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CQF中文2025年6月
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CQF正课-2506班讲义
01-【M1L1】The Random Behavior of Assets .sz
02-【M1L2】Binomial Models .sz
03-【Python1】Introduction to Financial Time Series .sz
04-【M1L3】PDEs & Transition Density Functions .sz
05-【M1L4】Applied Stochastic Calculus I .sz
06-【Python 2】Binomial Trees in Option Pricing .sz
07-【M1L5】 Applied Stochastic Calculus II .sz
08-【Tutorial 1】Further Probability Theory .sz
09-【M1L6】 Martingales .sz
10-【Tutorial 2】Further Binomial Model .sz
11-【M2L1】 Portfolio Management .sz
12-【M2L2】Fundamentals of Optimization .sz
13-【Python3】Portfolio Optimization .sz
14-【M2L3】 Value at Risk & Expected Shortfall .sz
15-【M2L4】 Asset Returns. Key Imperial Stylized Facts .sz
16-【M2L5】Volatility Models. The ARCH Framework .sz
17-【Tutorial 3】Statistical Essentials for VaR & ES .sz
18-【Python4】Value at Risk & GARCH .sz
19-【M2L6】Risk Regulation & Basel III.IV .sz
20-【M2L7】 Collateral & Margins .sz
21-【M3L1】 Black Scholes Model .sz
22-【M3L2】 Martingales Theory .sz
23-【Python 5】Black Scholes Option Pricing .sz
24-【M3L3】Option Pricing Models. Connecting the Dots .sz
25-【Tutorial 4】Differential Equations - Theory & Applications .sz
26-【M3L4】Intro to Numerical Methods .sz
27-【Python 6】Monte Carlo Simulation .sz
28-【M3L5】Further Numerical Methods .sz
29-【Tutorial 5】Further Numerical Methods in MC&FDM .sz
30-【M3L6】Understanding Volatility .sz
31-【M3L7】Exotic Options .sz
32-【M3L8】Things They Don't Teach You In School .sz
33-【M3L9】Common Quant Mistakes .sz
34-【M3L10】FX Options .sz
35-【M3L11】Advanced Volatility Modeling in CompleteMkt .sz
36-【Python 7】Finite Difference Methods .sz
37-【Python 8】 Implied Volatility .sz
38-【M4L1】An Introduction to Machine Learning I .sz
39-【M4L2】 An Introduction to Machine Learning II .sz
40-【M4L3】Math Toolbox for Machine Learning .sz
41-【M4L4】Supervised Learning I .sz
42-【M4L5】Supervised Learning II .sz
43-【Python9】 Introduction to ML using Scikit-learn .sz
44-【Python10】Trend prediction using LR .sz
45-【M4L6】Decision Trees & Ensemble Models .sz
46-【M4L7】Practical ML Case Studies for Finance .sz
47-【Python11】Gradient Boosting for Price Prediction .sz
48-【M5L1】Unsupervised Learning I .sz
49-【M5L2】 Unsupervised Learning II .sz
50-【Python12】K-Means Clustering & Self Organizing Maps .sz
51-【M5L3】Deep Learning & Neural Networks .sz
52-【M5L4】 Natural Language Processing .sz
53-【M5L5】 Reinforcement Learning Theory .sz
54-【Python13】Application of Neural Networks using TensorFlow & Keras .sz
55-【M5L6】 Reinforcement Learning in Practice .sz
56-【Tutorial 6】Data Source & Market Prediction .sz
57-【M5L7】Reinforcement Learning for Dynamic Asset Allocation .sz
58-【M5L8】Practical ML Case Studies for Finance .sz
59-【M5L9】 Quantum Computing .sz
60-【Pythonlab 14】Reinforcement Learning .sz
61-【M6L1】Fixed Income Products & Analysis .sz
62-【M6L2】 Stochastic Interest Rate Modeling .sz
63【M6L3】Calibration & Data Analysis .sz
64-【M6L4】 Probabilistic Methods for Interest Rates .sz
65-【M6L5】 Heath Jarrow & Morton Model .sz
66-【Python15】Yield Curve Data Analysis .sz
67-【M6L6】Multifactor Forward Rate Modelling .sz
68-【M6L7】Further Monte Carlo .sz
69-【M6L8】Cointegration for Trading .sz
70-【Workshop 1】Final Project Workshop I .sz
71-【M6L9】 Credit Default Swaps .sz
72-【Tutorial 7】Yield Curve Construction .sz
73-【M6L10】Structural Models for Default Prediction .sz
74-【Workshop 2】Final Project Workshop II .sz
75-【Tutorial】Final Project Tutorial I .sz
76-【M6L11】 Intensity Models .sz
77-【Tutorial】Final Project Tutorial II .sz
78-【M6L12】CDO & Correlation Sensitivity .sz
79-【Python16】Intensity Models .sz
80-【Tutorial】Final Project Tutorial III .sz
81-【M6L13】X Valuation Adjustment .sz
82-【Python17】CDS Pricing .sz
83-【Tutorial】Final Project Tutorial IV .sz
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