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Measures temperature through RTD connected to circuit and displays graph of temperature versus time. Implements pyfirmata module and communicates to Arduino Uno using Jupyter Notebook.

Performs circuit calculations given any number of in-series resistors and initial voltage.

Implements pyfirmata, threading, numpy, matplotlib, time, and jupyterplot to communicate with an Arduino board and plot the voltage readings of a 1.5V battery over time. Three different graphing methods were used; two of which are animated.

Example project for creating new state observers in mc_rtc

This package contains the simulation files for the E10 - Open the door episode for the 1st SciRoc Challenge

“Volatility is the backbone of finance in the sense that it not only provides an information signal to investors, but it also is an input to various financial models” (Karasan, n.d) 4.

Volatility can be seen as uncertainty or risk in the financial market. High-volatility stocks have prices that fluctuate greater and more frequently, and higher stock market volatility often translates to greater investment risks. As a result, modelling and forecasting volatility becomes an important strategy when navigating the stock market.

This project will explore the different models of volatility prediction, first, using GARCH(p,q) model, and then LSTM-GARCH hybrid models. This study therefore considers the volatility of the data_ml stock index returns.