Strategi perdagangan adaptif berdasarkan indikator ADX
ChaoZhang
Ringkasan
Inti dari strategi ini adalah menggunakan indikator ADX untuk menilai tren pasar, dan mengkombinasikan selisih indikator DI+- untuk mengidentifikasi titik-titik terobosan secara otomatis, sehingga dapat melakukan perdagangan yang disesuaikan. Strategi ini dapat secara otomatis mengidentifikasi titik-titik terobosan tren, tanpa intervensi manusia, dan cocok untuk memegang garis tengah.
Prinsip Strategi
Perhitungan True Range, Indikator Gerak Arah, mendapatkan indikator seperti DI+, DI- , DX dan ADX.
Bandingkan amplitudo diferensial DI+ dan ADX1, amplitudo diferensial DI- dan ADX2。
Ketika amplitude1 lebih besar dari set threshold (seperti 10), maka akan tercipta sinyal multitasking; bila amplitude2 lebih besar dari set threshold (seperti 10), maka akan tercipta sinyal blanko.
Dan meminta ADX berada di antara DI+ dan DI- untuk memfilter sinyal yang salah.
Dengan demikian, ketika pasar memasuki kondisi tren, DI+ atau DI- akan jelas memimpin ADX, sehingga menghasilkan sinyal perdagangan; ketika tren pasar berakhir, DI+, DI- dan ADX akan kembali mendekati, menghindari mengejar naik dan turun.
Keunggulan Strategis
Ini adalah salah satu cara yang paling efektif untuk mengidentifikasi titik-titik tren tanpa penilaian manual.
Fleksibilitas penyesuaian nilai terendah DI dan ADX untuk menyesuaikan dengan kondisi pasar yang berbeda.
Kombinasi dengan indikator ADX, dapat memfilter sinyal yang salah secara efektif.
Pemilihan saham yang lebih lama, tidak memerlukan transaksi yang lebih sering, dan tingkat penggunaan dana yang lebih tinggi.
Pengunduran diri dapat dikendalikan, pertumbuhan stabil.
Risiko Strategis
Indikator ADX terlambat, mungkin kehilangan peluang perdagangan pendek. Dapat dikombinasikan dengan indikator lain atau mengurangi parameter ADX untuk meningkatkan sensitivitas.
Hal ini dapat dilakukan dengan menerapkan strategi stop loss atau menambahkan kondisi penyaringan ADX untuk mengurangi probabilitas penarikan.
Jika terjadi pembalikan tren yang besar, maka akan terjadi kerugian yang sangat besar. Anda dapat mengatur stop loss bergerak atau stop loss tracking untuk mengendalikan risiko.
Optimasi Strategi
Anda dapat menguji pasar dan varietas yang berbeda untuk menyesuaikan kombinasi parameter terbaik.
Dapat dipertimbangkan untuk meningkatkan akurasi sinyal, seperti MACD, KD, dll.
Menambahkan strategi stop loss untuk mengendalikan penarikan dan kerugian maksimum.
Memperkenalkan manajemen posisi, menyesuaikan posisi perdagangan sesuai dengan kondisi pasar.
Optimalkan pilihan titik masuk dan kondisi keluar untuk mengurangi risiko transaksi.
Meringkaskan
Strategi ini mengintegrasikan keuntungan dari indikator ADX dan DI, memungkinkan penilaian tren yang efektif dan perdagangan yang beradaptasi sendiri. Tidak perlu sering mengoperasikan, cocok untuk memegang garis panjang tengah. Namun, ada juga risiko tertentu, perlu menambahkan indikator teknis tambahan dan alat manajemen dana untuk perbaikan, yang dapat meningkatkan stabilitas strategi.
/*backtest
start: 2023-01-10 00:00:00
end: 2024-01-16 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/
// © MAURYA_ALGO_TRADER
//@version=5
strategy("Monthly Performance by Dr. Maurya", overlay=true, default_qty_value = 15, commission_type = strategy.commission.percent, commission_value = 0.1)
len = input(14)
th = input(20)
TrueRange = math.max(math.max(high - low, math.abs(high - nz(close[1]))), math.abs(low - nz(close[1])))
DirectionalMovementPlus = high - nz(high[1]) > nz(low[1]) - low ? math.max(high - nz(high[1]), 0) : 0
DirectionalMovementMinus = nz(low[1]) - low > high - nz(high[1]) ? math.max(nz(low[1]) - low, 0) : 0
SmoothedTrueRange = 0.0
SmoothedTrueRange := nz(SmoothedTrueRange[1]) - nz(SmoothedTrueRange[1]) / len + TrueRange
SmoothedDirectionalMovementPlus = 0.0
SmoothedDirectionalMovementPlus := nz(SmoothedDirectionalMovementPlus[1]) - nz(SmoothedDirectionalMovementPlus[1]) / len + DirectionalMovementPlus
SmoothedDirectionalMovementMinus = 0.0
SmoothedDirectionalMovementMinus := nz(SmoothedDirectionalMovementMinus[1]) - nz(SmoothedDirectionalMovementMinus[1]) / len + DirectionalMovementMinus
DIPlus = SmoothedDirectionalMovementPlus / SmoothedTrueRange * 100
DIMinus = SmoothedDirectionalMovementMinus / SmoothedTrueRange * 100
DX = math.abs(DIPlus - DIMinus) / (DIPlus + DIMinus) * 100
ADX = ta.sma(DX, len)
//diff_1 = math.abs(DIPlus - DIMinus)
diff_2 = math.abs(DIPlus-ADX)
diff_3 = math.abs(DIMinus - ADX)
long_diff = input(10, "Long Difference")
short_diff = input(10, "Short Difference")
buy_condition = diff_2 >=long_diff and diff_3 >=long_diff and (ADX < DIPlus and ADX > DIMinus)
sell_condition = diff_2 >=short_diff and diff_3 >=short_diff and (ADX > DIPlus and ADX < DIMinus)
if buy_condition
strategy.entry("Long Entry", strategy.long, comment = "Long")
if sell_condition
strategy.entry("Short Entry", strategy.short, comment = "Short")
// Copy below code to end of the desired strategy script
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// monthly pnl performance by Dr. Maurya @MAURYA_ALGO_TRADER //
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
show_performance = input.bool(true, 'Show Monthly Monthly Performance ?', group='Monthly Performance')
dash_loc_mp = input("Bottom Right","Location" ,options=["Top Right","Bottom Right","Top Left","Bottom Left", "Middle Right","Bottom Center"] ,group='Monthly Performance', inline = "performance")
text_size_mp = input('Small',"Size" ,options=["Tiny","Small","Normal","Large"] ,group='Monthly Performance', inline = "performance")
bg_c = input.color( color.rgb(7, 226, 242, 38), "Background Color", group='Monthly Performance')
text_head_color = input.color( color.rgb(0,0,0), "Month/Year Heading Color", group='Monthly Performance')
tab_month_c = input.color( color.white, "Month PnL Data Color", group='Monthly Performance')
tab_year_c = input.color( color.rgb(0,0,0), "Year PnL Data Color", group='Monthly Performance')
border_c = input.color( color.white, "Table Border Color", group='Monthly Performance')
var table_position_mp = dash_loc_mp == 'Top Left' ? position.top_left :
dash_loc_mp == 'Bottom Left' ? position.bottom_left :
dash_loc_mp == 'Middle Right' ? position.middle_right :
dash_loc_mp == 'Bottom Center' ? position.bottom_center :
dash_loc_mp == 'Top Right' ? position.top_right : position.bottom_right
var table_text_size_mp = text_size_mp == 'Tiny' ? size.tiny :
text_size_mp == 'Small' ? size.small :
text_size_mp == 'Normal' ? size.normal : size.large
/////////////////
strategy.initial_capital =50000
/////////////////////////////////////////////
// var bool new_month = na
new_month = ta.change(month) //> 0 ? true : false
newest_month = new_month and strategy.closedtrades >= 1
// profit
only_profit = strategy.netprofit
initial_balance = strategy.initial_capital
// month number
var int month_number = na
month_number := (ta.valuewhen(newest_month, month(time), 0)) //and month(time) > 1 ? (ta.valuewhen(newest_month, month(time), 0) - 1) : 12 //1 to 12
//month_year
var int month_time = na
month_time := ta.valuewhen(newest_month, time, 0) - 2419200000
var int m_counter = 0
if newest_month
m_counter += 1
// current month values
var bool new_year = na
new_year := ta.change(year)
curr_m_pnl = only_profit - nz(ta.valuewhen(newest_month, only_profit, 0), 0)
curr_m_number = newest_month ? ta.valuewhen(newest_month, month(time), 0) : month(time)
curr_y_pnl = (only_profit - nz(ta.valuewhen(new_year, only_profit, 0),0))
var float [] net_profit_array = array.new_float()
var int [] month_array = array.new_int()
var int [] month_time_array = array.new_int()
if newest_month
array.push(net_profit_array, only_profit)
array.push(month_array, month_number)
array.push(month_time_array, month_time)
var float [] y_pnl_array = array.new_float()
var int [] y_number_array = array.new_int()
var int [] y_time_array = array.new_int()
newest_year = ta.change(year) and strategy.closedtrades >= 1
get_yearly_pnl = nz(ta.valuewhen(newest_year, strategy.netprofit, 0) - nz(ta.valuewhen(newest_year, strategy.netprofit, 1), 0), 0)
get_m_year = ta.valuewhen(newest_year, year(time), 1)
get_y_time = ta.valuewhen(newest_year, time, 0)
if newest_year
array.push(y_pnl_array, get_yearly_pnl)
array.push(y_number_array, get_m_year)
array.push(y_time_array, get_y_time)
var float monthly_profit = na
var int column_month_number = na
var int row_month_time = na
var testTable = table.new(position = table_position_mp, columns = 14, rows = 40, bgcolor = bg_c, border_color = border_c, border_width = 1)
if barstate.islastconfirmedhistory and show_performance
table.cell(table_id = testTable, column = 0, row = 0, text = "YEAR", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 1, row = 0, text = "JAN", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 2, row = 0, text = "FEB", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 3, row = 0, text = "MAR", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 4, row = 0, text = "APR", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 5, row = 0, text = "MAY", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 6, row = 0, text = "JUN", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 7, row = 0, text = "JUL", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 8, row = 0, text = "AUG", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 9, row = 0, text = "SEP", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 10, row = 0, text = "OCT", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 11, row = 0, text = "NOV", text_color = text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 12, row = 0, text = "DEC", text_color =text_head_color, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 13, row = 0, text = "YEAR P/L", text_color = text_head_color, text_size=table_text_size_mp)
for i = 0 to (array.size(y_number_array) == 0 ? na : array.size(y_number_array) - 1)
row_y = year(array.get(y_time_array, i)) - year(array.get(y_time_array, 0)) + 1
table.cell(table_id = testTable, column = 13, row = row_y, text = str.tostring(array.get(y_pnl_array , i), "##.##") + '\n' + '(' + str.tostring(array.get(y_pnl_array , i)*100/initial_balance, "##.##") + ' %)', bgcolor = array.get(y_pnl_array , i) > 0 ? color.green : array.get(y_pnl_array , i) < 0 ? color.red : color.gray, text_color = tab_year_c, text_size=table_text_size_mp)
curr_row_y = array.size(month_time_array) == 0 ? 1 : (year(array.get(month_time_array, array.size(month_time_array) - 1))) - (year(array.get(month_time_array, 0))) + 1
table.cell(table_id = testTable, column = 13, row = curr_row_y, text = str.tostring(curr_y_pnl, "##.##") + '\n' + '(' + str.tostring(curr_y_pnl*100/initial_balance, "##.##") + ' %)', bgcolor = curr_y_pnl > 0 ? color.green : curr_y_pnl < 0 ? color.red : color.gray, text_color = tab_year_c, text_size=table_text_size_mp)
for i = 0 to (array.size(net_profit_array) == 0 ? na : array.size(net_profit_array) - 1)
monthly_profit := i > 0 ? ( array.get(net_profit_array, i) - array.get(net_profit_array, i - 1) ) : array.get(net_profit_array, i)
column_month_number := month(array.get(month_time_array, i))
row_month_time :=((year(array.get(month_time_array, i))) - year(array.get(month_time_array, 0)) ) + 1
table.cell(table_id = testTable, column = column_month_number, row = row_month_time, text = str.tostring(monthly_profit, "##.##") + '\n' + '(' + str.tostring(monthly_profit*100/initial_balance, "##.##") + ' %)', bgcolor = monthly_profit > 0 ? color.green : monthly_profit < 0 ? color.red : color.gray, text_color = tab_month_c, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 0, row =row_month_time, text = str.tostring(year(array.get(month_time_array, i)), "##.##"), text_color = text_head_color, text_size=table_text_size_mp)
curr_row_m = array.size(month_time_array) == 0 ? 1 : (year(array.get(month_time_array, array.size(month_time_array) - 1))) - (year(array.get(month_time_array, 0))) + 1
table.cell(table_id = testTable, column = curr_m_number, row = curr_row_m, text = str.tostring(curr_m_pnl, "##.##") + '\n' + '(' + str.tostring(curr_m_pnl*100/initial_balance, "##.##") + ' %)', bgcolor = curr_m_pnl > 0 ? color.green : curr_m_pnl < 0 ? color.red : color.gray, text_color = tab_month_c, text_size=table_text_size_mp)
table.cell(table_id = testTable, column = 0, row =curr_row_m, text = str.tostring(year(time), "##.##"), text_color = text_head_color, text_size=table_text_size_mp)
//============================================================================================================================================================================