Example #1
0
def getNormalizedEstimatedPrice(market_trend, time_x=datetime.utcnow()):
    timeX = (toCryptsyServerTime(time_x) - epoch).total_seconds()
    estimatedPrice = estimateValue(timeX,
                                   market_trend.m, market_trend.n,
                                   market_trend.minX, market_trend.scalingFactorX,
                                   market_trend.minY, market_trend.scalingFactorY)
    normalizedEstimatedPrice = float(estimatedPrice) / 100000000
    return normalizedEstimatedPrice
Example #2
0
def plot_diagram(market_name, market_id):
    interval = timedelta(days=1, hours=4)
    cryptsy_mongo = CryptsyMongo(host="192.168.1.33")
    timeStart = datetime.utcnow() - interval
    cryptoCurrencyDataSamples = cryptsy_mongo.markets_collection.find(
        {"name": market_name, "lasttradetime": {"$gt": timeStart.strftime("%Y-%m-%d %H:%M:%S")}})
    tradeData = [(cryptoCurrencySample['lasttradetime'], cryptoCurrencySample['lasttradeprice']) for
                 cryptoCurrencySample in cryptoCurrencyDataSamples]
    uniqueTradeData = list(set(tradeData))
    uniqueTradeData = sorted(uniqueTradeData, key=(lambda x: x[0]))
    times = [(datetime.strptime(tradeDataSample[0], '%Y-%m-%d %H:%M:%S') - epoch).total_seconds()
             for tradeDataSample in uniqueTradeData]
    prices = [float(tradeDataSample[1]) for tradeDataSample in uniqueTradeData]
    trades = cryptsy_mongo.trades_collection.find(
        {"marketid": str(market_id), "datetime": {"$gt": timeStart.strftime("%Y-%m-%d %H:%M:%S")}})
    trade_samples = []
    for trade in trades:
        trade_samples.append(((datetime.strptime(trade['datetime'], '%Y-%m-%d %H:%M:%S') - epoch).total_seconds(),
                              float(trade['tradeprice']), trade['tradetype']))
    buy_trade_times = [trade_sample[0] for trade_sample in trade_samples if trade_sample[2] == 'Buy']
    buy_trade_price = [trade_sample[1] for trade_sample in trade_samples if trade_sample[2] == 'Buy']
    sell_trade_times = [trade_sample[0] for trade_sample in trade_samples if trade_sample[2] == 'Sell']
    sell_trade_price = [trade_sample[1] for trade_sample in trade_samples if trade_sample[2] == 'Sell']

    times_x = []
    prices_y = []
    market_trend = cryptsy_mongo.calculateMarketTrend(market_name, market_id)
    for hour in range(0, 24):
        time_x = datetime.utcnow() - timedelta(hours=hour)
        price_y = getNormalizedEstimatedPrice(market_trend, time_x)
        times_x.append((toCryptsyServerTime(time_x) - epoch).total_seconds())
        prices_y.append(price_y)

    plt.plot(times, prices)
    plt.plot(buy_trade_times, buy_trade_price, 'ro')
    plt.plot(sell_trade_times, sell_trade_price, 'go')
    plt.plot(times_x, prices_y, 'ko')
    plt.savefig("{}.png".format("{}-{}".format(market_name.replace('/', '-'), market_id)), format='png')
    plt.close()
Example #3
0
 def test_toCryptsyServerTime(self):
     now = datetime.now()
     cryptsy_time = toCryptsyServerTime(now)
     self.assertEqual(cryptsy_time, now - timedelta(hours=CRYPTSY_HOURS_DIFFERENCE))
def investBTC(btcBalance, active_markets, markets):
    market_names = [market for market in markets]

    btcMarketNames = filter(lambda x: 'BTC' in x and 'Points' not in x, market_names)

    logger.debug("activeMarkets: {}".format(active_markets))

    inactive_btc_markets = filter(lambda x: int(markets[x]) not in active_markets, btcMarketNames)

    logger.debug("inactive_btc_markets: {}".format(
        [int(markets[inactive_btc_market]) for inactive_btc_market in inactive_btc_markets]))

    market_trends, marketIds = getMarketTrends(inactive_btc_markets, markets)

    sorted_market_trends = sorted(market_trends, key=lambda x: abs(0.0 - x.m))

    sorted_market_trend_ids = [x.marketId for x in sorted_market_trends]

    logger.info("sorted_market_trend_ids: {}".format(sorted_market_trend_ids))

    avg_filtered_market_trends = filter(lambda x: x.m != 0.0 and x.m >= -0.1 and x.avg >= 0.000001,
                                        sorted_market_trends)

    avg_filtered_market_trends_ids = [x.marketId for x in avg_filtered_market_trends]

    logger.debug("avg_filtered_market_trends_ids: {}".format(avg_filtered_market_trends_ids))

    # sorted_market_trends_to_bet_on = filter(lambda x: x.std > (x.avg * FEE + x.avg * DESIRED_EARNING),
    # avg_filtered_market_trends)

    # sorted_market_trends_to_bet_on = filter(lambda x: x.std > 2 * (x.avg * FEE), avg_filtered_market_trends)
    sorted_market_trends_to_bet_on = avg_filtered_market_trends

    sorted_market_trends_to_bet_on_ids = [x.marketId for x in sorted_market_trends_to_bet_on]

    logger.info("sorted_market_trends_to_bet_on_ids: {}".format(sorted_market_trends_to_bet_on_ids))

    best_markets_last_3h = cryptsy_mongo.getBestPerformingMarketsFrom(
        toCryptsyServerTime(datetime.utcnow() - timedelta(hours=3)))

    logger.debug("best_markets_last_3h: {}".format(best_markets_last_3h))

    worst_markets_last_30m = cryptsy_mongo.getWorstPerformingMarketsFrom(
        toCryptsyServerTime(datetime.utcnow() - timedelta(minutes=30)))

    logger.debug("worst_markets_last_30m: {}".format(worst_markets_last_30m))

    worst_performing_markets = [int(market_id) for market_id in set(worst_markets_last_30m)]

    logger.info("worst_performing_markets: {}".format(worst_performing_markets))

    best_performing_markets = [int(market) for market in best_markets_last_3h if
                               int(market) not in worst_performing_markets]

    logger.info("best_performing_markets: {}".format(best_performing_markets))

    logger.info("marketIds: {}".format(marketIds))

    logger.info("userMarketIds: {}".format(userMarketIds))

    suggested_market_ids = filter(lambda x: x in marketIds, userMarketIds) + filter(lambda x: x in marketIds,
                                                                                    best_performing_markets)

    suggested_market_trends = []

    for market_id in suggested_market_ids:
        for market_trend in market_trends:
            if int(market_trend.marketId) == market_id:
                suggested_market_trends.append(market_trend)

    other_sorted_market_trends = filter(
        lambda x: int(x.marketId) not in suggested_market_ids and int(x.marketId) not in worst_performing_markets,
        sorted_market_trends_to_bet_on)

    marketTrendsToInvestOn = suggested_market_trends + other_sorted_market_trends

    market_multipliers = cryptsy_mongo.getMarketsMultipliers()

    logger.info("Buy - Markets Multiplier: {}".format(market_multipliers))

    for market_trend in marketTrendsToInvestOn:

        if btcBalance < MINIMUM_AMOUNT_TO_INVEST:
            break

        market_multiplier = market_multipliers[
            market_trend.marketId] if market_trend.marketId in market_multipliers else 0

        # logger.info(
        # "Buy - {}({}) multiplier: {}".format(market_trend.marketName, market_trend.marketId, market_multiplier))

        if int(market_trend.marketId) in userMarketIds:
            desiredAmountToInvest = TEST_STAKE
        elif market_multiplier > 0:
            desiredAmountToInvest = BASE_STAKE * market_multiplier
        elif market_multiplier == 0:
            desiredAmountToInvest = TEST_STAKE
        elif market_multiplier < 0:
            desiredAmountToInvest = TEST_STAKE
        else:
            desiredAmountToInvest = TEST_STAKE

        amountToInvest = min(desiredAmountToInvest, btcBalance)

        one_hour_trend = getMarketTrendFor(market_trend.marketName, market_trend.marketId, 1)

        two_hours_trend = getMarketTrendFor(market_trend.marketName, market_trend.marketId, 2)

        three_hours_trend = getMarketTrendFor(market_trend.marketName, market_trend.marketId, 3)

        if three_hours_trend.m == 0.0 or three_hours_trend.m < 0.0 or three_hours_trend.num_samples < 25:
            logger.info(
                "Buy - REJECTED - {}({}) has m: {} and number samples: {}".format(three_hours_trend.marketName,
                                                                                  three_hours_trend.marketId,
                                                                                  three_hours_trend.m,
                                                                                  three_hours_trend.num_samples))
            continue
        elif two_hours_trend.m > one_hour_trend.m < 0.3:
            logger.info(
                "Buy - REJECTED - {}({}) has 3h-2h-1h: {}, {}, {} ".format(three_hours_trend.marketName,
                                                                           three_hours_trend.marketId,
                                                                           three_hours_trend.m,
                                                                           two_hours_trend.m,
                                                                           one_hour_trend.m))
            continue

        buyPrice = getBuyPrice(three_hours_trend)

        quantity = calculateQuantity(amountToInvest, FEE, buyPrice)

        if buyPrice <= 0.0 or quantity <= 0.0:
            logger.info(
                "Buy - REJECTED - {}({}) quantity: {} price: {}.".format(market_trend.marketName, market_trend.marketId,
                                                                         quantity,
                                                                         toEightDigit(buyPrice)))
            continue

        logger.info(
            "Buy - PLACING - {}({}) quantity: {}, price: {}".format(three_hours_trend.marketName,
                                                                    three_hours_trend.marketId,
                                                                    quantity,
                                                                    toEightDigit(buyPrice)))

        responseBody, apiCallSucceded = cryptsyClient.placeBuyOrder(market_trend.marketId, quantity, buyPrice)
        if apiCallSucceded:
            btcBalance -= amountToInvest
Example #5
0
def main(argv):
    global public
    global private

    getEnv(argv)

    global cryptsy_client
    cryptsy_client = CryptsyPy(public, private)
    # cryptsy_mongo = CryptsyMongo(host="192.168.1.33")
    cryptsy_mongo = CryptsyMongo()

    recent_market_trends = cryptsy_mongo.getRecentMarketTrends()

    recent_trades = cryptsy_client.getRecentTrades()
    if recent_trades is not None:
        cryptsy_mongo.persistTrades(recent_trades)

    if hours is not None:
        start_time = toCryptsyServerTime(datetime.utcnow() - timedelta(hours=int(hours)))
    else:
        now = datetime.utcnow()
        start_time = toCryptsyServerTime(datetime(now.year, now.month, now.day))

    total_buy_best = 0.0
    total_sell_best = 0.0
    total_fee_best = 0.0
    print "Best markets:"
    mongotradeStats = cryptsy_mongo.getAllTradesFrom(start_time)
    filteredTradeStats = filter(
        lambda x: mongotradeStats[x]['Sell'] >= mongotradeStats[x]['Fee'] + mongotradeStats[x]['Buy'],
        mongotradeStats)
    sortedTradeStats = sorted(filteredTradeStats,
                              key=lambda x: mongotradeStats[x]['Sell'] - mongotradeStats[x]['Buy'] - mongotradeStats[x][
                                  'Fee'],
                              reverse=True)

    for tradeStat in sortedTradeStats:
        sell = float(mongotradeStats[tradeStat]['Sell'])
        buy = float(mongotradeStats[tradeStat]['Buy'])
        fee = float(mongotradeStats[tradeStat]['Fee'])

        total_buy_best += buy
        total_sell_best += sell
        total_fee_best += fee

        std = next((toEightDigit(market_trend.std) for market_trend in recent_market_trends if
                    int(market_trend.marketId) == int(tradeStat)), None)
        print "MarketId: {}, Std:{}, Sell: {}, Buy: {}, Earn: {}".format(tradeStat, std,
                                                                         toEightDigit(sell), toEightDigit(buy),
                                                                         toEightDigit(sell - buy - fee))

    print "Best markets total: buy: {}, sell: {}, fee:{} - earnings: {}".format(total_buy_best, total_sell_best,
                                                                                total_fee_best,
                                                                                total_sell_best - total_buy_best - total_fee_best)

    total_buy_worst = 0.0
    total_sell_worst = 0.0
    total_fee_worst = 0.0
    print "Worst markets:"
    mongotradeStats = cryptsy_mongo.getAllTradesFrom(start_time)
    filteredTradeStats = filter(
        lambda x: 0 < mongotradeStats[x]['Sell'] < mongotradeStats[x]['Fee'] + mongotradeStats[x]['Buy'],
        mongotradeStats)
    sortedTradeStats = sorted(filteredTradeStats,
                              key=lambda x: mongotradeStats[x]['Sell'] - mongotradeStats[x]['Buy'] - mongotradeStats[x][
                                  'Fee'])

    for tradeStat in sortedTradeStats:
        sell = float(mongotradeStats[tradeStat]['Sell'])
        buy = float(mongotradeStats[tradeStat]['Buy'])
        fee = float(mongotradeStats[tradeStat]['Fee'])

        total_buy_worst += buy
        total_sell_worst += sell
        total_fee_worst += fee

        std = next((toEightDigit(market_trend.std) for market_trend in recent_market_trends if
                    int(market_trend.marketId) == int(tradeStat)), None)
        print "MarketId: {}, Std:{}, Sell: {}, Buy: {}, Earn: {}".format(tradeStat, std,
                                                                         toEightDigit(sell), toEightDigit(buy),
                                                                         toEightDigit(sell - buy - fee))

    print "Worst markets total: buy: {}, sell: {}, fee:{} - earnings: {}".format(total_buy_worst, total_sell_worst,
                                                                                 total_fee_worst,
                                                                                 total_sell_worst - total_buy_worst - total_fee_worst)

    print "Total stats: total earning: {}".format(
        (total_sell_best + total_sell_worst) - (total_buy_best + total_buy_worst + total_fee_best + total_fee_worst))