An unusual view on Africa's revival and route to global dominance The golden age has seen the rise of herbal drugs over orthodox medication. Herbal solutions have a means for people to live long whilst maintaining a healthy lifestyle less void of harsh side effect – this is the shortfall of orthodox medical solution that … Continue reading The Golden Age
Volatility and ARIMA estimation of J.P. Morgan Chase (JPM) stock index using R
# Read JPM #######S&P 500_1, monthly data loading JPM <- read.csv("JPM.csv",header = TRUE, stringsAsFactors = F) JPMclose <- JPM$Adj.Close #(1)Test for the stationarity of the monthly adjusted closing prices for JPM. adf.test(JPMclose, alternative="stationary") #not stationary #Transformation to make stationary JPMclose_t JPMclose_t adf.test(JPMclose_t, alternative="stationary") #not stationary 2. Test for the stationarity of the monthly returns … Continue reading Volatility and ARIMA estimation of J.P. Morgan Chase (JPM) stock index using R
Sentiment analysis ;twitter stock and S&P index performance using Python
import pandas as pd import seaborn as sns import matplotlib import matplotlib.pyplot as plt import numpy as np import itertools import sklearn.covariance from sklearn import preprocessing from sklearn import datasets import scipy as sp import scipy.stats as stats import time import datetime import statsmodels.api as sm import statsmodels.tsa.stattools as ts from ipykernel import kernelapp as … Continue reading Sentiment analysis ;twitter stock and S&P index performance using Python
The Path to Substance
Go to bed with thoughts of greatness for tomorrow, map out a functional plan on how to deal with those interesting challenges, put in even more effort and always remember that work is life and work is life and pain only exist in the mind. You are supposed to find fulfillment and contempt at what … Continue reading The Path to Substance
How do I forecast an irregular time series (in R) with high frequency data when you have time stamps with each minute with missing time stamps in between? How does imputation work when the number of observations is high?
How high is the data frequency. I believe you are looking at data by minutes and hours (higher than daily stock data). Multiple Imputation(MI) is one effective way in dealing with missing observations, especially if the count is more than a-fifth of the vector set. There are several methods to make forecasts of equidistant time … Continue reading How do I forecast an irregular time series (in R) with high frequency data when you have time stamps with each minute with missing time stamps in between? How does imputation work when the number of observations is high?
What is the difference between parameters in GARCH(m,s) and ARCH(m)? Is the parameter M the same? How will I get parameters?
In an autoregressive AR(m) model, the current value of the process is a weighted sum of the past n values together with a random term. where the weightings are fixed and the random innovations are independent and identically distributed. This model is homoskedastic. The random changes at each time step all come from the same … Continue reading What is the difference between parameters in GARCH(m,s) and ARCH(m)? Is the parameter M the same? How will I get parameters?
How do I find long memory in a time series?
Familiarity with the workings of exponential decay and power-like decay, is focal to identifying long memory or long-range dependence. Imagine that patterns observed in stock market movements, changing rates of cryptocurrency, surveillance video and speech recognition. What you want to do here, is to extract the characteristics of these patterns by analysing the dataset. Autocorrelation … Continue reading How do I find long memory in a time series?
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What is the best way to do data analysis for a novice?
In generic terms, it’s easy for me to make recommendations to data analysis courses online and also refer you to certain dummy notes and lecture materials online. You could even get some good videos online. As a beginner ‘dummy’, i advice you set your mind right. Is this the path i want to follow? Why … Continue reading What is the best way to do data analysis for a novice?
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