V2EX = way to explore
V2EX 是一个关于分享和探索的地方
现在注册
已注册用户请  登录
RaboXie
V2EX  ›  Bitcoin

有玩比特币 自动化套利的么? okcoin 平台,我们进来聊聊哟

  •  
  •   RaboXie · 2016-05-06 17:14:53 +08:00 · 4290 次点击
    这是一个创建于 3159 天前的主题,其中的信息可能已经有所发展或是发生改变。

    用的开源软件为 http://galts-gulch.github.io/avarice/ 现在模拟套利,发现 Indicators 的组合有太多需要研究的东东,有老司机来带带路和讨论下么

    10 条回复    2016-06-29 15:14:48 +08:00
    GhostEX
        1
    GhostEX  
       2016-05-06 17:24:52 +08:00 via iPhone
    比特币这东西已经过时很久了吧 还套利...
    RaboXie
        2
    RaboXie  
    OP
       2016-05-06 17:26:42 +08:00
    @GhostEX 你不懂, 51 一波小行情, 2w 就赚了 7000 ,这叫过时?
    GhostEX
        3
    GhostEX  
       2016-05-06 20:26:43 +08:00 via iPhone
    @RaboXie 哦 我去年套一次分级盈利十万
    timothyye
        4
    timothyye  
       2016-05-06 20:40:48 +08:00 via Android
    楼上都是壕
    frienmo
        5
    frienmo  
       2016-05-07 04:22:36 +08:00
    炒比特币还需要研究?闭着眼睛买多就可以了。
    RaboXie
        6
    RaboXie  
    OP
       2016-05-07 08:44:09 +08:00
    @frienmo 短线啊,不是定投
    h4x3rotab
        7
    h4x3rotab  
       2016-05-07 12:50:26 +08:00 via iPhone
    感兴趣,观望
    RaboXie
        8
    RaboXie  
    OP
       2016-05-08 16:50:04 +08:00
    Supported Indicators
    SMA (Simple Movement Average)
    NOTE: We support two SMA trade strategies specified in genconfig.SMA.IndicatorStrategy; "CD" (convergence/divergence), and "Diff" (waits to pass up or down diff threshold before trend is determined)
    Does two calculations off SMAShortPeriod and SMALongPeriod
    SMA = (Sum of last SMAPeriod candles) / SMAPeriod
    SMADiff = 100 * (shortSMA - longSMA) / ((shortSMA + longSMA) / 2)
    EMA (Exponential Movement Average)
    NOTE: We support two EMA trade strategies specified in genconfig.EMA.IndicatorStrategy; "CD" (convergence/divergence), and "Diff" (waits to pass up or down diff threshold before trend is determined
    We trade this as a crossover (convergence/divergence) indicator. This is one of our supported EMA trade strategies. On 10/21, when EMA10 \< EMA21, we sell (and visa versa). Differs from MACD due to lack of third signal line.
    NOTE: does two calculations using EMAShort and EMALong.
    The first iteration uses SMA to generate the first EMA.
    Multiplier = (2 / EMAPeriod) + 1
    EMA = ((Current Close - Previous EMA) * Multiplier) + Previous EMA
    EMADiff = 100 * (shortEMA - longEMA) / ((shortEMA + longEMA) / 2)
    EMAwbic (Exponential Movement Average using @wbic16 logic)
    NOTE: it's recommended to set genconfig's SingleTrade to False, and lower TradeVolume if acting as the only indicator. When used with other indicators, it aids in mean reversion confirmation.
    This buys when the price is \< Bid Percent of the EMA, and sells when the price is > Ask Percent of the EMA.
    DEMA (Double Exponential Movement Average)
    NOTE: We support two DEMA trade strategies specified in genconfig.DEMA.IndicatorStrategy; "CD" (convergence/divergence), and "Diff" (waits to pass up or down diff threshold before trend is determined
    Similar points as the "EMA" section above, however with more of a weight on the last EMA (LOWER LATENCY THAN EMA).
    DEMA = 2 * EMA – EMA(EMA)
    DEMADiff = 100 * (shortDEMA - longDEMA) / ((shortDEMA + longDEMA) / 2)
    FRAMA (Fractal Adaptive Moving Average)
    NOTE: We support two FRAMA trade strategies specified in genconfig.FRAMA.IndicatorStrategy; "CD" (convergence/divergence), and "Diff" (waits to pass up or down diff threshold before trend is determined
    N = (highest price - lowest price) / period ; split into 3 periods - first half, second half, full period.
    D = (Log(N1 + N2) - Log(N3)) / Log(2)
    Alpha = exp(-4.6 * (D-1))
    FRAMA = Alpha * Price + (1 - Alpha) * LastFRAMA
    FRAMADiff = 100 * (shortFRAMA - longFRAMA) / ((shortFRAMA + longFRAMA) / 2)
    MACD (Moving Average Convergence-Divergence)
    NOTE: We support two MACD trade strategies specified in genconfig.MACD.IndicatorStrategy; "CD" (convergence/divergence), and "Diff".
    CD: When MACD \< signal, we sell (and visa versa).
    Diff: Traditionally, this MACD strategy would sell if MACD goes below zero line (and visa versa). We do the same, but for MACDDiffUp and MACDDiffDown for fewer false positives (recommend configuring as you see fit).
    MACD = MACDShortEMA - MACDLongEMA
    MACDSignal = MACDSignal period EMA of MACD
    DMACD (Double Moving Average Convergence-Divergence)
    We use MACDLong, MACDShort, and MACDPeriod settings for DMACD
    NOTE: We support two DMACD trade strategies specified in genconfig.DMACD.IndicatorStrategy; "CD" (convergence/divergence), and "Diff".
    Similar to the MACD section above, except we use DEMAs instead of EMAs (yes, even on signal). See DEMA above if unsure what this means.
    RSI (Relative Strength Index Oscillator)
    NOTE: avg gains and losses are smoothed after first iteration
    NOTE: Want to try out RSI(2) or RSI(3)? Set those periods (2 or 3), and run 90/10 or 95/5 as ask/bid thresholds.
    RS = avg_gain / avg_loss
    RSI = 100 - (100 / (1 + RSI))
    FastStochRSI (Stochastic RSI Oscillator)
    NOTE: lowest/highest are from RSIPeriod
    FastStochRSIK = ((RSI - Lowest RSI) / (Highest RSI - Lowest RSI)) * 100
    FastStochRSID = FastStochRSIDPeriod SMA of FastStochRSIK
    FullStochRSID
    NOTE: We support two FullStochRSID trade strategies specified in genconfig.FullStochRSID.IndicatorStrategy. "CD" uses convergence/divergence of FastStochRSID. "Diff" uses standard bid/ask.
    FullStochasticRSID = FullStochRSIDPeriod SMA of FastStochRSID
    FastStochK (Fast Stochastic Oscillator %K)
    FastStochasticK = ((Current Close - Low) / (High - Low)) * 100
    FastStochD
    FastStochasticD = FastStochDPeriod SMA of %K
    FullStochD
    NOTE: FullStochK is not includes since it's equivalent to FastStochD
    FullStochasticD = FullStochDPeriod SMA of Fast %D
    KDJ
    NOTE: Uses new FullStoch %K and FullStoch %D calculations.
    NOTE: Supports both CD and Diff in genconfig.KDJ.IndicatorStrategy.
    CD: When K \< D, we sell (and visa versa)
    Diff: When J is above KDJJAsk, we sell. When J is below KDJJBid, we buy. J may go above and below 100 and 0.
    J = (3 * D) - (2 * K)
    Aroon (Aroon Oscillator)
    NOTE: Supports both CD and Diff in genconfig.Aroon.IndicatorStrategy.
    CD: When AroonOscillator \< 0, we sell (and visa versa). This is because when AroonOscillator is 0, AroonUp and AroonDown converge/diverge.
    Diff: When Aroon is below AroonBid, we buy. When Aroon is above AroonAsk, we sell.
    AroonUp = 100 * ((AroonPeriod - Candles since last AroonPeriod high) / AroonPeriod)
    AroonDown = 100 * ((AroonPeriod - Candles since last AroonPeriod low) / AroonPeriod)
    Aroon = AroonUp - AroonDown
    Ichimoku (Ichimoku Cloud)
    NOTE: Utilizes Ichimoku.IndicatorStrategy for Strong, Optimized, Weak, and CloudOnly strategies.
    NOTE: Chikou Span's cool and all, but we don't care. We want to trade in real time, and a price list 26 periods behind only confirms if we were right or wrong. Because proper Ichimoku cloud relies on Senkou Span A being plotted ChikouSpan periods in the future, we still set this integer.
    Strong: Buy if (price > Ichimoku cloud min) and (price \< Kijun-Sen) and (price > Tenkan-Sen). Sell if (price \< Ichimoku cloud max) and (price > Kijun-Sen) and (price \< Tenkan-Sen).
    Optimized: Buy if (Price > Ichimoku cloud min) and ((Tenkan-Sen > Kijun-Sen)). Sell if (Price \< Ichimoku cloud max) and ((Kijun-Sen > Tenkan-Sen)).
    Weak: Buy if (Tenkan-Sen > Kijun-Sen). Sell on the inverse. Weak is more of a standard crossover strategy.
    CloudOnly: Doesn't support persistence. This is designed for quick and early entries and exits when price hits the cloud. A full price crossover across the bottom and top of the cloud will generate two signals.
    Tenkan-sen = (TenkanSenPeriod high + TenkanSenPeriod low)/2))
    Kijun-sen = (KijunSenPeriod high + KijunSenPeriod low)/2))
    Senkou Span A = (Tenkan-sen + Kijun-sen)/2)) ; Plotted ChikouSpanPeriods in the future.
    Senkou Span B = (SenkouSpanPeriod high + SenkouSpanPeriod low)/2))
    StdDev (Sampled Standard Deviation)
    Only functional when combined with a non-volatility indicator
    The following is ripped/edited from stockcharts.com since it summarizes the Std Dev calculations quite well:
    Calculate the average (mean) price for the number of periods or observations.
    Determine each period's deviation (close less average price).
    Square each period's deviation.
    Sum the squared deviations.
    Divide this sum by the number of samples.
    The standard deviation is then equal to the square root of that number.
    BollBands (Bollinger Bands)
    Only here for custom written strategies
    Middle Band = BollBandPeriod SMA
    Upper Band = BollBandPeriod SMA + (BollBandPeriod StdDev * 2)
    Lower Band = BollBandPeriod SMA - (BollBandPeriod StdDev * 2)
    BollBandwidth (Bollinger Bandwidth)
    Only functional when combined with a non-volatility indicator
    Threshold should be tested before usage. The Bandwidth changes wildly on different candle sizes. To see values ot get an idea of a good configuration, set:

    VerboseIndicators = ['BollBandwidth']
    BollBandwidth = (Upper Band - Lower Band)/Middle Band

    ATR (Average True Range)
    Only functional when combined with a non-volatility indicator
    Threshold should be tested before usage. Wilder used 20 and 10, however he also used 1 day periods. To see values to get an idea of a good configuration, set:

    VerboseIndicators = ['ATR']
    Uses Wilder's MA instead of EMA like tradingview.

    true range=max[(high - low), abs(high - previous close), abs (low - previous close)]
    ATR is Wilder's MA of true range values.
    ChandExit (Chandelier Exit)
    Only should be used as a combined indicator
    Must run long enough for price to cross short or long exits to determine which to use.
    This is a good combined to rule out false signals if a trend is still persisting. This may also be used as a stop loss indicator later in development (TODO).
    Chandelier Exit (long) = Period High - ATR(Period) x Multiplier
    Chandelier Exit (short) = Period Low + ATR(Period) x Multiplier
    DMI (Directional Movement)/ADX
    'Volatility' is functional when combined with a non-volatility indicator. 'Full' may be used independently as a full indicator.
    Threshold should be tested before usage. Wilder used 25, however he also used 1 day periods. To see values to get an idea of a good configuration, while on 'Volatility', set:

    VerboseIndicators = ['DMI']
    UpMove = Current High - Previous High

    DownMove = Current Low - Previous Low
    If UpMove > DownMove and UpMove > 0, then +DM = UpMove, else +DM = 0
    +DI = Wilder's MA of (+DM / Average True Range)
    +DI = Wilder's MA of (-DM / Average True Range)
    ADX = Wilder's MA of the Absolute Value of (+DI- -DI) / (+DI + -DI)
    In 'Full', ADX with threshold is used as a volatility filter, and +DI/-DI crossovers are used to determine trend.
    SROC (Simple Rate of Change AKA Movement)
    SROC = (Close - Close n periods ago)
    if current SROC > 0, and previous SROC \<= 0, BUY. Sell during the inverse.
    gaoqr2001
        9
    gaoqr2001  
       2016-05-12 21:26:26 +08:00
    怎么 RUN?
    pheyer
        10
    pheyer  
       2016-06-29 15:14:48 +08:00
    看了一下, avarice 已经不维护了
    关于   ·   帮助文档   ·   博客   ·   API   ·   FAQ   ·   实用小工具   ·   1835 人在线   最高记录 6679   ·     Select Language
    创意工作者们的社区
    World is powered by solitude
    VERSION: 3.9.8.5 · 23ms · UTC 16:15 · PVG 00:15 · LAX 08:15 · JFK 11:15
    Developed with CodeLauncher
    ♥ Do have faith in what you're doing.