RedK成交量加速定向能量比
Author: 雨幕（youquant）, Date: 2022-05-19 11:06:51Tags: WMAEMAsma
成交量加速定向能量比（VADER）利用价格变动（位移）和相关成交量（力度）来估计幕后的正（买入）和负（卖出）“能量”，使交易者能够更详细地“解读市场行为”，并相应地调整其交易决策。
VADER是怎么工作的？ 我一直是技术分析概念的粉丝，这些概念很简单，并且将价格行为和交易量结合在一起——维德背后的概念其实很简单。
让我们来看看它，避免太过技术化： 与大宗交易相关的大宗价格变动意味着买家（如果涨价）或卖家（如果涨价）都是认真的，并且“控制”了交易 另一方面，当价格波动很小但成交量很大时，这意味着在买入和卖出之间存在一场斗争，或更多的能量平衡。 此外，当大宗价格变动与相对有限的成交量相关联时，买家或卖家都缺乏“能量”——像这样的变动通常是短暂的。
与VADER的类比是，我们将价格波动（2 bar之间的收盘变化）视为位移（或动作结果），将相关的交易量视为该动作背后的“作用力”——将位移和作用力这两个值结合在一起，为我们提供了潜在能量（在特定方向）的表示或代理。 当两个值（位移和作用力）都较高时，则产生的能量较高-如果其中一个值较低，则产生的能量较低。
然后，我们取每个方向上的相对能量的平均值（正=买入，负=卖出），并计算净能量。
请注意，我们是从交易的角度来进行类比，而不是从物理学的角度：）–我们需要明白，物理学中的能量计算是不同的。
/*backtest
start: 2022-04-19 09:00:00
end: 2022-05-18 15:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_CTP","currency":"FUTURES"}]
args: [["ContractType","rb888",360008]]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © RedKTrader
//@version=5
indicator('RedK Volume-Accelerated Directional Energy Ratio', 'RedK VADER v3.0', precision=0, timeframe='', timeframe_gaps=false)
// ***********************************************************************************************************
// Choose volume calculation method.. Relative vs full.
// Relative magnifies effect of recent volume spikes (up or down)
f_RelVol(_value, _length) =>
min_value = ta.lowest(_value, _length)
max_value = ta.highest(_value, _length)
ta.stoch(_value, max_value, min_value, _length) / 100
// ***********************************************************************************************************
// ***********************************************************************************************************
// Choose MA type for the base DER calculation ..
// WMA is my preference and is default .. SMA is really slow and lags a lot - but added for comparison
f_derma(_data, _len, MAOption) =>
value =
MAOption == 'SMA' ? ta.sma(_data, _len) :
MAOption == 'EMA' ? ta.ema(_data, _len) :
ta.wma(_data, _len)
// ***********************************************************************************************************
// ===========================================================================================================
// Inputs
// ===========================================================================================================
price = close
length = input.int(6, '周期', minval=1)
DER_avg = input.int(5, '均值', minval=1, inline='DER', group='方向能量比')
MA_Type = input.string('WMA', 'DER MA 类型', options=['WMA', 'EMA', 'SMA'], inline='DER', group='方向能量比')
smooth = input.int(3, '平滑', minval=1, inline='DER_1', group='方向能量比')
show_senti = input.bool(false, '显示观点', inline='DER_s', group='方向能量比')
senti = input.int(20, '观点周期', minval=1, inline='DER_s', group='方向能量比')
v_calc = input.string('Relative', '计算选项', options=['Relative', 'Full', 'None'], group='成交量参数')
vlookbk = input.int(10, '回看周期 (相对的)', minval=1, group='成交量参数')
// ===========================================================================================================
// Calculations
// ===========================================================================================================
// Volume Calculation Option -- will revert to no volume acceleration for instruments with no volume data
vola =
v_calc == 'None' or na(volume) ? 1 :
v_calc == 'Relative' ? f_RelVol(volume, vlookbk) :
volume
R = (ta.highest(2) - ta.lowest(2)) / 2 // R is the 2-bar average bar range - this method accomodates bar gaps
sr = ta.change(price) / R // calc ratio of change to R
rsr = math.max(math.min(sr, 1), -1) // ensure ratio is restricted to +1/-1 in case of big moves
c = fixnan(rsr * vola) // add volume accel -- fixnan adresses cases where no price change between bars
c_plus = math.max(c, 0) // calc directional vol-accel energy
c_minus = -math.min(c, 0)
// plot(c_plus)
// plot(c_minus)
avg_vola = f_derma(vola, length, MA_Type)
dem = f_derma(c_plus, length, MA_Type) / avg_vola // directional energy ratio
sup = f_derma(c_minus, length, MA_Type) / avg_vola
adp = 100 * ta.wma(dem, DER_avg) // average DER
asp = 100 * ta.wma(sup, DER_avg)
anp = adp - asp // net DER..
anp_s = ta.wma(anp, smooth)
// Calculate Sentiment - a VADER for a longer period and can act as a baseline (compared to a static 0 value)
// note we're not re-calculating vol_avg, demand or supply energy for sentiment. this would've been a different approach
s_adp = 100 * ta.wma(dem, senti) // average DER for sentiment length
s_asp = 100 * ta.wma(sup, senti)
V_senti = ta.wma(s_adp - s_asp, smooth)
// ===========================================================================================================
// Colors & plots
// ===========================================================================================================
c_adp = color.new(color.aqua, 30)
c_asp = color.new(color.orange, 30)
c_fd = color.new(color.green, 80)
c_fs = color.new(color.red, 80)
c_zero = color.new(#ffee00, 70)
c_up = color.new(#359bfc, 0)
c_dn = color.new(#f57f17, 0)
c_sup = color.new(#33ff00, 80)
c_sdn = color.new(#ff1111, 80)
up = anp_s >= 0
s_up = V_senti >=0
hline(0, 'Zero Line', c_zero, hline.style_solid)
// =============================================================================
// v3.0 --- Sentiment will be represented as a 4-color histogram
c_grow_above = #1b5e2080
c_grow_below = #dc4c4a80
c_fall_above = #66bb6a80
c_fall_below = #ef8e9880
sflag_up = math.abs(V_senti) >= math.abs(V_senti[1])
plot(show_senti ? V_senti : na, "Sentiment", style=plot.style_columns,
color = s_up ? (sflag_up ? c_grow_above : c_fall_above) :
sflag_up ? c_grow_below : c_fall_below)
// =============================================================================
s = plot(asp, 'Supply Energy', c_asp, 2, style=plot.style_circles, join=true)
d = plot(adp, 'Demand Energy', c_adp, 2, style=plot.style_cross, join=true)
fill(d, s, adp > asp ? c_fd : c_fs)
plot(anp, 'VADER', color.new(color.gray, 30), display=display.none)
plot(anp_s, 'Signal', up ? c_up : c_dn, 3)
// ===========================================================================================================
// v2.0 adding alerts
// ===========================================================================================================
Alert_up = ta.crossover(anp_s,0)
Alert_dn = ta.crossunder(anp_s,0)
Alert_swing = ta.cross(anp_s,0)
// "." in alert title for the alerts to show in the right order up/down/swing
alertcondition(Alert_up, ". VADER Crossing 0 Up", "VADER Up - Buying Energy Detected!")
alertcondition(Alert_dn, ".. VADER Crossing 0 Down", "VADER Down - Selling Energy Detected!")
alertcondition(Alert_swing, "... VADER Crossing 0", "VADER Swing - Possible Reversal")
// ===========================================================================================================
// v3.0 more alerts for VADER crossing Sentiment
// ===========================================================================================================
v_speedup = ta.crossover(anp_s, V_senti)
v_slowdn = ta.crossunder(anp_s, V_senti)
alertcondition(v_speedup, "* VADER Speeding Up", "VADER Speeding Up!")
alertcondition(v_slowdn, "** VADER Slowing Down", "VADER Slowing Down!")
if Alert_up
strategy.entry("Enter Long", strategy.long)
else if Alert_dn
strategy.entry("Enter Short", strategy.short)
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