Quantitative Investment Management, LLC

Quantitative Investment Management, LLC (QIM) is a Charlottesville, Virginia–based quantitative hedge fund manager and commodity trading advisor. Founded by Jaffray Woodriff, Michael Geismar, and Grayum Givens, the firm built its franchise around systematic managed‑futures and global macro strategies, later expanding into additional quantitative equity and multi‑asset programs. QIM manages capital for institutional investors, fund‑of‑funds, and other qualified clients through private funds and separately managed accounts. QIM is registered with the U.S. Securities and Exchange Commission as an investment adviser and also registered as a commodity trading advisor and commodity pool operator with U.S. derivatives regulators. It appears in SEC records as an institutional investment manager under CIK #0001445911 and files quarterly Form 13F reports. These 13F filings disclose the firm’s reportable long U.S. equity and certain equity‑linked positions over which it has investment discretion. They represent only a narrow slice of QIM’s activity: the firm’s core exposures are expressed through futures, options, forwards, and swaps across equities, rates, currencies, and commodities—positions that are not captured in Form 13F. Organized into a time‑series 13F History, however, the filings provide a consistent, regulator‑defined window into the structure of QIM’s long U.S. equity sleeve.

QIM’s flagship strategies are systematic and multi‑asset, with a strong heritage in managed futures and trend‑following models applied across global futures and forwards. Over time, the platform has incorporated a broader range of signals—trend, carry, value, volatility, and other proprietary predictors—as well as systematic long/short equity and other relative‑value strategies. The firm’s research process is data‑intensive and model‑driven, emphasizing robust statistical testing, risk budgeting, and portfolio optimization. Key features of the approach include: - Development of predictive models that exploit time‑series and cross‑sectional relationships in futures, currencies, and equities. - Broad diversification across asset classes, geographies, sectors, and instruments, with careful control of factor exposures and correlation structure. - Systematic portfolio construction, in which position sizes are a function of signal strength, volatility, liquidity, and risk constraints rather than discretionary conviction. - Active use of leverage and both long and short exposures within tightly controlled risk limits. Within this framework, the long U.S. equity and ETF positions visible in Form 13F are typically the implementation leg of broader quantitative strategies, rather than a standalone long‑only product. They can arise from several sources: - Long components of systematic long/short or market‑neutral equity portfolios. - Equity or ETF holdings used to hedge or complement futures exposures (for example, proxy hedges or basis trades). - Positions that form part of cross‑asset or sector‑rotation models where the long side happens to reside in cash equities or ETFs. As a result, the 13F book is usually: - Broadly diversified across sectors and issuers, often with large issuer counts. - Structured to be approximately neutral to aggregate sector weights and major factors when viewed in the context of the corresponding short and derivative positions that are not reported. - High‑turnover relative to traditional long‑only managers, reflecting frequent rebalancing as model signals and risk estimates update. For allocators analyzing QIM’s public‑equity footprint, the most informative lens is the evolution of its 13F Portfolio Composition over time: breadth of names, shifts between single‑stock and ETF usage, and changes in capitalization and sector distributions that can be linked back—imperfectly—to changes in underlying model themes.

Viewed through its SEC filings under CIK #0001445911, Quantitative Investment Management, LLC appears as a large, quantitatively driven hedge fund platform whose 13F disclosures capture only one component of its multi‑asset strategies: the long U.S. equity and ETF sleeve. That sleeve is systematically diversified across sectors and issuers, high‑turnover, and constructed according to model outputs and risk constraints rather than discretionary stock picking—features entirely consistent with a statistical‑arbitrage and managed‑futures heritage. For institutional allocators and oversight teams, organizing QIM’s filings into a structured 13F History and analyzing them via a Portfolio Simulator or similar Backtesting Service can still add value. Patterns in 13F Portfolio Composition—including changes in breadth, sector balance, and ETF usage—combined with a reconstructed long‑only Volatility Profile, Historical Track Record, and implied Sharpe Ratio, help illuminate how the firm’s long‑equity expression has interacted with major market regimes: trend and reversal phases, growth‑versus‑value rotations, and episodes of elevated volatility and correlation. Because Form 13F‑based analysis omits shorts, derivatives, and non‑U.S. exposures that are central to QIM’s actual risk and return, it must be treated strictly as a secondary, partial lens. Integrated with confidential risk reports, factor and attribution analyses, and discussions of model architecture and leverage, these holdings‑based diagnostics can nonetheless help allocators answer a key question: how does the observable long‑equity sleeve of Quantitative Investment Management’s systematic process behave across regimes, and how might that regime sensitivity interact with other managers in a diversified, multi‑strategy portfolio?

At the strategy level, QIM’s risk profile is that of a diversified, multi‑asset systematic platform with substantial gross exposure and carefully controlled net exposures across assets and factors. Risk is budgeted by asset class, region, factor, and strategy sleeve, with portfolio construction targeting specified volatility and drawdown parameters. Futures and options dominate the risk budget, while the 13F‑reportable longs are just one implementation detail. Viewed solely through the 13F lens, the U.S. equity sleeve resembles a highly diversified equity portfolio with the following apparent characteristics: - Market and sector exposure (apparent, but not representative of net risk) – The long book reported in 13F carries significant notional exposure to U.S. equity beta and sector rotations if considered in isolation. In the actual portfolios, however, these exposures are typically offset by short equity positions, index futures, or other hedges, so the net beta and sector risk borne by investors is far lower than the gross long positions would imply. - Factor tilts – Even in a designedly neutral framework, modest residual tilts to style factors such as value, momentum, quality, or low volatility can emerge from QIM’s signals. Over time, these tilts may contribute to deviations in the reconstructed capital path of the 13F longs relative to broad indices. - Idiosyncratic diversification – Because QIM tends to hold large numbers of relatively small positions, idiosyncratic single‑name risk is limited when the 13F book is viewed as a whole; portfolio behavior is driven more by the systematic structure of signals and hedges than by any one stock. If one reconstructs the long equity positions from 13F as if they were an unhedged, long‑only strategy, the resulting Volatility Profile will typically resemble that of a broadly diversified U.S. equity basket—fully exposed to market drawdowns and rallies, with only moderate deviations in sector and factor risk. This is not the realized experience of investors in QIM’s funds, whose net exposure and drawdowns are defined by the interaction of longs, shorts, and derivatives across asset classes. Using QIM’s historical 13F filings, allocators can nonetheless build a holdings‑based proxy by mapping quarter‑end positions to underlying price histories and replaying these portfolios through time in a Portfolio Simulator or Backtesting Service, normalized to a chosen starting notional. This reconstruction yields an indicative Historical Track Record for the 13F‑visible long sleeve and can be analyzed for drawdown depth, participation in recoveries, and behavior during factor rotations and volatility spikes. From that reconstructed path, one can derive summary risk‑adjusted diagnostics, such as an implied Sharpe Ratio, as a rough measure of the efficiency of the long‑signal expression in isolation. These metrics should be interpreted cautiously: they apply only to the gross long U.S. equity subset and ignore short exposure, cross‑asset hedges, and non‑U.S. positions that dominate the true risk profile.