Directional and Relative Value Strategies

On Thanksgiving 2000, an equity-market-neutral fund closed the month up 15%. Long 400 undervalued stocks, short 400 overvalued, matched by sector and size. Seven years of 10-15% annual returns, near-zero correlation to the S&P 500. Then competitors noticed. Ten imitators launched in 2001, raising $8 billion collectively. By 2004, the original fund's returns collapsed to 1-2% gross. The strategy had not changed. The crowding had. That story is the curriculum's central thesis in miniature: markets stay only as inefficient as competition allows.

Directional strategies and efficiently inefficient markets. Directional strategies take intentional exposure to a market's direction, either a net long or a net short position. They can be implemented with traditional assets such as exchange-traded funds (ETFs). When actively traded, they often use listed derivatives (futures and options) and over-the-counter (OTC) derivatives.

The thesis that markets are perfectly efficient leads to two paradoxes of informational market efficiency:

• If markets are perfectly efficient, no one has an incentive to collect information, so no mechanism keeps markets informationally efficient.
• If markets are perfectly efficient, the fees paid to active managers imply that the markets for asset management are highly inefficient.

Common mistakes

• Confusing correlation with co-integration. Two stocks with correlation 0.95 can still have a spread that drifts forever because both are random walks. A pairs trade requires co-integration: a stationary linear combination of the prices. Trap answer: pick the highest-correlation pair. Correct: pick the pair whose log-price combination is stationary.
• Using raw prices instead of log prices in the pairs relation. The curriculum's co-integration relation uses natural logs, $\ln (p_t)-a\ln (s_t)=u_t$, to focus on returns. Writing the spread as a simple price difference misstates the model and the scaling parameter a.
• Stating Metcalfe's law as user base squared. The curriculum formula is $n(n-1)/2$, the number of connections among n users (4 users give 6 connections). Saying value scales with $n^2$ is only an approximation and is the wrong answer when the exam gives the exact form.

Bottom line

• Efficiently inefficient markets sit between two paradoxes of perfect efficiency: no incentive to gather information and impossibly high asset-management fees, leaving prices just inefficient enough to pay for skill.
• Directional strategies take net long or short exposure via ETFs, listed derivatives, or OTC derivatives.
• Technical directional strategies cover trend/momentum (cross-sectional vs time-series, point-and-figure) and divergence (signal-to-noise ratio, market divergence index).
• Fundamental directional strategies split into bottom-up and top-down, with four procedures, four mechanics, three macro schools, and two risks.

Exam shortcut

Identify the LO family first, then recall its exact list. For momentum, separate cross-sectional (relative ranking) from time-series (own performance). For divergence, the answer is the SNR formula (net move over summed absolute changes) and the MDI as its average. The favorite trap is substituting correlation for co-integration on pairs questions and calling market-neutral risk-free, so remember co-integration uses log prices and a stationary spread.

The full lesson (about 4,505 words, 30 min read) adds 2 worked examples, all 5 common mistakes, a self-check, free in the app.

Learning objectives

• model types
• fi models intro
• bdt model
• credit risk economics
• structural model overview
• merton model
• kmv model
• reduced form models
• empirical credit models
• one period binomial
• multi period binomial
• tree prices formation
• convertible valuation
• callable bonds tree
• multifactor asset pricing
• fama french
• empirical mf challenges
• factor investing
• adaptive markets
• efficiently inefficient
• trend following
• divergence
• fundamental directional
• behavioral finance
• directional factors
• digital asset valuation
• pca statistical factors
• multifactor regression
• partial autocorrelations
• dynamic risk exposure
• changing correlation
• multifactor return approaches
• performance persistence
• rv overview
• statistical pairs equities
• pairs commodity spreads
• pairs rates fx
• rv market neutral risks
• depreciation tax shields
• tax deferral gains
• after tax comparisons
• transaction based indices
• appraisal based indices

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