Alpha^{2}  Enhanced Hedge Fund Index Solution
Alpha Generation via Tactical Hedge Fund Index Allocation
GOAL
 To maximize the riskadjusted total return of a diversified portfolio of hedge fund subindices by actively overweighting and underweighting the components of the strategic portfolio
KEY PRODUCT DIFFERENTIATING FACTORS
 Innovative Solution: Alpha to be generated over and above Credit Suisse/Tremont investable hedgefund index based on statistical evidence of the predictability in hedge fund subindex returns
 Transparent Quantitative Process: A disciplined approach based on robust quantitative processes from initial longterm derivation of longterm optimal weights to the derivation of tactical alpha tilts
 Optimal Portfolio Construction: Equilibrium portfolio weights to be devised so as to meet investor’s objectives i.e. low correlation to traditional asset classes, maximum expected information ratio, low drawdown risks, or a combination of nonmutually exclusive objectives and constraints.
 Market and economic intuition: Signals driving alpha tilts to be based on systematic risk factors, consistent with market and economic intuition
THREE STEPS CONSTRUCTION PROCESS
1. Strategic Allocation: A disciplined and robust portfolio construction framework based on stateoftheart risk quantification and management techniques
 Application of correction techniques to overcome biases associated with hedge fund subindices
 Nonlinear dependence techniques to be applied to generate optimal equilibrium hedge fund basket weights (Rank Correlations, Copulas)
 Equilibrium portfolio allocations to be derived incorporating several predefined risk criteria and to be assessed with multiple methodologies (Reverse MeanVariance optimization, Value at Risk (VaR) and modified VaR, Copula/Extreme Value Theory optimizations)
 Optimal allocation to include all predefined investor specifications and risk preferences
2. Tactical views and alpha generation: An innovative and transparent approach to focus on higher riskadjusted opportunities
 Consistent incorporation of multiple dimensions of information including significant exogenous indicators and systematic risk factors
 Parsimonious number of signals are applied to all relevant sub hedgefund indices
 Signals’ sensitivities to be dynamically adjusted according to their explanatory power
 Direction and confidence of resulting tactical views expressed in expected mean and standard error
3. Disciplined and robust portfolio construction framework
 Tactical views to be integrated at the final portfolio optimization step, where strategic and tactical views are to be apportioned according to model derived associated confidence levels
 Final optimization: To include all investor preferences (orthogonality to traditional asset classes, longonly and no leverage restrictions).
 Flexible control of position turnover via a transaction penalty parameter
 Risks associated with final solution to be consistent with following predefined bounds: maximum acceptable loss assessed via stresstests, VaR, mVaR, and EVT parameters
OVERVIEW
 Initial objectives and constraints
 The objective is to consistently outperform the benchmark portfolio while staying within the prescribed risk limits
 No short selling or leverage is permitted in the overall portfolio
 Coverage includes CS/Tremont’s 10 main hedge fund indices:
 Convertible Arbitrage Index
 Dedicated Short Bias Index
 Emerging Market Index
 Equity Market Neutral Index
 Event Driven Index
 Fixed Income Arbitrage Index
 Global Macro Index
 Long/Short Equity Index
 Managed Futures Index
 MultiStrategy Index
 The Alpha^{2} model selects from 95 exogenous signals:
 Approach based on statistically sounds methodologies
 Exogenous signals and systematic risk factors are consistent with market and economic intuition
 Capability to expand the approach to additional hedge fund subsector indices
 The Alpha^{2} model offers an innovative and transparent approach to focus on profitable relative trades, allowing consistent incorporation of multiple dimensions of information advantage into the portfolio
 At the individual hedge fund subsector strategy level:
 A parsimonious number of signals are chosen
 Weights of signals are dynamically adjusted
 Direction and confidence of profitable investment views are derived
 Across hedge fund subsector strategies:
 Strategic equilibrium weights and tactical investment views are blended through a Bayesian framework based on their relative information advantage
 Expected returns for all hedge fund subsectors are derived alongside their associated confidence levels
 Portfolio construction:
 Tactical over/underweights are determined based on return and risk tradeoff, given the benchmark, constraints, turnover and transaction costs considerations

