US market small cap stocks with 1 yr % change in earnings per share > 25."""
    return news.get_current_aggressive_small_cap_stocks()

get_trending_finance_news() -> List[str]

根据 seekingalpha 返回金融市场中排名前 10 的热门新闻列表。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_trending_finance_news(self) -> List[str]:
    """Returns a list of top 10 trending news in financial market as per seekingalpha."""
    trends = news.get_topk_trending_news()
    return [t["title"] for t in trends]

get_google_trending_searches() -> Optional[DataFrame]

根据 Google Trends 返回美国的热门搜索。

如果找不到任何趋势，返回 None。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_google_trending_searches(self) -> Optional[pd.DataFrame]:
    """
    Returns trending searches in US as per google trends.

    If unable to find any trends, returns None.

    """
    return news.get_google_trending_searches(region="united_states")

get_google_trends_for_query(query: str) -> Optional[DataFrame]

在美国查找给定查询的 Google 搜索趋势。

如果找不到任何趋势，返回 None。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_google_trends_for_query(self, query: str) -> Optional[pd.DataFrame]:
    """
    Finds google search trends for a given query in United States.

    Returns None if unable to find any trends.

    """
    return news.get_google_trends_for_query(query=query, region="united_states")

获取股票最新新闻 #

get_latest_news_for_stock(stock_id: str) -> List[str]

给定表示公司名称或股票代码的 stock_id，返回过去 7 天内与美国热门商业文章相关的已发布新闻列表。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_latest_news_for_stock(self, stock_id: str) -> List[str]:
    """Given a stock_id representing the name of a company or the stock ticker symbol, Returns a list of news published related to top business articles in US in last 7 days from now."""
    articles = news.get_latest_news_for_stock(self._api_key, stock_id=stock_id)
    return [a["title"] for a in articles]

获取当前股票价格信息 #

get_current_stock_price_info(stock_ticker_symbol: str) -> Optional[Dict[str, Any]]

给定股票代码，返回该股票的当前价格信息。

如果提供的股票代码无效，返回 None。

源代码位于 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py 
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def get_current_stock_price_info(
    self, stock_ticker_symbol: str
) -> Optional[Dict[str, Any]]:
    """
    Given a stock's ticker symbol, returns current price information of the stock.

    Returns None if the provided stock ticker symbol is invalid.
    """
    price_info = news.get_current_stock_price_info(
        self._api_key, stock_ticker_symbol
    )
    if price_info is not None:
        return {
            "Current Price": price_info["c"],
            "High Price of the day": price_info["h"],
            "Low Price of the day": price_info["l"],
            "Open Price of the day": price_info["o"],
            "Percentage change": price_info["dp"],
        }
    return None