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Random Number Generation: ICDF Method for Inhomogeneous Exponential Distribution
Random Number GenerationICDFInhomogeneous Exponential Distribution
The Inverse Cumulative Distribution Function (ICDF) method is a general technique for generating random numbers from any probability distribution for which the CDF (Cumulative Distribution Function) has a well-defined inverse. Here's how to apply the ICDF method to generate random numbers from an inhomogeneous exponential distribution:
A very famous model in finance is the Capital Asset Pricing Model (CAPM). This is an equilibrium model that assumes investors hold a portfolio that gives maximum expected return for a given level of risk
5QQMN534: Algorithmic Finance Coursework: Resampling Returns Data and Strategy Analysis
5QQMN534Algorithmic FinanceStrategy AnalysisPython
You are a research analyst for AlphaMasterFOF a ‘fund of funds’. This is a type of fund that invests in other hedge funds. Your fund is considering investing in a strategy that has been trading for several years. The live performance record of the strategy is in the file ‘Strategy_returns.xlsx’.
FINA6229 Machine Learning in Finance Project 5: A Comprehensive Investment Project with Machine Learning
FINA6229Machine Learning in FinancePythonCAPMRidge regressionLASSO
The purpose of Project 5 is to give you some exposure to applying machine learning techniques to design an advanced investment strategy.
MFIN7034 Machine Learning and Artificial Intelligence in Finance - Problem Set 1 - Factor Model
MFIN7034Machine Learning and Artificial Intelligence in FinanceFactor ModelPython
In this assignment, you will run regressions to understand how the factor model explains asset return and construct an investment strategy based on the factor model.
[2022] SMU - QF633 C++ for Financial Engineering - Assignment 3 - Order Manager
C++QF633C++ for Financial EngineeringSMU
In this assignment, we will explore building a simple but very efficient order manager using the <algorithm> library.
[2022]University of Queensland - ECON7350: Applied Econometrics for Macroeconomics and Finance - Research Report 2
ECON7350: Applied Econometrics for Macroeconomics and FinanceR langMEM Approach
Use the observed icu data for the period 08 March 2021—31 March 2021 to qualitatively evaluate and compare forecasts generated by the MEM(s) to the forecasts you generated in Research Report 1. What implications can be drawn from this analysis for further developing / refining icu forecasting methods?
QF633 C++ for Financial Engineering - Course Project: Cryptocurrency Tick Data
SMUQF633C++ for Financial EngineeringCyrptocurrency Tick DataC++
Complete the FitSmiles function in VolSurfBuilder.h. It groups the market tick data by expiry date, pass the data of each expiry to the FitSmile function in the smile model to fit the model to the market data, and calculate the fitting error
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