Deep Dive: CFA® Level I Prep 2026

Dive into Simulation Methods from Quantitative Methods – CFA Level I with Mara Ellington & Dorian Hayes.

Turn randomness into insight, one simulation at a time.

Portfolio Mathematics – CFA Level I

Join Mara Ellington and Dorian Hayes as they turnChapter 1 Quantitative Methods into something you can actually use.

Perfect bite-sized review for your CFA Level I prep.

CFA® Level I Boost w/ Mara Ellington & Dorian Hayes

Learn how to turn messy scenarios into clean probability trees and sharp conditional expectations—in one focused session.

Perfect for commute-length revision and exam-day clarity.

Statistical Measures of Returns with Mara Ellington & Dorian Hayes.

In this bite-size Quant Methods episode, we turn raw return data into insight:

Perfect if you want CFA Level I stats to finally “click”.

Time Value of Money Deep Dive with Mara Ellington & Dorian Hayes.

In this episode we turn abstract formulas into real decisions:

Perfect for CFA Level I candidates reviewing Quant Methods, Chapter 1.

Hosted by Mara Ellington & Dorian Hayes

Ready to finally “get” rates & returns instead of memorising formulas? In this bite-size episode we turn Quant Methods – Chapter 1 into clear, exam-ready intuition.

Goal: walk away able to explain every key formula without looking at your notes.

This module brings ethics to life through realistic scenarios and case studies that apply the Code and Standards. You'll practice identifying violations, applying ethical reasoning, and making judgment calls in complex situations. It’s all about turning ethical principles into confident, day-to-day decision-making.

This module introduces the Global Investment Performance Standards (GIPS), a set of voluntary, ethics-based principles that promote fair and transparent reporting of investment results. You'll learn why GIPS exist, who uses them, and how they help clients compare performance across firms by standardizing calculations, disclosures, and presentation practices.

Standard VII reinforces the duty to uphold the reputation and integrity of the CFA designation. It requires members and candidates to comply with the Code and Standards, avoid any conduct that could harm the CFA Institute, and never misrepresent the meaning or implications of earning or pursuing the CFA charter.

Standard VI addresses the importance of identifying and managing conflicts of interest that could compromise objectivity. It requires full and fair disclosure of any potential conflicts—especially those involving ownership, compensation, or referral arrangements—so that clients and employers can make informed decisions with confidence.

Standard V focuses on maintaining the integrity and quality of investment research and decisions. It requires professionals to base analyses on thorough due diligence, clearly communicate investment recommendations and risks, and retain records that support the investment process. The standard ensures transparency and accountability in all investment actions.

Standard IV outlines the responsibilities investment professionals have toward their employers. It covers the duty of loyalty, maintaining competence, and acting with integrity while on the job. It also addresses proper conduct when leaving a firm and the importance of not misusing employer resources or confidential information.

Standard III emphasizes the fiduciary responsibility investment professionals owe to their clients. It outlines duties such as loyalty, prudence, and care; ensuring fair dealing; preserving confidentiality; and providing suitable, objective advice. This standard reinforces that clients’ interests must always come first.

Standard II protects the fairness and transparency of global capital markets. It focuses on two key areas: Material Nonpublic Information—ensuring analysts don’t misuse inside information—and Market Manipulation—prohibiting practices that distort prices or trading volume. The goal: promote investor confidence by keeping markets level and trustworthy.

Standard I covers the fundamental duty of acting with integrity and professionalism. It sets expectations around knowledge of the law, independence and objectivity, misrepresentation, and misconduct. You'll learn how to navigate conflicts, avoid biased research, and maintain trust in your professional interactions—especially when legal and ethical standards diverge.

This module introduces the CFA Institute Code of Ethics and the Standards of Professional Conduct, the backbone of ethical investment practice. You'll explore the six core ethical responsibilities and seven standards that guide duties to clients, employers, markets, and the profession. Each standard is explained with practical examples to help you apply them in real-world scenarios.

This opening module explains why ethics and trust are foundational to functioning capital markets. It explores how ethical conduct enhances investor confidence, defines professionalism, and reduces systemic risk. You'll also learn to distinguish ethical standards from legal ones, and understand the consequences when fiduciary duty is breached. This sets the tone for the rest of the Ethics curriculum.

The final chapter frames risk management as an enterprise-wide process. It describes risk governance, risk tolerance and budgeting, distinguishes financial from non-financial risks, and evaluates tools for measuring, preventing, accepting, transferring, or shifting risk—providing a comprehensive toolkit for modern risk managers. :contentReference[oaicite:5]{index=5}

Here the curriculum turns to behavioral finance, categorizing cognitive errors and emotional biases that can distort investor decisions. It illustrates common biases (e.g., overconfidence, loss aversion), links them to market anomalies such as momentum and bubbles, and discusses how awareness of these tendencies can improve wealth-management advice. :contentReference[oaicite:4]{index=4}

Focusing on practical implementation, this chapter explains the Investment Policy Statement—its key components, objectives, and constraints—and shows how client information feeds into capital-market expectations, strategic asset allocation, and ESG considerations when assembling portfolios. :contentReference[oaicite:3]{index=3}

The chapter adopts a portfolio perspective, highlighting diversification benefits and the risk–return trade-off. It walks through the three-step portfolio-management process (planning, execution, feedback), profiles individual and institutional investors, and surveys the structure and current trends of the global asset-management industry. :contentReference[oaicite:2]{index=2}

Building on Part I, this chapter introduces capital-market theory. It derives the Capital Market Line and the Security Market Line, decomposes total risk into systematic and nonsystematic components, develops the CAPM and beta, and presents key risk-adjusted performance measures such as the Sharpe, Treynor, M² and Jensen’s alpha. :contentReference[oaicite:1]{index=1}

This chapter lays the foundations of modern portfolio theory. It reviews the historical risk-return profile of major asset classes, explains risk aversion and utility, shows how diversification shapes the minimum-variance and efficient frontiers, and demonstrates how investors combine a risk-free asset with risky portfolios to reach an optimal allocation. :contentReference[oaicite:0]{index=0}

Long/short, event, relative-value, macro … Unpack the strategy zoo.

You’ll finish able to decode any hedge-fund pitch-book in under five minutes.

Timber, farmland, and commodities join the alternatives toolkit.

Perfect if you’ve ever wondered why soybeans and gold dance to verydifferent macro tunes.

Bricks, mortar & bridges. Compare the cash-flow engines ofincome-producing property and long-lived infrastructure projects.

After this module you’ll know why toll roads trade like bonds and officesbehave like equities.

From start-ups to leveraged buy-outs. Map the spectrum ofprivate equity (VC, growth, buy-out) and private debt (direct lending,mezzanine, distressed).

Essential listening before you quote IRRs at networking drinks.

Measuring performance is trickier here. Longer life-cycles,irregular cash flows, leverage and complex fees mean IRR and MOIC trump simpletime-weighted returns.

You’ll learn why “headline” numbers can mislead—and how to adjust them.

Why alternatives? They promise higher expected returns andlower correlations—but at the cost of liquidity, longer holding periods andspecialised know-how. This module:

The perfect launch-pad for everything that follows.

Construct a simple up/down binomial tree to price a European call. Learn risk-neutralprobabilities, replicate pay-offs with ∆-hedged portfolios, and generalise theframework for any derivative where pay-off depends on one period of pricemovement.

Employ put–call parity to replicate forwards, build collars, and decompose equityvalue into debt + option components. Extend to forward parity for off-marketstrikes and see how corporate finance uses these identities.

Break option value into intrinsic and time components, test moneyness, andstudy six core inputs (spot, strike, time, rate, volatility, income). Use arbitrage andreplication arguments to bound fair prices before jumping into models later.

View a plain-vanilla swap as a strip of forward contracts: solve for the par swaprate that sets initial value to zero, then track mark-to-market gains as rates move.Covers fixed-for-float interest swaps, currency swaps and the impact of clearing.

Derive fair-value futures prices at inception, then follow daily variation margin tosee how gains/losses crystallise. Compare futures with equivalent forwards, explorerate-futures versus FRAs, and note how central clearing reshapes counter-partyrisk.

Price and mark-to-market forwards between trade date and expiry—first fornon-income assets, then for instruments with cash flows. Extend the logic tounderlyings that have their own term structures (rates, FX), and master forwardrate agreements (FRAs) as a special case.

Link spot and forward prices through no-arbitrage. Build synthetic forwards bycombining cash positions with borrowing/lending, then adjust for dividends,storage, or FX rate differentials in the cost-of-carry. Understand why forwardprices can trade above or below spot—depending on net carry.

See how issuers hedge earnings, how investors gain cheap leverage or preciseexposures, and where dangers lurk: basis, liquidity, counter-party and systemicrisk. Real examples show futures lowering funding needs and swaps smoothingcash-flow volatility—alongside cautionary tales of excessive leverage.

Firm promises vs. flexible rights: dissect forwards, futures and swaps(linear pay-offs) then contrast them with options and credit derivatives(non-linear, buyer-only choice). Learn how margin, daily settlement and embeddedleverage shape risk, and why put–call parity lets you build a synthetic forward fromtwo options.

Quick tour of the derivatives universe: define what makes a contract aderivative, classify popular underlyings (equities, rates, FX, commodities, credit),and compare OTC versus exchange-traded markets—including how centralcounterparties (CCPs) reduce default risk. By the end you’ll know where eachinstrument trades, why standardisation matters for liquidity, and how margin keepsthe system safe.

From pass-throughs to CMOs we unpack prepayment mechanics, tranche types and commercial vs. residential differences. Understand PSA curves, extension risk and how agencies wrap credit.

Explore structural credit enhancement, tranche waterfalls and trigger tests. Compare classic asset classes—autos, cards—and newer niches like solar leases and whole-business deals.

Follow the pipeline from loan pool to special-purpose entity to tranche. See how credit- and time-tranching reshape risk for issuers and investors, plus the economic case for securitization.

Dive into business risk, moats, management and detailed financial ratios. Finish with recovery analysis across the capital stack and why ratings can lag the market.

Blend qualitative governance checks with quantitative debt, growth and external-balance ratios to rank sovereign default risk. Contrast with sub-sovereign and supranational analysis.

Define default, recovery and credit migration. Walk through structural vs. reduced-form models and see how ratings, leverage and cyclical forces feed into spread moves.

Swap from yield-shift to curve-shift analytics: key-rate durations, twist & butterfly exposures, plus empirical (regression) duration when cash-flow data are messy.

Add curvature to your risk toolkit. Topics: standalone bond convexity, duration-plus-convexity price estimates and building target-duration/convexity portfolios.

Compute modified, money duration and price-value-of-a-basis-point for bullets, zeros, floaters and perps. See how convexity tweaks the linear estimate.

Break total return into income, reinvestment and price change. Link Macaulay duration, investment horizon and curve shifts to work out when rising rates can still boost realised return.

Boot-strap spot curves, derive par & forward rates, and flip between them to price bonds or swaps. Finish with curve shapes and what they signal about growth, inflation and policy.

Floating notes aren’t risk-free. We calculate money-market yields, discount margins and quoted margins, then see how caps, floors and reference-rate changes alter valuation.

Deconstruct quoted yields: street-convention, bond-equivalent, periodicity tweaks and callable-bond option-adjusted spreads. Learn when each metric best explains risk-adjusted return.

Discount every coupon like a pro. Topics include PV with spot curves, YTM conventions, full vs. flat price, constant-yield price paths and matrix pricing when comparable issues are thinly traded.

Survey sovereign T-bills, notes & bonds, plus quasi-govt, municipal and supranational paper. We show auction formats, benchmark curves and the unique tax, liquidity and policy roles these securities play worldwide.

Short-term working-capital lines, ABCP, bank revolvers and repos vs. long-term IG or HY bonds—this module links funding choices to credit strength. Walk through loan covenants, backup liquidity lines and why HY issuers rely on collateral and call protection.

From roadshow to re-offer we track a new issue’s life, then dive into secondary-market micro-structure. Understand broad vs. sector indexes, turnover math and why liquidity clusters in the newest (“on-the-run”) paper. We also compare primary auctions, syndications and private placements.

Go beyond plain-vanilla coupons. We map amortizing schedules, sinking-funds, FRNs, zeros, linkers and deferred-coupon bonds. Compare issuer pros & investor cons, then learn how contingency features—calls, puts, converts—reshape risk/return for both sides of the deal.

First stop on the bond tour: what exactly are you buying? We break down issuer types, par value, coupons (fixed vs. floating), seniority in liquidation and the covenants that legally bind the borrower. See how each feature shapes cash-flow timing and default risk, and why investors demand different yields for different structures.

The capstone module—linking cash flows to price. Inside you will:

You’ll graduate able to triangulate value from first principles and market sentiment.

Turn history into forward numbers:

The result: defensible pro-formas ready for valuation.

No company operates in a vacuum. This module teaches you to:

You’ll pinpoint where a company sits on the competitive map—and why that drives valuation multiples.

A forensic look at a firm’s historical performance:

Mastering the rear-view mirror sets the stage for credible forward forecasts.

Dive into the world’s dominant asset class. Grasp what equity really represents and why its risk-return profile is unique. Highlights:

These building blocks are the foundation for later valuation work.

From the Efficient Market Hypothesis to behavioural anomalies, this module asks, “Can you really beat the market?” Key topics:

You’ll leave with a balanced view of when active skill adds value—and when indexing rules.

This module lifts the hood on the benchmarks we quote every day. You will:

By the end, an index’s construction secrets—and its biases—will be crystal-clear.

Why this matters: Every analyst’s idea eventually becomes a trade. This module maps the entire trading landscape—from the six core purposes of the financial system to the mechanics of orders, leverage and regulation.

Outcome: You’ll know exactly how ideas are executed, what makes a market “well-functioning,” and how that links back to valuation.

Build a three-statement model from revenue to valuation, bias-aware.

DuPont, ratios, regressions—turn numbers into stories and valuation inputs.

Spot bias, earnings management and GAAP departures before they wreck value.

Temporary vs. permanent differences, DTAs/DTLs, and real cash-tax impacts.

Leases, pensions, share-based comp—convert off-BS promises into debt-like risk.

PP&E, intangibles, leases—track the asset life-cycle from acquisition to impairment.

LIFO, FIFO, write-downs—see how inventory choices sway cost and margin.

Dive deeper: free cash flow, common-size cash flows, and liquidity ratios.

Trace cash through operations with direct vs. indirect methods and statement linkages.

Assets, liabilities, equity—learn placement, measurement and ratio signals.

From topline to EPS, decode how revenues, matching, and non-recurring items reshape the story.

Kick-start Season 4 by mapping the six-step framework analysts use to turn raw filings into insight.

Strip a company to its DNA: who it serves, what it sells, how it captures value.

Debt or equity? Peek inside the Modigliani–Miller lab and the real-world frictionsthat bend theory.

From factory floors to fintech apps—learn how issuers vet and fund projects.

Cash is the fuel—learn to measure it, speed it and never run dry.

Zoom in on boards, committees and incentives that make—or break—value creation.

Follow the cash—and the conflicts—between lenders, shareholders, boards, managersand the wider world.

Kick off Season 3 by mapping how businesses are legally built—and why it matters toanalysts.

Practice cross‑rates, forwards, premiums‑discounts and covered‑interest parity so you can price multicurrency cash‑flows with confidence.

Identify FX players, quote conventions, currency regimes and the trade‑balance link; assess how capital controls tilt returns and risk.

Weigh the gains, losses and welfare shifts from tariffs, quotas, subsidies and regional blocs; master comparative advantage and integration tiers.

Map state and non‑state actors, globalization forces, trade institutions and risk signposts so you can price political shocks into investments.

Dive into central‑bank mandates, policy rates, open‑market ops, reserve requirements and transmission channels from money to growth and inflation.

Unpack deficits, the debt burden, spending vs. tax levers and the fiscal multiplier so you can model how budgets shift aggregate demand.

Track expansion, peak, contraction and trough; link credit cycles, indicators and now‑casting tools to corporate earnings and asset returns.

Compare perfect, monopolistic and oligopoly markets; find breakeven and shutdown points; see how pricing power changes with concentration and scale.

Unpack the 3 Vs (+ veracity) of Big Data, AI & ML toolkits, data pipelines,visualisation, and NLP—all tailored to quantitative investing.

Estimate slopes and intercepts with OLS, check key assumptions, interpretANOVA, R², and transform data (log‑lin, lin‑log, log‑log) for better fits.

Learn to verify co‑movement: t‑tests for Pearson correlation, Spearman rankfor monotonic links, and chi‑square for independence in contingency tables.

Master the six‑step test framework, Type I/II errors, power, and the bread‑and‑buttert‑, χ²‑, F‑ and non‑parametric tests used throughout finance.

From sampling designs to the central‑limit theorem, nail standard errors andbootstrap confidence intervals so you can quantify parameter uncertainty likea pro.

Discover lognormal price behaviour, Monte Carlo pricing and risk, andbootstrap resampling when history is all you have—key tools for modernquant finance.