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Risk parity, also known as equal risk contribution, has recently gained increasing attention as a portfolio allocation method. However, solving portfolio weights must resort to numerical methods as the analytic solution is not available. This study improves two existing iterative methods: the cyclical coordinate descent (CCD) and Newton methods. The authors enhance the CCD method by simplifying the formulation using a correlation matrix and imposing an additional rescaling step. The authors also suggest an improved initial guess inspired by the CCD method for the Newton method. Numerical experiments show that the improved CCD method performs the best and is approximately three times faster than the original CCD method, saving more than 40% of the iterations.

The recent development of the European debt sovereign crisis showed that sovereign debt is not “risk free.” The traditional index bond management used during the last two decades such as the market-capitalization weighting scheme has been severely called into question. In order to overcome these drawbacks, alternative weighting schemes have recently prompted attention, both from academic researchers and from market practitioners. One of the key developments was the introduction of passive funds using economic fundamental indicators.

In this chapter, the authors introduced models with economic drivers with an aim of investigating whether the fundamental approaches outperformed the other models on risk-adjusted returns and on other terms.

The authors did this by constructing five portfolios composed of the Eurozone sovereigns bonds. The models are the Market-Capitalization RP, GDP model RP, Ratings RP model, Fundamental-Ranking RP, and Fundamental-Weighted RP models. These models were created exclusively for this chapter. Both Fundamental models are using a range of 10 country fundamentals. A variation from other studies is that this dissertation applied the risk parity concept which is an allocation technique that aims to equalize risk across different assets. This concept has been applied by assuming the credit default swap as proxy for sovereign credit risk. The models were run using the Generalized Reduced Gradient (GRG) method as the optimization model, together with the Lagrange Multipliers as techniques and the Karush–Kuhn–Tucker conditions. This led to the comparison of all the models mentioned above in terms of performance, risk-adjusted returns, concentration, and weighted average ratings.

By analyzing the whole period between 2006 and 2014, it was found that both the fundamental models gave very appealing results in terms of risk-adjusted returns. The best results were returned by the Fundamental-Ranking RP model followed by the Fundamental-Weighting RP model. However, better results for the mixed performance and risk-adjusted returns were achieved on a yearly basis and when sub-dividing the whole period in three equal periods. Moreover, the authors concluded that over the long term, the fundamental bond indexing triumphed over the other approaches by offering superior return and risk characteristics. Thus, one can use the fundamental indexation as an alternative to other traditional models.

The purpose of this paper is to develop a dynamic, stochastic, mechanistic simulation model of a dairy business to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting framework. A primary objective was to establish a flexible, user‐friendly, farm‐specific, decision‐making tool for dairy producers or their advisers and technology manufacturers.

The basic deterministic model was created in Microsoft Excel (Microsoft, Seattle, Washington). The @Risk add‐in (Palisade Corporation, Ithaca, New York) for Excel was employed to account for the stochastic nature of key variables within a Monte Carlo simulation. Net present value was the primary metric used to assess the economic profitability of investments. The model was composed of a series of modules, which synergistically provide the necessary inputs for profitability analysis. Estimates of biological relationships within the model were obtained from the literature in an attempt to represent an average or typical US dairy. Technology benefits were appraised from the resulting impact on disease incidence, disease impact, and reproductive performance. In this paper, the model structure and methodology were described in detail.

Examples of the utility of examining the influence of stochastic input and output prices on the costs of culling, days open, and disease were examined. Each of these parameters was highly sensitive to stochastic prices and deterministic inputs.

Decision support tools, such as this one, that are designed to investigate dairy business decisions may benefit dairy producers.

In asset management, what if clients want to purchase protection from risk factors, under the form of variance risk premia. This paper aims to address this topic by developing a portfolio optimization framework based on the criterion of the minimum variance risk premium (VRP) for any investor selecting stocks with an expected target return while minimizing the risk aversion associated to the portfolio according to “good” and “bad” times.

To accomplish this portfolio selection problem, the authors compute variance risk-premium as the difference from high-frequencies' realized volatility and options' implied volatility stemming from 19 stock markets, estimate a 2-state Markov-switching model on the variance risk-premia and optimize variance risk-premia portfolios across non-overlapping regions. The period goes from March 16, 2011, to March 28, 2018.

The authors find that optimized portfolios based on variance-covariance matrices stemming from VRP do not consistently outperform the benchmark based on daily returns. Several robustness checks are investigated by minimizing historical, realized or implicit variances, with/without regime switching. In a boundary case, accounting for the realized variance risk factor in portfolio decisions can be seen as a promising alternative from a portfolio performance perspective.

As a new management “style”, the realized volatility approach can, therefore, bring incremental value to construct the conditional covariance matrix estimates.

The authors assess the portfolio performance determined by the variance-covariance matrices that are derived by four models: “naive” (Markowitz returns benchmark), non-switching VRP, maximum likelihood regime-switching VRP and Bayesian regime switching VRP. The authors examine the best return-risk combination through the calculation of the Sharpe ratio. They also assess another different portfolio strategy: the risk parity approach.

Using data spanning 145 years for Sweden, the authors investigate the benefits of holding multi-family properties for investors who aim to hedge wage growth.

The authors assess the risk-adjusted excess return that results from adding multi-family properties to a mixed-asset portfolio that aims to track wage growth. The authors also analyse the macroeconomic determinants of asset returns. Finally, the authors test whether a causal relationship exists between the growth rate of real wages and that of real net operating income.

The benefits from holding multi-family properties are the greatest for low-risk allocation approaches. For more risky strategies, the role of real estate is more muted, and it varies greatly over time. Holding real estate was most beneficial during the first two decades of the 21st century. Multi-family properties are found to be the only asset class to be positively related to wage growth. The authors show that the net operating income acts as the transmission channel between wages and property returns.

The paper assesses whether the growing interest of pension funds for multi-family properties is warranted in the context of a portfolio that aims to track wage growth.

Using long term data makes it possible to use a rolling windows approach and hence to consider multiple outcomes for an allocation strategy over a typical investment horizon. This permits to assess the dispersion of performance across several periods rather than just one as is commonly done in the literature. The results show that the conclusions that would be drawn from looking at the past two or three decades of data differ substantially from those for earlier time periods.

The aim of the study was to analyze the performance of Black-Litterman (BL) portfolios using a views estimation procedure that simulates investor forecasts based on technical analysis.

Ibovespa, S&P500, Bitcoin and interbank deposit rate (IDR) indexes were respectively considered proxies for the national, international, cryptocurrency and fixed income stock markets. Forecasts were made out of the sample aiming at incorporating them in the BL model, using several portfolio weighting methods from June 13, 2013 to August 30, 2022.

The Sharpe, Treynor and Omega ratios point out that the proposed model, considering only variable return assets, generates portfolios with performances superior to their traditionally calculated counterparts, with emphasis on the risk parity portfolio. Nonetheless, the inclusion of the IDR leads to performance losses, especially in scenarios with lower risk tolerance. And finally, given the impact of turnover, the naive portfolio was also detected as a viable alternative.

The results obtained can contribute to improve investors practices, specifically by validating both the performance improvement – when including foreign assets and cryptocurrencies –, and the application of the BL model for asset pricing.

The main contributions of the study are: performance analysis incorporating cryptocurrencies and international assets in an uncertain recent period; the use of a methodology to compute the views simulating the behavior of managers using technical analysis; and comparing the performance of portfolio management strategies based on the BL model, taking into account different levels of risk and uncertainty.

The purpose of this paper is to address a research gap by providing a comprehensive survey of sovereign wealth funds (SWFs) as international institutional investors and clarifying the definition of SWFs. By doing so, this paper aims to provide a balanced set of policy prescriptions towards SWFs.

This paper conducted a comprehensive survey of world major 24 SWFs with assets under management of 500 million USD between 2008 and 2012. Key dimensions include objectives, funding and governance, asset allocation and investment activities.

SWFs are planning institutions with management direction. They present great variety in terms of funding mechanism, governance, asset allocation and investment strategies, but they in essence pursue financial returns. It is not evident that SWFs are primarily motivated by political objectives and distinctively different from other international institutional investors. Difficulty in interpreting SWFs should not lead to the imposition of constraints on SWFs.

More in-depth and dynamic analysis of SWFs requires better data access. For such a purpose, case studies and longitudinal studies should be adopted, with particular emphasis on comparing SWFs with different types of financial institutional investors as well as typical state-owned enterprises (SOEs) and multinational enterprises.

This study is trying to demystify SWFs based on a comprehensive survey. As a result, this paper may assist investors, policy-makers and regulators to gain a better understanding of SWFs, their investment behaviours and rationales behind.

SWFs like other long-term capital is important for economic and job growth. To attract long-term investments, creating an open, unbiased and welcoming investment environment is the key.

The contribution of this paper is that we provide a deeper understanding of the strategy and empirics of SWF operations. First, after a clearer definition of the phenomenon of SWFs, we can explain their investment strategies and behaviour as firms. Second, we can derive rational policy prescriptions, and third, we can propose a research agenda that will further deepen our understanding of SWFs and the appropriate policy prescriptions.

The purpose of this article is to help investors build less-concentrated portfolios as well as to construct optimal return-concentration portfolios.

An alternative portfolio objective is proposed where investors care about the level of concentration of their portfolio weights. Minimizing the concentration of portfolio weights leads to the well-known equal-weight portfolio as the optimal choice. Maximizing the trade-off between the portfolio's expected return and the weight concentration produces a novel portfolio with weights proportional to the expected return of each security.

An empirical application with 30 industry portfolios and 1,000 individual stocks finds that both proposed strategies perform well out-of-sample both in terms of the proposed concentration measure but also in terms of more traditional risk-based measures like Sharpe ratios, abnormal returns and market betas.

The optimal risk-concentration portfolio proposed in this paper is a novel result. The portfolio generalizes prior practitioner intuition on focusing on securities with the highest expected returns and the concept of diversification.

The economic phenomenon of “globalization” has broadly affected the health care industry and the medical profession in the late 20th century. Governmental and private sector managed care reach is expanding globally, as patients are “ecuritized” and traded as covered lives. Arbitrage of health care goods and services is creating commoditization effects, including trans‐border parallel markets (i.e. black markets). Consumers and governments are becoming concerned about privacy issues and product standardization, while Third World challenges remain in the public health realm (i.e., infectious pandemics, sanitation, nutrition and overpopulation).

The purpose of this paper is to look at how the faculty at West Point uses a student-managed investment fund (SMIF) to contribute to the development of Army officers.

The United States Military Academy at West Point started a student-managed investment fund in 1983. The Economics program, which has four finance classes within its curriculum, hosts the student-run SMIF. The students (cadets) in charge of the SMIF have recently started pursuing a risk parity strategy. This paper discusses the challenges that arise from taking on this strategy.

It argues that investment management, especially with a risk-aware strategy, helps the cadets learn to manage the risk/reward tradeoff as well as help them work on leadership skills, both of which will help them as future Army officers.

The authors suggest that the recent student-initiated changes to the SMIF at West Point highlight some of the leadership opportunities inherent to approaching a SMIF from a risk-aware, portfolio-based perspective. This can teach students important experiential lessons about how to manage prudent risk both in finance and as a leader.