Three cornerstones of quantitative finance are asset returns, interest rates, and volatilities. They appear in many fundamental formulas in finance. In this article, we consider their interplay and the underlying statistical issues in a classical topic in quantitative finance.

Jensen's inequality is perhaps the most famous theorem in quantitative finance (note that it is a "theorem" and not a model or a formula) and it is the reason why financial derivatives have value. Concept of convexity, Jensen's inequality, randomness and volatility of an asset price are intricately linked.

In empirical finance and many other domains, linear regression and the closely related linear prediction theory are commonly used statistical methods. Because of the wide range of applications, basic linear regression courses normally concentrate on the mathematically simplest scenario, which can be used in a variety of other applications.

Statistics is a discipline of applied mathematics that deals with the gathering, describing, analysing, and inferring conclusions from numerical data. Differential and integral calculus, linear algebra, and probability theory are all used substantially in statistics' mathematical theories.

The goal of this article is to create an algorithm that can understand simple spoken commands using the Speech Commands Dataset. We can improve product effectiveness and accessibility by improving the recognition accuracy of open-source voice interface tools.

On Ubuntu, I will show you how to instal RPM packages. The design of Debian-based systems like Ubuntu and RedHat-based systems like CentOS is quite similar. There are, however, a few minor differences. For example, RPM files are used to represent software packages on RedHat-based systems, while DEB files are used on Debian-based systems. An RPM package can be installed in one of two ways, by converting the RPM file to a DEB file or by installing the RPM file directly. Both approaches are easy, but depending on the package being installed, installing RPM packages on a Debian-based system can cause problems.

When adding statistics to the number of people and visits to the Hexo blog, according to the standard process of writing, pushing the number of people and visits after running found that the number of people simply do not load. Looking through the information found that the reason, busuanzi because in 2018/10/12 its domain name expired, so the number of people can not be displayed.

A supervised machine learning model has two phases, training and testing. When these models are learned, validated, and tested, the test and train data points are normally presumed to have the same distribution. In the real world, however, the training and test datasets rarely follow the same distribution.

This article tends to build a model that predicts stock price in the best way possible. This is an example of how you can use Long Short-Term Memory (LSTM) Neural Network on some real-world time series data with PyTorch. Hopefully, there are much better models that forecast the price of the stock.

In this article, a sentiment analysis is conducted through the lens of Harry Potter. I am a self-confessed Harry Potter devotee. I've read the books multiple times and watched the films more times than I can count. The lines of each characters in the movies are rich in emotionally charged experiences that the reader can viscerally feel. Can a computer capture that feeling? Let's check it out!

In Python, there are several choices of modules for morphological analysis. There are several types of kuromoji such as Janome, Juman, MeCab, and Esanpy, but this time we will use MeCab, which is said to be relatively fast and accurate.

The development of elec-tronic business is accelerated by the popularity of the internet. Millions of people buy products and post their reviews online. Public opinion analysis can be used with these reviews. Customers can make better decisions after reading other people's product reviews. There is a pressing need for building the system which can perform the sentiment classification job. In this article, I'll try to build a sentiment anaylsis model for Japanese customer reviews.

I'm trying to implement neural network from scratch in Python recently. Considering to solve multi-class classification problem using neural network, I try to create a simple neural network. The most important thing in neural network is backpropagation. Backpropagation is an algorithm for supervised learning of artificial neural networks using gradient descent. I want to find the derivation of cross-entropy loss function with softmax activation function, so this article will record the formula I calculated. As for the rest, I will discuss it in the future.

Viterbi Algorithm is usually used to find the most likely sequence in HMM. It is now also commonly used in speech recognition, speech synthesis, diarization, keyword spotting, computational linguistics, and bioinformatics. This semester, in the course "Speech Technology", the acoustic signal is treated as the observed sequence of events, and a string of text is considered to be the hidden cause of the acoustic signal in speech recognition task. The Viterbi algorithm finds the most likely string of text given the acoustic signal.

Tic-tac-toe is a paper-and-pencil game for two players, X and O, who take turns marking the spaces in a 3×3 grid. The player who succeeds in placing three of their marks in a diagonal, horizontal, or vertical row is the winner. It is a solved game with a forced draw assuming best play from both players. In this article, I want to discuss whether there's a must-win strategy for this game.

Paraphrasing and summarizing are vital so that you essay doesn't become one long quote of other academics' work. To paraphrase a piece of text is to write it in your own words. In this article, I will show you how I make an app that will help me rephrase the sentence I need.

Come up with a list of topics that I should research and understand to prepare for the first IBM interview. This interview will likely be more behavioral as well as testing to see how much I know about IBM. 

In this article, I will show you how to find the cube root of 9 digit number. This is a very effective way of finding cube root of such high numbers. If you practise rigorously, you can do it in 10 seconds!