A bootstrap-based comparison of portfolio insurance strategies

This study presents a systematic comparison of portfolio insurance strategies. We implement a bootstrap-based hypothesis test to assess statistical significance of the differences in a variety of downside-oriented risk and performance measures for pairs of portfolio insurance strategies. Our comparison of different strategies considers the following distinguishing characteristics: static versus dynamic protection; initial wealth versus cumulated wealth protection; model-based versus model-free protection; and strong floor compliance versus probabilistic floor compliance. Our results indicate that the classical portfolio insurance strategies synthetic put and constant proportion portfolio insurance (CPPI) provide superior downside protection compared to a simple stop-loss trading rule and also exhibit a higher risk-adjusted performance in many cases (dependent on the applied performance measure). Analyzing recently developed strategies, neither the TIPP strategy (as an ‘improved’ CPPI strategy) nor the dynamic VaR-strategy provides significant improvements over the more traditional portfolio insurance strategies.     

Relative performance of dynamic portfolio insurance strategies: Australian evidence

This paper simulates the performance of synthetic put portfolio insurance and Constant Proportion Portfolio Insurance (CPPI) using Australian data for the period from 1992 to 2000. These strategies are implemented by trading in the index and bills and simulation is conducted across 18 scenarios. We find that while the CPPI dominates in scenarios using daily rebalancing, the synthetic put strategy delivers better outcomes when value based triggers are used. More importantly, although the two per cent market move trigger emerges as the optimal rebalancing choice, overall, neither strategy appears justifiable in terms of achieving downside protection or allowing upside gain.     

Long-Term Synthetic Puts

We present the possibility of replicating the performance of a long-term put, which is not available in the financial markets, by a set of other traded financial assets. First, a benchmark portfolio is formed out of one share of stock and one put on the stock with a certain exercise price and a long time until maturity. The general form of a portfolio, consisting of shares of stock, bonds, and options on the stock, is discussed, which is expected to perform like the benchmark portfolio. Then a class of these synthetic puts is examined to determine which type of synthetic put may dominate the others.     

Portfolio Insurance Strategies when Hedging Affects Share Prices

Option-based portfolio insurance can result in coordinated buying and selling, which destabilizes markets such that hedgers fail to achieve their objective. Gennotte and Leland (1990) show portfolio insurance strategies can have an impact on price movements. Ramanlal and Mann (1996) show how price movements, in turn, can alter hedging strategies. In this paper, we combine these separate effects and develop an equilibrium, executable hedging strategy. This hedging strategy requires less rebalancing than traditional portfolio insurance; more important, it achieves downside protection with a less destabilizing impact on security prices.     

(S,s)-adjustment Strategies and Hedging under Markovian Dynamics

We study the destabilizing effect of hedging strategies under Markovian dynamics with transaction costs. Once transaction costs are taken into account, continuous portfolio rehedging is no longer an optimal strategy. Using a non-optimizing (local in time) strategy for portfolio rebalancing, explicit dynamics for the price of the underlying asset are derived, focusing in particular on excess volatility and feedback effects of these portfolio insurance strategies. Moreover, it is shown how these latter depend on the heterogeneity of the insured payoffs. Finally, conditions are derived under which it may be still reasonable, from a practical viewpoint, to implement Black–Scholes strategies.     

Can Investors Profit from the Prophets? Security Analyst Recommendations and Stock Returns

We document that purchasing (selling short) stocks with the most (least) favorable consensus recommendations, in conjunction with daily portfolio rebalancing and a timely response to recommendation changes, yield annual abnormal gross returns greater than four percent. Less frequent portfolio rebalancing or a delay in reacting to recommendation changes diminishes these returns; however, they remain significant for the least favorably rated stocks. We also show that high trading levels are required to capture the excess returns generated by the strategies analyzed, entailing substantial transactions costs and leading to abnormal net returns for these strategies that are not reliably greater than zero.     

Basis risk in static versus dynamic longevity-risk hedging

This paper provides a tractable, parsimonious model for assessing basis risk in longevity and its effect on the hedging strategies of Pension Funds and annuity providers. Basis risk is captured by a single parameter, that measures the co-movement between the portfolio and the reference population’s longevity. The paper sets out the static, full and customized swap-hedge for an annuity, and compares it with a dynamic, partial, and index-based hedge. We calibrate our model to the UK and Scottish populations. The effectiveness of static versus dynamic strategies depends on the rebalancing frequency of the second, on the relative costs, and on basis risk, which does not affect fully-customized, static hedges. We show that appropriately calibrated dynamic hedging strategies can still be reasonably effective, even at low rebalancing frequencies.     

Who gains and who loses on stock markets? Risk preferences and timing matter

This paper uses an agent-based multi-asset model to examine the effect of risk preferences and optimal rebalancing frequency on performance measures while tracking profit and risk-adjusted return. We focus on the evolution of portfolios managed by heterogeneous mean-variance optimizers with a quadratic utility function under different market conditions. We show that patient and risk-averse agents are able to outperform aggressive risk-takers in the long-run. Our findings also suggest that the trading frequency determined by the optimal tolerance for the deviation from portfolio targets should be derived from a tradeoff between rebalancing benefits and rebalancing costs. In a relatively calm market, the absolute range of 6% to 8% and the complete-way back rebalancing technique outperforms others. During particular turbulent periods, however, none of the existing rebalancing techniques improves tax-adjusted profits and risk-adjusted returns simultaneously.     

Omega performance measure and portfolio insurance

We analyze the performance of the two main portfolio insurance methods, the OBPI and CPPI strategies, using downside risk measures. For this purpose, we introduce Kappa performance measures and especially the Omega measure. These measures take account of the entire return distribution. We show that the CPPI method performs better than the OBPI. As a-by-product, we determine the set of threshold values for these risk/reward performance measures.     

An analysis of risk-based asset allocation and portfolio insurance strategies

This paper compares traditional portfolio insurance strategies with modern risk-based dynamic asset allocation strategies within a currency portfolio context for reserve management. Given the objective of preserving reserve value, the evaluation of the hedging performances of various strategies focuses on four perspectives regarding, in particular, the return distribution of the hedged portfolio. In terms of the Sharpe Ratio, the constant proportional portfolio insurance is the best performer due to having the lowest volatility, while the Value at Risk strategy based upon the normal distribution is the worst due to its having the smallest return. From the perspective that the return distribution of the hedged portfolio is shifted to the right, the synthetic put performs the best, with the expected shortfall strategy the second best. In terms of the cumulative portfolio return across years, the expected shortfall strategy using the historical distribution ranks first, as a result of its participation in upward markets. Furthermore, the expected shortfall-based strategy results in a lower turnover within the investment horizon, thereby saving transaction costs.     

Index composition changes and the cost of incumbency

This paper provides evidence of information effects and portfolio rebalancing effects that occur when stocks are added to or excluded from the S&P 500 index and finds that incumbents in the index realize negative excess returns when S&P revises the composition of the index. We also find that for incumbents that are in the same industry as the added firm, the price-pressure effects are mitigated by positive industry-level information and momentum effects. For index exclusions, the magnitude of the loss sustained by incumbents from the same industry as the excluded firm is larger than that realized by the non-industry incumbents, as the negative information and momentum effects reinforce the price-pressure effects. Our results suggest that changes in the composition of the index are not information-free events; however, the portfolio rebalancing effects dominate the industry information effects.     

Commonalities in investment strategy and the determinants of performance in mutual fund mergers

This paper examines the determinants of cross-sectional variation in post-merger mutual fund performance. Mergers between funds with similar management objectives, as reflected by average portfolio book-to-market ratio, price–earnings ratio, beta and market capitalization values, outperform mergers between funds with dissimilar strategies. This superior performance transcends lower portfolio rebalancing costs which might be realized between merging funds which hold more assets in common. These results suggest that mutual fund mergers create collaborative benefits between funds with similar strategies. We also examine if fund governance structures influence the fund pairing process, testing if stronger fund oversight mitigates pairing mismatches. We find that less independent boards of trustees and boards with higher compensation are related to greater strategic mismatches between funds. These results suggest that more entrenched boards are more tolerant of fund mismatches which benefit the investment company, yet are not in investor’s best interests.     

Portfolio Insurance with Liquidity Risk

This paper studies a portfolio insurance problem with liquidity risk. We consider an investor who wants to maximize the expected growth rate of wealth in a low liquid market. The investor can trade assets only at random times and his wealth must not fall below a predetermined floor. We find the optimal expected growth rate and an optimal strategy. The optimal strategy is closely related with a traditional constant proportion portfolio insurance strategy. Also we show that the same strategy maximizes the growth rate almost surely. Further we study the floor effect on the growth rate.     

Monetary policy and portfolio rebalancing: Evidence from European equity mutual funds

In this study, we provide empirical evidence on the portfolio rebalancing of European equity mutual funds following both conventional (CMP) and unconventional monetary policies (UMP). We use 1772 equity mutual funds’ portfolio holdings over the period 2002Q4–2016Q4. This level of granularity allows us to characterise the funds’ asset allocation in different portfolio dimensions: the size, style, currency, and domicile of the stocks, and managers’ preferred investment strategies. Using a panel fixed effect estimator, our results support the existence of portfolio rebalancing across equity categories following UMP. European equity mutual funds’ assets are, on average, reallocated towards mid-cap, and core stocks and developing economies, and shifted away from small-cap and value stocks and home as well as developed countries. Furthermore, mutual funds seem to concentrate on their preferred and historical investment strategies. These two results suggest that managers are more willing to invest in safer and familiar stocks following UMP announcements thereby decreasing the risk of asymmetry of information. We finally show that the funds size, returns volatility and expense ratio affect the strength of the rebalancing.     

Where is the value added of rebalancing? A systematic comparison of alternative rebalancing strategies

This study compares the performance of different rebalancing strategies under realistic market conditions by reporting statistical significance levels. Our analysis is based on historical data from the United States, the United Kingdom, and Germany and comprises three different classes of rebalancing (periodic, threshold, and range rebalancing). Despite cross-country differences, our history-based simulation results show that all rebalancing strategies outperform a buy-and-hold strategy in terms of Sharpe ratios, Sortino ratios, and Omega measures. The differences in risk-adjusted performance are not only statistically significant, but also economically relevant. However, the choice of a particular rebalancing strategy is of only minor economic importance.     

Behavioral portfolio insurance strategies

Financial Markets and Portfolio Management - Portfolio insurance strategies that ensure a certain minimum portfolio value or floor such as the Constant Proportion Portfolio Insurance (CPPI) and the...     

Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products

Portfolio insurance strategies are used on both the institutional and the retail side of the asset management industry. While standard utility theory struggles to provide an explanation, this study justifies the popularity of portfolio insurance strategies in a behavioral finance context. We run Monte Carlo simulations as well as historical simulations for popular portfolio insurance strategies and benchmark strategies in order to evaluate the outcomes using cumulative prospect theory. Our simulation results indicate that most portfolio insurance strategies are the preferred investment strategy for a prospect theory investor. Moreover, the analysis provides insights into how portfolio insurance products should be designed and structured to meet the preferences of prospect theory investors as accurately as possible.     

New Evidence on Optimal Asset Allocation

Brocato and Steed (1998) showed that portfolio rebalancing based on NBER business cycle turning points substantially improves in‐sample Markowitz efficiency. In a similar vein, we investigate potential improvements from rebalancing based on turning points in the monetary cycle. We find that the monetary cycle has greater influence than the business cycle on the variance/covariance structure of multiple asset classes. Furthermore, we find substantial improvements in in‐sample efficiency beyond a buy‐and‐hold strategy and the business‐cycle approach. Importantly, our indicator of monetary cycle turning points has a practical advantage over NBER business cycle turning points, in that it relies only on ex ante information. In out‐of‐sample tests, we continue to find superior portfolio performance after transactions costs using the monetary cycle to time portfolio rebalancing.     

Long-term optimal portfolios with floor

Long-term risk-sensitive portfolio optimization is studied with floor constraint. A simple rule to characterize its solution is mentioned under a general setting. Following this rule, optimal portfolios are constructed in several ways, using the optimal portfolio without floor constraint, combined with ideas of dynamic portfolio insurance, such as CPPI (constant proportion portfolio insurance), OBPI (option-based portfolio insurance), and DFP (dynamic fund protection). In addition, examples are presented with explicit computations of solutions.     

Computing optimal rebalance frequency for log-optimal portfolios

Log-optimal investment portfolio is deemed to be impractical and cost-prohibitive due to inherent need for continuous rebalancing and significant overhead of trading cost. We study the question of how often a log-optimal portfolio should be rebalanced for any given finite investment horizon. We develop an analytical framework to compute the expected log of portfolio growth when a given discrete-time periodic rebalance frequency is used. For a certain class of portfolio assets, we compute the optimal rebalance frequency. We show that it is possible to improve investor log utility using this quasi-passive or hybrid rebalancing strategy. Simulation studies show that an investor shall gain significantly by rebalancing periodically in discrete time, overcoming the limitations of continuous rebalancing.