FMZ Quant: Analisis Contoh Desain Persyaratan Umum di Pasar Cryptocurrency (I)

Dalam ruang perdagangan aset cryptocurrency, memperoleh dan menganalisis data pasar, menanyakan tingkat, dan memantau pergerakan aset akun adalah semua operasi penting.

Bagaimana saya menulis kode untuk mendapatkan mata uang dengan kenaikan tertinggi dalam 4 jam di Binance Spot?

Ketika menulis program strategi perdagangan kuantitatif di platform FMZ, hal pertama yang perlu Anda lakukan ketika Anda menemukan persyaratan adalah menganalisisnya.

• Bahasa pemrograman apa yang harus digunakan? Rencananya adalah menggunakan JavaScript untuk menerapkannya.
• Membutuhkan kutipan real-time spot di semua mata uang Hal pertama yang kami lakukan ketika kami melihat persyaratan adalah mencari dokumen API Binance untuk mengetahui apakah ada kutipan agregat (yang terbaik adalah memiliki kutipan agregat, itu banyak pekerjaan untuk mencari satu per satu). Kami menemukan antarmuka kutipan agregat:GET https://api.binance.com/api/v3/ticker/priceAku tidak tahu. Di platform FMZ, gunakanHttpQueryfungsi untuk mengakses antarmuka ticker pertukaran (antarmuka publik yang tidak memerlukan tanda tangan).
• Perlu menghitung data untuk periode jendela bergulir 4 jam Konsepsi bagaimana merancang struktur program statistik.
• Menghitung fluktuasi harga dan menyortirnya Berpikir tentang algoritma fluktuasi harga, adalah:price fluctuations (%) = (current price - initial price) / initial price * 100dalam %.

Setelah mencari tahu masalah, serta mendefinisikan program, kami kemudian turun ke bisnis merancang program.

Desain Kode

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 Kode

• 1. Struktur data

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

sementara (benar) { /... {\cH00FFFF}

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 < arr.length; i++) /... {\cH00FFFF}

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

{\cH00FFFF}menangkapnya. Log ((e.name:, e.name, e.stack:, e.stack, e.message:, e.message) {\cH00FFFF}

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) { /... {\cH00FFFF}

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

untuk (var i = 0; i < entries.length; i++) { /... {\cH00FFFF}

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/premiumIndexCobalah var arr = JSON.parse ((HttpQuery(https://fapi.binance.com/fapi/v1/premiumIndex”)) jika (!Array.isArray(arr)) { Tidur ((5000) Lanjutkan {\cH00FFFF}

        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.

{\cH00FFFF} simbol:STMXUSDT, markPrice: 0.00883606, indexPrice: 0.00883074, perkiraan harga stabil: 0.00876933, Rata Pendanaan Terakhir: 0.00026573, Rata bunga: 0.00005000, NextFundingTime:1702828800000, waktu:1702816229000 {\cH00FFFF}

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```:

{\cH00FFFF} kode:0, data:[ {\cH00FFFF} waktu pendanaan:1702828800000, fundingList: {\cH00FFFF} instId: BTC-USDT-SWAP, nextFundingRate: 0.0001102188733642, minFundingRate:-0.00375, Rata pendanaan: 0,0000821861465884, maxFinancingRate:0.00375 {\cH00FFFF}...

Specific code:

permintaan impor mengimpor json dari waktu impor tidur dari waktu tanggal waktu impor

Definisi utama: sementara True: #https://www.okx.com/priapi/v5/public/funding-rate-all?currencyType=1Cobalah: respon = 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, daftar): 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)

` Uji coba perdagangan langsung:

Penghentian

Contoh-contoh ini memberikan ide-ide desain dasar dan metode panggilan, proyek sebenarnya mungkin perlu membuat perubahan dan ekstensi yang sesuai berdasarkan kebutuhan spesifik.