ChaoZhang
概述
这是一个利用支点作为入场信号的量化交易策略。它会计算出上升支点和下降支点,一旦价格突破这些支点,就会启动长仓或短仓。
策略原理
该策略主要基于支点反转理论。它会首先计算出左侧N根K线和右侧M根K线的支点。然后实时监控价格是否突破这些支点。
当价格突破上升支点时,说明ranchang力量已经不足以继续推高价格,这时做空可以获得较好收益。当价格突破下降支点时,说明空头力量已耗尽,此时做多可以获得较好收益。
具体来说,该策略通过ta.pivothigh和ta.pivotlow函数计算出上升支点和下降支点。然后比较当前最高价是否突破上升支点,最低价是否突破下降支点。如果突破,则启动相应的做多做空策略。
此外,该策略还使用止损来控制风险。具体做法是,当价格突破支点后,立即下单,同时设置止损位于支点另一侧,这样可以最大程度避免失败的single导致亏损扩大。
优势分析
这种基于支点反转的策略具有以下几个优势:
- 支点反转信号较为可靠,胜率较高
- 风险控制到位,止损设置合理
- 易于实现,代码简洁
- 适用于不同品种,灵活性较好
风险分析
该策略也存在一些风险需要注意:
- 支点可能发生失效,导致错误信号
- 突破支点后可能出现回调,造成止损被触发
- 交易频率可能较高,交易费用是一种隐性成本
- 效果与品种、参数设置有关,需要调优
为了降低风险,可以考虑以下几点:
- 优化左右侧K线数量,确保支点计算更加可靠
- 适当放宽止损范围,避免止损过密
- 设置最小盈利目标,减少频繁反复交易
- 测试不同品种和参数,找到最佳配置
优化方向
该策略还有进一步优化的空间:
- 结合其他指标判断支点突破的可靠性
- 增加机器学习模型判断价格趋势
- 利用高频数据提升交易信号灵敏度
- 增加仓位管理模块,根据条件动态调整仓位
- 接入详细账户模块,计算真实交易费用
这些优化可以提高策略的胜率、盈利水平、稳定性。
总结
综上所述,这是一个基于支点反转理论的量化交易策略。它利用价格突破支点作为交易信号,同时使用止损机制控制风险。该策略易于实现,适用面广,是一种实用的量化交易策略。但也存在一定的风险,需要进一步测试和优化,在实际使用中找到最佳配置。
策略源码
/*backtest
start: 2022-12-05 00:00:00
end: 2023-12-11 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=5
strategy('Weekly Returns with Benchmark', overlay=true,
default_qty_type=strategy.percent_of_equity, default_qty_value=25,
commission_type=strategy.commission.percent, commission_value=0.1)
////////////
// Inputs //
// Pivot points inputs
leftBars = input(2, group = "Pivot Points")
rightBars = input(1, group = "Pivot Points")
// Styling inputs
prec = input(1, title='Return Precision', group = "Weekly Table")
from_date = input(timestamp("01 Jan 3000 00:00 +0000"), "From Date", group = "Weekhly Table")
prof_color = input.color(color.green, title = "Gradient Colors", group = "Weeky Table", inline = "colors")
loss_color = input.color(color.red, title = "", group = "Weeky Table", inline = "colors")
// Benchmark inputs
use_cur = input.bool(true, title = "Use current Symbol for Benchmark", group = "Benchmark")
symb_bench = input('BTC_USDT:swap', title = "Benchmark", group = "Benchmark")
disp_bench = input.bool(false, title = "Display Benchmark?", group = "Benchmark")
disp_alpha = input.bool(false, title = "Display Alpha?", group = "Benchmark")
// Pivot Points Strategy
swh = ta.pivothigh(leftBars, rightBars)
swl = ta.pivotlow (leftBars, rightBars)
hprice = 0.0
hprice := not na(swh) ? swh : hprice[1]
lprice = 0.0
lprice := not na(swl) ? swl : lprice[1]
le = false
le := not na(swh) ? true : le[1] and high > hprice ? false : le[1]
se = false
se := not na(swl) ? true : se[1] and low < lprice ? false : se[1]
if le
strategy.entry('PivRevLE', strategy.long, comment='PivRevLE', stop=hprice + syminfo.mintick)
if se
strategy.entry('PivRevSE', strategy.short, comment='PivRevSE', stop=lprice - syminfo.mintick)
plot(hprice, color=color.new(color.green, 0), linewidth=2)
plot(lprice, color=color.new(color.red, 0), linewidth=2)
///////////////////
// WEEKLY TABLE //
new_week = weekofyear(time[1]) != weekofyear(time)
new_year = year(time) != year(time[1])
eq = strategy.equity
bench_eq = close
// benchmark eq
bench_eq_htf = request.security(symb_bench, timeframe.period, close)
if (not use_cur)
bench_eq := bench_eq_htf
bar_pnl = eq / eq[1] - 1
bench_pnl = bench_eq / bench_eq[1] - 1
// Current Weekly P&L
cur_week_pnl = 0.0
cur_week_pnl := bar_index == 0 ? 0 :
time >= from_date and (time[1] < from_date or new_week) ? bar_pnl :
(1 + cur_week_pnl[1]) * (1 + bar_pnl) - 1
// Current Yearly P&L
cur_year_pnl = 0.0
cur_year_pnl := bar_index == 0 ? 0 :
time >= from_date and (time[1] < from_date or new_year) ? bar_pnl :
(1 + cur_year_pnl[1]) * (1 + bar_pnl) - 1
// Current Weekly P&L - Bench
bench_cur_week_pnl = 0.0
bench_cur_week_pnl := bar_index == 0 or (time[1] < from_date and time >= from_date) ? 0 :
time >= from_date and new_week ? bench_pnl :
(1 + bench_cur_week_pnl[1]) * (1 + bench_pnl) - 1
// Current Yearly P&L - Bench
bench_cur_year_pnl = 0.0
bench_cur_year_pnl := bar_index == 0 ? 0 :
time >= from_date and (time[1] < from_date or new_year) ? bench_pnl :
(1 + bench_cur_year_pnl[1]) * (1 + bench_pnl) - 1
var week_time = array.new_int(0)
var year_time = array.new_int(0)
var week_pnl = array.new_float(0)
var year_pnl = array.new_float(0)
var bench_week_pnl = array.new_float(0)
var bench_year_pnl = array.new_float(0)
// Filling weekly / yearly pnl arrays
if array.size(week_time) > 0
if weekofyear(time) == weekofyear(array.get(week_time, array.size(week_time) - 1))
array.pop(week_pnl)
array.pop(bench_week_pnl)
array.pop(week_time)
if array.size(year_time) > 0
if year(time) == year(array.get(year_time, array.size(year_time) - 1))
array.pop(year_pnl)
array.pop(bench_year_pnl)
array.pop(year_time)
if (time >= from_date)
array.push(week_time, time)
array.push(year_time, time)
array.push(week_pnl, cur_week_pnl)
array.push(year_pnl, cur_year_pnl)
array.push(bench_year_pnl, bench_cur_year_pnl)
array.push(bench_week_pnl, bench_cur_week_pnl)
// Weekly P&L Table
table_size = size.tiny
var weekly_table = table(na)
if array.size(year_pnl) > 0 and barstate.islastconfirmedhistory
weekly_table := table.new(position.bottom_right,
columns=56, rows=array.size(year_pnl) * 3 + 5, border_width=1)
// Fill weekly performance
table.cell(weekly_table, 0, 0, 'Perf',
bgcolor = #999999, text_size= table_size)
for numW = 1 to 53 by 1
table.cell(weekly_table, numW, 0, str.tostring(numW),
bgcolor= #999999, text_size= table_size)
table.cell(weekly_table, 54, 0, ' ',
bgcolor = #999999, text_size= table_size)
table.cell(weekly_table, 55, 0, 'Year',
bgcolor = #999999, text_size= table_size)
max_abs_y = math.max(math.abs(array.max(year_pnl)), math.abs(array.min(year_pnl)))
max_abs_m = math.max(math.abs(array.max(week_pnl)), math.abs(array.min(week_pnl)))
for yi = 0 to array.size(year_pnl) - 1 by 1
table.cell(weekly_table, 0, yi + 1,
str.tostring(year(array.get(year_time, yi))),
bgcolor=#cccccc, text_size=table_size)
table.cell(weekly_table, 53, yi + 1, ' ',
bgcolor=#999999, text_size=table_size)
table.cell(weekly_table, 54, yi + 1, ' ',
bgcolor=#999999, text_size=table_size)
y_color = color.from_gradient(array.get(year_pnl, yi), -max_abs_y, max_abs_y, loss_color, prof_color)
table.cell(weekly_table, 55, yi + 1,
str.tostring(math.round(array.get(year_pnl, yi) * 100, prec)),
bgcolor=y_color, text_size=table_size)
int iw_row= na
int iw_col= na
for wi = 0 to array.size(week_time) - 2 by 1
w_row = year(array.get(week_time, wi)) - year(array.get(year_time, 0)) + 1
w_col = weekofyear(array.get(week_time, wi))
w_color = color.from_gradient(array.get(week_pnl, wi), -max_abs_m, max_abs_m, loss_color, prof_color)
if iw_row + 1 == w_row and iw_col + 1 == w_col
table.cell(weekly_table, w_col, w_row-1,
str.tostring(math.round(array.get(week_pnl, wi) * 100, prec)),
bgcolor=w_color, text_size=table_size)
else
table.cell(weekly_table, w_col, w_row,
str.tostring(math.round(array.get(week_pnl, wi) * 100, prec)),
bgcolor=w_color, text_size=table_size)
iw_row:= w_row
iw_col:= w_col
// Fill benchmark performance
next_row = array.size(year_pnl) + 1
if (disp_bench)
table.cell(weekly_table, 0, next_row, 'Bench',
bgcolor=#999999, text_size=table_size)
for numW = 1 to 53 by 1
table.cell(weekly_table, numW, next_row, str.tostring(numW),
bgcolor= #999999, text_size= table_size)
table.cell(weekly_table, 54, next_row, ' ' ,
bgcolor = #999999, text_size=table_size)
table.cell(weekly_table, 55, next_row, 'Year',
bgcolor = #999999, text_size=table_size)
max_bench_abs_y = math.max(math.abs(array.max(bench_year_pnl)), math.abs(array.min(bench_year_pnl)))
max_bench_abs_w = math.max(math.abs(array.max(bench_week_pnl)), math.abs(array.min(bench_week_pnl)))
for yi = 0 to array.size(year_time) - 1 by 1
table.cell(weekly_table, 0, yi + 1 + next_row + 1,
str.tostring(year(array.get(year_time, yi))),
bgcolor=#cccccc, text_size=table_size)
table.cell(weekly_table, 53, yi + 1 + next_row + 1, ' ',
bgcolor=#999999, text_size=table_size)
table.cell(weekly_table, 54, yi + 1 + next_row + 1, ' ',
bgcolor=#999999, text_size=table_size)
y_color = color.from_gradient(array.get(bench_year_pnl, yi), -max_bench_abs_y, max_bench_abs_y, loss_color, prof_color)
table.cell(weekly_table, 55, yi + 1 + next_row + 1,
str.tostring(math.round(array.get(bench_year_pnl, yi) * 100, prec)),
bgcolor=y_color, text_size=table_size)
int iw_row1= na
int iw_col1= na
for wi = 0 to array.size(week_time) - 1 by 1
w_row = year(array.get(week_time, wi)) - year(array.get(year_time, 0)) + 1
w_col = weekofyear(array.get(week_time, wi))
w_color = color.from_gradient(array.get(bench_week_pnl, wi), -max_bench_abs_w, max_bench_abs_w, loss_color, prof_color)
if iw_row1 + 1 == w_row and iw_col1 + 1 == w_col
table.cell(weekly_table, w_col, w_row + next_row ,
str.tostring(math.round(array.get(bench_week_pnl, wi) * 100, prec)),
bgcolor=w_color, text_size=table_size)
else
table.cell(weekly_table, w_col, w_row + next_row + 1,
str.tostring(math.round(array.get(bench_week_pnl, wi) * 100, prec)),
bgcolor=w_color, text_size=table_size)
iw_row1:= w_row
iw_col1:= w_col
// Fill Alpha
if (disp_alpha)
// columns
next_row := array.size(year_pnl) * 2 + 3
table.cell(weekly_table, 0, next_row, 'Alpha',
bgcolor=#999999, text_size= table_size)
for numW = 1 to 53 by 1
table.cell(weekly_table, numW, next_row, str.tostring(numW),
bgcolor= #999999, text_size= table_size)
table.cell(weekly_table, 54, next_row, ' ' ,
bgcolor=#999999, text_size= table_size)
table.cell(weekly_table, 55, next_row, 'Year',
bgcolor=#999999, text_size= table_size)
max_alpha_abs_y = 0.0
for yi = 0 to array.size(year_time) - 1 by 1
if (math.abs(array.get(year_pnl, yi) - array.get(bench_year_pnl, yi)) > max_alpha_abs_y)
max_alpha_abs_y := math.abs(array.get(year_pnl, yi) - array.get(bench_year_pnl, yi))
max_alpha_abs_w = 0.0
for wi = 0 to array.size(week_pnl) - 1 by 1
if (math.abs(array.get(week_pnl, wi) - array.get(bench_week_pnl, wi)) > max_alpha_abs_w)
max_alpha_abs_w := math.abs(array.get(week_pnl, wi) - array.get(bench_week_pnl, wi))
for yi = 0 to array.size(year_time) - 1 by 1
table.cell(weekly_table, 0, yi + 1 + next_row + 1,
str.tostring(year(array.get(year_time, yi))),
bgcolor=#cccccc, text_size= table_size)
table.cell(weekly_table, 53, yi + 1 + next_row + 1, ' ',
bgcolor=#999999, text_size= table_size)
table.cell(weekly_table, 54, yi + 1 + next_row + 1, ' ',
bgcolor=#999999, text_size= table_size)
y_color = color.from_gradient(array.get(year_pnl, yi) - array.get(bench_year_pnl, yi), -max_alpha_abs_y, max_alpha_abs_y, loss_color, prof_color)
table.cell(weekly_table, 55, yi + 1 + next_row + 1,
str.tostring(math.round((array.get(year_pnl, yi) - array.get(bench_year_pnl, yi)) * 100, prec)),
bgcolor=y_color, text_size= table_size)
int iw_row2= na
int iw_col2= na
for wi = 0 to array.size(week_time) - 1 by 1
w_row = year(array.get(week_time, wi)) - year(array.get(year_time, 0)) + 1
w_col = weekofyear(array.get(week_time, wi))
w_color = color.from_gradient(array.get(week_pnl, wi) - array.get(bench_week_pnl, wi), -max_alpha_abs_w, max_alpha_abs_w, loss_color, prof_color)
if iw_row2 + 1 == w_row and iw_col2 + 1 == w_col
table.cell(weekly_table, w_col, w_row + next_row ,
str.tostring(math.round((array.get(week_pnl, wi) - array.get(bench_week_pnl, wi)) * 100, prec)),
bgcolor=w_color, text_size= table_size)
else
table.cell(weekly_table, w_col, w_row + next_row + 1 ,
str.tostring(math.round((array.get(week_pnl, wi) - array.get(bench_week_pnl, wi)) * 100, prec)),
bgcolor=w_color, text_size= table_size)
iw_row2:= w_row
iw_col2:= w_col
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