Including commodity futures in asset allocation in China

In this paper, we investigate the role of eight commodity futures in asset allocation in China during the period January 2004–December 2015. The Chinese commodities and stocks are moderately correlated. We use quantile regressions based on a value-at-risk model to examine the relation between these two markets. We find no risk spillovers between the markets, suggesting that stocks and commodities in China are exposed to different risks. Using different asset allocation strategies, we show that including soymeal and soybeans in the Chinese stock index can offer some diversification gains. However, other Chinese commodities may not be useful for portfolio diversification.     

Optimal consumption and asset allocation with unknown income growth

Recent empirical evidence supports the view that the income process has an individual-specific growth rate component [Baker, M., 1997. Growth-rate heterogeneity and the covariance structure of life-cycle earnings. Journal of Labor Economics 15, 338-375; Guvenen, F., 2007b. Learning your earning: Are labor income shocks really very persistent? American Economic Review 97, 687-712; Huggett, M., Ventura, G., Yaron, A., 2007. Sources of life-cycle inequality. Working paper, University of Pennsylvania]. Moreover, the individual-specific growth component may be stochastic. Motivated by these empirical observations, I study an individual's optimal consumption-saving and portfolio choice problem when he does not observe his income growth. As in standard income fluctuation problems, the individual cannot fully insure himself against income shocks. In addition to the standard income-risk-induced precautionary saving demand, the individual also has learning-induced precautionary saving demand, which is greater when belief is more uncertain. With constant unobserved income growth, changes in belief are not predictable. However, with stationary stochastic income growth, belief is no longer a martingale. Mean reversion of belief reduces hedging demand on average and in turn mitigates the impact of estimation risk on consumption-saving and portfolio decisions.     

Optimal asset allocation under linear loss aversion

We study the asset allocation of a linear loss-averse (LA) investor and compare it to the more traditional mean-variance (MV) and conditional value-at-risk (CVaR) investors. First we derive conditions under which the LA problem is equivalent to the MV and CVaR problems and solve analytically the two-asset problem of the LA investor for a risk-free and a risky asset. Then we run simulation experiments to study properties of the optimal LA and MV portfolios under more realistic assumptions. We find that under asymmetric dependence LA portfolios outperform MV portfolios, provided investors are sufficiently loss-averse and dependence is large. Finally, using 13 EU and US assets, we implement the trading strategy of a linear LA investor who reallocates his/her portfolio on a monthly basis. We find that LA portfolios clearly outperform MV and CVaR portfolios and that incorporating a dynamic update of the LA parameters significantly improves the performance of LA portfolios.     

Optimal asset allocation for a large number of investment opportunities

This paper introduces a stock‐picking algorithm that can be used to perform an optimal asset allocation for a large number of investment opportunities. The allocation scheme is based upon the idea of causal risk. Instead of referring to the volatility of the assets time series, the stock‐picking algorithm determines the risk exposure of the portfolio by concerning the non‐forecastability of the assets. The underlying expected return forecasts are based on time‐delay recurrent error correction neural networks, which utilize the last model error as an auxiliary input to evaluate their own misspecification. We demonstrate the profitability of our stock‐picking approach by constructing portfolios from 68 different assets of the German stock market. It turns out that our approach is superior to a preset benchmark portfolio. Copyright © 2005 John Wiley & Sons, Ltd.     

Optimal asset allocation using a combination of implied and historical information

This paper investigates the contribution of option-implied information for strategic asset allocation for individuals with minimum-variance preferences and portfolios with a variety of assets. We propose a covariance matrix that exploits a mixture of historical and option-implied information. Implied variance measures are proposed for those assets for which option-implied information is available. Historical variance and correlation measures are applied to the remaining assets. The performance of this novel approach for constructing optimal investment portfolios is assessed out-of-sample using statistical and economic measures. An empirical application to a sophisticated portfolio comprised by a combination of equities, fixed income, alternative securities and cash deposits shows that implied variance measures with risk premium correction outperform variance measures constructed from historical data and implied variance without correction. This result is robust across investment portfolios, volatility and portfolio performance metrics, and rebalancing schemes.     

Optimal tracking for asset allocation with fixed and proportional transaction costs

This paper studies the asset allocation problem of optimally tracking a target mix of asset categories when there are transaction costs. We consider the trading strategy for an investor who is trying to minimize both fixed and proportional transaction costs while simultaneously minimizing the tracking error with respect to a specified, target asset mix. We use imupulse control theory in a continuous-time, dynamic setting to deal with this problem in a general and analytical way, showing that the optimal trading strategy can be characterized in terms of a quasi-variational inequality. We derive an explicit solution for the two-asset case, and we use this to provide a sensitivity analysis, showing how the optimal strategy depends upon individual input parameters. We also use some theory for one-dimensional diffusion processes to derive analytical expressions for various measures of performance such as the average time between transactions.     

International asset allocation using the market implied cost of capital

The Black and Litterman (Financ Anal J 48(5):28–43, 1992) (BL) approach to portfolio optimization requires investor views on expected asset returns as an input. I demonstrate that the market implied cost of capital (ICC) is ideal for quantifying those views on a country level. I benchmark this approach against a BL optimization using time-series models as investor views, the equally weighted portfolio, and allocation methods based on stock market capitalization and GDP. I find that the ICC portfolio offers an increase in average return of 2.1 percentage points (yearly) as compared to the value-weighted portfolio, while having a similar standard deviation. The resulting difference in Sharpe ratios is statistically significant and robust to the inclusion of transaction costs, varying BL parameters, and a less strictly defined investment universe.     

Calibrating a market model with stochastic volatility to commodity and interest rate risk

Based on the multi-currency LIBOR Market Model, this paper constructs a hybrid commodity interest rate market model with a stochastic local volatility function allowing the model to simultaneously fit the implied volatility surfaces of commodity and interest rate options. Since liquid market prices are only available for options on commodity futures, rather than forwards, a convexity correction formula for the model is derived to account for the difference between forward and futures prices. A procedure for efficiently calibrating the model to interest rate and commodity volatility smiles is constructed. Finally, the model is fitted to an exogenously given correlation structure between forward interest rates and commodity prices (cross-correlation). When calibrating to options on forwards (rather than futures), the fitting of cross-correlation preserves the (separate) calibration in the two markets (interest rate and commodity options), while in the case of futures a (rapidly converging) iterative fitting procedure is presented. The fitting of cross-correlation is reduced to finding an optimal rotation of volatility vectors, which is shown to be an appropriately modified version of the ‘orthonormal Procrustes’ problem in linear algebra. The calibration approach is demonstrated in an application to market data for oil futures.     

A note on asset management and market risk

The textbook view on risk in asset management companies is summarized by Hull (Risk Management and Financial Institutions, p. 372, 2007): “For an asset manager the greatest risk is operational risk.” Using evidence from various panel regression models, we show that asset management revenues carry substantial market risks, a finding that challenges not only academic risk management literature on the predominance of operative risks, but also the current industry practice of not hedging market risks that are systematically built into the revenue-generation process. For asset management companies to return to an annuity model, these risks need to be managed more actively. Shareholders do not want to be exposed to market beta by investing in asset management companies; they want to participate in these companies’ alpha generation and take advantage of their fund-gathering expertise as financial intermediaries.     

Beyond Sharpe ratio: Optimal asset allocation using different performance ratios

As the assumption of normality in return distributions is relaxed, classic Sharpe ratio and its descendants become questionable tools for constructing optimal portfolios. In order to overcome the problem, asymmetrical parameter-dependent performance ratios have been recently proposed in the literature. The aim of this note is to develop an integrated decision aid system for asset allocation based on a toolkit of eleven performance ratios. A multi-period portfolio optimization up covering a fixed horizon is set up: at first, bootstrapping of asset return distributions is assessed to recover all ratios calculations; at second, optimal rebalanced-weights are achieved; at third, optimal final wealth is simulated for each ratios. Eventually, we make a robustness test on the best performance ratios. Empirical simulations confirm the weakness in forecasting of Sharpe ratio, whereas asymmetrical parameter-dependent ratios, such as the Generalized Rachev, Sortino–Satchell and Farinelli–Tibiletti ratios show satisfactorily robustness.     

Explain systemic risk of commodity futures market by dynamic network

Since inflation of commodities is becoming more and more severe recently caused by many macro events, such as COVID-19 and Russian-Ukrainian conflict, systemic risk of commodity futures market is getting more attention from academic and industrial areas. Instead of using external factors to explain this risk as previous researches, we explain it by internal topology and structures of commodity futures market. This method helps us understand its key driving factors and their different impact to Chinese and international commodity futures markets.     

Optimal asset allocation for participating contracts under the VaR and PI constraint

ABSTRACT

Participating contracts provide a maturity guarantee for the policyholder. However, the terminal payoff to the policyholder should be related to financial risks of participating insurance contracts. We investigate an optimal investment problem under a joint value-at-risk and portfolio insurance constraint faced by the insurer who offers participating contracts. The insurer aims to maximize the expected utility of the terminal payoff to the insurer. We adopt a concavification technique and a Lagrange dual method to solve the problem and derive the representations of the optimal wealth process and trading strategies. We also carry out some numerical analysis to show how the joint value-at-risk and the portfolio insurance constraint impacts the optimal terminal wealth.     

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.     

Optimal commodity taxation with duty-free shopping

International travellers are frequently offered the opportunity to purchase a certain quantity of goods duty-free. Individuals differ in their opportunities to benefit from duty-free shopping, and we focus on the implications of these differences for optimal commodity taxation within a version of the optimal tax model of Mirrlees (Review of Economic Studies, 38, 175–208, 1971). We show how duty-free alters the constraints on the use of commodity taxes to reduce the distortionary costs of income taxation or to reflect externalities. Beyond characterising optimal taxes in the duty-free regime, we discuss conditions under which allowing duty-free would increase or reduce social welfare.      

Optimal tax-timing and asset allocation when tax rebates on capital losses are limited

This article studies the portfolio problem with realization-based capital gain taxation when limited amounts of losses qualify for tax rebate payments, as is the case under current US tax law. When the tax rate applicable to realized losses exceeds that on realized capital gains, it can be optimal to realize capital gains immediately and pay capital gain taxes to regain the option to use potential future losses against a higher tax rate. This incentive adds an entirely new and as yet unstudied dimension to the portfolio problem. It causes risk averse investors to hold more equity and attain higher welfare levels than is the case when trading under a tax system that seeks to collect the same amount of taxes, but does not allow for tax rebate payments. This is because the benefit to these investors from having their losses subsidized is greater than the suffering from having profits taxed at a higher rate.     

Beyond risk-based portfolios: balancing performance and risk contributions in asset allocation

Asset allocation using a new Performance/Risk Contribution measure improves the performance of risk-based portfolios     

Computing the market price of volatility risk in the energy commodity markets

In this paper, we demonstrate the need for a negative market price of volatility risk to recover the difference between Black–Scholes [Black, F., Scholes, M., 1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637–654]/Black [Black, F., 1976. Studies of stock price volatility changes. In: Proceedings of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, pp. 177–181] implied volatility and realized-term volatility. Initially, using quasi-Monte Carlo simulation, we demonstrate numerically that a negative market price of volatility risk is the key risk premium in explaining the disparity between risk-neutral and statistical volatility in both equity and commodity-energy markets. This is robust to multiple specifications that also incorporate jumps. Next, using futures and options data from natural gas, heating oil and crude oil contracts over a 10 year period, we estimate the volatility risk premium and demonstrate that the premium is negative and significant for all three commodities. Additionally, there appear distinct seasonality patterns for natural gas and heating oil, where winter/withdrawal months have higher volatility risk premiums. Computing such a negative market price of volatility risk highlights the importance of volatility risk in understanding priced volatility in these financial markets.     

Dynamic asset allocation with stochastic income and interest rates

We solve for optimal portfolios when interest rates and labor income are stochastic with the expected income growth being affine in the short-term interest rate in order to encompass business cycle variations in wages. Our calibration based on the Panel Study of Income Dynamics (PSID) data supports this relation with substantial variation across individuals in the slope of this affine function. The slope is crucial for the valuation and riskiness of human capital and for the optimal stock/bond/cash allocation both in an unconstrained complete market and in an incomplete market with liquidity and short-sales constraints.     

Lifetime asset allocation with idiosyncratic and systematic mortality risks

This paper considers a lifetime asset allocation problem with both idiosyncratic and systematic mortality risks. The novelty of the paper is to integrate stochastic mortality, stochastic interest rate and stochastic income into a unified framework. An investor, who is a wage earner receiving a stochastic income, can invest in a financial market, consume part of his wealth and purchase life insurance or annuity so as to maximize the expected utility from consumption, terminal wealth and bequest. The problem is solved via the dynamic programming principle and the Hamilton–Jacobi–Bellman equation. Analytical solutions to the problem are derived, and numerical examples are provided to illustrate our results. It is shown that idiosyncratic mortality risk has significant impacts on the investor’s investment, consumption, life insurance/annuity purchase and bequest decisions regardless of the length of the decision-making horizon. The systematic mortality risk is largely alleviated by trading the longevity bond. However, its impacts on consumption, purchase of life insurance/annuity and bequest as well as the value function are still pronounced, when the decision-making horizon is sufficiently long.