From c2789584c2975066f909415de8649bf45ab1b5b8 Mon Sep 17 00:00:00 2001
From: Kamil <kogol99@gmail.com>
Date: Sat, 6 Jun 2020 18:04:07 +0200
Subject: [PATCH] add Lab6

---
 simulation.py | 96 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 96 insertions(+)
 create mode 100644 simulation.py

diff --git a/simulation.py b/simulation.py
new file mode 100644
index 00000000..6a966fec
--- /dev/null
+++ b/simulation.py
@@ -0,0 +1,96 @@
+from datetime import datetime
+import requests
+import matplotlib.pyplot as plt
+from statsmodels.tsa.arima_model import ARIMA
+
+CURRENCY_LIST = ["BTC_LTC", "BTC_ETH", "USDT_BTC"]
+API_URL = "https://poloniex.com/public?command=returnChartData"
+PERIOD = 14400
+
+"""
+avaible
+300 = 5min
+900 = 15min
+1800 = 30min
+7200 = 120 min = 2h
+14400 = 240 min = 4h
+86400 = 1440 min = 24h
+"""
+
+
+def downloading_historical_data(currency, date_from, date_to):
+    date_from = converting_date_to_second(date_from)
+    date_to = converting_date_to_second(date_to)
+    trade_history = requests.get(API_URL + "&currencyPair=" + str(currency) + "&start=" + str(date_from) + "&end=" +
+                                 str(date_to) + "&period=" + str(PERIOD))
+    trade_history_json = trade_history.json()
+    if not trade_history_json[0] == "error":
+        return trade_history_json
+    else:
+        raise Exception
+
+
+def converting_date_to_second(date):
+    yyyy = int(date[0:4])
+    mm = int(date[5:7])
+    dd = int(date[8:10])
+    h = int(date[11:13])
+    minutes = int(date[14:16])
+    s = int(date[17:19])
+    return int(datetime.timestamp(datetime(yyyy, mm, dd, h, minutes, s)))
+
+
+def converting_second_to_date(timestamp):
+    date = str(datetime.fromtimestamp(timestamp))
+    if PERIOD >= 86400:
+        return date[0:10]
+    else:
+        return date
+
+
+def speculation(data, currency):
+    time_api = []
+    exhange_rate_api = []
+    for i in range(len(data)):
+        time_api.append(converting_second_to_date(data[i]["date"]))
+        exhange_rate_api.append(data[i]["close"])
+
+    data_size = len(exhange_rate_api)
+    for x in range(data_size):
+        model = ARIMA(exhange_rate_api, order=(1, 1, 1))
+        model_fit = model.fit(disp=False)
+        expected_data = model_fit.predict(len(exhange_rate_api), len(exhange_rate_api), typ='levels')
+
+        new_date = converting_second_to_date(converting_date_to_second(time_api[len(time_api) - 1]) + PERIOD)
+        time_api.append(new_date)
+        exhange_rate_api.append(expected_data[0])
+
+    half_number_of_data = int(len(exhange_rate_api) / 2)
+    some_date_data_from_api = time_api[0:half_number_of_data]
+    some_rate_data_from_api = exhange_rate_api[0:half_number_of_data]
+
+    some_date_data_predicted = time_api[half_number_of_data-1::]
+    some_rate_data_predicted = exhange_rate_api[half_number_of_data-1::]
+
+    plt.plot(some_date_data_from_api,
+             some_rate_data_from_api)
+    plt.plot(some_date_data_predicted,
+             some_rate_data_predicted)
+    plt.grid(True)
+    plt.xlabel("Data")
+    plt.ylabel("Kurs waluty")
+    plt.title("Wykres kursu kryptowaluty: " + currency[:3] + "-" + currency[4:])
+    plt.show()
+
+
+def predict_the_future_on_the_stock_exchange(currency, date_from, date_to):
+    data = downloading_historical_data(currency, date_from, date_to)
+    speculation(data, currency)
+
+
+def main():
+    predict_the_future_on_the_stock_exchange(CURRENCY_LIST[0], "2020-05-01 00:00:00", "2020-06-01 00:00:00")
+
+
+if __name__ == '__main__':
+    main()