FMZ Quant: Analisis Contoh Reka Bentuk Keperluan Umum di Pasaran Cryptocurrency (I)

Dalam ruang perdagangan aset cryptocurrency, mendapatkan dan menganalisis data pasaran, menanyakan kadar, dan memantau pergerakan aset akaun adalah semua operasi kritikal.

Bagaimana saya menulis kod untuk mendapatkan mata wang dengan kenaikan tertinggi dalam masa 4 jam di Binance Spot?

Apabila menulis program strategi perdagangan kuantitatif di platform FMZ, perkara pertama yang perlu anda lakukan apabila anda menghadapi keperluan adalah untuk menganalisisnya.

• Bahasa pengaturcaraan mana yang perlu digunakan? Rancangan adalah untuk menggunakan Javascript untuk melaksanakannya.
• Memerlukan sebut harga spot masa nyata dalam semua mata wang Perkara pertama yang kami lakukan apabila kami melihat keperluan adalah mencari dokumen API Binance untuk mengetahui sama ada terdapat sebarang sebut harga agregat (yang terbaik adalah mempunyai sebut harga agregat, ia adalah banyak kerja untuk mencari satu demi satu). Kami menemui antara muka petikan agregat:GET https://api.binance.com/api/v3/ticker/price. Pada platform FMZ, gunakanHttpQueryfungsi untuk mengakses antara muka ticker pertukaran (antara muka awam yang tidak memerlukan tandatangan).
• Perlu mengira data untuk tempoh tetingkap bergulir 4 jam Konsepsi bagaimana untuk mereka bentuk struktur program statistik.
• Mengira turun naik harga dan menyusun mereka Berfikir tentang algoritma turun naik harga, adalah ia:price fluctuations (%) = (current price - initial price) / initial price * 100dalam %.

Selepas menyelesaikan masalah, dan juga menentukan program, kami mula merancang program.

Reka bentuk Kod

var dictSymbolsPrice = {}

function main() {
    while (true) {
        // GET https://api.binance.com/api/v3/ticker/price
        try {
            var arr = JSON.parse(HttpQuery("https://api.binance.com/api/v3/ticker/price"))
            if (!Array.isArray(arr)) {
                Sleep(5000)
                continue 
            }
            
            var ts = new Date().getTime()
            for (var i = 0; i < arr.length; i++) {
                var symbolPriceInfo = arr[i]
                var symbol = symbolPriceInfo.symbol
                var price = symbolPriceInfo.price

                if (typeof(dictSymbolsPrice[symbol]) == "undefined") {
                    dictSymbolsPrice[symbol] = {name: symbol, data: []}
                }
                dictSymbolsPrice[symbol].data.push({ts: ts, price: price})
            }
        } catch(e) {
            Log("e.name:", e.name, "e.stack:", e.stack, "e.message:", e.message)
        }
        
        // Calculate price fluctuations
        var tbl = {
            type : "table",
            title : "Price fluctuations",
            cols : ["trading pair", "current price", "price 4 hours ago", "price fluctuations", "data length", "earliest data time", "latest data time"],
            rows : []
        }
        for (var symbol in dictSymbolsPrice) {
            var data = dictSymbolsPrice[symbol].data
            if (data[data.length - 1].ts - data[0].ts > 1000 * 60 * 60 * 4) {
                dictSymbolsPrice[symbol].data.shift()
            }

            data = dictSymbolsPrice[symbol].data
            dictSymbolsPrice[symbol].percentageChange = (data[data.length - 1].price - data[0].price) / data[0].price * 100
        }

        var entries = Object.entries(dictSymbolsPrice)
        entries.sort((a, b) => b[1].percentageChange - a[1].percentageChange)

        for (var i = 0; i < entries.length; i++) {
            if (i > 9) {
                break
            }   
            var name = entries[i][1].name
            var data = entries[i][1].data
            var percentageChange = entries[i][1].percentageChange
            var currPrice = data[data.length - 1].price
            var currTs = _D(data[data.length - 1].ts)
            var prePrice = data[0].price
            var preTs = _D(data[0].ts)
            var dataLen = data.length

            tbl.rows.push([name, currPrice, prePrice, percentageChange + "%", dataLen, preTs, currTs])
        }
        
        LogStatus(_D(), "\n", "`" + JSON.stringify(tbl) + "`")
        Sleep(5000)
    }
}

Analisis Kod

• 1. Struktur data

- 2. Main function main()
  2.1. Infinite loop

sementara (benar) { //... { C: $ 00FFFF }

The program continuously monitors the Binance API trading pair prices through an infinite loop.
  2.2. Get price information

var arr = JSON.parse(HttpQuery(https://api.binance.com/api/v3/ticker/price”))

Get the current price information of the trading pair via Binance API. If the return is not an array, wait for 5 seconds and retry.
  2.3. Update price data

untuk (var i = 0; i < panjang; i++) { /... {}

Iterate through the array of obtained price information and update the data in dictSymbolsPrice. For each trading pair, add the current timestamp and price to the corresponding data array.
  2.4. Exception processing

♪ menangkap ♪ Log ((e.name:, e.name, e.stack:, e.stack, e.message:, e.message) {}

Catch exceptions and log the exception information to ensure that the program can continue to execute.
  2.5. Calculate the price fluctuations

untuk (simbol var dalam dictSymbolsPrice) { //... { C: $ 00FFFF }

Iterate through dictSymbolsPrice, calculate the price fluctuations of each trading pair, and remove the earliest data if it is longer than 4 hours.
  2.6. Sort and generate tables

var entri = Object.entries ((dictSymbolsPrice) entries.sort (((a, b) => b[1].peratusanPerubahan - a[1].peratusanPerubahan)

untuk (var i = 0; i < entri.panjang; i++) { /... {}

Sort the trading pairs in descending order of their price fluctuations and generate a table containing information about the trading pairs.
  2.7. Log output and delay

LogStatus(_D(), \n, " + JSON.stringify(tbl) + ") Tidur ((5000)

Output the table and the current time in the form of a log and wait for 5 seconds to continue the next round of the loop.

The program obtains the real-time price information of the trading pair through Binance API, then calculates the price fluctuations, and outputs it to the log in the form of a table. The program is executed in a continuous loop to realize the function of real-time monitoring of the prices of trading pairs. Note that the program includes exception processing to ensure that the execution is not interrupted by exceptions when obtaining price information.

### Live Trading Running Test

![FMZ Quant: An Analysis of Common Requirements Design Examples in the Cryptocurrency Market (I)](/upload/asset/28e4c99554fea236762df.png)

Since data can only be collected bit by bit at the beginning, it is not possible to calculate the price fluctuations on a rolling basis without collecting enough data for a 4-hour window. Therefore, the initial price is used as the base for calculation, and after collecting enough data for 4 hours, the oldest data will be eliminated in order to maintain the 4-hour window for calculating the price fluctuations.

## 2. Check the full variety of funding rates for Binance U-denominated contracts
Checking the funding rate is similar to the above code, first of all, we need to check the Binance API documentation to find the funding rate related interface. Binance has several interfaces that allow us to query the rate of funds, here we take the interface of the U-denominated contract as an example:

GEThttps://fapi.binance.com/fapi/v1/premiumIndex

### Code Implementation
Since there are so many contracts, we're exporting the top 10 largest funding rates here.

Fungsi utama sementara (benar) { // Dapatkanhttps://fapi.binance.com/fapi/v1/premiumIndexCuba. var arr = JSON.parse(HttpQuery(https://fapi.binance.com/fapi/v1/premiumIndex”)) jika (!Array.isArray(arr)) { Tidur ((5000) Lanjutkan { C: $ 00FFFF }

        arr.sort((a, b) => parseFloat(b.lastFundingRate) - parseFloat(a.lastFundingRate))
        var tbl = {
            type: "table",
            title: "Top 10 funding rates for U-denominated contracts",
            cols: ["contracts", "funding rate", "marked price", "index price", "current rate time", "next rate time"],
            rows: []
        }
        for (var i = 0; i < 9; i++) {
            var obj = arr[i]
            tbl.rows.push([obj.symbol, obj.lastFundingRate, obj.markPrice, obj.indexPrice, _D(obj.time), _D(obj.nextFundingTime)])
        }
        LogStatus(_D(), "\n", "`" + JSON.stringify(tbl) + "`")
    } catch(e) {
        Log("e.name:", e.name, "e.stack:", e.stack, "e.message:", e.message)
    }
    Sleep(1000 * 10)
}

}

The returned data structure is as follows, and check the Binance documentation, it shows that lastFundingRate is the funding rate we want.

{ tanda:STMXUSDT, markPrice: 0.00883606, indexPrice: 0.00883074, StimasiSettlePrice: 0.00876933, Rata Pembiayaan Terakhir: 0.00026573, kadar faedah: 0.00005000, NextFundingTime:1702828800000, waktu:1702816229000 {}

Live trading running test:

![FMZ Quant: An Analysis of Common Requirements Design Examples in the Cryptocurrency Market (I)](/upload/asset/28d94562e5a8199b5446a.png)

### Getting OKX exchange contract funding rates of Python version
A user has asked for a Python version of the example, and it's for the OKX exchange. Here is an example:

The data returned by the interface ```https://www.okx.com/priapi/v5/public/funding-rate-all?currencyType=1```:

{ kod:0, data:[ { waktu pembiayaan:1702828800000, daftar pembiayaan:[ { instId: BTC-USDT-SWAP, berikutRata Pembiayaan: 0.0001102188733642, minFundingRate:-0.00375, Rata pembiayaan: 0.0000821861465884, maxRata Pembiayaan: 0.00375 ..

Specific code:

Permintaan import Import json dari masa import tidur dari tarikh waktu import

def utama ((): sementara True: #https://www.okx.com/priapi/v5/public/funding-rate-all?currencyType=1Cuba: jawapan = permintaan.get(https://www.okx.com/priapi/v5/public/funding-rate-all?currencyType=1”) arr = response.json() [data][0][fundingList] Log ((arr) Jika tidak, contohnya (arr, senarai): tidur ((5) Lanjutkan

        arr.sort(key=lambda x: float(x["fundingRate"]), reverse=True)

        tbl = {
            "type": "table",
            "title": "Top 10 funding rates for U-denominated contracts",
            "cols": ["contracts", "next rate", "minimum", "current", "maximum"],
            "rows": []
        }

        for i in range(min(9, len(arr))):
            obj = arr[i]
            row = [
                obj["instId"],
                obj["nextFundingRate"],
                obj["minFundingRate"],
                obj["fundingRate"],
                obj["maxFundingRate"]
            ]
            tbl["rows"].append(row)

        LogStatus(_D(), "\n", '`' + json.dumps(tbl) + '`')

    except Exception as e:
        Log(f"Error: {str(e)}")

    sleep(10)

` Ujian berjalan perdagangan langsung:

END

Contoh-contoh ini memberikan idea reka bentuk asas dan kaedah panggilan, projek sebenar mungkin perlu membuat perubahan dan pelanjutan yang sesuai berdasarkan keperluan tertentu.