In this part, we will analyze seasonal forecast data on the go (without downloading and saving the data on the disk). Then, we will look at calculating monthly anomaly (departure of each month from its historical mean state). The data that we will be focusing on is going to be the NMM...
This module can be used for the below given puposes: Calculating the interest earned over the amount deposited. Representation of change of Interest,Balance with respect to years through line or bar graphs. Representation of ratios between Deposit and interest applied over it through pie chart. Ca...
It is helpful to do the Monte Carlo simulation on a simplified DCF valuation model instead of the more common examples you see showing valuation of options or other derivatives, since for this we don’t need any math beyond the basics of calculating the financial statements and discounting cash...
# First value is a simple SMA Data[window - 1, whereSMA] = np.mean(Data[:window - 1, what]) # Calculating first EMA Data[window, whereEMA] = (Data[window, what] * alpha) + (Data[window - 1, whereSMA] * beta)# Calculating the rest of EMA for i in range(window + 1, len...
Python is one of the best programming languages that is used for the domain of Data Science. ZaranTech is offering the definitive Python for Data Science training course for learning Python coding, running it on various systems like Windows, Linux and Mac thus making it one of the highly ver...
Python gives you several ways to check where your code is spending time, from simple timers to line-by-line breakdowns. These tools help you focus your effort where it counts. Here’s a rundown of profiling tools that can take you from “why is this so slow?” to “oh, that’s why...
The common use cases for rounding up numbers include the following: Financial Calculations: Rounding up is often used in financial calculations to ensure conservative estimates. For instance, when calculating interest rates or taxes, rounding up to the nearest cent ensures that the values are not ...
It is of great interest for senior managers and shareholders. VaR is computed based on a pre-specified confidence level, usually 90%, 95% or 99%. In order to get an intuitive insight into the essence of VaR, let us denote the confidence level as c and L as the loss, measured as a...
Analyze street networks: routing, visualization, and calculating network stats 1. Get administrative place boundaries and shapefiles To acquire administrative boundary GIS data, one must typically track down shapefiles online and download them. But what about for bulk or automated acquisition and analysi...
The following code example shows an example of calculating the first order differentiation for parameters K, B, S0, sigma, mu, r‘:inputs = torch.tensor([[110.0, 100.0, 120.0, 0.35, 0.1, 0.05]]).cuda() inputs.requires_grad = True x = model(inputs) x.backward() first_order_...