Strategi ini adalah strategi perdagangan grid adaptif berdasarkan platform perdagangan kuantitatif. Ini mengatur rentang perdagangan grid otomatis atau manual dan menempatkan pesanan beli dan jual pada interval yang sama dalam rentang untuk menerapkan perdagangan grid. Ketika harga menembus batas atas atau bawah grid, strategi secara otomatis menyesuaikan rentang grid.
Atur harga batas atas dan bawah untuk jaringan. Otomatis menghitung harga dalam interval tertentu dari harga tertinggi dan terendah historis sebagai batas atas dan bawah, atau mengatur harga batas atas dan bawah tetap secara manual.
Menghitung interval harga untuk setiap jaringan berdasarkan harga batas atas dan bawah dan jumlah jaringan.
Atur beberapa titik beli dan jual pada interval yang sama antara harga batas atas dan bawah sebagai grid.
Ketika harga pasar melewati batas bawah grid, tempatkan pesanan beli di grid berikutnya di bawah grid di mana pesanan yang belum ditutup terakhir berada; ketika harga pasar melewati batas atas grid, tempatkan pesanan jual di grid di atas grid di mana pesanan yang belum ditutup terakhir berada.
Dengan demikian, terus membeli dan menjual operasi dalam batas atas dan bawah grid.
Perdagangan grid dapat menghasilkan keuntungan di pasar yang terikat dan berosilasi.
Penyesuaian adaptif rentang grid dapat disesuaikan secara otomatis berdasarkan fluktuasi pasar tanpa intervensi manual.
Jumlah investasi modal dapat ditetapkan untuk mengalokasikan risiko di seluruh jaringan.
Logikanya sederhana dan mudah dimengerti, dan parameternya fleksibel untuk disesuaikan.
Melanggar batas atas dan bawah dapat menyebabkan kerugian
Tren pasar dapat menyebabkan kerugian berulang
Pengaturan parameter yang tidak benar
Menggunakan pembelajaran mesin untuk memprediksi rentang fluktuasi harga dan tren untuk menyesuaikan parameter grid secara dinamis.
Berubah ke perdagangan tren di pasar tren untuk menghindari kerugian perdagangan jaringan.
Masukkan langkah-langkah pengendalian risiko berdasarkan tingkat pemanfaatan modal, tingkat pengembalian, dll.
Diversifikasi di berbagai jenis aset untuk meningkatkan pemanfaatan modal.
Strategi ini adalah strategi grid adaptif dengan parameter yang dapat disesuaikan secara otomatis, cocok untuk saham, mata uang kripto dan produk devisa dengan pergerakan fluktuatif dan berkisar. Dengan Parameter yang disesuaikan, dapat beradaptasi dengan kondisi pasar yang berbeda dan memiliki nilai praktis.
/*backtest start: 2024-01-01 00:00:00 end: 2024-01-24 23:59:59 period: 1h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=4 //hk4jerry strategy("Grid Bot Backtesting", overlay=false, pyramiding=3000, close_entries_rule="ANY", default_qty_type=strategy.cash, initial_capital=100.0, currency="USD", commission_type=strategy.commission.percent, commission_value=0.025) i_autoBounds = input(group="Grid Bounds", title="Use Auto Bounds?", defval=true, type=input.bool) // calculate upper and lower bound of the grid automatically? This will theorhetically be less profitable, but will certainly require less attention i_boundSrc = input(group="Grid Bounds", title="(Auto) Bound Source", defval="Hi & Low", options=["Hi & Low", "Average"]) // should bounds of the auto grid be calculated from recent High & Low, or from a Simple Moving Average i_boundLookback = input(group="Grid Bounds", title="(Auto) Bound Lookback", defval=250, type=input.integer, maxval=500, minval=0) // when calculating auto grid bounds, how far back should we look for a High & Low, or what should the length be of our sma i_boundDev = input(group="Grid Bounds", title="(Auto) Bound Deviation", defval=0.10, type=input.float, maxval=1, minval=-1) // if sourcing auto bounds from High & Low, this percentage will (positive) widen or (negative) narrow the bound limits. If sourcing from Average, this is the deviation (up and down) from the sma, and CANNOT be negative. i_upperBound = input(group="Grid Bounds", title="(Manual) Upper Boundry(상단 가격)", defval=0.285, type=input.float) // for manual grid bounds only. The upperbound price of your grid i_lowerBound = input(group="Grid Bounds", title="(Manual) Lower Boundry(하단 가격)", defval=0.225, type=input.float) // for manual grid bounds only. The lowerbound price of your grid. i_gridQty = input(group="Grid Lines", title="Grid Line Quantity(그리드 수)", defval=30, maxval=999, minval=1, type=input.integer) // how many grid lines are in your grid initial_balance = input(group="Trading option", title="Initial balance(투자금액)", defval=100, step=0.01) start_time = input(group="Trading option",defval=timestamp('15 March 2023 06:00'), title='Start Time', type = input.time) end_time = input(group="Trading option",defval=timestamp('31 Dec 2035 20:00'), title='End Time', type = input.time) isAfterStartDate = true tradingtime= (timenow - start_time)/(86400000*30) yeartime=tradingtime/12 f_getGridBounds(_bs, _bl, _bd, _up) => if _bs == "Hi & Low" _up ? highest(close, _bl) * (1 + _bd) : lowest(close, _bl) * (1 - _bd) else avg = sma(close, _bl) _up ? avg * (1 + _bd) : avg * (1 - _bd) f_buildGrid(_lb, _gw, _gq) => gridArr = array.new_float(0) for i=0 to _gq-1 array.push(gridArr, _lb+(_gw*i)) gridArr f_getNearGridLines(_gridArr, _price) => arr = array.new_int(3) for i = 0 to array.size(_gridArr)-1 if array.get(_gridArr, i) > _price array.set(arr, 0, i == array.size(_gridArr)-1 ? i : i+1) array.set(arr, 1, i == 0 ? i : i-1) break arr var upperBound = i_autoBounds ? f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, true) : i_upperBound // upperbound of our grid var lowerBound = i_autoBounds ? f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, false) : i_lowerBound // lowerbound of our grid var gridWidth = (upperBound - lowerBound)/(i_gridQty-1) // space between lines in our grid var gridLineArr = f_buildGrid(lowerBound, gridWidth, i_gridQty) // an array of prices that correspond to our grid lines var orderArr = array.new_bool(i_gridQty, false) // a boolean array that indicates if there is an open order corresponding to each grid line var closeLineArr = f_getNearGridLines(gridLineArr, close) // for plotting purposes - an array of 2 indices that correspond to grid lines near price var nearTopGridLine = array.get(closeLineArr, 0) // for plotting purposes - the index (in our grid line array) of the closest grid line above current price var nearBotGridLine = array.get(closeLineArr, 1) // for plotting purposes - the index (in our grid line array) of the closest grid line below current price if isAfterStartDate for i = 0 to (array.size(gridLineArr) - 1) if close < array.get(gridLineArr, i) and not array.get(orderArr, i) and i < (array.size(gridLineArr) - 1) buyId = i array.set(orderArr, buyId, true) strategy.entry(id=tostring(buyId), long=true, qty=(initial_balance/(i_gridQty-1))/close, comment="#"+tostring(buyId)) if close > array.get(gridLineArr, i) and i != 0 if array.get(orderArr, i-1) sellId = i-1 array.set(orderArr, sellId, false) strategy.close(id=tostring(sellId), comment="#"+tostring(sellId)) if i_autoBounds upperBound := f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, true) lowerBound := f_getGridBounds(i_boundSrc, i_boundLookback, i_boundDev, false) gridWidth := (upperBound - lowerBound)/(i_gridQty-1) gridLineArr := f_buildGrid(lowerBound, gridWidth, i_gridQty) closeLineArr := f_getNearGridLines(gridLineArr, close) nearTopGridLine := array.get(closeLineArr, 0) nearBotGridLine := array.get(closeLineArr, 1) var table table = table.new(position.top_right,6,8, frame_color = color.rgb(255, 255, 255),frame_width = 2,border_width = 2, border_color=color.rgb(255, 255, 255)) //제목 table.cell(table,0,0,"상단 라인 :", bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,0,1,"하단 라인 :",bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,0,2,"그리드 수 :",bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,0,3,"투자금액 :",text_color =color.white,bgcolor=color.new(color.black,0)) table.cell(table,0,4,"그리드당 투자금액 :",text_color =color.white,bgcolor=color.new(color.black,0)) //수치 table.cell(table,1,0, tostring(upperBound, '###.#####')+ " USDT", bgcolor=color.new(#5a637e, 0),text_color =color.white) table.cell(table,1,1, tostring(lowerBound, '###.#####')+ " USDT", bgcolor=color.new(#5a637e, 0),text_color =color.white) table.cell(table,1,2, tostring(i_gridQty, '###'), bgcolor=color.new(#5a637e, 0),text_color =color.white) table.cell(table,1,3, tostring(initial_balance,'###.##')+ " USDT", bgcolor=color.new(#5a637e, 0),text_color =color.white) table.cell(table,1,4, tostring(initial_balance/i_gridQty,'###.##')+ " USDT", bgcolor=color.new(#5a637e, 0),text_color =color.white) //제목 table.cell(table,2,0,"현재 포지션 :",text_color =color.white,bgcolor=color.new(color.black,0)) table.cell(table,2,1,"현재 포지션 평단가 :",text_color =color.white,bgcolor=color.new(color.black,0)) table.cell(table,2,2,"현재 포지션 수익 :",bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,2,3,"현재 포지션 수익 % :",bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,2,4,"현재 포지션 수수료 :",text_color =color.white,bgcolor=color.new(color.black,0)) //수치 table.cell(table,3,0, tostring(strategy.position_size) + syminfo.basecurrency + "\n" + tostring(strategy.position_size*strategy.position_avg_price/1, '###.##') + "USDT" ,text_color =color.white,bgcolor=color.new(#5a637e, 0)) table.cell(table,3,1, text=strategy.position_size>0 ? tostring(strategy.position_avg_price,'###.####')+ " USDT" : "NOT TRADING",text_color =color.white,bgcolor=color.new(#5a637e, 0)) table.cell(table,3,2, tostring(strategy.openprofit, '###.##')+ " USDT",text_color =color.white,bgcolor=strategy.openprofit > 0 ? color.teal : color.maroon) table.cell(table,3,3, tostring(strategy.openprofit/initial_balance*100, '###.##')+ "%",text_color =color.white,bgcolor=strategy.openprofit > 0 ? color.teal : color.maroon) table.cell(table,3,4, "-" + tostring(strategy.position_avg_price*strategy.position_size*0.025/100,'###.##')+ " USDT",text_color =color.white,bgcolor=color.new(#5a637e, 0)) //제목 table.cell(table,4,0,"그리드 수익 :",text_color =color.white,bgcolor=color.new(color.black,0)) table.cell(table,4,1,"그리드 수익률 :",text_color =color.white,bgcolor=color.new(color.black,0)) table.cell(table,4,2,"총 수익 :", bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,4,3,"총 수익률 :",bgcolor=color.new(color.black,0),text_color =color.white) table.cell(table,4,4,"현재 자산 :",bgcolor=color.new(color.black,0),text_color =color.white) //수치 table.cell(table,5,0, tostring(strategy.netprofit, '###.#####')+ "USDT", text_color =color.white,bgcolor=strategy.netprofit > 0 ? color.teal : color.maroon) table.cell(table,5,1, tostring((strategy.netprofit)/initial_balance*100/tradingtime, '####.##') + "%",text_color =color.white,bgcolor=strategy.netprofit > 0 ? color.teal : color.maroon) table.cell(table,5,2, tostring(strategy.netprofit+strategy.openprofit, '###.##') + " USDT",text_color =color.white,bgcolor=strategy.netprofit+strategy.openprofit > 0 ? color.teal : color.maroon) table.cell(table,5,3, tostring((strategy.netprofit+strategy.openprofit)/initial_balance*100, '####.##') + "%",text_color =color.white,bgcolor=strategy.netprofit+strategy.openprofit > 0 ? color.teal : color.maroon) table.cell(table,5,4, tostring(initial_balance+strategy.netprofit+strategy.openprofit, '###.##')+ " USDT", text_color =color.white,bgcolor=color.new(#3d4d7c, 0)) // plot(strategy.initial_capital+ strategy.netprofit+strategy.openprofit, "총 수익 USDT",color=color.rgb(81, 137, 128)) // plot(initial_balance, "투자금액",color=color.rgb(81, 137, 128))