Exam ACCA

Deep Quant Finance

Analytics & Modeling
By Peaks2Tails
5 (5552)

~175 Hrs | English

Description

Sn
Topics 

Finance basics with Python 
01
Setting up Python Infrastructure
Anaconda installation
Exploring Jupyter
02
Arithmetic operations
Basic operators
Using the ‘math’ library
03
Data Structure
Int, float, bool, string
Tuple, list, set, dictionary
04
Object Oriented Programming
Functions
Class
PythonLab – Create a Custom Class for Black Scholes Option Price and Greeks
05
Numerical computing with NumPy
Lists vs NumPy arrays
Indexing
Vectorization
Linear algebra
Python Lab – Create a Custom Class for Multiple Linear Regression
06
Data Analysis with Pandas
The DataFrame Class
Data pre-processing
Basic Analytics
Basic Visualization
Concatenation, Joining & Merging
Pivot Table
07
Data Visualization with Matplotlib, Seaborn & Cufflinks
2D plots (Scatter, line chart, column chart, bar chart, histograms)
3D plots (3D scatter, Surface plots, Contour plots)
Financial Plots (Candle stick, Bollinger bands)
08
Calculus
Limits & Derivatives
Integration
ODEs / PDEs using SciPy.
Python Lab – Solving the heat equation
09
Numerical Integration
Riemann Integral
Trapezoidal method
Simpson’s method
Gaussian Quadrature
Python Lab – Custom class to find CDF of normal distribution using numerical integration
10
Probability & Statistics with SciPy
Discrete distributions (Bernoulli, Binomial, Poisson, Uniform)
Continuous distributions (Normal, T, lognormal, Chi-squared, F)
Python Lab – Custom Class for numerical computation of Expectation and Variance
11
Univariate Financial Time Series Analysis with Statsmodels
Prices and Returns
Moments (Mean, Variance, Skewness, Kurtosis)
Correlation & Covariance
ACF, PACF
AR, MA, ARMA, ARIMA models
Stationarity & Unit root tests
Regression with ARMA errors
Cointegration
Seasonality
Excel & Python Lab – Custom class to perform Box-Jenkins methodology to fit the best model.
12
Multivariate Financial Time Series Analysis with Statsmodels
VAR
VECM
Excel & Python Lab – Joint forecasting of macro-economic time series
13
Conditional Volatility Models
EWMA
GARCH
Excel & Python Lab – Custom Class for Value-at-Risk under different volatility models
14
Monte Carlo Methods
Generating Random numbers
Value of PI using Monte Carlo
Solving an integral with Monte Carlo
Acceptance Rejection Method
Conditional Monte Carlo
Variance Reduction techniques (Antithetic Sampling, Control Variate)
Low discrepancy sequence (Halton, Sobol)
15
Copula Models
Copula definition and properties
Gaussian and T copula
Archimedean Copula
Excel & Python Lab – Simulating default times for a nth to default basket CDS.
.



Stochastic Calculus for Finance 
01
Stochastic process
Random Walk process
Wiener process
Named stochastic process (ABM, GBM, OU)
Conditional Expectation
Martingales & Markov properties
Ito’s Lemma
Ito Isometry
Ito Integral
Estimation & Calibration
02
Change of Measure
Probability, Sigma Algebra, Filtration
Tower property
Radon Nikodym derivative
Girsanov theorem
Excel & Python Lab – ABM, GBM, OU



Equity Derivatives
01
Binomial Asset Pricing Model
Stock price model
Valuing a European Option
Replicating strategy
Delta-hedging strategy
Risk neutral expectation
Value an American Option
Option with dividends
Excel & Python Lab – Custom Class for pricing an option using binomial tree model
02
Black Scholes
Derivation of BSM PDE
Formula for European Option Price and Greeks
03
Jump Process
Jumps in Asset Dynamics
Exponential Levy process
Variance Gamma process
Characteristic Function
Fast Fourier transform for Option pricing
04
Finite Difference Methods for Option pricing
Explicit Scheme
Implicit Scheme
Crank Nicolson
Stability Analysis
Excel & Python Lab – Price first generation exotics using Finite Difference
05
Monte Carlo methods for Option pricing
Fundamental theorem of Asset pricing
Feynman-Kac theorem
Simulating GBM (Euler Scheme, Milstein Scheme, Explicit Scheme)
Pricing First generation exotics using MCS.
Least Square Monte Carlo for Bermudan Options
Fast Monte Carlo Greeks (pathwise & likelihood ratio methods)
Excel & Python Lab – Custom class for Exotic pricing and Greeks
06
Volatility Surface
Historical volatility, Local volatility, Implied Volatility
Term Structure, Smile, Surface
Dupire Local volatility model
Stochastic volatility models (SABR, Heston)
Excel & Python Lab – Custom class for pricing under Heston and SABR models



Interest Rate & FX Derivatives
01
Rates and Rate Instruments
Spot vs forward
Short rates vs instantaneous forward rates
Term structure concepts
Fundamental theorem of asset pricing
Bank account & zero-coupon bond
Coupon bond (fixed, floating)
FRAs, Swaps, CMS
Excel & Python Lab – valuation of Bonds, FRAs and Swaps
02
Term Structure Models
Short rate models (Vasicek, CIR)
No Arbitrage Models (Ho Lee, Hull-White I, Hull-White II)
The HJM framework
Market Models (BGM)
02
Options on rates
The Black-76 model.
Caps & Floors
Swaptions
Excel & Python Lab – Calibration of swaption volatility surface
03
FX Instruments
FX forward
FX option
FX swap
Cross Currency Interest rate swap
Excel & Python Lab – Pricing of FX derivatives with volatility smile
Excel & Python Lab – CVA calculation for a portfolio of derivatives



Quantitative Portfolio Management
01
Portfolio Theory & Optimization
Modern Portfolio Theory
CAPM
Mean Variance Optimization
Black Litterman
Excel & PythonLab – A real life portfolio optimization problem
Excel & Python Lab – Implementation of Pairs-trading (A statistical arbitrage trading strategy)



Machine Learning for Finance
01
Traditional Supervised algorithms using Scikit Learn
Logistic Regression for predicting default.
Support Vector Machines for anomaly detection
Naïve Bayes for Sentiment Classification
Ensemble methods (Bagging, Boosting) for LGD
02
Traditional Unsupervised algorithms using Scikit Learn
PCA based value at risk for an interest rate portfolio.
K means clustering for volatility regime
03
Deep Learning with Tensorflow
Artificial Neural Network for Option Price
LSTM for stock price prediction
Building a Trading strategy with Reinforcement learning (OpenAI Gym)

Other Info

  • Duration : ~175 Hrs
  • Language : English
  • ₹ 40000

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