The performance of cash protection strategies implemented in the South African market are investigated in order to establish if investors are able to add value through the use of dynamic portfolio insurance methods. The analysis is performed, using monthly data, from January 1961 to August 2014 using six alternative methodologies including both a Fixed Rate and Rolling Average Stop-Loss approach, a Lock-In approach, a Constant Mix strategy, a Constant Proportion Portfolio Insurance ("CPPI") approach and an alternative CPPI approach using a Ratchet mechanism. The results indicate that the use of such cash protection strategies can markedly improve portfolio performance from a risk return perspective compared to a pure diversified investment strategy. Notably, the use of older, simpler trading strategies such as the Stop-Loss and Lock-In approaches at optimum threshold levels can still offer investors higher risk to reward benefits with less commitment required. These strategies, though, lack the flexibility observed with the more recently developed dynamic trading strategies in terms of providing for varying risk appetites.

Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2018-11-09T18:21:24Z No. of bitstreams: 1 JoseHenriquedeOliveiraVarandaDissertacao2018.pdf: 3107527 bytes, checksum: ea06abcabf1c014758cc880bcf0b0726 (MD5) / Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2018-11-13T16:00:57Z (GMT) No. of bitstreams: 1 JoseHenriquedeOliveiraVarandaDissertacao2018.pdf: 3107527 bytes, checksum: ea06abcabf1c014758cc880bcf0b0726 (MD5) / Made available in DSpace on 2018-11-13T16:00:57Z (GMT). No. of bitstreams: 1 JoseHenriquedeOliveiraVarandaDissertacao2018.pdf: 3107527 bytes, checksum: ea06abcabf1c014758cc880bcf0b0726 (MD5) Previous issue date: 2018-07-02 / This study evaluates which modifications can restore the theoretical performance of dynamic asset allocation strategies that uses insurance and leverage, specifically those known as Constant Proportion Portfolio Insurance (CPPI), when confronted with realistic premises and scenarios. Simulations using GARCH models are applied to assess the effects of path dependency and volatility on those strategies and to evaluate how selected modifications mitigates those effects. These modifications are tested using the Farinelli- Tibilleti ratio and derivations, like de Upside Potential Ratio. As main finding, the modifications that mitigates path dependency can restore the theoretical performance of portfolio insurance with high significance, making those preferred strategies in relation to Buy-and-Hold (BH) or Constant-Mix (CM) for most investors in several scenarios. This work also presents a novel modification, adapted for the risk-free market in Brazil, that resulted in the best performing portfolio insurance strategy with great significance. / Este trabalho avalia quais modificações reestabelecem o desempenho teórico das estratégias dinâmicas de alocação de ativos com seguro e alavancagem, denominadas Constant Proportion Portfolio Insurance (CPPI), quando confrontadas com premissas e cenários realistas. São realizadas simulações de modelos da família GARCH, com parâmetros estimados do mercado, para exercitar os efeitos da dependência do caminho e da volatilidade nestas estratégias e avaliar como as modificações selecionadas ajudam a combate-los. A significância das modificações é testada pela medida Farinelli-Tibiletti, sobre tudo a combinação que resulta na razão Upside Potential, onde conclui-se que existem modificações significantes que são capazes de resgatar o desempenho teórico da estratégia CPPI, inclusive tornando-a preferível às estratégias clássicas Buy-and-Hold (BH) e Constant-Mix (CM) em certos cenários. Por fim, o trabalho apresenta uma modificação inovadora, derivada do ajuste à realidade do mercado brasileiro, que acabou por apresentar o maior nível de desempenho relativo do método CPPI, com elevada significância.

A robust computational framework is presented for the risk-neutral valuation of capital guarantees written on discretely-reallocated portfolios following the Constant Proportion Portfolio Insurance (CPPI) strategy. Aiming to address the (arguably more realistic) cases where analytical results are unavailable, this framework accommodates risky-asset jumps, volatility surfaces, borrowing restrictions, nonuniform reallocation schedules and autonomous CPPI floor trajectories. The two-asset state space representation developed herein facilitates visualising the CPPI strategy, which in turn provides insight into grid design and interpolation. It is demonstrated that given a deterministic process for the risk-free rate, the pricing problem can be cast as solving cascading systems of 1D partial integro-differential equations (PIDEs). This formulation’s stability and monotonicity are studied. In addition to making more sense financially, the limited borrowing variant of the CPPI strategy is found to be better suited than the classical (unlimited borrowing) counterpart for bounded-domain calculations. Consequently, it is demonstrated how the unlimited borrowing problem can be approximated by imposing an artificial borrowing limit. For implementation validation, analytical solutions to special cases are derived. Numerical tests are presented to demonstrate the versatility of this framework.

A robust computational framework is presented for the risk-neutral valuation of capital guarantees written on discretely-reallocated portfolios following the Constant Proportion Portfolio Insurance (CPPI) strategy. Aiming to address the (arguably more realistic) cases where analytical results are unavailable, this framework accommodates risky-asset jumps, volatility surfaces, borrowing restrictions, nonuniform reallocation schedules and autonomous CPPI floor trajectories. The two-asset state space representation developed herein facilitates visualising the CPPI strategy, which in turn provides insight into grid design and interpolation. It is demonstrated that given a deterministic process for the risk-free rate, the pricing problem can be cast as solving cascading systems of 1D partial integro-differential equations (PIDEs). This formulation’s stability and monotonicity are studied. In addition to making more sense financially, the limited borrowing variant of the CPPI strategy is found to be better suited than the classical (unlimited borrowing) counterpart for bounded-domain calculations. Consequently, it is demonstrated how the unlimited borrowing problem can be approximated by imposing an artificial borrowing limit. For implementation validation, analytical solutions to special cases are derived. Numerical tests are presented to demonstrate the versatility of this framework.