Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds
| Date | Stars |
|---|---|
| 2026-07-24 | 3542 |
| 2026-07-25 | 3544 |
| 2026-07-28 | 3544 |
| 2026-07-30 | 3544 |
| 2026-08-06 | 3544 |
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# Quant-Developers-Resources
### Quant Roles
`Quant Analyst` `Quant Researcher` `Quant Trader` `Quant Developer` `Algorithmic Trader` `Quant Strategist` `Quant Risk Analyst` `Quant Modeler` `Fixed Income Desk Quant` `Quant Finance Analyst`
`Quantitative Engineering` `Quant Consultant` `Interest Rate Derivative Quant` `Treasury Quantitative Analyst` `Risk Analyst` `Market Risk Quant` `Risk Manager` `Financial Engineer` `Credit Risk Analyst`
`Market Risk Analyst` `Model Risk Analyst` `Model Validation Analyst`
## 🔥Hiring Process
- 1) `Mental Math/Speed Math/Logic/Numerical Tests`
- 2) `BrainTeasers and Puzzles`
- 3) `Probability and Statistics`
- 4) `Market Making/Betting & Trading Games`
- 5) `Pattern Finding and Logic`
- 6) `Technical Rounds`
- 7) `Behavioral/Role Fit Rounds`
## 🚀 Most Important Topics for Quant Interviews
1) Probability and Statistics
2) Derivatives
3) Option Pricing Models
4) Greeks (Delta, Gamma, Rho, Theta, Vega)
5) Fixed Income Product
6) Stochastic Calculus
7) Machine Learning and Data Science
8) Econometrics
9) Risk-Neutral Valuation
10) Interest Rate Models
11) Volatility
12) Numerical Methods
13) Arbitrage Pricing Theory and No-Arbitrage Principle
14) Credit Derivatives
15) Regulatory Framework
16) Portfolio Management and Hedging Strategies
17) Exotic Options
18) Market Microstructure
19) Real-World Applications and Recent Trends
20) Portfolio Theory and Optimization
21) Algo Trading
### 🧰 Mathematics & Other Topics
- Linear Algebra
- Calculus
- Permutations & Combinations
- Probability Theory
- Statistics
- Optimization
- Differential Equations
- Ordinary Differential Equations (ODEs)
- Partial Differential Equations (PDEs)
- Taylor Series Approximation
- Applied Stochastic Calculus
- Ito's Lemma
- Martingales
- Brownian Motion
- Stochastic Differential Equations
- Stochastic Integrals
- Laws of Motion for Asset Pricing
- Limit Theorems
- Law of Large Numbers
- Central Limit Theorem
- Weak Law of Large Numbers
- Time Value of Money
- Asset Classes
- Fixed Income
- Equity
- Derivatives
- Commodity
- Options Pricing Models
- Black-Scholes-Merten Model for European Options
- GreeksA(Alpha, Gramma, Theta, Delta, Vega, Rho)
- Exotic Options and Pricing Methods
- Portfolio Optimization
- Arbitrage Theory
- Risk Management
- Value at Risk (VaR)
- Conditional Value at Risk(CVaR)
- Expected shortfall
- Risk Measures
- Portfolio Risk Assessment
- Financial Theories and Models
- Randomized Algorithms
- Volatility Modeling
- Mathematical Puzzles
- Logical Reasoning
### 🧰 Programming Languages
- Statistical Languages
- Programming Languages
- Python
- C++
- R
- MATLAB
- SAS
- Best Practices in Programming
### 🧰 Data Stack
- Data Science and Machine Learning
- Regression Analysis Ordinary Least Squares (OLS)
- Logistic Regression
- Generalized Linear Models
- Time Series Analysis
- Basics of Time Series and Stochastics Processes
- AR & MA models
- Stationarity & Ergodicity
- Autocorrelation & Partial Autocorrelation functions
- GARCH, ARCH & EWMA models for Volatility forecasting
- Monte Carlo Methods
- Monte Carlo Simulation for pricing and risk assessment
- Variance Reduction techniques(eg., control variates, antithetic variates)
- Markov Chains
- Transition Matrices and Markov Property
- State Space, absorbing states and recurrent states
- Steady-State and long-term behavior of Markov Chains
- Nonparametric Methods
- Data Cleaning and Processing
- Data Exploration
- Exploratory Data Analysis(EDA)
- Supervised Learning and Unsupervised Learning
- Advanced Machine Learning Techniques
- Neural Networks
- Gradient Boosting
### 🤟Best Lectures on Stochastic Calculus 🎯🎯
1. MIT Financial Mathematics --> [Link](https://lnkd.in/ghfKjRJC)
2.Excerpt of 16,603 characters
Read on GitHub
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:5398a54df8eb1287, topic:quantitative-finance, readme:financial, desc:quantitative