The price of shelter - Downside risk reduction with precious metals

Investor aversion to extreme losses may motivate them to seek out investments perceived to function as a safe haven during times of crisis. In this study, we consider the potential for precious metals to mitigate downside risk when combined with equities, and evaluate the impact on portfolio risk-adjusted returns. Each of gold, silver and platinum are found to contribute to downside risk reduction at short horizons, but diversification into silver and platinum may result in increased long horizon portfolio risk. The price of sheltering an equity portfolio from downside risk is a relative reduction in portfolio risk-adjusted returns. Variance and kurtosis properties of precious metals are identified as marginal contributors to downside risk reduction. Futures markets on precious metals are also shown to present an interesting and viable diversification alternative to physical metals.     

The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach

In this study, we examine the role of global economic conditions in the predictability of gold market volatility using alternative measures. Based on the available data frequency for the relevant series, we adopt the GARCH-MIDAS approach which allows for mixed-data frequencies. We find that global economic conditions contribute significantly to gold market volatility, albeit with mixed outcomes. While the results also lend support to the safe-haven properties of the gold market, the outcome can be influenced by the choice of measure for global economic conditions. For completeness, we extend the analyses to other precious metals (palladium, platinum, rhodium and silver) and find that the global economic conditions forecast the return volatility of the gold market better than these other precious metals. Our results are robust to multiple forecast horizons and offer useful insights on the plausible investment choices in the precious metals market.     

Modeling Time-Varying Correlations in Volatility Between BRICS and Commodity Markets

This article investigates the asymmetric and long memory volatility properties and dynamic conditional correlations (DCCs) between Brazilian, Russian, Indian, Chinese, and South African (BRICS) stock markets and commodity (gold and oil) futures markets, using the trivariate DCC-fractionally integrated asymmetric power autoregressive conditional heteroskedasticity (FIAPARCH) model. We identify significant asymmetric and long memory volatility properties and DCCs for pairs of BRICS stock and commodity markets, and variability in DCCs and Markov Switching regimes during economic and financial crises. Finally, we analyze optimal portfolio weights and time-varying hedge ratios, demonstrating the importance of overweighting optimal portfolios between BRICS stock and commodity assets.     

Return spillovers between white precious metal ETFs: The role of oil,gold, and global equity

This paper investigates the relationship between white precious metals and gold, oil and global equity by means of spillovers and volatility transmission. Relying on the recently introduced ETFs, this study is the first to analyse return spillovers derived from an E-GARCH model and to take into account frequency dynamics to understand changes in connectedness across periods of time. Results uncover numerous channels of return transmission across the selected ETF markets over the last 10years and highlight the role of gold ETFs as the most influential market in the sample. Furthermore, our work provides insights into the characteristics of white precious metal markets using a hidden semi-Markov model. Finally, we argue that even though silver and platinum have gained more importance as investment assets over the last few years, palladium still very much remains an industrial metal.     

How predictable are precious metal returns?

This paper provides strong evidence of time-varying return predictability of three precious metals from January 1987 to September 2014. We use three variations of the variance ratio test, the nonlinear Brock, Dechert and Schieinkman test as well as the Hurst exponent to evaluate the time-varying return predictability of precious metals to reduce the risk of spurious results. Our full sample results report mixed findings where some tests indicate significant predictability while some suggest no predictability. However through a time-varying procedure, we show that each precious metal market goes through periods of significant predictability as well as periods of unpredictability. Therefore this finding suggests that return predictability does vary over time and is not a static, all-or-nothing condition and therefore is consistent with the adaptive market hypothesis. We also show that platinum is the most predictable of the three precious metals and silver the least predictable, which may be of great to investors who include precious metals in their investment portfolios.     

Risk Reduction and Mean-Variance Analysis: An Empirical Investigation

Abstract:  I examine the performance of global minimum variance (GMV) and minimum tracking error variance (TEV) portfolios in UK stock returns using different models of the covariance matrix. I find that both GMV and TEV portfolios deliver portfolio risk reduction benefits in terms of significantly lower volatility and tracking error volatility relative to passive benchmarks for every model of the covariance matrix used. However, the GMV (TEV) portfolios do not provide significantly superior Sharpe (1966) (adjusted Sharpe) performance relative to passive benchmarks except for the restricted GMV portfolios. I find that a number of alternative covariance matrix models can improve the performance of the restricted TEV portfolio formed using the sample covariance matrix but not the restricted GMV portfolio. I also find that simpler covariance matrix models perform as well as the more sophisticated models.     

Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors

Using one-minute intraday data and wavelet decomposition of stochastic processes we obtain realised VCOV matrices with and without price discontinuities in the U.S. Treasuries and precious metals futures. Our work provides determinants of co-jumps in gold, silver and U.S. Treasuries across the yield curve and empirically demonstrates impact of price discontinues on hypothetical investor through realised correlations, hedging effectiveness ratios and several portfolio settings. We find that co-jumps in gold and silver have similar monetary characteristics to co-jumps in gold or silver with U.S. Treasuries futures. We further unpack investor choices between precious metals and U.S. bonds under the presence of high-frequency risks. We show that behaviour puzzle of simultaneous demand for safety and quality during market turmoils disappears if investors are seeking maximum diversification. We also find that runs to safety do not offer statistically significant improvements in diversification benefits unlike runs to short-term quality. Other results uncover higher investments to gold due to the shifts in the U.S. yield curve and potential gains in realised hedging effectiveness for the end of the yield curve investors through asymmetry in co-jumps of gold and U.S. Treasuries during periods of extreme market volatility such as beginning of the COVID-19 pandemic.     

Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management

This paper quantitatively examines return transmission and volatility spillovers between banking sector stocks in the US and eight other countries by applying our newly extended VAR-DCC-MEGARCH-M model with asymmetric spillovers and Student-t or skew-t errors. Our investigations clarify almost unidirectional stock return transmission from the US banking sector to all other eight international banking sectors. In addition, we also uncover bidirectional volatility spillovers between the US and other eight international banking sector stocks, which are all tied to the leverage effect. Moreover, using the dynamic conditional variances and covariances from our extended model, we derive the time-varying optimal hedge ratios and optimal portfolio weights. These analyses reveal that, except for such extraordinary periods as during financial crises, we can hedge the US banking sector stocks with other international banking sector stocks, and that well-balanced portfolios of the US and other banking sector stocks are optimal. Furthermore, additional analysis using gold, silver, and platinum futures reveals that we can hedge international banking sector stocks with precious metal futures highly effectively, and that well-balanced portfolios of banking stocks and precious metals are optimal. Based on the results from our analyses, this paper derives many significant interpretations and implications for financial and systemic risk management.     

Precious metals under the microscope: a high-frequency analysis

Taking advantage of a trades-and-quotes high-frequency database, we document the main stylized facts and dynamic properties of spot precious metals, i.e. gold, silver, palladium and platinum. We analyse the behaviours of spot prices, returns, volume and selected liquidity measures. We find clear evidence of periodic patterns matching the trading hours of the most active markets round-the-clock. The time series of spot returns have, thus, properties similar to those of traditional financial assets with fat tails, asymmetry, periodic behaviours in the conditional variances and volatility clustering. Gold (platinum) is the most (least) liquid and least (most) volatile asset. Commonality in liquidities of precious metals is very strong.     

Do precious metals hedge crude oil volatility jumps?

In this study, we investigate the impacts of contemporaneous and lagged implied oil volatility (OVX) jumps on precious metals (gold, palladium, platinum, and silver) with the focus on hedging property of precious metals. Additionally, the impacts of OVX jumps on precious metals is investigated in returns and volatility. The results show that gold returns are relatively less responsive against contemporaneous and lagged OVX jumps, thus, gold acts as a weak hedge against OVX jumps. However, other metals (copper, palladium, platinum, and silver) do not serve as a hedge against contemporaneous OVX jumps. Nevertheless, these metals takeover the traditional hedging favourite ‘gold’ in the case of lagged OVX jumps and offers a strong hedge. It suggests that ignoring past information could severely undermine the investigation of OVX and the precious metal relationship. OVX jumps result in an increased volatility in precious metals, thereby indicating that all precious metals behave as a single asset class in terms of volatility transmissions. Moreover, gold is the contemporaneous metal of choice when risk perception is high or investors are averse to risk. Nevertheless, as information is diffused, other metals yield better performance as a hedge.     

Corporate Sustainability Performance and Idiosyncratic Risk: A Global Perspective

Does investing in sustainability leaders affect portfolio performance? Analyzing two mutually exclusive leading and lagging global corporate sustainability portfolios (Dow Jones) finds that (1) leading sustainability firms do not underperform the market portfolio, and (2) their lagging counterparts outperform the market portfolio and the leading portfolio. Notably, we find leading (lagging) corporate social performance (CSP) firms exhibit significantly lower (higher) idiosyncratic risk and that idiosyncratic risk might be priced by the broader global equity market. We develop an idiosyncratic risk factor and find that its inclusion significantly reduces the apparent difference in performance between leading and lagging CSP portfolios.     

Comparative analysis on the effects of the Asian and global financial crises on precious metal markets

The global financial crisis has vigorously struck major financial markets around the world, in particular in the developed economies since they have suffered the most. However, some commodity markets, and in particular the precious metal markets, seem to be unscathed by this financial downturn. This paper investigates therefore the nature of volatility spillovers between precious metal returns over fifteen years (1995-2010 period) with the attention being focused on these markets’ behavior during the Asian and the global financial crises. Daily closing values for precious metals are analyzed. In particular, the variables under study are the US$/Troy ounce for gold, the London Free Market Platinum price in US$/Troy ounce, the London Free Market Palladium price in US$/Troy once, and the Zurich silver price in US$/kg. The main sample is divided into a number of sub periods, prior to, during and after the Asian crisis. The aim of this division is to provide a wide and deep analysis of the behavior of precious metal markets during this financial event and of how these markets have reacted during times of market instability. In addition, this paper also looks at the effects of the global financial crisis from August 2007 to November 2010 using GARCH and EGARCH modeling. The main results show that there is clear evidence of volatility persistence between precious metal returns, a characteristic that is shared with financial market behavior as it has been demonstrated extensively by the existing literature in the area. In terms of volatility spillover effects, the main findings evidence volatility spillovers running in a bidirectional way during the periods; markets are not affected by the crises, with the exception of gold, that tends to generate effects in all other metal markets. However, there is little evidence in the case of the other precious metals generating any kind of influence on the gold market. On the other hand, there is little evidence of spillover effects during the two crisis episodes. Finally, the results from asymmetric spillover effects show that negative news/information have a stronger impact in these markets than positive news, again a characteristic that has been also exhibited by financial markets.     

Market capitalization and Value-at-Risk

The potential of economic variables for financial risk measurement is an open field for research. This article studies the role of market capitalization in the estimation of Value-at-Risk (VaR). We test the performance of different VaR methodologies for portfolios with different market capitalization. We perform the analysis considering separately financial crisis periods and non-crisis periods. We find that VaR methods perform differently for portfolios with different market capitalization. For portfolios with stocks of different sizes we obtain better VaR estimates when taking market capitalization into account. We also find that it is important to consider crisis and non-crisis periods separately when estimating VaR across different sizes. This study provides evidence that market fundamentals are relevant for risk measurement.     

Portfolio credit-risk optimization

This paper evaluates several alternative formulations for minimizing the credit risk of a portfolio of financial contracts with different counterparties. Credit risk optimization is challenging because the portfolio loss distribution is typically unavailable in closed form. This makes it difficult to accurately compute Value-at-Risk (VaR) and expected shortfall (ES) at the extreme quantiles that are of practical interest to financial institutions. Our formulations all exploit the conditional independence of counterparties under a structural credit risk model. We consider various approximations to the conditional portfolio loss distribution and formulate VaR and ES minimization problems for each case. We use two realistic credit portfolios to assess the in- and out-of-sample performance for the resulting VaR- and ES-optimized portfolios, as well as for those which we obtain by minimizing the variance or the second moment of the portfolio losses. We find that a Normal approximation to the conditional loss distribution performs best from a practical standpoint.     

Spillovers and connectedness between major precious metals and major currency markets: The role of frequency factor

We examine the volatility spillovers and hedging characteristics between four major precious metals futures (gold, palladium, platinum, and silver) and seven major currencies (Australian dollar, British pound, Canadian dollar, Chinese yuan, Euro, Japanese yen, and Swiss franc) at three time horizons (short term, intermediate term, and long term). We draw our empirical results using the index methods of Diebold and Yilmaz, 2012, Diebold and Yilmaz, 2014 and Baruník and Křehlík (2018). The results show that the precious metals, except for gold, have the largest spillovers on the Australian dollar and Canadian dollar and receive the largest spillovers from these currencies for all the time horizons. In addition, with the exception of gold, the smallest spillovers from the precious metals are exerted on the Japanese yen and Chinese yuan and these currencies have the smallest spillovers to the precious metals. The Japanese yen and Chinese yuan act primarily as spillover receivers, whereas the other currencies act as both spillover transmitters and receivers in different time periods. The spillovers for most of the pairs are asymmetric for all the time horizons, are more pronounced in the short term, and noticeably increase during times of financial and economic uncertainty. Finally, adding precious metal futures contracts to currency portfolios provides diversification and hedging advantages, with hedging effectiveness higher in the short term than in the intermediate and long terms.     

Sources of Capital Market Segmentation: Empirical Evidence from Finland

Because Finland has experienced profound economic changes and financial deregulation since the mid‐1980s, we use it as a laboratory to explore issues related to time‐varying global equity market integration. Using a Finnish perspective, we construct two different portfolios of Finnish firms and a conditional one‐factor international asset pricing model. We examine whether the segmentation varies over time and across assets. We use time‐series variables for changing market integration (lagged foreign equity ownership, difference between Finnish and German short‐term interest rates, and a portfolio‐specific liquidity measure) and crosssectional variables (size and book‐to‐market ratios and industry sector) to show variation in integration.     

Financial crisis,Value-at-Risk forecasts and the puzzle of dependency modeling

Forecasting Value-at-Risk (VaR) for financial portfolios is a crucial task in applied financial risk management. In this paper, we compare VaR forecasts based on different models for return interdependencies: volatility spillover (Engle & Kroner, 1995), dynamic conditional correlations (Engle, 2002, 2009) and (elliptical) copulas (Embrechts et al., 2002). Moreover, competing models for marginal return distributions are applied. In particular, we apply extreme value theory (EVT) models to GARCH-filtered residuals to capture excess returns.Drawing on a sample of daily data covering both calm and turbulent market phases, we analyze portfolios consisting of German Stocks, national indices and FX-rates. VaR forecasts are evaluated using statistical backtesting and Basel II criteria. The extensive empirical application favors the elliptical copula approach combined with extreme value theory (EVT) models for individual returns. 99% VaR forecasts from the EVT-GARCH-copula model clearly outperform estimates from alternative models accounting for dynamic conditional correlations and volatility spillover for all asset classes in times of financial crisis.     

Market Risk of Developed and Emerging Countries During the Global Financial Crisis

This study compares the performance of the widely used risk measure, value at risk (VaR), across a large sample of developed and emerging countries. The performance of VaR is assessed using both the unconditional and conditional tests of Kupiec and Christoffersen, respectively, as well as the quadratic loss function. The results indicate that VaR performs much more poorly when measuring the risk of developed countries than of emerging ones. One possible reason might be the deeper initial impact of the global financial crisis on developed countries. The results also provide evidence of the decoupling of the market risk of emerging and developed countries during the global financial crisis.     

Portfolio selection with commodities under conditional copulas and skew preferences

This article investigates the portfolio selection problem of an investor with three-moment preferences taking positions in commodity futures. To model the asset returns, we propose a conditional asymmetric t copula with skewed and fat-tailed marginal distributions, such that we can capture the impact on optimal portfolios of time-varying moments, state-dependent correlations, and tail and asymmetric dependence. In the empirical application with oil, gold and equity data from 1990 to 2010, the conditional t copulas portfolios achieve better performance than those based on more conventional strategies. The specification of higher moments in the marginal distributions and the type of tail dependence in the copula has significant implications for the out-of-sample portfolio performance.     

Performance analysis of a collateralized fund obligation (CFO) equity tranche

This article examines the performance of the junior tranche of a collateralized fund obligation (CFO), i.e. the residual claim (equity) on a securitized portfolio of hedge funds. We use a polynomial goal programming model to create optimal portfolios of hedge funds, conditional to investor preferences and diversification constraints (maximum allocation per strategy). For each portfolio, we build CFO structures that have different levels of leverage, and analyze both the stand-alone performance as well as potential diversification benefits (low systematic risk exposures) of investing in the equity tranche of these structures. We find that the unconstrained mean-variance portfolio yields a high performance, but greater exposure to systematic risk. We observe the exact opposite picture in the case of unconstrained optimization, where a skewness bias is added, thus proving the existence of a trade-off between stand-alone performance and low exposure to systematic risk factors. We provide evidence that leveraged exposure to these hedge fund portfolios through the structuring of CFOs creates value for the equity tranche investor, even during the recent financial crisis.