Analyst Academy By Fundamental Edge – Free Download Course By Brett Caughran
You’ll get a flexible asynchronous academy equipping you with the frameworks, tools, & training to fast track your buy-side career on your schedule!
✅ About This Course:
✅ Course Author: Brett Caughran, Fundamental Edge
✅ Official Course Price: $5400
✅ Free For Our VIP Members? : Yes
✅ Download Links : Mega & Google Drive
✅ Course Size : 36.29 GB
✅ Updatable? : Yes, all future updates included.
✅ Sales Page : You can check at the bottom of this page.
🏆 Here’s What You Get & Learn With This Course:
Introductory Tools – Modules 1-4
Foundational Tools:
Modules 1-4
Analyst Toolkit Deep-Dives: the 12 core modules that teach the skills a buy-side analyst will need when PM asks, “hey go look at XYZ stock and let me know what you think”
1) Fundamental Foundations
Fundamental analysis importance in market economies
Myth of efficient markets and reality
Four reasons why markets are not efficient
Alpha load and forms of mispricing
Recipe: skills, process, sound judgment
Idea generation and 10% mindset
Role of process and judgment in forming belief
Voting machine vs weighing machine
Goal: Identify mispricings, harvest alpha
Pareto distribution and top performer challenges
2) LIFE ON THE BUY-side
Buy-side primer: structure, roles, investment objectives
Limited partners (LPs) and their investment goals
Hedge funds: single-manager vs. multi-manager structures
Long-only funds: business model and challenges
Analyst role: idea generation to thesis development
Investment process: idea assessment to monitoring
Buy-side mindset
Leveraging information edge to generate alpha
Anatomy of a top-performing buy-side analyst
Creating a rigorous, repeatable investment process
3) Thesis Development
Thesis-driven investing: a structured approach
Analyst’s role: developing expertise and ideas
Coverage models impact thesis development latency
Nine-step thesis development process
Model construction: key tool for analysis
Structured due diligence: FEV framework
Identifying key drivers and differentiated insights
Constructing the thesis: key elements, delivery
Presenting the thesis: succinct, focused, humble
Idea maintenance: monitoring key drivers, catalysts
4) Why Stocks Move Up and Down
Stocks move due to supply and demand
Market price: capital-weighted consensus of value
Drivers: fundamentals, expectations, valuation, non-fundamental factors
Stock price differs from business value
EPS growth, revisions, re-ratings
Focus Five framework: key business value drivers
Model linkage helps identify key drivers
Exceptionalism, perception shifts, narratives
Risk reduction and visibility impact valuations
Inflections and themes
Intermediate Tools:
Modules 5-11
Analyst Toolkit Deep-Dives: the 12 core modules that teach the skills a buy-side analyst will need when PM asks, “hey go look at XYZ stock and let me know what you think”
5) IDEA Generation
Efficiency: avoiding deep dives prematurely
Seeking mispriced stocks likely to have alpha
Compounders, exceptionalism, and change/confusion
Thematic investing: themes drive revenue and value
Pattern recognition from experience guides idea generation
FEV framework: fundamentals, expectations, valuation
Cyclical vs secular trends often misunderstood
Idea screening using multiple lenses and criteria
Ingredients of compelling ideas: mispricing and catalysts
Efficient idea vetting process with PM check-ins
6) Buyside Modeling
The six reasons buy-side analysts build models
A step-by-step raw build: TSLA walk-through
Common modeling challenges
Bells & whistles: incr margin, 2-year stack & more
Understanding consensus & estimate revisions
Seven hacks for identifying variance vs. street
Mental frameworks for better forecasting
The three statements for stock pickers
What your PM is looking for in your model
The model & stock selection: NVST case
7) Analyze a Business
Read 10-K, earnings calls, sell-side research
Build simple model, identify key drivers
Assess business quality, viability, momentum
Analyze unit economics and cash economics
Understand market expectations priced in
Develop bull, base, bear cases
Focus research on 3 key drivers
Evaluate management and capital allocation
Compare to peers on key metrics
Analyze catalysts and risk/reward setup
8) Analyze an Industry
Learn industry through primers, experts, conferences
Develop universe tracker and comp sheets
Understand sector economics with industry P&L
Maintain coverage through regular blocking & tackling
Use model to identify inflections, catalysts
Connect dots between competitors and industry
Pursue both quick dives and deep dives
Long compounders with durable growth algorithms
Short melting ice cubes with structural headwinds
Pair trades can provide persistent alpha
9) Management & CapitaL Allocation
Why management matters (and when it doesn’t)
A framework to evaluate management
Doing a deep dive on a management team
The obsession with corporate access
A structured management meeting process
The role of investor relations
Navigating an investor conference
Analyzing stock-based compensation
Five options for deployment of cash
Analyzing stock buy-backs
10) Assessing Expectations
Stocks move based on expectations vs reality
Management guidance, sell-side estimates influence expectations
Price-implied expectations uncover market assumptions
Buy-side whisper reflects true market expectations
Assess positioning via ownership data, trading signals
Contrarian positioning can yield alpha but risks
Expectations gap: market view vs internal view
Differentiated, variant view key to generating alpha
Core debate, key drivers guide expectations work
Critical questions: situation overview, differentiation, monetization path
11) Applied Valuation
Stock valuation based on discounted cash flows
Key approaches: DCF, multiples, normalized earnings
Multiples are shorthand for a DCF
P/E roll-forward approach
Choosing an appropriate multiple
Earnings power approach
Develop risk/reward framework
Disaggregate stock returns
Create scenario trees with weighted outcomes
Be aware of terminal value perception
Advanced Tools – Modules 12-15
Advanced Tools:
Modules 12-15
This week we’ve assembled leading experts that span across the industry to give you insight and access to some of the brightest and innovative minds on Wall St. and beyond.
12) SHORT SELLING
Short selling basics and mechanics
Challenges and risks of shorting stocks
Shorting approaches: alpha, structural, event-driven, hedging
Identifying short ideas: fundamentals, expectations, valuation
Short alpha buckets and types of shorts
Importance of timing and risk management
Earnings season tactics for shorts
De-grossing: reducing exposure in tough markets
Quantitative short selection framework
Applying short selling mindset to long-investing
13) EARNINGS SEASON
Earnings season drives outsized stock volatility
Expectations gap and catalyst framework explained
Preparing for earnings: previews, positioning, catalysts
Updating models and assessing results efficiently
Evaluating surprise factor and algorithmic shifts
Estimating upside/downside moves and risk/reward
Tactics for earnings day and beyond
Analyzing read-throughs and adapting expectations bar
Identifying spring-loaded and peak-on-peak setups
Reacting to prints and fading overreactions
14) PITCH LIKE A PRO
Turn a promising idea into compelling thesis
Construct thesis using firm’s preferred format
Key elements: summary, thesis points, risks, valuation
Tell a story with strong supporting data
Anticipate questions and prepare concise responses
Deliver pitch succinctly balancing confidence and humility
Follow up promptly on any open questions
Avoid thesis creep using a trading plan
Conduct pre-mortem and post-mortem using thesis document
When evaluating pitches, prepare to poke holes
15) WRAPPING UP
Rank stocks using reward/risk and qualitative scores
Idea stack: long and short book rankings
Three-year double: EPS growth and P/E expansion
Risk management: VaR, quant models, event frameworks
MIC: market view, internal view, convergence
FEV: fundamentals, expectations, valuation for idea generation
Achieving ETIK, focusing on key drivers (KDs)
Communicate idea with structured pitch script
Portfolio construction balancing risk/reward
across ideas
Analyst progression: junior to “full stack” partner
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You can find more info on the sales page here.
