Optimal rebalance rules for the constant proportion portfolio insurance strategy – Evidence from China

The constant proportion portfolio insurance (CPPI) strategy is one of the most popular asset allocation strategies employed by guaranteed-return financial products investors. Rebalance disciplines play an important role in determining the CPPI performance in practice. This paper examines whether the selection of rebalance rules affects CPPI strategy performance in the context of Chinese equity markets and, if so, in what pattern, and whether an optimal parameter of rebalance exists. We find that, (1) the three alternative rebalance disciplines – time discipline, market move discipline and lag discipline – are indifferent in affecting the performance of CPPI strategy; (2) in terms of optimal parameters of each rebalance rule, the optimal rebalancing period for the time discipline is 3 trading days, the optimal trading threshold of the market move discipline 4%, and the optimal lag factor of the lag discipline 6%. These optimal parameters are not influenced by the length of investment.     

CONSTANT PROPORTION PORTFOLIO INSURANCE IN THE PRESENCE OF JUMPS IN ASSET PRICES

Constant proportion portfolio insurance (CPPI) allows an investor to limit downside risk while retaining some upside potential by maintaining an exposure to risky assets equal to a constant multiple of the cushion , the difference between the current portfolio value and the guaranteed amount. Whereas in diffusion models with continuous trading, this strategy has no downside risk, in real markets this risk is nonnegligible and grows with the multiplier value. We study the behavior of CPPI strategies in models where the price of the underlying portfolio may experience downward jumps. Our framework leads to analytically tractable expressions for the probability of hitting the floor, the expected loss, and the distribution of losses. This allows to measure the gap risk but also leads to a criterion for adjusting the multiplier based on the investor's risk aversion. Finally, we study the problem of hedging the downside risk of a CPPI strategy using options. The results are applied to a jump-diffusion model with parameters estimated from returns series of various assets and indices.     

CPPI投资组合保险策略的实证分析

本文首先简要介绍了CPPI投资组合保险策略,通过采用上证综合指数,对多头、空头和震荡三个时期,以及不同的最低保险额和乘数,对CPPI策略进行历史数据实证模拟,并与B&H策略做比较,发现CPPI策略在我国证券市场是能够起到有效保险作用的。     

Estimating portfolio risk for tail risk protection strategies

We forecast portfolio risk for managing dynamic tail risk protection strategies, based on extreme value theory, expectile regression, copula‐GARCH and dynamic generalized autoregressive score models. Utilizing a loss function that overcomes the lack of elicitability for expected shortfall, we propose a novel expected shortfall (and value‐at‐risk) forecast combination approach, which dominates simple and sophisticated standalone models as well as a simple average combination approach in modeling the tail of the portfolio return distribution. While the associated dynamic risk targeting or portfolio insurance strategies provide effective downside protection, the latter strategies suffer less from inferior risk forecasts, given the defensive portfolio insurance mechanics.     

我国保本基金保值效果的比较研究

本文简要介绍了保本基金的三种投资策略,并在此基础上对我国目前发行的五只保本基金的投资策略及资产配置原则进行了描述并作出评价.本文从理论上对各基金投资策略的有效性进行论证后,又通过数据对其保本效果进行了检验.利用图形与数据,比较了其价值增长线的有效性,基金净值变化的波动性,股票仓位变动的合理性,并通过各项指标,借助主成分分析法,对各基金在一定风险下的收益进行了比较.     

The effectiveness of the VaR-based portfolio insurance strategy: An empirical analysis

This paper proposes an approach to constructing the insured portfolios under the VaR-based portfolio insurance strategy (VBPI) and provides a comprehensive analysis of its hedging effectiveness in comparison with the buy-and-hold (B&H) as well as the constant proportion portfolio insurance (CPPI) strategies in the context of the Chinese market. The results show that both of the insurance strategies are able to limit the downward returns while retaining certain upside returns, and their capabilities of reshaping the return distributions increase as the guarantee or the confidence level rises. In general, the VBPI strategy tends to outperform the CPPI strategy in terms of both the degree of downside protection and the return performance.     

基于沪深300股指期货的动态套期保值实证研究

文章运用沪深300股指期货对CPPI投资组合中的风险资产部分进行套期保值,利用ECM-GARCH模型估计最优风险套期保值比率,按照最优套期保值比例对CPPI投资组合中的风险资产部分进行套期保值。通过实证研究,运用沪深300股指期货套期保值能够在保证收益的条件下有效降低投资组合的风险。     

A dynamic autoregressive expectile for time-invariant portfolio protection strategies

“Constant proportion portfolio insurance” is a popular technique among portfolio insurance strategies: the risky part of a portfolio is reallocated with respect to market conditions, via a fixed parameter (the multiple), guaranteeing a predetermined floor. We propose here to use a conditional time-varying multiple as an alternative. We provide the main properties of the conditional multiples for some mainstream cases, including discrete-time rebalancing and an underlying risk asset driven by the Lévy process, while evaluating conditional and unconditional gap risks. Finally, we evaluate the use of a dynamic autoregressive expectile model for estimating the conditional multiple in such a context.     

我国的保本基金保本策略创新研究

保本基金作为一种低风险的理财工具,起点比较低,非常适合大众投资者和具有保本倾向的机构资金,但目前我国保本基金发展遭遇瓶颈,我们认为除了市场因素之外,保本基金保本策略方面创新不足导致收益率不高是主要原因,文章从我国实际出发,提出利用权证和即将推出的股指期货构建保本组合将会提高保本基金的保本能力。     

Model-free CPPI

We consider Constant Proportion Portfolio Insurance (CPPI) and its dynamic extension, which may be called Dynamic Proportion Portfolio Insurance (DPPI). It is shown that these investment strategies work within the setting of Föllmer's pathwise Itô calculus, which makes no probabilistic assumptions whatsoever. This shows, on one hand, that CPPI and DPPI are completely independent of any choice of a particular model for the dynamics of asset prices. They even make sense beyond the class of semimartingale sample paths and can be successfully defined for models admitting arbitrage, including some models based on fractional Brownian motion. On the other hand, the result can be seen as a case study for the general issue of robustness in the face of model uncertainty in finance.