Strategi lindung nilai dinamik Delta Options Deribit
Penulis:FMZ~Lydia, Dicipta: 2022-11-01 17:49:07, Dikemas kini: 2023-09-15 20:49:52
Strategi yang dibawa FMZ Quant adalah strategi Deribit Options Delta Dynamic Hedging, atau pendeknya DDH (Dynamic Delta Hedging).
Untuk kajian perdagangan opsyen, kita biasanya perlu menguasai konsep-konsep ini:
· Model penetapan harga opsyen, model B-S, harga opsyen ditentukan berdasarkan [harga subjek], [harga kuasa], [masa yang tersisa hingga tamat tempoh], [vokaliti tersirat], dan [ kadar bebas risiko].
· Eksposur opsyen:
-Delta
Penjelasan strategi DDH:
· Penjelasan prinsip DDH Arahan perdagangan yang netral risiko dicapai dengan menyamakan Delta opsyen dan niaga hadapan. Selepas mengambil kedudukan dalam kontrak opsyen dan menyeimbangkan Delta dengan lindung nilai niaga hadapan, keseluruhan Delta akan menjadi tidak seimbang lagi apabila harga subjek bergerak. Gabungan pilihan dan kedudukan niaga hadapan sedemikian memerlukan lindung nilai dinamik berterusan untuk menyamakan Delta.
· Sebagai contoh: Apabila kita membeli pilihan panggilan, kita memegang kedudukan dalam arah panjang pada ketika ini. Pada masa ini, adalah perlu untuk pergi pendek niaga hadapan untuk lindung nilai Delta pilihan, mencapai keseluruhan Delta neutral (0 atau dekat dengan 0). Mari kita abaikan masa yang tersisa untuk tamat tempoh kontrak opsyen, turun naik dan faktor lain. Skenario 1: Apabila harga subjek naik, Delta pilihan meningkat, dan keseluruhan Delta bergerak ke nombor positif, dan niaga hadapan perlu lindung nilai lagi. (Sebelum menyeimbangkan semula, Delta opsyen adalah besar, manakala masa hadapan adalah agak kecil. Keuntungan marginal opsyen panggilan melebihi kerugian marginal kedudukan kontrak pendek, dan keseluruhan portfolio akan menghasilkan.)
Skenario 2: Apabila harga subjek jatuh, bahagian opsyen Delta menurun dan keseluruhan Delta bergerak ke nombor negatif, menutup sebahagian daripada kedudukan niaga hadapan pendek dan membawa keseluruhan Delta ke keseimbangan semula. (Sebelum menyeimbangkan semula, pada masa ini, Delta opsyen adalah kecil, manakala masa hadapan adalah agak besar. Kerugian marginal opsyen panggilan adalah kurang daripada keuntungan marginal jawatan kontrak pendek, dan keseluruhan portfolio masih akan menghasilkan keuntungan.)
Oleh itu, dalam keadaan ideal, peningkatan dan penurunan subjek akan membawa manfaat selagi pasaran turun naik.
Walau bagaimanapun, terdapat juga faktor yang perlu dipertimbangkan: nilai masa, kos transaksi, dan faktor lain.
Oleh itu, penjelasan hotshot di Zhihu dipetik:
The focus of Gamma Scalping is not on delta, dynamic delta hedging is just a way to avoid underlying price risk in the process.
Gamma Scaling focuses on alpha, which is not the alpha of stock selection. Here, alpha=gamma/theta, that is, how much gamma is exchanged for the time loss of unit Theta.
This is the point of concern. It is possible to construct a portfolio that floats both up and down, but it must be accompanied by time loss, and then the problem lies in the cost effectiveness.
Author: Xu Zhe
URL: https://www.zhihu.com/question/51630805/answer/128096385
Penjelasan reka bentuk strategi DDH
· Pengelupasan antara muka pasaran agregat, reka bentuk kerangka kerja · Reka bentuk UI Strategi · Reka bentuk interaksi strategik · Reka bentuk fungsi lindung nilai automatik Kod sumber:
// Construct functions
function createManager(e, subscribeList, msg) {
var self = {}
self.supportList = ["Futures_Binance", "Huobi", "Futures_Deribit"] // of the supported exchanges
// Object attributes
self.e = e
self.msg = msg
self.name = e.GetName()
self.type = self.name.includes("Futures_") ? "Futures" : "Spot"
self.label = e.GetLabel()
self.quoteCurrency = ""
self.subscribeList = subscribeList // subscribeList : [strSymbol1, strSymbol2, ...]
self.tickers = [] // All market data obtained by the interface, define the data format: {bid1: 123, ask1: 123, symbol: "xxx"}}
self.subscribeTickers = [] // The required market data, define the data format: {bid1: 123, ask1: 123, symbol: "xxx"}}
self.accData = null
self.pos = null
// Initialize the function
self.init = function() {
// Judge if the exchange is supported
if (!_.contains(self.supportList, self.name)) {
throw "not support"
}
}
self.setBase = function(base) {
// Switching base address for switching to analog bot
self.e.SetBase(base)
Log(self.name, self.label, "switch to analog bot:", base)
}
// Judging data precision
self.judgePrecision = function (p) {
var arr = p.toString().split(".")
if (arr.length != 2) {
if (arr.length == 1) {
return 0
}
throw "judgePrecision error, p:" + String(p)
}
return arr[1].length
}
// Update assets
self.updateAcc = function(callBackFuncGetAcc) {
var ret = callBackFuncGetAcc(self)
if (!ret) {
return false
}
self.accData = ret
return true
}
// Update positions
self.updatePos = function(httpMethod, url, params) {
var pos = self.e.IO("api", httpMethod, url, params)
var ret = []
if (!pos) {
return false
} else {
// Organize data
// {"jsonrpc":"2.0","result":[],"usIn":1616484238870404,"usOut":1616484238870970,"usDiff":566,"testnet":true}
try {
_.each(pos.result, function(ele) {
ret.push(ele)
})
} catch(err) {
Log("Error:", err)
return false
}
self.pos = ret
}
return true
}
// Update the market data
self.updateTicker = function(url, callBackFuncGetArr, callBackFuncGetTicker) {
var tickers = []
var subscribeTickers = []
var ret = self.httpQuery(url)
if (!ret) {
return false
}
// Log("test", ret)// test
try {
_.each(callBackFuncGetArr(ret), function(ele) {
var ticker = callBackFuncGetTicker(ele)
tickers.push(ticker)
if (self.subscribeList.length == 0) {
subscribeTickers.push(ticker)
} else {
for (var i = 0 ; i < self.subscribeList.length ; i++) {
if (self.subscribeList[i] == ticker.symbol) {
subscribeTickers.push(ticker)
}
}
}
})
} catch(err) {
Log("Error:", err)
return false
}
self.tickers = tickers
self.subscribeTickers = subscribeTickers
return true
}
self.getTicker = function(symbol) {
var ret = null
_.each(self.subscribeTickers, function(ticker) {
if (ticker.symbol == symbol) {
ret = ticker
}
})
return ret
}
self.httpQuery = function(url) {
var ret = null
try {
var retHttpQuery = HttpQuery(url)
ret = JSON.parse(retHttpQuery)
} catch (err) {
// Log("Error:", err)
ret = null
}
return ret
}
self.returnTickersTbl = function() {
var tickersTbl = {
type : "table",
title : "tickers",
cols : ["symbol", "ask1", "bid1"],
rows : []
}
_.each(self.subscribeTickers, function(ticker) {
tickersTbl.rows.push([ticker.symbol, ticker.ask1, ticker.bid1])
})
return tickersTbl
}
// Back to the position table
self.returnPosTbl = function() {
var posTbl = {
type : "table",
title : "pos|" + self.msg,
cols : ["instrument_name", "mark_price", "direction", "size", "delta", "index_price", "average_price", "settlement_price", "average_price_usd", "total_profit_loss"],
rows : []
}
/* Format of the position data returned by the interface
{
"mark_price":0.1401105,"maintenance_margin":0,"instrument_name":"BTC-25JUN21-28000-P","direction":"buy",
"vega":5.66031,"total_profit_loss":0.01226105,"size":0.1,"realized_profit_loss":0,"delta":-0.01166,"kind":"option",
"initial_margin":0,"index_price":54151.77,"floating_profit_loss_usd":664,"floating_profit_loss":0.000035976,
"average_price_usd":947.22,"average_price":0.0175,"theta":-7.39514,"settlement_price":0.13975074,"open_orders_margin":0,"gamma":0
}
*/
_.each(self.pos, function(ele) {
if(ele.direction != "zero") {
posTbl.rows.push([ele.instrument_name, ele.mark_price, ele.direction, ele.size, ele.delta, ele.index_price, ele.average_price, ele.settlement_price, ele.average_price_usd, ele.total_profit_loss])
}
})
return posTbl
}
self.returnOptionTickersTbls = function() {
var arr = []
var arrDeliveryDate = []
_.each(self.subscribeTickers, function(ticker) {
if (self.name == "Futures_Deribit") {
var arrInstrument_name = ticker.symbol.split("-")
var currency = arrInstrument_name[0]
var deliveryDate = arrInstrument_name[1]
var deliveryPrice = arrInstrument_name[2]
var optionType = arrInstrument_name[3]
if (!_.contains(arrDeliveryDate, deliveryDate)) {
arr.push({
type : "table",
title : arrInstrument_name[1],
cols : ["PUT symbol", "ask1", "bid1", "mark_price", "underlying_price", "CALL symbol", "ask1", "bid1", "mark_price", "underlying_price"],
rows : []
})
arrDeliveryDate.push(arrInstrument_name[1])
}
// Iterate through arr
_.each(arr, function(tbl) {
if (tbl.title == deliveryDate) {
if (tbl.rows.length == 0 && optionType == "P") {
tbl.rows.push([ticker.symbol, ticker.ask1, ticker.bid1, ticker.mark_price, ticker.underlying_price, "", "", "", "", ""])
return
} else if (tbl.rows.length == 0 && optionType == "C") {
tbl.rows.push(["", "", "", "", "", ticker.symbol, ticker.ask1, ticker.bid1, ticker.mark_price, ticker.underlying_price])
return
}
for (var i = 0 ; i < tbl.rows.length ; i++) {
if (tbl.rows[i][0] == "" && optionType == "P") {
tbl.rows[i][0] = ticker.symbol
tbl.rows[i][1] = ticker.ask1
tbl.rows[i][2] = ticker.bid1
tbl.rows[i][3] = ticker.mark_price
tbl.rows[i][4] = ticker.underlying_price
return
} else if(tbl.rows[i][5] == "" && optionType == "C") {
tbl.rows[i][5] = ticker.symbol
tbl.rows[i][6] = ticker.ask1
tbl.rows[i][7] = ticker.bid1
tbl.rows[i][8] = ticker.mark_price
tbl.rows[i][9] = ticker.underlying_price
return
}
}
if (optionType == "P") {
tbl.rows.push([ticker.symbol, ticker.ask1, ticker.bid1, ticker.mark_price, ticker.underlying_price, "", "", "", "", ""])
} else if(optionType == "C") {
tbl.rows.push(["", "", "", "", "", ticker.symbol, ticker.ask1, ticker.bid1, ticker.mark_price, ticker.underlying_price])
}
}
})
}
})
return arr
}
// Initialization
self.init()
return self
}
function main() {
// Initialization, clear logs
if(isResetLog) {
LogReset(1)
}
var m1 = createManager(exchanges[0], [], "option")
var m2 = createManager(exchanges[1], ["BTC-PERPETUAL"], "future")
// Switch to analog bot
var base = "https://www.deribit.com"
if (isTestNet) {
m1.setBase(testNetBase)
m2.setBase(testNetBase)
base = testNetBase
}
while(true) {
// Options
var ticker1GetSucc = m1.updateTicker(base + "/api/v2/public/get_book_summary_by_currency?currency=BTC&kind=option",
function(data) {return data.result},
function(ele) {return {bid1: ele.bid_price, ask1: ele.ask_price, symbol: ele.instrument_name, underlying_price: ele.underlying_price, mark_price: ele.mark_price}})
// Perpetual futures
var ticker2GetSucc = m2.updateTicker(base + "/api/v2/public/get_book_summary_by_currency?currency=BTC&kind=future",
function(data) {return data.result},
function(ele) {return {bid1: ele.bid_price, ask1: ele.ask_price, symbol: ele.instrument_name}})
if (!ticker1GetSucc || !ticker2GetSucc) {
Sleep(5000)
continue
}
// Update positions
var pos1GetSucc = m1.updatePos("GET", "/api/v2/private/get_positions", "currency=BTC&kind=option")
var pos2GetSucc = m2.updatePos("GET", "/api/v2/private/get_positions", "currency=BTC&kind=future")
if (!pos1GetSucc || !pos2GetSucc) {
Sleep(5000)
continue
}
// Interactions
var cmd = GetCommand()
if(cmd) {
// Handle interactions
Log("Interaction commands", cmd)
var arr = cmd.split(":")
// cmdClearLog
if(arr[0] == "setContractType") {
// parseFloat(arr[1])
m1.e.SetContractType(arr[1])
Log("exchanges[0] contract set by exchange object.", arr[1])
} else if (arr[0] == "buyOption") {
var actionData = arr[1].split(",")
var price = parseFloat(actionData[0])
var amount = parseFloat(actionData[1])
m1.e.SetDirection("buy")
m1.e.Buy(price, amount)
Log("execution price: ", price, "execution amount: ", amount, "execution direction: ", arr[0])
} else if (arr[0] == "sellOption") {
var actionData = arr[1].split(",")
var price = parseFloat(actionData[0])
var amount = parseFloat(actionData[1])
m1.e.SetDirection("sell")
m1.e.Sell(price, amount)
Log("execution price: ", price, "execution amount: ", amount, "execution direction: ", arr[0])
} else if (arr[0] == "setHedgeDeltaStep") {
hedgeDeltaStep = parseFloat(arr[1])
Log("set the parameter hedgeDeltaStep:", hedgeDeltaStep)
}
}
// Obtain the future contract prices
var perpetualTicker = m2.getTicker("BTC-PERPETUAL")
var hedgeMsg = " PERPETUAL:" + JSON.stringify(perpetualTicker)
// Obtain the total delta value from the account data
var acc1GetSucc = m1.updateAcc(function(self) {
self.e.SetCurrency("BTC_USD")
return self.e.GetAccount()
})
if (!acc1GetSucc) {
Sleep(5000)
continue
}
var sumDelta = m1.accData.Info.result.delta_total
if (Math.abs(sumDelta) > hedgeDeltaStep && perpetualTicker) {
if (sumDelta < 0) {
// Hedging futures go short if delta is greater than 0
var amount = _N(Math.abs(sumDelta) * perpetualTicker.ask1, -1)
if (amount > 10) {
Log("Exceed the hedging threshold, current total delta:", sumDelta, "Buy futures")
m2.e.SetContractType("BTC-PERPETUAL")
m2.e.SetDirection("buy")
m2.e.Buy(-1, amount)
} else {
hedgeMsg += ", hedging order volume less than 10"
}
} else {
// Hedging futures go long if delta is less than 0
var amount = _N(Math.abs(sumDelta) * perpetualTicker.bid1, -1)
if (amount > 10) {
Log("Exceed the hedging threshold, current total delta:", sumDelta, "Sell futures")
m2.e.SetContractType("BTC-PERPETUAL")
m2.e.SetDirection("sell")
m2.e.Sell(-1, amount)
} else {
hedgeMsg += ", hedging order volume less than 10"
}
}
}
LogStatus(_D(), "sumDelta:", sumDelta, hedgeMsg,
"\n`" + JSON.stringify([m1.returnPosTbl(), m2.returnPosTbl()]) + "`", "\n`" + JSON.stringify(m2.returnTickersTbl()) + "`", "\n`" + JSON.stringify(m1.returnOptionTickersTbls()) + "`")
Sleep(10000)
}
}
Alamat Strategi:https://www.fmz.com/strategy/265090
Operasi strategi:
Strategi ini adalah strategi tutorial, berorientasikan pembelajaran, sila gunakan dengan berhati-hati dalam bot sebenar.
- Ciri baru FMZ Quant: Gunakan fungsi _Serve untuk membuat perkhidmatan HTTP dengan mudah
- Pencipta mengutip ciri baru: mudah membuat perkhidmatan HTTP menggunakan fungsi _Serve
- FMZ Quant Trading Platform Panduan Akses Protokol Sesuai
- Strategi Pemerolehan dan Pemantauan Kadar Pembiayaan FMZ
- FMZ Rate Pengambilan dan Pemantauan Strategi
- Templat Strategi membolehkan anda menggunakan WebSocket Market dengan lancar
- Satu templat dasar yang membolehkan anda menggunakan sektor WebSocket dengan lancar
- Pencipta Panduan Akses Platform Perdagangan Kuantitatif
- Cara Membina Strategi Dagangan Multi-Mata Wang Universal dengan Cepat Selepas Peningkatan FMZ
- Bagaimana untuk membina strategi perdagangan multi-mata wang yang universal dengan cepat selepas peningkatan FMZ
- Perdagangan DCA: Strategi Kuantitatif yang Digunakan Secara meluas