Yuttakan Sangchai ProAek11

AI-Frendersis - Strategy Trading

financial-python / chatgpt_sentiment_analysis.py

Last active February 22, 2024 15:26

	"""
	2 Pre-Requisites - install the package, and get an OpenAI API key

	pip install openai

	"""

	#import the package and add your key
	import openai
	openai.api_key = "YOUR_API_KEY_HERE"

ProAek11 / hmm_market_behavior_compare_hidden_states.py

Created March 9, 2020 11:25 — forked from lamres/hmm_market_behavior_compare_hidden_states.py

	def mean_confidence_interval(vals, confidence):
	a = 1.0 * np.array(vals)
	n = len(a)
	m, se = np.mean(a), scipy.stats.sem(a)
	h = se * scipy.stats.t.ppf((1 + confidence) / 2., n-1)
	return m - h, m, m + h

	def compare_hidden_states(hmm_model, cols_features, conf_interval, iters = 1000):
	plt.figure(figsize=(15, 15))
	fig, axs = plt.subplots(len(cols_features), hmm_model.n_components, figsize = (15, 15))

ProAek11 / hmm_market_behavior_features.py

Created March 9, 2020 11:23 — forked from lamres/hmm_market_behavior_features.py

	# Normalized st. deviation
	def std_normalized(vals):
	return np.std(vals) / np.mean(vals)

	# Ratio of diff between last price and mean value to last price
	def ma_ratio(vals):
	return (vals[-1] - np.mean(vals)) / vals[-1]

	# z-score for volumes and price
	def values_deviation(vals):

ProAek11 / hmm_market_behavior_get_data.py

Created March 9, 2020 11:05 — forked from lamres/hmm_market_behavior_get_data.py

	start_date_string = '2014-04-01'
	asset = 'BITFINEX/BTCUSD'
	column_price = 'Last'
	column_high = 'High'
	column_low = 'Low'
	column_volume = 'Volume'

	quandl.ApiConfig.api_key = YOUR_QUANDL_API
	dataset = quandl.get(asset, collapse = 'daily',
	trim_start = start_date_string)

ProAek11 / hmm_market_behavior_libraries.py

Created March 9, 2020 11:00 — forked from lamres/hmm_market_behavior_libraries.py

	import quandl
	import numpy as np
	import pandas as pd
	import statsmodels.api as sm
	from scipy import stats
	from matplotlib import cm, pyplot as plt
	from hmmlearn.hmm import GaussianHMM
	import scipy
	import datetime
	import json

ProAek11 / stock_lstm_2.py

Created February 28, 2020 05:40 — forked from witchapong/stock_lstm_2.py

	from matplotlib import pyplot
	import pandas as pd
	from IPython.core.display import display, HTML
	display(HTML("<style>.container { width:90% !important; }</style>"))
	pd.options.display.max_columns = 999
	pd.options.display.max_rows = 999

	# function สำหรับ preprocess ข้อมูล time series หลายตัวแปร
	def series_to_supervised(data, n_in=1, n_out=1, dropnan=True,feat_name=None):