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In this paper, we use the improved Diebold & Yilmaz method based on TVP-VAR-SV model to analyze dynamic connectedness between energy, precious metal, industrial metal, agriculture and livestock commodity markets. The results show that the energy, industrial metal, and precious metal commodity markets are the information transmitters in commodity markets, and the agriculture and livestock commodity markets play the roles of information receivers. Furthermore, we employ the GARCH-MIDAS model to study the influence of geopolitical risk on the dynamic connectedness between five commodity markets. We find that geopolitical risk, especially geopolitical act risk, significantly affects the overall connectedness of commodity markets. And more notably, the impacts on the net spillover of various commodity markets are different. Geopolitical risk has positive effects on the net spillover of energy, agriculture and livestock commodity markets, and negative effects on precious metal and industrial metal commodity markets.

We examine the hedging and safe-haven characteristics between four major precious metals (gold, silver, platinum, and palladium) and three major US stock market indices. The metal markets are known for hedging and safety characteristics during financial distress. The paper sheds new insights into the hedging and safe-haven ability of the precious metals under extreme stock market volatility conditions caused by the COVID-19 by drawing empirical estimates using two different copula approaches. The results show that gold outperforms all other precious metals such as silver, platinum, and palladium in hedging abilities under extreme stock market conditions. Likewise, gold remains a safe-haven asset both in calm and turbulent periods, and silver possibly remains the next best alternative, albeit as a weak safe-haven asset.

In our study, we individually forecast 26 metal prices one-month ahead and outperform the predefined benchmark model, a random-walk (with drift) in 18 (18) cases. These forecasts are based on an overview over a large set of potential predictors for mineral commodities, originating from studies which only consider a selection of attributes and apply them to predict specific commodities or commodity indices. We pre-select the relevant, commodity-specific, individual factors through a correlation analysis, followed by a BIC based regression selection. The results of our out-of-sample, one-month ahead forecasts show a significant outperformance for 18 of the 26 commodities considered, especially those in the minor metals sector. The differences in predictability between the metal groups are remarkable, as we are able to forecast 13 of 17 minor metals, 5 of 6 industrial metals, but no precious metal, highlighting the heterogeneity in metal commodity markets. Focusing on the influential factors, the value factor has a dominating, highly significant, negative effect in the prediction and determination of prices.

We report new evidence that speculation in energy and precious metal futures are more prevalent in crisis periods and even more so during the COVID-19 pandemic. In contrast, agricultural futures attract more hedging pressure. Post-GFC patterns mirror the 1980s’ recessions. Using quantile regression on a long-horizon sample we also find that speculative pressure generally coincides with abnormal returns in normal circumstances but not in the current pandemic. Instead, volatility is strongly and often non-linearly associated with speculation across instruments.

Some economists have argued theoretically that the private minting of circulating precious metal coins would be inefficient: Due to information asymmetry, money-users would be chronically victimized by low-quality or underweight coins. An examination of experience with private mints during gold rushes in the United States 1830-61, drawing on contemporary accounts and numismatic literature, finds otherwise. While some private gold mints produced underweight coins, from incompetence or fraudulent intent, such mints did not last long. Informed by newspapers about the findings of assays, money-users quickly and systematically abandoned underweight coins in favor of full-weight coins. Only honest mints survived.

The scarcity and weak durability of precious metal catalysts are among biggest obstacles to achieving cost-effective electrocatalysts in fuel cells. Hence, it is imperative to develop low-cost non-precious metal catalysts with comparable oxygen reduction reaction (ORR) activity to the precious metal catalysts. Herein, we report a highly effective strategy for facile synthesis of Fe/N-functionalized 3D porous carbon networks. A major advantage of the newly designed catalyst is that ultrafine Fe4N nanoparticles are grown and uniformly mounted on the carbon framework upon pyrolysis treatment at 800 °C, and co-existing with numerous in-situ formed Fe-Nx moieties in the carbon matrix, being evidenced by using X-ray absorption and photoelectron spectroscopy. The new electrocatalysts yield high ORR activity, comparable/superior to that of the state-of-the-art Fe/N-carbon based catalysts reported to date. Specifically, the catalysts show a half-wave potential of 0.890 V and a limited current density of 6.18 mA cm-2, both surpassing the commercial Pt/C. By resorting to the experimental measurements and density-functional theory (DFT) calculations, the synergistic effects between Fe-N4 moieties and the Fe4N support are identified for the first time, which play a key role in boosting catalytic performance of the Fe/N-functionalized porous carbon networks.

This discussion paper examines the possibilities of relationships between two seemingly disparate industries, blockchain and the extractive sectors, by considering the potential for blockchain solutions in the mining of Cobalt, a precious metal, looking in particular at the supply chain, oversight, and production efficiencies that are made possible through synergistic elements between the two sectors.

In addition to a myriad of industrial uses, precious metals continue to play an important role in the global financial system; they are increasingly popular as an investment and form part of a well diversified portfolio in addition to acting as central bank reserves. Understanding how macro-economic events shape liquidity in this market is important for a number of market participants, and also helps policy makers assess the efficacy of the policy transmission mechanism. Using high-frequency data, we consider liquidity provision in the period around monetary policy announcements and relate this to prevailing levels of investor sentiment. We are able to contrast changes in liquidity in the gold and silver markets, and across three instruments (futures, ETFs, and physical/bullion). We show that liquidity is removed from the market around 5-minutes prior to the announcement and then reverts to normal within 10-minutes (gold market) and 16-minutes (silver market). The magnitude of the liquidity response is determined by both the scale of surprise in the FOMC announcement, and the prevailing level of investor sentiment. Both sentiment and monetary policy surprises have a greater impact on liquidity during periods of low sentiment.

We use multivariate random forests to compute out-of-sample forecasts of a vector of returns of four precious metal prices (gold, silver, platinum, and palladium). We compare the multivariate forecasts with univariate out-of-sample forecasts implied by random forests independently fitted to every single returns series. Using univariate and multivariate forecast evaluation criteria, we show that multivariate forecasts are more accurate than univariate forecasts.

In the years of 21st century, the world palladium demand has increased steadily and dramatically. However, its spot price still has not reached the peak level observed in January 17, 2001. In 2008, a single-day increase of the palladium spot price has exceeded 37%, which witnesses significant risk for investments in the world palladium market. In this paper, we apply the GARCH model with heavy-tailed distributions into the palladium spot returns series for risk management purpose. We compare empirical performance of the Student’s t distribution and the normal reciprocal inverse Gaussian (NRIG) distribution. Our results show the newly-developed distribution, the NRIG, cannot outperform the older fashion one, the Student’s t distribution. Nevertheless, our results do demonstrate that it is important to incorporate conditional heavy tails for precious metals’ spot return modelling.

Turkish Abstract: Bu calismanin amaci, kiymetli metal piyasalarinin dogrusal olmayan yapilarini Cok Degiskenli Markov Rejim Degisim Modelleriyle (MMS-VAR) analiz etmektir. Calismanin gozlem araligi 02 Ocak 2002 – 28 Mart 2016 olup, spot altin, gumus, paladyum ve platine ait gunluk kapanis fiyatlarini icermektedir. Arastirma sonuclari, uluslararasi kiymetli metal piyasasinin daralma, ilimli buyume ve genisleme rejimlerinden olusan bir yapiya sahip olduguna dair kanitlar sunmaktadir. English Abstract: The aim of this study is to analyze whether the precious metals have a nonlinear pattern by using Multivariate Markov SwitchingVector Autoregressive Models (MMS-VAR). The observation period is between 02 January 2002 and 28 March 2016 and includes daily closed prices of gold, silver, palladium and platinum. Research results have evidence that the international precious metal market have a structure with three regimes as depression, moderate growth and expansion.

The role of gold as a safe haven asset has been extensively studied in recent years. This article extends previous literature and examines time varying safe haven properties versus equities and bonds of four precious metals (gold, silver, platinum and palladium) across eleven countries. Results suggest that the metals each play safe haven roles; there are times when one metal is not while another may be a safe haven against an asset. The second part of this article attempts to identify robust economic and political determinants of precious metals’ safe haven properties applying zero-inflated Poisson regression (ZIP) and extreme bound analysis (EBA). Economic Policy Uncertainty is found to be a positive and robust determinant of a precious metal being a safe haven. This holds across countries. Stock volatility, exchange rates, interest rate and credit spreads are also found to be significant, but results are quite mixed for different markets and are fragile of model specification.

Given the increased attention of precious metals by investors and the finance literature as well as the growth of high frequency trading, the behaviour of intraday precious metal markets is of great interest and importance. Therefore, this paper examines the stylized facts, correlation and interaction between volatility and returns at the 5-minute frequency of gold, silver, platinum and palladium from May 2000 to April 2015. We study the full sample period, as well as three sub-samples to determine how high-frequency data of precious metals have developed over time. We find that over the full sample period that the number of trades has increased substantially over time for each precious metal while the bid-ask spread has narrowed over time, indicating an increase in liquidity and efficiency. We also find strong evidence of periodicity in returns, volatility, volume and bid-ask spread. Returns and volume both experience strong intraday periodicity linked to the opening and closing of major markets around the world while the BAS is at its lowest when European markets are open. We also show a bilateral Granger causality between returns and volatility of each precious metal, which holds for the vast majority subsamples.

We study the impact and changes to the precious metal fixing structure that took place in 2014 and 2015 for Gold, Silver, Palladium and Platinum. On average, we find that there is negative price pressure going into the fixing auction, for all precious metals Futures, outside active US trading hours regardless of fixing structure. For active US trading hours, there is no obvious, observable persistent price pressures. Price pressure into the AM Fix usually reverses part of the prior gains that have taken place throughout the overnight session.Price for most metals generally increases between the PM Fix to the AM Fix and the negative price pressure may be due to liquidity effects as the Future price converges to an arbitrage free price or due to geographic preferences. The overnight market is illiquid for all metals. We find no conclusive signs that the price is manipulated into the fix given the data set, at least not on average. Nor do we find any significant change in the price and volume structure before and after the Fix changes. Given the higher transparency and more Fix participants we would have expected changes in the structure if it was manipulated before the change in the Fix structure. However, absence of evidence is not evidence of absence but we would need a different data set to conclude that the new Fix fixed the Fix.The drift we observe during the AM Fix is more likely based on expectations that the spot price established in the auction will be lower than the Future price that seems to have been pushed up outside US trading hours.

Since 1897 the London Silver Fixing has conducted a daily auction which, to this day, sets the daily benchmark price for the precious metal. This private pricing club functions alongside active public markets for silver, including the physical spot and futures markets. This empirical market microstructure study analyses publicly traded silver instruments to assess the impact the fixing has on public markets. The study spans fourteen years of fixings, from January 2000 to December 2013, which includes the introduction of contemporaneous silver futures trading in late 2006. It finds statistically significantly lower prices around the time of the fixing in both spot and futures markets, elevated levels of trade volume and price volatility immediately following the fixing’s start, well before the conclusion of the fixing and the publication of its outcome. Further, it finds statistically significant return advantages in the four minutes following the start of the fixing for informed traders while no significant returns follow the publication of the fixing outcome. Trades in the opening minutes of the fixing are highly predictive of the price direction of the fixings. The size and significance of these results increase after the introduction of contemporaneous futures trading.

Exploring the information contained in Commodity Futures Trading Commission’s (CFTC) Commitments of Traders (COT) reports, this analysis investigates the forecasting ability of investor sentiment index in three major precious metal futures markets, namely, Gold, Silver, and Platinum. A strong contemporaneous relationship between investor sentiment and market returns has been found. In specific, commercial traders’ sentiment acts oppositely to the price changes while that of non-commercial and non-reporting traders positively correlated with the market returns. However, the bivariate Granger causality test shows little evidence that investor sentiment index could lead market returns. On the other hand, market returns generally lead investor sentiment. Particularly, commercial traders are trend counters while non-commercial and non-reporting traders are trend followers. Extreme traders’ position also fails to display significant forecasting ability of subsequent price movements. In general, the results do not support the use of investor sentiment as an indicator to predict price movements in precious metal futures markets. Nevertheless, we find that investor sentiment could play as a signal of buying or selling and the trading system is highly profitable compared to naive long position in all of three markets.

We investigate whether proxies for mood play a role in the pricing of gold, silver, platinum and palladium. Using several mood proxies derived from weather and biorhythms factors, our tests suggest some individually significant relationships, but with very low overall explanatory power. We conclude that, unlike in equity pricing, there does not appear to be, at this stage, a role for mood proxies in further developing our understanding of precious metal pricing.

Gold is a large Global business and represents the most liquid commodity market other than crude oil. These notes offer an overview of issues relating to Gold market and should be looked at as only information presented after the investigation of the structure of gold, trading as a futures contract on the NCDEX. In Part I, as an introduction to the precious metal Gold and its origin, a brief review of a prominent book on Gold and its history titled “The Ages of Gold” by Timothy Green is presented, Part II emphasizes on the demand and supply of gold in the world market with trend analysis, Part III emphasizes on aspects of the Gold Futures market, exchange trading of Gold futures with an overview of the now familiar GARCH properties (autoregressive conditional heteroscedasticity). Part IV emphasizes on a the Indian gold futures market and illustrates a rarely used measure in the capital markets–the Garman Klass estimator – is used to provide new insights in intraday and interday gold counter dynamics. As part of the closing remarks an executive summary is presented encompassing latest data on gold from a Global perspective. Scope for further research – Trend analysis of the Indian Gold futures market in the backdrop of the more mature American market would result in better forecasting of prices and demand.

Following a huge run-up in the 1970’s, precious metal prices have, until recent years, been very subdued. Investors tend to overlook precious metals, except to take note of the strong correlation properties with other asset classes, which justifies only a small allocation. However, given current macroeconomic conditions and the extreme policy response that has been initiated due to these conditions, investors should not only be looking at the correlation properties, but also the exceptional returns that precious metals will provide in the coming years.

Crude oil and precious metals, silver and especially gold, prices have been more volatile in the recent years. Investors and speculators such as investment banks, hedge funds, mutual funds, etc. pay close attention to the price and volatility of these commodities. The daily returns of Brent, gold and silver from 8 April 1999 to 7 April 2009 are employed to model the volatility and volatility spillovers across markets. The univariate conditional volatility models suggest that there is time-varying volatility in all assets. Moreover, asymmetry is observed in the Brent and gold markets. For multivariate conditional volatility models, the previous gold and silver volatility have no spillovers effects to the Brent market. The previous volatility in Brent and silver are spillovers to the gold volatility, but only previous gold volatility spillovers to silver volatility. Therefore, silver and gold precious metals investors have to be aware of other precious metal market volatility. Particularly, gold investors should consider the previous Brent market volatility. Asymmetric effects exist in Brent and gold markets. Therefore, we can state that asymmetric models are clearly superior to symmetric models for the Brent and gold markets. However, rolling windows suggest that the assumption of constant conditional correlations is too restrictive.

We investigate key macroeconomic factors that impact the price returns of precious metals markets over a 20 year period. The markets investigated are gold, silver, platinum and palladium; whereas the macroeconomic factors accommodated business cycle, monetary environment and financial market sentiment factors. The key findings present limited evidence that the same macroeconomic factors jointly influence the volatility processes of the precious metal price series, although there is some evidence of volatility feedback between the precious metals. This finding lends weight to views that individual commodities are too distinct to be considered a single asset class or represented by a single index; a finding of considerable importance for portfolio managers and investors.

When money was made of gold and silver, individuals faced the problem of determining the intrinsic content of coins in many exchange situations. In this paper we look at a well-documented solution to this problem, and a key institution of the commodity money system: coin assaying. To that goal we build a model of search and matching in which agents trade using coins that are imperfectly recognizable, but have access to a coin inspection technology that reveals the intrinsic content of coins for a fee. We consider two sources of imperfect information: counterfeit coins and clipping. With counterfeits we show that coin assaying reduced the extent of inefficiencies associated with imperfect coins recognizability (namely lower traded quantities and lower trading frequencies). Yet it did not necessarily increase welfare because it unmasked counterfeits which then traded at a discount, reducing total output. With clipping, we show that agents clip for two reasons: in the hope of passing an inferior coin for a superior one, and to reduce the purchasing power of coins that are too valuable. While coin assaying could remove the first type of clipping, it had no effect on the second. While framed in the context of the commodity money system, our analysis relates to the more general issue of asset trading under imperfect information.

We demonstrate for the first time the existence of a lunar cycle on precious metal returns. This appears to be more pronounced in silver than gold, with very little evidence for an effect in platinum.

The recent bull market of gold and other precious metal industry point to obvious questions: Are corporations' hedging strategies still valuable for their shareholders and how is this information reflected in the financial analysts' forecast? The impact of using derivatives on a firm's equity return is an ongoing issue in both corporate and asset management. Although theoretical literature describes why firms should or should not hedge, we do not know much about the empirical validity of these predictions. This paper provides descriptive evidence on the risk management activities of two gold mining firms and investigates whether a firm's use of derivatives materially reduces the overall expected equity-return risk as well as the forecasted earnings risk. Results of this study confirm that derivatives can be used to reduce a firm's risk exposure. Specifically, the empirical results show a firm that employs intensive hedging activities through derivatives tends to experience both statistically and economically significant risk reductions on its future cash-flows as well as equity returns. In addition, the results indicate that financial analysts incorporate the information of a firm's hedging strategy and that it is reflected in their earnings forecasts.