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Volume Energy Driven Strategy

Author: ChaoZhang, Date: 2024-01-04 15:38:54
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Overview

The volume energy driven strategy judges the sentiment changes of the market participants by analyzing the changes of trading volume. It divides trading volume into bullish volume and bearish volume, calculates their weighted moving average, generates bullish signals when bullish volume dominates, and generates bearish signals when bearish volume dominates.

Strategy Logic

The strategy first divides the trading volume of each candlestick into bullish volume and bearish volume based on the relationship between the closing price and opening price. If the closing price is greater than the opening price, the entire trading volume of the candlestick is bullish volume. If the closing price is less than the opening price, the bullish volume is calculated according to the ratio of (highest price - opening price) / (highest price - lowest price), and the remaining is bearish volume.

Then it calculates the weighted moving average of bullish and bearish volume of the last n candlesticks respectively. If the moving average of bullish volume is greater than bearish volume, and their difference divided by bullish volume is greater than a preset threshold, a bullish signal is generated. The rule for generating bearish signals is similar.

It also sets a baseline with average trading volume to identify consolidation zones. If there is no significant difference between bullish and bearish volume, it indicates that the market is currently in consolidation.

Advantage Analysis

  • Use volume information to judge market participants’ sentiment with theoretical basis
  • Automatically identify consolidation zones to avoid missing important signals
  • Customizable parameters adapt to different trading products and timeframes
  • Can identify bullish and bearish signals separately or follow one side only

Risk Analysis

  • Trading volume data can be manipulated
  • Default parameters may not suit all products, optimization needed
  • Improper consolidation identification parameters may miss signals
  • False signals may occur in short periods

Methods like parameter optimization and combining with other indicators can help reduce risks.

Optimization Directions

  • Test different methods of calculating trading volume
  • Try different types of moving averages, like EMA, SMMA etc
  • Optimize the period of calculating average volume
  • Optimize parameters for identifying consolidation
  • Combine with other technical indicators to filter signals

Summary

The volume energy driven strategy intelligently judges the distribution of bullish and bearish trading volume to determine market sentiment and trend changes. It can be used alone or combined with other strategies. Further improvements on stability and profitability can be achieved through parameter optimization and indicator combination.


/*backtest
start: 2022-12-28 00:00:00
end: 2024-01-03 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Shuttle_Club
//@version=5

strategy('Volume fight strategy', default_qty_type=strategy.cash, default_qty_value=10000, currency='USD', commission_value=0.04, calc_on_order_fills=false, calc_on_every_tick=false, initial_capital=10000)

direction = input.string('ANY', 'Direction', options=['LONG', 'SHORT', 'ANY'], tooltip='Select the direction of trade.\n\nВыберите направление торговли.')
ma = input.int(11, 'Search_range', minval=1, tooltip='The range of estimation of the predominance of bullish or bearish volume (quantity bars). The smaller the TF, the higher the range value should be used to filter out false signals.\n\nДиапазон оценки преобладания бычьего или медвежьего объема (количество баров). Чем меньше ТФ, тем выше следует использовать значение диапазона, чтобы отфильтровать ложные сигналы.')
delta = input.float(15, 'Smoothing_for_flat,%', step=0.5, minval=0, tooltip='Smoothing to reduce false signals and highlight the flat zone. If you set the percentage to zero, the flat zones will not be highlighted, but there will be much more false signals, since the indicator becomes very sensitive when the smoothing percentage decreases.\n\nСглаживание для уменьшения ложных сигналов и выделения зоны флета. Если выставить процент равным нулю, то зоны флета выделяться не будут, но будет гораздо больше ложных сигналов, так как индикатор становится очень чувствительным при снижении процента сглаживания')
bgshow = input.bool(true, 'Show background zones', tooltip='Show the color background of the current trading zone.\n\nПоказывать цветовой фон текущей торговой зоны.')
all_signal_show = input.bool(false, 'Show each setup in zone', tooltip='Show every signals into trading zone.\n\nПоказывать каждый сигнал внутри торговой зоны.')

/////   CALCULATION
bull_vol = open < close ? volume : volume * (high - open) / (high - low)  //determine the share of bullish volume
bear_vol = open > close ? volume : volume * (open - low) / (high - low)  //determine the share of bearish volume
avg_bull_vol = ta.vwma(bull_vol, ma)  //determine vwma
avg_bear_vol = ta.vwma(bear_vol, ma)
diff_vol = ta.sma(avg_bull_vol / volume - 1 - (avg_bear_vol / volume - 1), ma)  //normalize and smooth the values
vol_flat = math.abs(avg_bull_vol + avg_bear_vol) / 2  //determine average value for calculation flat-filter

/////   SIGNALS
up = int(na), up := nz(up[1])
dn = int(na), dn := nz(dn[1])
bull = avg_bull_vol > avg_bear_vol and vol_flat / avg_bull_vol < 1 - delta / 100  //determine up zones
bear = avg_bull_vol < avg_bear_vol and vol_flat / avg_bear_vol < 1 - delta / 100  //determine dn zones

if bull
    up += 1, dn := 0
    dn
if bear
    dn += 1, up := 0
    up
if not bull and not bear and all_signal_show
    up := 0, dn := 0
    dn

/////   PLOTTING
plotshape(bull and up == 1, 'UP', location=location.bottom, style=shape.triangleup, color=color.new(color.green, 0), size=size.tiny)
plotshape(bear and dn == 1, 'DN', location=location.top, style=shape.triangledown, color=color.new(color.red, 0), size=size.tiny)
bgcolor(title='Trading zones', color=bgshow and avg_bull_vol > avg_bear_vol and vol_flat / avg_bull_vol < 1 - delta / 100 ? color.new(color.green, 85) : bgshow and avg_bull_vol < avg_bear_vol and vol_flat / avg_bear_vol < 1 - delta / 100 ? color.new(color.red, 85) : na)
plot(diff_vol, 'Volume difference', style=plot.style_area, color=avg_bull_vol > avg_bear_vol and vol_flat / avg_bull_vol < 1 - delta / 100 ? color.new(color.green, 0) : avg_bull_vol < avg_bear_vol and vol_flat / avg_bear_vol < 1 - delta / 100 ? color.new(color.red, 0) : color.new(color.gray, 50))

strategy.close('Short', comment='close', when=bull and up == 1)
strategy.close('Long', comment='close', when=bear and dn == 1)
strategy.entry('Long', strategy.long, when=direction != 'SHORT' and bull and up == 1)
strategy.entry('Short', strategy.short, when=direction != 'LONG' and bear and dn == 1)

if bull and up==1
    alert('Bullish movement! LONG trading zone', alert.freq_once_per_bar_close)
if bear and dn==1
    alert('Bearish movement! SHORT trading zone', alert.freq_once_per_bar_close)
    

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