Time-independent Models for estimating Value at Risk
Parametic and historical method for calculation of VARs. Both time-independent and time-dependent models are included.
- statistics 7
- risk_management 6
- mathematics 4
- data_science 3
- python 3
- pca 2
- nlp 2
- web_scrapping 2
- text_analysis 2
- asset_pricing 2
- fixed_income 2
- macroeconomics 2
- regression 1
- classfication 1
- DNN 1
- designing 1
- SVM 1
- clustering 1
- unsupervised 1
- k-means 1
- anomaly_detection 1
- reccomemder_system 1
- collaborative_filtering 1
- gradient_descent 1
- large_scale 1
- data_visualization 1
- speaking 1
- mathjax 1
- latex 1
- holee 1
- svd 1
- tsne 1
- visualization 1
- interest_rate_model 1
- linear_regression 1
- ols 1
- qmj 1
- mkt 1
- factors 1
statistics
Notes for “Return to RiskMetrics – The Evolution of a Standard”
An update and restatement of the mathematical models in the 1996 RiskMetrics Technical Document, now known as RiskMetrics Classic. RiskMetrics Classic was th...
Statistics - HKU Bootcamp
Basic topics of statsitics convered in the HKU stats bootcamp.
Quantitative Financial Risk Management
Anoter book from Michael B. Miller, which is organized around topics in risk management, such as market risk, credit risk and liquidity risk.
Mathematics and Statistics for Financial Risk Management—Part 3
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
Mathematics and Statistics for Financial Risk Management—Part 2
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
Mathematics and Statistics for Financial Risk Management—Part 1
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
risk_management
Time-independent Models for estimating Value at Risk
Parametic and historical method for calculation of VARs. Both time-independent and time-dependent models are included.
Notes for “Return to RiskMetrics – The Evolution of a Standard”
An update and restatement of the mathematical models in the 1996 RiskMetrics Technical Document, now known as RiskMetrics Classic. RiskMetrics Classic was th...
Quantitative Financial Risk Management
Anoter book from Michael B. Miller, which is organized around topics in risk management, such as market risk, credit risk and liquidity risk.
Mathematics and Statistics for Financial Risk Management—Part 3
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
Mathematics and Statistics for Financial Risk Management—Part 2
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
Mathematics and Statistics for Financial Risk Management—Part 1
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
mathematics
Quantitative Financial Risk Management
Anoter book from Michael B. Miller, which is organized around topics in risk management, such as market risk, credit risk and liquidity risk.
Mathematics and Statistics for Financial Risk Management—Part 3
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
Mathematics and Statistics for Financial Risk Management—Part 2
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
Mathematics and Statistics for Financial Risk Management—Part 1
Notes for the book by Michael B. Miller. It includes basic concepts in mathemtacs and statistics which are commonly used in the risk mangement process.
data_science
Machine Learning With Python
Review for the implementation of machine learning algorithms with python.
Data Visualization
Introduction to basic data visualization tools.
Data Analysis With Python
Framework for data analysis form IBM certificate corse.
python
Machine Learning With Python
Review for the implementation of machine learning algorithms with python.
Data Visualization
Introduction to basic data visualization tools.
Data Analysis With Python
Framework for data analysis form IBM certificate corse.
pca
Visualization of high-dimensional datasets using PCA and t-SNE
Use PCA and T-SNE to reduce the dimension of dataset, for better visualization result, as well as better accuracy for machine learning models.
Machine Learning Part 5：Clustering
Introduction to several useful unsupervised algorithms for clustering, dimensionality reduction and anomaly detection.
nlp
Can Tweets Explain Stocks
A blog post by ‘Group Researches’. In this blog, we summarize our findings on the topic of ‘Analyzing the relationship between tweets about SP500 and the rea...
Twint - Twitter Intelligence Tool
An advanced Twitter scraping & OSINT tool written in Python that doesn’t use Twitter’s API, allowing you to scrape a user’s followers, following, Tweets ...
web_scrapping
Can Tweets Explain Stocks
A blog post by ‘Group Researches’. In this blog, we summarize our findings on the topic of ‘Analyzing the relationship between tweets about SP500 and the rea...
Twint - Twitter Intelligence Tool
An advanced Twitter scraping & OSINT tool written in Python that doesn’t use Twitter’s API, allowing you to scrape a user’s followers, following, Tweets ...
text_analysis
Can Tweets Explain Stocks
A blog post by ‘Group Researches’. In this blog, we summarize our findings on the topic of ‘Analyzing the relationship between tweets about SP500 and the rea...
Twint - Twitter Intelligence Tool
An advanced Twitter scraping & OSINT tool written in Python that doesn’t use Twitter’s API, allowing you to scrape a user’s followers, following, Tweets ...
asset_pricing
Ho-Lee Model (a Binomial Tree Model)
An implementation of Ho-Lee model with Bionimal Tree Framework. It can be used for pricing interest rate derivatives and bonds.
Asset Pricing Methods
Some notes about different approches for asset pricing.
fixed_income
Fixed Income Securities and Interest Rate Models
Notes for MFIN 7036 Fixed Income Securities and Interest Modelling. Also add some important information from other sources.
Ho-Lee Model (a Binomial Tree Model)
An implementation of Ho-Lee model with Bionimal Tree Framework. It can be used for pricing interest rate derivatives and bonds.
macroeconomics
Macroeconomics, Economic Principles in the Real World - Part 2
Notes for The Power of Macroeconomics: Economic Principles in the Real World from coursera.
Macroeconomics, Economic Principles in the Real World - Part 1
Notes for The Power of Macroeconomics: Economic Principles in the Real World from coursera.
regression
Machine Learning Part 1： Basics
A brief introduction to machine learning. Foundamental concepts and algorithms for regression and classification are given.
classfication
Machine Learning Part 1： Basics
A brief introduction to machine learning. Foundamental concepts and algorithms for regression and classification are given.
DNN
Machine Learning Part 2： DNN
Problem representation and learning algorithms for neural networks.
designing
Machine Learning Part 3：Evaluating and Designing
An introductin to evaluating and designing machine learning algorithms. Specifically, we talk about the balance between bias and variances and the learning c...
SVM
Machine Learning Part 4：Support Vector Machine (SVM)
The algorithm of SVM for linear classfication. Kernal functions are introduced for the application of SVM in non-linear classfications.
clustering
Machine Learning Part 5：Clustering
Introduction to several useful unsupervised algorithms for clustering, dimensionality reduction and anomaly detection.
unsupervised
Machine Learning Part 5：Clustering
Introduction to several useful unsupervised algorithms for clustering, dimensionality reduction and anomaly detection.
k-means
Machine Learning Part 5：Clustering
Introduction to several useful unsupervised algorithms for clustering, dimensionality reduction and anomaly detection.
anomaly_detection
Machine Learning Part 5：Clustering
Introduction to several useful unsupervised algorithms for clustering, dimensionality reduction and anomaly detection.
reccomemder_system
Machine Learning Part 6：Recommender System
About how to use the collaborative filtering algorithm to build a recommemder system.
collaborative_filtering
Machine Learning Part 6：Recommender System
About how to use the collaborative filtering algorithm to build a recommemder system.
gradient_descent
Machine Learning Part 7：Large Scale Machine Learning
Gradient descent and data parallelism for large scale machine learning problems.
large_scale
Machine Learning Part 7：Large Scale Machine Learning
Gradient descent and data parallelism for large scale machine learning problems.
data_visualization
Data Visualization
Introduction to basic data visualization tools.
speaking
How to Speak by Patrick Winston
Patrick Winston’s How to Speak talk has been an MIT tradition for over 40 years. Offered every January, the talk is intended to improve your speaking ability...
mathjax
MathJax basic tutorial and quick reference
Some tricks about mathjax and the block enviroment for theorems, lemmas and proofs, etc.
latex
MathJax basic tutorial and quick reference
Some tricks about mathjax and the block enviroment for theorems, lemmas and proofs, etc.
holee
Ho-Lee Model (a Binomial Tree Model)
An implementation of Ho-Lee model with Bionimal Tree Framework. It can be used for pricing interest rate derivatives and bonds.
svd
Visualization of high-dimensional datasets using PCA and t-SNE
Use PCA and T-SNE to reduce the dimension of dataset, for better visualization result, as well as better accuracy for machine learning models.
tsne
Visualization of high-dimensional datasets using PCA and t-SNE
Use PCA and T-SNE to reduce the dimension of dataset, for better visualization result, as well as better accuracy for machine learning models.
visualization
Visualization of high-dimensional datasets using PCA and t-SNE
Use PCA and T-SNE to reduce the dimension of dataset, for better visualization result, as well as better accuracy for machine learning models.
interest_rate_model
Fixed Income Securities and Interest Rate Models
Notes for MFIN 7036 Fixed Income Securities and Interest Modelling. Also add some important information from other sources.
linear_regression
Quantitative Trading - 1. Introduction
Based on notes of MFIN 7037 Quantitative Trading of HKU.
ols
Quantitative Trading - 1. Introduction
Based on notes of MFIN 7037 Quantitative Trading of HKU.
qmj
Quantitative Trading - 1. Introduction
Based on notes of MFIN 7037 Quantitative Trading of HKU.
mkt
Quantitative Trading - 1. Introduction
Based on notes of MFIN 7037 Quantitative Trading of HKU.
factors
Quantitative Trading - 1. Introduction
Based on notes of MFIN 7037 Quantitative Trading of HKU.