Portfolio allocation and the investment horizon: a multiscaling approach

A new approach is proposed for analysing portfolio allocation over various time scales. This new approach is based on wavelet analysis, which decomposes a given time series on a scale-by-scale basis. Empirical results indicate that, as the investment horizon lengthens, a greater weighting should be allocated to stocks. An explanation for this result is that the mean-reverting property of stock returns causes investors to perceive that stocks are less risky than bonds and T-bills at longer time scales compared with shorter time scales. When we include the effect of risk aversion, it is found that the higher the risk aversion, the less the Sharpe ratio, indicating that a more conservative investor prefers a smoother consumption stream.     

Multi-scale variation,path risk and long-term portfolio management

Mean–variance analysis is constrained to weight the frequency bands in a return time series equally. A more flexible approach allows the user to assign preference weightings to short or longer run frequencies. Wavelet analysis provides further flexibility, removing the need to assume asset returns are stationary and encompassing alternative return concepts. The resulting portfolio choice methodology establishes a reward–energy efficient frontier that allows the user to trade off expected reward against path risk, reflecting preferences as between long or short run variation. The approach leads to dynamic analogues of mean–variance such as band pass portfolios that are more sensitive to variability at designated scales.     

An economic evaluation of stock–bond return comovements with copula-based GARCH models

Owing to their importance in asset allocation strategies, the comovements between the stock and bond markets have become an increasingly popular issue in financial economics. Moreover, the copula theory can be utilized to construct a flexible joint distribution that allows for skewness in the distribution of asset returns as well as asymmetry in the dependence structure between asset returns. Therefore, this paper proposes three classes of copula-based GARCH models to describe the time-varying dependence structure of stock–bond returns, and then examines the economic value of copula-based GARCH models in the asset allocation strategy. We compare their out-of-sample performance with other models, including the passive, the constant conditional correlation (CCC) GARCH and the dynamic conditional correlation (DCC) GARCH models. From the empirical results, we find that a dynamic strategy based on the GJR-GARCH model with Student-t copula yields larger economic gains than passive and other dynamic strategies. Moreover, a less risk-averse investor will pay higher performance fees to switch from a passive strategy to a dynamic strategy based on copula-based GARCH models.     

Equity risk versus retirement adequacy: asset allocation solutions for KiwiSaver

New Zealand's KiwiSaver superannuation system operates with a conservatively low asset allocation towards equity investments. Evidence suggests ‘conservative’ portfolios are riskier than portfolios holding more growth assets when considering shortfall risk. This study employs stochastic simulation to determine the optimal asset allocation to improve the balance of probabilities for retirement adequacy. The findings show that KiwiSaver default funds are excessively conservative, preventing investors from reaching their retirement goals. Increasing the asset allocation to equities across the range of available KiwiSaver funds is the only solution to significantly improve retirement adequacy in New Zealand given the low contribution rates observed.     

Historical simulation approach to the estimation of stochastic discount factor models

We propose an approach to the estimation of the parameters of stochastic discount factor (SDF) models which is based on the idea that the next period joint distribution of the variables in a SDF and asset returns can be well approximated by their joint historical distribution. The estimates of the SDF parameters may therefore be found as the values of the parameters at which the mean of the historical distribution of the product of the SDF with an asset return equals one. Each time period, the estimates are updated using the most recent periods of data and hence can change over time. This method can be viewed as an alternative to the approaches that specify a particular functional form relating the SDF parameters to proxies for the state of the world.     

Least-squares approach to risk parity in portfolio selection

The risk parity portfolio selection problem aims to find such portfolios for which the contributions of risk from all assets are equally weighted. Portfolios constructed using the risk parity approach are a compromise between two well-known diversification techniques: minimum variance optimization and the equal weighting approach. In this paper, we discuss the problem of finding portfolios that satisfy risk parity over either individual assets or groups of assets. We describe the set of all risk parity solutions by using convex optimization techniques over orthants and we show that this set may contain an exponential number of solutions. We then propose an alternative non-convex least-squares model whose set of optimal solutions includes all risk parity solutions, and propose a modified formulation which aims at selecting the most desirable risk parity solution according to a given criterion. When general bounds are considered, a risk parity solution may not exist. In this case, the non-convex least-squares model seeks a feasible portfolio which is as close to risk parity as possible. Furthermore, we propose an alternating linearization framework to solve this non-convex model. Numerical experiments indicate the effectiveness of our technique in terms of both speed and accuracy.     

On the equivalence of the static and dynamic asset allocation problems

A classic dynamic asset allocation problem optimizes the expected final-time utility of wealth, for an individual who can invest in a risky stock and a risk-free bond, trading continuously in time. Recently, several authors considered the corresponding static asset allocation problem in which the individual cannot trade but can invest in options as well as the underlying. The optimal static strategy can never do better than the optimal dynamic one. Surprisingly, however, for some market models the two approaches are equivalent. When this happens the static strategy is clearly preferable, since it avoids any impact of market frictions. This paper examines the question: when, exactly, are the static and dynamic approaches equivalent? We give an easily tested necessary and sufficient condition, and many non-trivial examples. Our analysis assumes that the stock follows a scalar diffusion process, and uses the completeness of the resulting market model. A simple special case is when the drift and volatility depend only on time; then the two approaches are equivalent precisely if (μ (t)? r)/σ²(t) is constant. This is not the Sharpe ratio or the market price of risk, but rather a nondimensional ratio of excess return to squared volatility that arises naturally in portfolio optimization problems.     

Market risks in asset management companies

This paper shows that revenues from a sample of publicly traded US asset management companies carry substantial market risks. Not only does this challenge the academic risk management literature about the predominance of operative risks in asset management, it is also at odds with current practice in asset management firms. Asset managers do not hedge market risks even though these risks are systematically built into the revenue generation process. This is surprising as shareholders would not optimally choose asset management companies as their source of market beta. They rather prefer to participate in alpha generation and fund gathering expertise of investment managers as financial intermediaries. At the very minimum, asset managers need to monitor their ‘fees at risk’ to understand what impact product design, benchmark choice and fee contract design have on revenue volatility. This calls for a much wider interpretation of the risk management function that too narrowly focuses on client risks.     

Mortality regimes and longevity risk in a life annuity portfolio

This paper explores the presence of changes of trends or jumps in French mortality from 1947 to 2007, and assesses their implications on the longevity risk management of a life annuity portfolio. We accomplish this by extending the Poisson log-bilinear regression developed by Brouhns et al. (2002) with a regime-switching model. Estimation results show that French mortality is characterized by two distinct regimes. One refers to a strong uncertainty state, which corresponds to the longevity conditions observed during the decade following World War II. The second regime is related to the low volatility of longevity improvements observed during the last 30 years. We use these results to analyze the impact of mortality regimes on the longevity risk management of a life annuity portfolio. Simulation results suggest that the changes of trends in the mortality process have some implications for longevity risk management.     

Optimal portfolio allocation with higher moments

We model the risky asset as driven by a pure jump process, with non-trivial and tractable higher moments. We compute the optimal portfolio strategy of an investor with CRRA utility and study the sensitivity of the investment in the risky asset to the higher moments, as well as the resulting wealth loss from ignoring higher moments. We find that ignoring higher moments can lead to significant overinvestment in risky securities, especially when volatility is high.      

Momentum investing and the asset allocation decision

This study examines the active asset allocation decisions of Australian multisector fund managers to determine whether active fund managers engage in momentum strategies. We find evidence supporting the existence of momentum investing in active asset allocation strategies. This evidence exists in the Australian Equities, Australian Fixed Interest and Listed Property asset classes. Interestingly, balanced funds adopt contrarian strategies in the International Equities asset class. We also examine whether there is any association between a fund's market timing skill and the execution of momentum strategies. Our results show that fund managers with no market timing skill are momentum investors.     

Macroeconomic influences on optimal asset allocation

We develop a tactical asset allocation strategy that incorporates the effects of macroeconomic variables. The joint distribution of financial asset returns and the macroeconomic variables is modelled using a VAR with a multivariate GARCH (M-GARCH) error structure. As a result, the portfolio frontier is time varying and subject to contagion from the macroeconomic variable. Optimal asset allocation requires that this be taken into account. We illustrate how to do this using three risky UK assets and inflation as a macroeconomic factor. Taking account of inflation generates portfolio frontiers that lie closer to the origin and offers investors superior risk-return combinations.     

Asset allocation in markets with contagion: The interplay between volatilities,jump intensities,and correlations

We study the impact of financial contagion on the dynamic asset allocation problem of a CRRA investor facing an incomplete market with two risky assets. We apply a Markov chain regime-switching framework with state-dependent jump intensities, diffusion volatilities and diffusion correlations. The key model feature that a switch to the bad contagion regime is triggered by a loss in one of the risky assets allows for the implementation of a hedging demand against contagion risk. Moreover, a state-dependent diffusion correlation combined with heterogeneity in jump intensities and volatilities can, e.g., generate a flight to quality effect upon a systemic jump.     

A novel equity valuation and capital allocation model for use by long-term value-investors

We present a novel asset pricing model that captures the investment wisdom and stock-selection approach of the long-term value-investors Benjamin Graham and Warren Buffett. Taking a longer term view of business prospects and business risks, we explicitly consider the time period in which a business enjoys a competitive advantage over its peers as the central tenet of our model and capture the eventual demise of this competitive advantage in a probabilistic manner. Assuming that our investor has log utility, our model answers the question of capital allocation in a two-asset scenario. The model does not enforce the Efficient Market Hypothesis and is shown to explain some well-known empirical studies on stock returns.     

Earning the right premium on the right factor in portfolio planning

The optimal portfolio as well as the utility from trading stocks and derivatives depends on the risk factors and on their market prices of risk. We analyze this dependence for a CRRA investor in models with stochastic volatility, jumps in the stock price, and jumps in volatility. We find that the compartment of the total variance into diffusion risk and jump risk has a small impact on the utility in an incomplete market only. In contrast, the decomposition of the equity risk premium into a diffusion component and a jump risk component and the compartment of the latter into its various elements has a huge impact on the utility in a complete market. The more extreme the market prices of risk, i.e. the more they deviate from their equilibrium values, the larger the utility of the investor. Additionally, we show that the structure of the optimal exposures to jump risk crucially depends on which elements of jump risk are priced.     

Greenness index: IPO performance and portfolio allocation

This study examines how the greenness of the firm affects the short- and long-term performance of IPOs. To measure the greenness of the firm, we develop the Greenness Index based on the emissions produced. We find that the greenness of the firms operating in services and financial sectors is higher than in other sectors. To examine the short- and long-run performance of IPOs, we classify our sample into high and low green firms. In the short-run, high green firms obtain a lower return than low green firms. However, high green firms perform better than low green firms in the long-run. This study also determines the factors that cause short- and long-run performance, and the results suggest that the firm’s greenness negatively influences initial returns and underperformance of IPOs. Finally, we develop a theoretical model in terms of the portfolio's allocation and assert that investors participate in high-green firms to optimize their portfolio.     

我国微观主体资产选择行为对货币需求结构的影响

我国经济开放程度日益增加,经济转型程度逐步加深,处于经济转型期的居民、企业、金融机构等微观主体的资产选择行为发生了重要变化。文章对我国经济主体的资产选择行为对货币需求影响的作用机理进行深入的研究。通过不同样本区间的比较,分析宏观大环境发生变化的条件下,我国微观主体的资产选择行为对我国货币需求的影响路径,并根据实证结果提出保持较高利率水平下合理的利率市场化形成机制的政策建议。     

Monotonicity in asset returns: New tests with applications to the term structure,the CAPM,and portfolio sorts

Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model (CAPM) implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.     

Political uncertainty and cross-border equity portfolio allocation decisions: International evidence

Political risk models highlight that political uncertainty matters for corporate investment decisions. However, how political uncertainty matters for investment allocation decisions is relatively under-explored. In this study, we examine the impact of political uncertainty associated with national elections on foreign equity portfolio in 48 countries. Our results indicate that political uncertainty reduces international equity allocations to the host country and such reduction appears more pronounced in the election year. Further analysis shows that the interaction between political uncertainty and institutional quality has a positive and significant effect on international equity portfolio flow, suggesting that the value of institutional quality outweighs the negative effects of political uncertainty. Lastly, we find equity home bias to be negative and significant; however, the interaction between political uncertainty and equity home bias appears insignificant.     

Correlation risk,cross-market derivative products and portfolio performance*

We consider portfolios whose returns depend on at least three variables and show the effect of the correlation structure on the probabilities of the extreme outcomes of the portfolio return, using a multivariate binomial approximation. the portfolio risk is then managed by using derivatives. We illustrate this risk management both with simple options, whose payoff depends upon only one of the underlying variables, and with more complex instruments, whose payoffs (and values) depend upon the correlation structure The question of benchmarking portfolio performance is complicated by the use of derivatives, especially complex derivatives, since these instruments fundamentally alter the distribution of returns. We use the multivariate binomial model to set performance benchmarks for multicurrency, international portfolios. Our model is illustrated using a simple example where a German institution invests a proportion of its funds in Germany equities and the remainder in UK equities. Portfolio performance is measured in Deutsche Marks and depends upon (1) the DAX index, (2) the FTSE index and (3) the Deutsche Mark-Sterling exchange rate. The output of the model is a simulation of possible outcomes from the portfolio hedging strategy. the difference in our methodology is that we are able to retain the simplicity of the binomial distribution, used extensively in the analysis of options, in a multivariate context. This is achieved by building three (or more) binomial trees for the individual variables and capturing the correlation structure with the use of varying conditional probabilities.