Investment fund selection techniques from the perspective of Brazilian pension funds

ABSTRACT The aim of this article was to evaluate the effectiveness of investment fund selection techniques from the perspective of Brazilian pension funds. Asset liability management (ALM) and liability driven investment (LDI) strategies are usually adopted to guide pension fund managers in relation to strategic allocation in asset classes that should compose their investment portfolios and to the liquidity needed in each period, but not specifying in which assets to allocate resources from among the infinity of assets available in the financial market. This article contributes to tactical management in the fixed income and stock segments outsourced via funds and demonstrates that adopting simple indicators can increase investment performance. The article broadens the knowledge on pension fund investment decisions and creates confidence in the adoption of the Sharpe ratio as a technique for choosing investment funds. We analyzed the returns obtained by hypothetical portfolios built using the following techniques: (i) the Sharpe ratio; (ii) the alpha of a multifactor model; (iii) data envelopment analysis (DEA) efficiency; and (iv) the different combinations of these techniques. We considered information on 369 funds from 2013 to 2018, adopting 12 temporal windows for choosing and re-evaluating the portfolios. The returns obtained were compared with the mean actuarial goal of the benefits plans administered by the pension funds, by means of the unplanned divergence (UD). When outsourcing pension fund investments in fixed income and stock investment funds it was verified that the Sharpe ratio contributes significantly to pension fund performance, compared with other indicators and techniques or a combination of them.摘要 本研究旨在从巴西养老基金的视角，评估投资基金甄选技术的有效性。资产负债管理（Asset Liability Management, ALM）与负债驱动投资（Liability Driven Investment, LDI）策略通常用于指导养老基金经理进行投资组合构成资产类别的战略配置，以及各周期所需的流动性管理，但并未明确在金融市场海量可投资资产中，具体应将资金配置于哪些资产。本研究有助于通过基金外包的固定收益与股票板块的战术管理，并证实采用简易指标可提升投资业绩。本研究拓展了养老基金投资决策相关的认知，并为采用夏普比率（Sharpe Ratio）作为投资基金甄选技术提供了信心支撑。我们对采用以下方法构建的假想投资组合的收益进行了分析：(i) 夏普比率；(ii) 多因子模型阿尔法；(iii) 数据包络分析（Data Envelopment Analysis, DEA）效率；(iv) 上述方法的不同组合形式。本研究纳入了2013年至2018年间共369只基金的相关信息，并采用12个时间窗口对投资组合进行甄选与重评估。本研究通过非预期偏差（Unplanned Divergence, UD）指标，将所获收益与养老基金管理的福利计划的精算平均目标进行了对比。当养老基金将固定收益与股票类投资通过基金外包时，相较于其他指标、方法或其组合，夏普比率可显著提升养老基金的投资业绩，这一点已得到验证。