The Wall Street Quants BootCamp

The Wall Street Quants BootCamp

Finally, A Bootcamp For Quant Finance
A bootcamp run by Wall Street quants to break you into top tier hedge funds, HFTs, investment banks and more.

LEARN FROM THE BEST
BUILT BY QUANTS FOR QUANTS
Senior quants from top shops like Point72, Millennium, SIG (and more) show you how to land leading roles.

#2 PERFECT THE RIGHT SKILLS

 Stand Out with a Legit Quant Project
Impress employers by completing a side project they’d want done themselves. You’ll research and deploy a full-fledged quant strategy (on real money).

 Master the Skills Quant Firms Need
Our program teaches all the skills you need for quant (including coding) from the ground up, and mimics the training you would get within the first 2 years at a top-tier firm.

#3 NAIL RECRUITING & INTERVIEWS

 Resume Reviews
Craft the perfect resume with feedback from insiders. Learn how your candidacy is actually viewed by quant firms and tell your story persuasively.

 Interview Preparation
Prep for interviews efficiently with mock interviews, methods for cracking the technical component, strategies for the behavioral section, and guidance on take-home interview-projects (with samples).

 Recruiting Strategy
Get insider knowledge on various firms, roles/teams and headhunters. Get insights on where and how to apply given your background.

WHO IS THIS FOR?
Anyone Who Wants To Advance Their Career In Quant Finance

UNDERGRADUATE STUDENTS

Undergraduates looking for an internship or full-time role

GRADUATE STUDENTS

Masters or phd students looking for an internship or full-time role

CAREER SWITCHERS

Candidates from different industries (i.e. tech) looking to move into quant

CURRENT QUANTS

Quants who want to excel on the job and get ahead

LEARN THE PERFECT QUANT SKILLSET
No more guessing which major or courses you need. Follow a curriculum designed by Wall Street quants to give you the right skills. By the end, you’ll be able to research & code quant strategies like the hedge funds.

COURSE OUTLINE
Everything you’d learn in your first 2 years at a top-tier firm

#1 THE BIG PICTURE
We guide you through a 30,000 foot tour of quant research & trading. Develop a high-level understanding of key concepts before we dive into the fine details.

Sub-topics: backtesting, overfitting, idea generation, types of quant strategies, the major quant firms

#2 CODING FOR QUANT FINANCE
Learn the most widely used coding language by quants today: Python. We teach it from the ground up with attention to the specific skills & libraries desired by quant firms. There are lots of practical code examples (focusing on quant applications) and interactive exercises designed to bring you up to speed even if you don’t have a coding background.

Sub-topics: python, numpy, pandas, data analysis, data sources, plotting

#3 EVALUATING QUANT STRATEGIES
Quants have a rigorous framework for deciding if a strategy is any good. You can’t manage what you don’t measure! Learn the current industry-standard techniques & metrics used in strategy evaluation.

Sub-topics: sharpe ratios, regressions, volatility, returns, drawdowns, alpha, beta

#4 BUILDING QUANT MODELS (WEIGHTING/OPTIMIZATION)
Mature quant models are often combinations of many (sometimes hundreds!) underlying strategies. Understand best-practices for building powerful quant models by optimally combining individual strategies.

Sub-topics: correlation, breadth, covariance matrix, volatility-weighting, risk-parity, sharpe ratio – weighting, generalized weighting, robust weighting

#5 PORTFOLIO CONSTRUCTION
You’ve found a dataset / signal that you think predicts returns. Now, how do you robustly and accurately express this signal as a tradable portfolio of securities?

Sub-topics: signal transformations, cross-sectional (XS) models, time-series (TS) models, implementation

#6 BACKTESTING
Backtesting, the art & science of simulating your strategy with historical data, is the bread and butter of quant. We teach the two types of backtesting used in the quant workflow.

Sub-topics: unconstrained backtests, optimized backtests

#7 STRATEGY (“ALPHA”) RESEARCH BEST PRACTICES
Conducting “alpha” research to discover new strategies is an art! Learn industry best-practices and how to avoid common pitfalls (including overfitting).

Sub-topics: overfitting, out of sample testing, priors, model complexity, the utility of machine learning

#8 STRATEGIES (STATISTICAL ARBITRAGE)
Learn the main strategy types used in industry today and leave with a powerful arsenal! There’s a focus on stronger “statistical arbitrage” strategies. We also teach methods/frameworks for improving strategies and taking them to the next level.

Sub-topics: event-driven, momentum, reversal, pairs trading, statistical arbitrage, value, crypto strategies

#9 COURSE PROJECT – “STATISTICAL ARBITRAGE IN CRYPTOCURRENCIES”
We guide you through a project that mimics the actual work you’d do at a quant hedge fund.

The goal is to develop a statistical arbitrage strategy in cryptocurrencies. We provide a research outline for the project, including a framework for building profitable mean-reversion & momentum strategies. Ambitious students can deploy their strategy on real money using code provided at the end of the course in Part 13.

#10 EXECUTION
Trading costs can make or break a strategy, especially for higher frequency “statistical arbitrage” strategies. Learn the main types of trading costs and how to incorporate them in backtests. We further explore transaction cost modeling and methods for minimizing costs.

Sub-topics: commissions, slippage, bid-ask spread, turnover, transaction cost modeling, portfolio optimization

#11 RISK
Understand different risk sources (“factors”) beyond the market (“beta”), how to measure them and how to immunize (“neutralize”) your portfolio to them to build a more robust strategy.

Sub-topics: risk factors, barra risk models, fama-french factor models, beta/loading, risk contribution, risk-neutralization

#12 PORTFOLIO OPTIMIZATION
Most quants use an optimization as the “final step” in forming portfolios. Optimizers strategically balance return, risk, transaction costs and portfolio constraints (IE. long-only). Learn how to implement one from scratch using convex-optimization and the cvxpy library.

Sub-topics: mean-variance optimization, convex optimization, cvxpy, transaction cost models, portfolio constraints

#13 LIVE PYTHON TRADING LIBRARY
We wrap up the course by walking you through the code for a flexible python trading library that allows for live trading (and backtesting) fully-automated quant strategies on real money. Learn how to implement a robust end-to-end production trading system, and impress employers by building a live personal track-record.

Sub-topics: order management, live data feeds, broker APIs, logging

STATISTICAL ARBITRAGE IN CRYPTO
Our bootcamp features a project designed to set your resume apart. You’ll build a realistic quant strategy employers would want themselves. Ambitious students can stand out by using our python trading library to deploy your new strategy on real money and showcase a profitable track record.

• Research outline with frameworks for building stat-arb models, including mean-reversion & momentum strategies
• Code examples and institutional-grade python trading library for backtesting and live trading your new strategy
• How to communicate your results maturely and intelligently
• Continuous guidance by instructors so you don’t get stuck

If you have any questions regarding this product, please contact us by email: [email protected]