Directional and Relative Value Strategies

Imagine a hypothetical long/short fund whose excess returns shrink as copycat funds pile into the same trades: markets stay only as inefficient as competition allows.

Directional strategies and efficiently inefficient markets. Directional strategies deliberately hold a net long or net short exposure to where a market is heading. You can build them with traditional assets such as exchange-traded funds (ETFs). Active traders frequently turn to exchange-listed futures and options and to over-the-counter (OTC) derivatives.

If you assume prices always reflect all available information, you run into two paradoxes of informational market efficiency:

• In a perfectly efficient market, nobody would bother paying to gather information. Yet without information gatherers, nothing would keep prices efficient.
• Investors pay active managers substantial fees. If asset markets were perfectly efficient, those fees would mean the market for asset management itself is highly inefficient.

Efficiently inefficient markets resolve this. In these markets, average mispricing is large enough to pay managers and investors for the costs and risks of skill-based strategies.

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. Under the co-integration approach, a pair qualifies only if a linear combination of the log prices is stationary. Choosing the highest-correlation pair can therefore give you a spread that never reverts.
• 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 overstates the exact connection count (16 instead of 6 for 4 users).

Bottom line

• Efficiently inefficient markets sit between two paradoxes of perfect efficiency: no incentive to gather information, and active-management fees implying a highly inefficient asset-management market. Inefficiency varies across markets and through time.
• Directional strategies take net long or short exposure via ETFs, listed derivatives, or OTC derivatives.
• Technical directional strategies bet on positive return autocorrelation (trends) or negative return autocorrelation (mean reversion). Momentum (cross-sectional vs time-series) exploits continuation, while mean-reversion strategies exploit reversals; charting tools include moving averages and point-and-figure charts.
• Fundamental directional strategies split into bottom-up (scenario-weighted value, concentrated positions) and top-down (business cycle, inflation, monetary and fiscal policy), 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. Two costly confusions are 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 7,438 words, 50 min read) adds 2 worked examples, all 5 common mistakes, a self-check, free in the app.

Learning objectives

• model types
• credit risk economics
• structural model overview
• merton model
• kmv model
• reduced form models
• empirical credit models
• multifactor asset pricing
• fama french
• empirical mf challenges
• asset strategy complexity
• 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
• 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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