如何飞到安全的地方而不多付机票钱

IF 1.2 Q3 ECONOMICS Economics and Business Review Pub Date : 2023-04-01 DOI:10.18559/ebr.2023.2.738
Tomasz Kaczmarek, Przemysław Grobelny
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引用次数: 0

摘要

对于大多数积极的投资者来说,国库券提供了分散投资,从而降低了投资组合的风险。在风险升高的时候,政府的这些特征变得特别可取,这种风险以“逃向安全”(FTS)现象的形式出现。为政府提供的FTS在市场动荡期间提供了一个避难所,对减少投资组合的风险特别有益。然而,如果美国国债的预期回报不令人满意,导致投资者不愿增持债券,那该怎么办?本文提出了一种深度目标波动率股票-债券配置(Deep Target Volatility equity - bond Allocation, DTVEBA)方法来解决这一问题。该策略由最先进的循环神经网络(RNN)驱动,该网络可以预测第二天的市场波动。一项为期12年的样本外分析发现,使用DTVEBA,投资者可能会将国债配置减少两(三)倍,以获得相同的夏普(卡尔马)比率,并比标准普尔500指数高出43%(115%)。
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How to fly to safety without overpaying for the ticket
Abstract For most active investors treasury bonds (govs) provide diversification and thus reduce the risk of a portfolio. These features of govs become particularly desirable in times of elevated risk which materialize in the form of the flight-to-safety (FTS) phenomenon. The FTS for govs provides a shelter during market turbulence and is exceptionally beneficial for portfolio drawdown risk reduction. However, what if the unsatisfactory expected return from treasuries discourages higher bonds allocations? This research proposes a solution to this problem with Deep Target Volatility Equity-Bond Allocation (DTVEBA) that dynamically allocate portfolios between equity and treasuries. The strategy is driven by a state-of-the-art recurrent neural network (RNN) that predicts next-day market volatility. An analysis conducted over a twelve year out-of-sample period found that with DTVEBA an investor may reduce treasury allocation by two (three) times to get the same Sharpe (Calmar) ratio and overper-forms the S&P500 index by 43% (115%).
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CiteScore
1.40
自引率
28.60%
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