Python BasicData.getStockDate方法代码示例

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcROC(stock_code, date, period):
    pday = bd.getStockDate(stock_code, date, period)
    BX = bd.getBasicData("CLOSE_TODAY", stock_code, pday)
    close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
    AX = close_today - BX
    ROC = AX / BX * 100
    return round(ROC, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def analyze(stock_code, date):
    score = 0
    signal = ""
    pday = bd.getStockDate(stock_code, date, 1)
    KDJ_K, KDJ_D, KDJ_J = getKDJ(stock_code, date)
    KDJ_K_pday, KDJ_D_pday, KDJ_J_pday = getKDJ(stock_code, pday)

    if KDJ_K >= 90:
        score -= 1
        signal += "[-1]K线是快速确认线——数值在90以上为超买;"
    if KDJ_K <= 10:
        score += 1
        signal += "[1]K线是快速确认线——数值在10以下为超卖;"

    if KDJ_D >= 80:
        score -= 1
        signal += "[-1]D线是慢速主干线——数值在80以上为超买;"
    if KDJ_D <= 20:
        score += 1
        signal += "[1]D线是慢速主干线——数值在20以下为超卖;"

    if KDJ_J >= 90:
        score -= 1
        signal += "[-1]J线为方向敏感线，当J值大于90，特别是连续5天以上，股价至少会形成短期头部;"
    if KDJ_J <= 10:
        score += 1
        signal += "[1]J线为方向敏感线，当J值小于10，特别是连续数天以上，股价至少会形成短期底部;"

    if KDJ_K_pday < KDJ_D_pday and KDJ_K > KDJ_D:
        score += 1
        signal += "[1]K线从下方上穿D线，所以在图形上K线向上突破D线时，俗称金叉，即为买进的讯号;"
        if KDJ_K < 20 and KDJ_D < 20:
            score += 1
            signal += "[1]当K，D线在20以下交叉向上，此时的短期买入的信号较为准确;"
        # TODO 如果K值在50以下，由下往上接连两次上穿D值，形成右底比左底高的“W底”形态时，后市股价可能会有相当的涨幅。

    if KDJ_K_pday > KDJ_D_pday and KDJ_K < KDJ_D:
        score -= 1
        signal += "[-1]K线从上方下穿D线，显示趋势是向下的，所以在图形上K线向下突破D线时，俗称死叉，即为卖出的讯号;"
        if KDJ_K > 20 and KDJ_D > 20:
            score -= 1
            signal += "[-1]当K，D线在80以上交叉向下，此时的短期卖出的信号较为准确;"
        # TODO 如果K值在50以上，由上往下接连两次下穿D值，形成右头比左头低的“M头”形态时，后市股价可能会有相当的跌幅。。

    # TODO 4. 通过KDJ与股价背离的走势，判断股价顶底也是颇为实用的方法：4.1股价创新高，而KD值没有创新高，为顶背离，应卖出;4.2股价创新低，而KD值没有创新低，为底背离，应买入
    '''
    print KDJ_K
    print KDJ_D
    print KDJ_J

    print KDJ_K_pday
    print KDJ_D_pday
    print KDJ_J_pday
    '''
    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("KDJ", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcAMA(stock_code, date, period1, period2, period3):
    AMA = calcDMA(stock_code, date, period2, period3)
    # print AMA
    for i in range(1, period1):
        next_date = bd.getStockDate(stock_code, date, i)
        # print next_date + " " + str(calcDMA(stock_code, next_date, period2, period3))
        AMA += calcDMA(stock_code, next_date, period2, period3)

    AMA = AMA / period1
    return round(AMA, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcTRIX(stock_code, date, period):
    global ITERATOR_COUNT
    TR = calcEMA(stock_code, date, period)

    pday = du.convertDateToString(bd.getStockDate(stock_code, date, 1), "%Y-%m-%d")
    ITERATOR_COUNT = 0
    TR_pday = calcEMA(stock_code, pday, period)
    print TR
    print pday
    print TR_pday
    return (TR - TR_pday) / TR_pday * 100

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def getROCEMAs(stock_code, date, period):
    ROCEMAs = []
    count = 0
    last_day = date
    while count < period:
        ROCEMA = calcROCEMA(stock_code, last_day, ROCEMA_PARAM)
        #print last_day + " " + str(ROCEMA)
        count += 1
        last_day = bd.getStockDate(stock_code, last_day, 1)
        ROCEMAs.append(ROCEMA)

    return ROCEMAs

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def analyze(stock_code, date, period):
    score = 0.0
    signal = ""
    pday = bd.getStockDate(stock_code, date, 1)

    CCI = getCCI(stock_code, date)
    CCI_pday = getCCI(stock_code, pday)
    CCIs = getCCIs(stock_code, date, period)
    CCI_K1 = mu.getPoly(CCIs, 1)[0]
    CCI_K2 = mu.getPoly(CCIs, 2)[0]

    print CCI
    print CCI_pday
    print CCIs
    print CCI_K1
    print CCI_K2


    if CCI > 100:
        score -= 0.5
        signal += "[-0.5]当CCI＞﹢100时，表明股价已经进入非常态区间—超买区间;"
        if CCI_K1 > 0:
            score += 1
            signal += "[1]CCI曲线向上突破﹢100线而进入非常态区间后，只要CCI曲线一直朝上运行，就表明股价强势依旧，中短线应及时买入，如果有比较大的成交量配合，买入信号则更为可靠;"
        if CCI_K2 < 0 and (CCI -100) >= CCI_THREHOLD:
            score -= 1
            signal += "[-1]当CCI曲线在﹢100线以上的非常态区间,在远离﹢100线的地方开始掉头向下时，表明股价的强势状态将难以维持，是股价比较强的转势信号。如果前期的短期涨幅过高时，更可确认。此时，投资者应及时逢高卖出股票;"

    if CCI < -100:
        score += 0.5
        signal += "[0.5]当CCI＜﹣100时，表明股价已经进入另一个非常态区间—超卖区间;"
        if CCI_K1 < 0:
            score -= 1
            signal += "[-1]当CCI曲线向下突破﹣100线而进入另一个非常态区间后，只要CCI曲线一路朝下运行，就表明股价弱势依旧，投资者可一路观望;"
        if CCI_K2 > 0:
            score += 0.5
            signal += "[0.5]当CCI曲线向下突破﹣100线而进入另一个非常态区间，如果CCI曲线在超卖区运行了相当长的一段时间后开始掉头向上，表明股价的短期底部初步找到，投资者可少量建仓。CCI曲线在超卖区运行的时间越长，越可以确认短期的底部;"

    if CCI_pday >= 100 and CCI < 100:
        score -= 1
        signal += "[-1]当CCI指标从上向下突破﹢100线而重新进入常态区间时，表明股价的上涨阶段可能结束，将进入一个比较长时间的盘整阶段。投资者应及时逢高卖出股票;"

    if CCI_pday <= -100 and CCI > -100:
        score += 0.5
        signal += "[0.5]当CCI指标从下向上突破﹣100线而重新进入常态区间时，表明股价的探底阶段可能结束，又将进入一个盘整阶段。投资者可以逢低少量买入股票;"

    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("CCI", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcEMA(stock_code, date, period):
    if ITERATOR_COUNT >= MAX_ITERATOR:
        EXPMA = MA.calcMA(stock_code, date, period)
        # print "MIN Date： " +date+ " MA:"+ str(EXPMA)
        return EXPMA
    else:
        global ITERATOR_COUNT
        ITERATOR_COUNT = ITERATOR_COUNT + 1

        close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
        pday = du.convertDateToString(bd.getStockDate(stock_code, date, 1), "%Y-%m-%d")
        EXPMA_pday = calcEMA(stock_code, pday, period)
        EXPMA = 2 * (close_today - EXPMA_pday) / (period + 1) + EXPMA_pday
        # print date + ": EXPMA: "+str(EXPMA_PDAY)+" CLOSE: " + str(CLOSE_TODAY) + " EXPMA = " +str(EXPMA)
        return round(EXPMA, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcAverageLoss(stock_code, date, period):
    global iterator_count
    price_changed = bd.getBasicData("PRICE_CHANGED", stock_code, date)
    current_loss = 0.0
    if price_changed < 0:
        current_loss = price_changed

    if iterator_count >= max_iterator:
        return calcFirstAverageLoss(stock_code, date, period)
    else:
        iterator_count += 1
        average_loss = (calcAverageLoss(stock_code, bd.getStockDate(stock_code, date, 1), period) * (
            period - 1) + abs(current_loss)) / period
        # print date + " " + str(average_loss) + " Current Loss: " + str(current_loss)
        return round(average_loss, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcAverageGain(stock_code, date, period):
    global iterator_count
    price_changed = bd.getBasicData("PRICE_CHANGED", stock_code, date)
    current_gain = 0.0
    if price_changed > 0:
        current_gain = price_changed

    if iterator_count >= max_iterator:
        return calcFirstAverageGain(stock_code, date, period)
    else:
        iterator_count += 1
        average_gain = (calcAverageGain(stock_code, bd.getStockDate(stock_code, date, 1), period) * (
            period - 1) + abs(current_gain)) / period
        # print date + " Average Gain: " + str(average_gain) + " Current Gain: " + str(current_gain)
        return round(average_gain, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcOBV(stock_code, date, period):
    global ITERATOR_COUNT
    close_today = bd.getBasicData("CLOSE_TODAY", stock_code, date)
    close_pervious_day = bd.getBasicData("CLOSE_PERVIOUS_DAY", stock_code, date)
    volumn = bd.getBasicData("VOLUMN", stock_code, date)
    today_volumn = 0.0
    if close_today > close_pervious_day:
        today_volumn = volumn
    if close_today < close_pervious_day:
        today_volumn = today_volumn*-1

    if ITERATOR_COUNT >= MAX_ITERATOR:
        return today_volumn
    else:
        ITERATOR_COUNT = ITERATOR_COUNT + 1
        pday = bd.getStockDate(stock_code, date, 1)
        OBV = today_volumn + calcOBV(stock_code, pday, period)
        return round(OBV, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def analyze(stock_code, date, period):
    score = 0
    signal = ""
    pday = bd.getStockDate(stock_code, date, 1)

    ROC = getROC(stock_code, date)
    ROCMA = calcROCMA(stock_code, date, ROCMA_PARAM)
    ROCEMA = calcROCEMA(stock_code, date, ROCEMA_PARAM)

    ROC_pday = getROC(stock_code, pday)
    ROCMA_pday = calcROCMA(stock_code, pday, ROCMA_PARAM)
    ROCEMA_pday = calcROCEMA(stock_code, pday, ROCEMA_PARAM)

    ROCs = getROCs(stock_code, date, period)
    ROCMAs = getROCMAs(stock_code, date, period)
    ROCEMAs = getROCEMAs(stock_code, date, period)

    ROC_K = mu.getPoly(ROCs, 1)[0]
    ROCMA_K = mu.getPoly(ROCMAs, 1)[0]
    ROCEMA_K = mu.getPoly(ROCEMAs, 1)[0]

    if ROC < 0 and ROCEMA < 0 and ROCMA < 0:
        if ROC > ROC_pday:
            if ROC > ROCEMA and ROC > ROCEMA and ROC_pday < ROCEMA_pday and ROC_pday < ROCMA_pday:
                if (ROC - ROC_pday)/ROC_pday >= ROC_RAISE_RATE and (ROCMA - ROCMA_pday)/ROCMA_pday >= ROCMA_RAISE_RATE \
                        and (ROCEMA - ROCEMA_pday)/ROCEMA_pday >= ROCEMA_RAISE_RATE:
                    score += 1
                    signal += "[1]当ROC，ROCMA，ROCEMA三条线均小于零轴时，ROC迅速同时上穿ROCMA和ROCEMA两条线，而且ROCMA和ROCEMA两条线也处于缓缓上行中，为短线黑马买入信号;"

    if ROC > ROCMA > ROCEMA and ROC_K > ROCMA_K > ROCEMA_K:
        score += 1
        signal += "[1]当ROC，ROCMA，ROCEMA三条线是处于多头排列中，成交量处于间隙式放大或温和放大过程时，表明股价正运行于上升趋势中，仍有继续上涨趋势;"

    if ROC < ROCMA < ROCEMA and ROC_K < ROCMA_K < ROCEMA_K:
        score -= 1
        signal += "[-1]当ROC，ROCMA，ROCEMA三条线是处于空头排列中，表明股价正运行于下行趋势中，仍有继续下跌趋势;"
    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("ROC", str(score) + ";" + signal, stock_code, date)
    return [score, signal]

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
import BasicData as fd
from datetime import *
import DateUtil as du
import ROC

# Main function
if __name__ == '__main__':
    '''
    start_date = datetime.strptime("2016-02-01", '%Y-%m-%d')
    end_date = date.today()

    stocks = fd.getStocks(True)
    print stocks
    print "**********************************"
    stocks = fd.getStocks(False)
    print stocks
    print "**********************************"
    index = fd.getBasicData("0000001", start_date, end_date)
    print index
    print "**********************************"
    rf = fd.getRecoveryFactor("0600079", "600079", start_date)
    print rf
    print "**********************************"
    resultSet = ROC.getROC("000001", "2015-12-21")
    print resultSet[0][0]
    '''
    print du.convertDateToString(fd.getStockDate("000001", "2015-12-21", 1)[0][0], "%Y-%m-%d")

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def calcROCEMA(stock_code, date, period):
    pday = bd.getStockDate(stock_code, date, 1)
    ROC_today = getROC(stock_code, date)
    ROC_pday = getROC(stock_code, pday)
    ROCEMA = (2 * ROC_today + (period - 1) * ROC_pday) / (period + 1)
    return round(ROCEMA, 3)

# 需要导入模块: import BasicData [as 别名]
# 或者: from BasicData import getStockDate [as 别名]
def analyze(stock_code, date, period):
    score = 0.0
    signal = ""

    DMA = getDMA(stock_code, date)
    AMA = getAMA(stock_code, date)
    DMAs = getDMAs(stock_code, date, period)
    AMAs = getAMAs(stock_code, date, period)

    DMA_K1 = mu.getPoly(DMAs, 1)[0]
    AMA_K1 = mu.getPoly(AMAs, 1)[0]

    DMA_K2 = mu.getPoly(DMAs, 2)[0]
    AMA_K2 = mu.getPoly(AMAs, 2)[0]

    #1. DMA和AMA的值及线的运动方向
    if AMA > 0 and DMA > 0 and AMA_K1 > 0 and DMA_K1 > 0:
        score += 1
        signal += "[1]当DMA和AMA均大于0，并向上移动时，一般表示为股市处于多头行情中，可以买入或持股;"

    if AMA < 0 and DMA < 0 and AMA_K1 < 0 and DMA_K1 < 0:
        score -= 1
        signal += "[-1]当DMA和AMA均小于0, 并向下移动时，一般表示为股市处于空头行情中，可以卖出股票或观望;"

    if AMA > 0 and DMA > 0 and AMA_K2 > 0 and DMA_K2 > 0:
        score -= 1
        signal += "[-1]当DMA和AMA均大于0，但在经过一段比较长时间的向上运动后，如果两者同时从高位向下移动时，一般表示为股票行情处于退潮阶段，股票将下跌，可以卖出股票和观望;"

    if AMA < 0 and DMA < 0 and AMA_K1 < 0 and DMA_K1 < 0:
        score += 1
        signal += "[1]当DMA和AMA均小于0时，但在经过一段比较长时间的的向下运动后，如果两者同时从低位向上移动时，一般表示为短期行情即将启动，股票将上涨，可以短期买进股票或持股待涨;"

    close_in_period = bd.getBasicDataInPeriod("CLOSE_TODAY",stock_code, date, period)
    volumn_in_period = bd.getBasicDataInPeriod("VOLUMN", stock_code, date, period)
    close_K1 = mu.getPoly(close_in_period, 1)[0]
    volumn_K1 = mu.getPoly(volumn_in_period, 1)[0]

    #2. DMA曲线和股价曲线的配合使用
    if AMA < 0 and DMA < 0 and AMA_K1 > 0 and DMA_K1 > 0 and close_in_period > 0:
        score += 1
        signal += "[1]当DMA曲线与股价曲线从低位同步上升，表明空头力量已经衰弱、多头力量开始积聚，短期内股价有望止跌企稳，投资者应可以开始少量逢低买入;"

    if -1 <= AMA <= 1 and -1 <= DMA <= 1 and AMA_K1 > 0 and DMA_K1 > 0 and volumn_K1 > 0:
        score += 1
        signal += "[1]当DMA曲线与股价曲线从0值附近向上攀升时，表明多头力量开始大于空头力量，股价将在成交量的配合下，走出一波向上扬升的上涨行情。此时，投资者应逢低买入或坚决持股待涨;"

    pday = bd.getStockDate(stock_code, date, 1)
    DMA_pday = getDMA(stock_code, pday)
    AMA_pday = getAMA(stock_code, pday)

    #3. DMA线和AMA线的几次交叉情况
    if close_K1 < 0 and DMA_pday < AMA_pday and DMA > AMA:
        score += 1
        signal += "[1]当股价经过一段很长时间的下跌行情后，DMA线开始向上突破AMA线时，表明股市即将转强，股价跌势已经结束，将止跌朝上，可以开始买进股票，进行中长线建仓;"
    if close_K1 > 0 and DMA_pday > AMA_pday and DMA < AMA:
        score -= 1
        signal += "[-1]当股价经过前期一段很长时间的上升行情后，股价涨幅已经很大的情况下，一旦DMA线向下突破AMA时，表明股市即将由强势转为弱势，股价将大跌，这时应卖出大部分股票而不能买股票;"

    print DMA
    print DMA_pday
    print AMA
    print AMA_pday
    print score
    print signal.decode("utf-8").encode("gbk")
    bd.updateAnalysisData("DMA", str(score) + ";" + signal, stock_code, date)
    return [score, signal]