Evaluation and Comparison with Other Predictive Models for Stock Market Predictions and Feature Selection via Step-wise Regression and Lasso. — You can download the Notebook from the GitHub. It’s important to note that predicting the stock market is a challenging task, and machine learning algorithms are not always accurate in their predictions. Several external factors such as global events, political turmoil, and economic shifts can also impact the stock market…

Modelling Long-Term Relationship in Finance — 1. Theoretical Background Why are non-stationarity tests necessary? There are numerous reasons why the concept of non-stationary is significant and why non-stationary variables must be treated differently than stationary variables. In general, non-stationary data are unexpected and cannot be modelled or predicted. The findings generated by utilizing non-stationary time series may be misleading in the sense that they…

Analysis of Multiple Stock Symbols Downloaded from Yahoo Finance — You can download Notebook from GitHub. The getSymbols function of the quantmod package can be used to obtain data from Yahoo Finance for various tickers in R. This function enables us to define a vector of ticker symbols and download the corresponding financial data in R. Install and Load Libraries Define a Vector of Ticker Symbols and Download Data

Estimation of Asymmetric GARCH Models with normal and non-normal Innovations using rugrach() package — You can download Data and Notebook from GitHub. 1. Asymmetric GARCH Models According to the symmetric GARCH model, the conditional variance responds to positive and negative market shocks of equivalent significance in the same way. When compared to good news or positive shocks, bad news or negative shocks have a greater impact on volatility…

Estimation of ARCH and GARCH Models with normal and non-normal Innovations using rugrach() package — You can download Data and Notebook from GitHub. ARIMA-type models are unable to explain a number of important features common to most financial time series. In a separate post, I discussed all the stylized facts of financial returns. There are many distinct kinds of non-linear time series models. The ARCH…

Installing the necessary packages one by one takes time and can be frustrating at times. It is extremely simple to install and load multiple packages at the same time. The next command install and loads packages that aren’t already installed and loaded on your system.

Tendencies of Volatility Clustering, Fat Tail and Non-Normal Distribution — Something that is typically accurate but is not always is referred to as a stylized fact. We observe a number of stylized facts from the data analysis of the returns on the S&P 500 index that typically hold true for other assets. I will use the daily stock prices of…

AR, MA, ARMA , ARIMA and Auto-ARIMA Models You can download Data from GitHub and Jupyter Notebook from Kaggle. Univaraite time series models are a type of specification that aims to model and predict financial variables just using information provided within their own past values, as well as perhaps current…

Periodic compounding, annual interest rate, Taylor series What is continuous compounding interest rate It is possible for interest to compound weekly, daily, or, in the most exceptional scenario, continuously, which means that your balance increases somewhat every moment. All interest income experiences instantaneous compounding under continuous compounding. …