Constant proportion portfolio insurance strategies in contagious markets

Constant Proportion Portfolio Insurance (CPPI) strategies are popular as they allow to gear up the upside potential of a stock index while limiting its downside risk. From the issuer’s perspective it is important to adequately assess the risks associated with the CPPI, both for correct ‘gap’ fee charging and for risk management. The literature on CPPI modelling typically assumes diffusive or Lévy-driven dynamics for the risky asset underlying the strategy. In either case the self-contagious nature of asset prices is not taken into account. In order to account for contagion while preserving analytical tractability, we introduce self-exciting jumps in the underlying dynamics via Hawkes processes. Within this framework we derive the loss probability when trading is performed continuously. Moreover, we estimate measures of the risk involved in the practical implementation of discrete-time rebalancing rules governing the CPPI product. When rebalancing is performed on a frequency less than weekly, failing to take contagion into account will significantly underestimate the risks of the CPPI. Finally, in order to mimic a situation with low liquidity, we impose a daily trading cap on the risky asset and find that the Hawkes process driven models give rise to the highest risk measures even under daily 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.     

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.     

Performance evaluation of portfolio insurance strategies using stochastic dominance criteria

This paper evaluates the performance of the stop-loss, synthetic put and constant proportion portfolio insurance techniques based on a block-bootstrap simulation. We consider not only traditional performance measures, but also some recently developed measures that capture the non-normality of the return distribution (value-at-risk, expected shortfall, and the Omega measure). We compare them to the more comprehensive stochastic dominance criteria. The impact of changing the rebalancing frequency and level of capital protection is examined. We find that, even though a buy-and-hold strategy generates higher average excess returns, it does not stochastically dominate the portfolio insurance strategies, nor vice versa. Our results indicate that a 100% floor value should be preferred to lower floor values and that daily-rebalanced synthetic put and CPPI strategies dominate their counterparts with less frequent rebalancing.     

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.     

Dynamic preferences for popular investment strategies in pension funds

In this paper, we characterize dynamic investment strategies that are consistent with the expected utility setting and more generally with the forward utility setting. Two popular dynamic strategies in the pension funds industry are used to illustrate our results: a constant proportion portfolio insurance (CPPI) strategy and a life-cycle strategy. For the CPPI strategy, we are able to infer preferences of the pension fund’s manager from her investment strategy, and to exhibit the specific expected utility maximization that makes this strategy optimal at any given time horizon. In the Black–Scholes market with deterministic parameters, we are able to show that traditional life-cycle funds are not optimal to any expected utility maximizers. We also prove that a CPPI strategy is optimal for a fund manager with HARA utility function, while an investor with a SAHARA utility function will choose a time-decreasing allocation to risky assets in the same spirit as the life-cycle funds strategy. Finally, we suggest how to modify these strategies if the financial market follows a more general diffusion process than in the Black–Scholes market.     

Estimating Transaction-Based Price Indices of Local Commercial Real Estate Markets Using Public Assessment Data

This study examines the feasibility of constructing reliable commercial property price indices using property tax records. We employ the Clapp and Giacotto (Journal of American Statistical Association, 87(418), 300–306, 1992) assessed-value method to estimate price indices for commercial properties in Florida. The estimated Florida commercial property price index is compared to the Moody’s/REAL Commercial Property Price Index (CPPI) and to the transaction-based index (TBI) produced at MIT. Our results are promising, suggesting that this widely-available data source can be used to produce commercial property price indices for a variety of precise market locations and specific investor segments. A secondary but interesting objective of this paper is to use our rich and comprehensive database to examine the price performance of two specific subsets of properties in more detail. First, we narrow our range to focus on just the office sector for Florida. We compare price movements for the Florida office sector with the comparable CPPI. Estimates produce very similar price movements providing support to both methods. Second, we contrast the price performance of higher- and lower-valued properties and reject the hypothesis that their periodic price index levels are equal. The mean price changes of Florida commercial properties assessed at $2.5 million and above are observed to be slightly higher than for properties assessed below $2.5 million, although not statistically different. In particular, higher-valued properties had higher mean price changes relative to lower-valued properties during periods of economic expansion. This economic difference represents an important contribution toward beginning to understand the relative performance of smaller and investment-grade commercial properties.     

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.     

Performance ratio-based coherent risk measure and its application

Utilizing a specific acceptance set, we propose in this paper a general method to construct coherent risk measures called the generalized shortfall risk measure. Besides some existing coherent risk measures, several new types of coherent risk measures can be generated. We investigate the generalized shortfall risk measure’s desirable properties such as consistency with second-order stochastic dominance. By combining the performance evaluation with the risk control, we study in particular the performance ratio-based coherent risk (PRCR) measures, which is a sub-class of generalized shortfall risk measures. The PRCR measures are tractable and have a suitable financial interpretation. Based on the PRCR measure, we establish a portfolio selection model with transaction costs. Empirical results show that the optimal portfolio obtained under the PRCR measure performs much better than the corresponding optimal portfolio obtained under the higher moment coherent risk measure.     

Unveiling the embedded coherence in divergent performance rankings

This paper focuses on analyzing functional relationships among performance measures, centered on the adjusted differential risk premium between the asset and the benchmark and on Sharpe-1994 ratio. First, we develop a risk normalization procedure for variance and Aumann–Serrano riskiness which turns contradictory rankings into coherent ones, and combines the effects of correlation and outliers into the analysis. On this basis, we deduce functional connections among performance measures, arriving at a new indicator which expresses performance as the addition of three effects due to Sharpe ratio, correlation and outliers. We show it is a strictly increasing function of Homm–Pigorsch ratio.     

Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes

This paper contributes to the literature on the impact of the Shari’ah filtering criteria on the risk of Dow Jones Islamic indexes relative to their conventional counterparts. We show that Islamic and conventional indexes are affected by the same extreme events which can bias the estimation of the risk, especially the period of the Global Financial Crisis of 2007–2008 and its aftermath which is characterized by a very high level of volatility. Then, we examine whether the Islamic indexes are more risky than the conventional indexes using different risk measures. We also analyze the performance of both indexes from various risk-adjusted performance measures. Overall, the Islamic indexes seem to be more risky than their conventional counterparts as well as exhibit a higher performance on the full period (1996–2013). The sample period is further divided into low volatility period and high volatility period based on the detection of structural breaks in the volatility. The results also show that both indexes have been affected by variance changes. We show that most of the Islamic indexes have higher level of risk than the conventional indexes, whatever the sub-periods. Consequently, this finding means that the Islamic indexes are riskier than the non-Islamic indexes. We also find that in most cases the Islamic indexes either outperform the non-Islamic indexes or there is no significant difference in performance between both indexes. These findings can be explained as a consequence of less diversification in Islamic indexes, leading to higher concentration risk in some sectors, such as basic material, industrial and technology firms. Further, we find some differences of risk and performance between the jurisdictions.     

Can investors benefit from the performance of alternative UCITS funds?

We study the performance persistence of alternative UCITS funds, which are a hybrid between mutual funds and hedge funds. Persistence is gauged by alternative measures of performance and risk. Based on contingency tables, we find that performance persists for up to 2 years following ranking. However, persistence is stronger in the short run, and ranked portfolio tests indicate that investors can benefit from persistence for only up to 1 year. The evidence for persistence in risk is ambiguous. We link fund characteristics to performance persistence and find that offshore hedge fund experience enhances persistence. Our results are robust against survivorship bias and other potential database biases.     

High-temperature exposure risk,corporate performance and pricing efficiency of the stock market

Using the daily temperature data of the national meteorological stations, we measure the high-temperature exposure risk of Chinese A-share listed enterprises, investigate the impact of high-temperature exposure risk on corporate prime operating revenue and performance, and further discuss securities analysts' forecasts for this risk. We find that increased exposure to high temperature reduces corporate prime operating revenue, and the response of enterprises to high-temperature risk will lead to a rise in management expenses and the deterioration of business performance. Further evidence suggests that securities analysts generally underestimate or ignore the impact of high-temperature exposure risk, and our results are robust to different measures and samples.     

The effect of benchmarked performance measures and strategic analysis on auditors’ risk assessments and mental models

As the audit environment becomes more demanding and complex, so does the set of analytical tools available to an auditor. The purpose of this paper is to examine the effect of two complex audit technologies commonly used by auditors, benchmarking of performance measures and strategic analysis, on the risk judgments of auditors carrying out the initial planning of an audit. We conduct an experiment that utilizes a Balanced Scorecard for organizing and evaluating analytical evidence about the performance of business units within a large client. Our first principal finding is that external benchmarking can cause an auditor to focus on performance measures that are unique to a business unit and disregard performance measures that are common to multiple business units but not benchmarked. However, our second finding is that an in-depth strategic analysis completed prior to assessing a client’s business risk or risk of material misstatement allows an auditor to incorporate more information from performance measures in risk assessments regardless of whether the performance measures are benchmarked. Strategic analysis facilitates a more balanced and accurate assessment of the risks across the business units being evaluated. We also provide evidence that the latter result occurs because in-depth strategic analysis allows auditors to develop a more complete mental model of a client, which has been a long time belief of advocates of business risk audit methodologies and consistent with current and emerging auditing standards on risk assessment.     

Tail dependence and indicators of systemic risk for large US depositories

In this study, we investigate the extreme loss tail dependence between stock returns of large US depository institutions. We find that stock returns exhibit strong loss dependence even in their limiting joint extremes. Motivated by this result, we derive extremal dependence-based systemic risk indicators. The proposed systemic risk indicators reflect downturns in the US financial industry very well. We also develop a set of firm-level average extremal dependence measures. We show that these firm-level measures could have been used to identify the firms that were more vulnerable to the 2007–2008 financial crisis. Additionally, we explore the performance of selected systemic risk indicators in predicting the crisis performance of large US depository institutions and find that the average stock return correlations are also good predictors of crisis period returns. Finally, we identify factors predictive of extremal dependence for the US depository institutions in a panel regression setting. Strength of extremal dependence increases with asset size and similarity of financial fundamentals. On the other hand, strength of extremal dependence decreases with capitalization, liquidity, funding stability and asset quality. We believe the proposed indicators have the potential to inform the prudential supervision of systemic risk.     

A Model Forecasting Risk for Emerging Market Currencies

In this paper, we propose a risk forecasting model for emerging market currencies. Our model is based on the Markov regime switch which is constructed by exploiting daily equity market information, and we show that our model outperforms the existing model using macroeconomic information. We evaluate it by the performance measures, the goodness-of-fit and the Wilcoxon rank-sum test.     

Does the stock market value bank diversification?

This paper investigates whether or not functionally diversified banks have a comparative advantage in terms of long-term performance/risk profile compared to their specialized competitors. To that end, this study uses market-based measures of return potential and bank risk. We calculate the franchise value over time of European banks as a measure of their long-run performance potential. In addition, we measure risk as both the systematic and the idiosyncratic risk components derived from a bank stock return model. Finally, we analyze the return/risk trade-off implied in different functional diversification strategies using a panel data analysis over the period 1989–2004. A higher share of non-interest income in total income affects banks’ franchise values positively. Diversification of revenue streams from distinct financial activities increases the systematic risk of banks while the effect on the idiosyncratic risk component is non-linear and predominantly downward-sloping. These findings have conflicting implications for different stakeholders, such as investors, bank shareholders, bank managers and bank supervisors.     

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...     

Effects of Corporate Diversification: Evidence From the Property–Liability Insurance Industry

Using a sample of property–liability insurers over the period 1995–2004, we develop and test a model that explains performance as a function of line‐of‐business diversification and other correlates. Our results indicate that undiversified insurers consistently outperform diversified insurers. In terms of accounting performance, we find a diversification penalty of at least 1 percent of return on assets or 2 percent of return on equity. These findings are robust to corrections for potential endogeneity bias, alternative risk measures, alternative diversification measures, and an alternative estimation technique. Using a market‐based performance measure (Tobin's Q) we find that the market applies a significant discount to diversified insurers. The existence of a diversification penalty (and diversification discount) provides strong support for the strategic focus hypothesis. We also find that insurance groups underperform unaffiliated insurers and that stock insurers outperform mutuals.     

Measuring executive personality using machine-learning algorithms: A new approach and audit fee-based validation tests

We present a novel approach for measuring executive personality traits. Relying on recent developments in machine learning and artificial intelligence, we utilize the IBM Watson Personality Insights service to measure executive personalities based on CEOs’ and CFOs’ responses to questions raised by analysts during conference calls. We obtain the Big Five personality traits – openness, conscientiousness, extraversion, agreeableness and neuroticism – based on which we estimate risk tolerance. To validate these traits, we first demonstrate that our risk-tolerance measure varies with existing inherent and behavioural-based measures (gender, age, sensitivity of executive compensation to stock return volatility, and executive unexercised-vested options) in predictable ways. Second, we show that variation in firm-year level personality trait measures, including risk tolerance, is largely explained by manager characteristics, as opposed to firm characteristics and firm performance. Finally, we find that executive inherent risk tolerance helps explain the positive relationship between client risk and audit fees documented in the prior literature. Specifically, the effect of CEO risk-tolerance – as an innate personality trait – on audit fees is incremental to the effect of increased risk appetite from equity risk-taking incentives (Vega). Measuring executive personality using machine-learning algorithms will thus allow researchers to pursue studies that were previously difficult to conduct.