Is Gold a Hedge or a Safe Haven? an Analysis of Stocks, Bonds and Gold
TL;DR: In this paper, the authors investigated the relationship between stocks, bonds and gold and found that gold is a hedge against stocks on average and a safe haven in extreme stock market conditions.
Abstract: Is gold a hedge against sudden changes in stock and bond returns, or does it instead have a subtly different property, that of being a safe haven? This paper addresses these two interlinked questions. A safe haven is defined as a security that is uncorrelated with stocks and bonds in case of a market crash. This is counterpoised against a hedge, defined as a security that is uncorrelated with stocks or bonds on average. We study constant and time-varying relationships between stocks, bonds and gold in order to investigate the existence of a hedge and a safe haven. The empirical analysis examines US, UK and German stock and bond returns and their relationship with gold returns. We find that gold is a hedge against stocks on average and a safe haven in extreme stock market conditions. This finding suggests that the existence of a safe haven enhances the stability and resiliency of financial markets since it reduces investors' losses at times when a reduction is needed the most. A portfolio analysis further shows that the safe haven property is extremely short-lived so that an investor buying gold one day after a shock loses money.
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TL;DR: This paper examined the role of gold in the global financial system and found that gold is both a hedge and a safe haven for major European stock markets and the US but not for Australia, Canada, Japan and large emerging markets such as the BRIC countries.
Abstract: The aim of this paper is to examine the role of gold in the global financial system. We test the hypothesis that gold represents a safe haven against stocks of major emerging and developing countries. A descriptive and econometric analysis for a sample spanning a 30 year period from 1979-2009 shows that gold is both a hedge and a safe haven for major European stock markets and the US but not for Australia, Canada, Japan and large emerging markets such as the BRIC countries. We also distinguish between a weak and strong form of the safe haven and argue that gold may act as a stabilizing force for the financial system by reducing losses in the face of extreme negative market shocks. Looking at specific crisis periods, we find that gold was a strong safe haven for most developed markets during the peak of the recent financial crisis.
1,158 citations
Cites background from "Is Gold a Hedge or a Safe Haven? an..."
...This paper builds on the work of Baur and Lucey (2009), by extending the analysis in a number of important ways....
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...The section builds on the definitions provided in Baur and Lucey (2009) but extends their work in one important respect....
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...With the exception of Baur and Lucey (2009) none of the above literature explicitly examines the role of gold as a safe haven against losses in financial markets....
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...Evidence of the potential for gold to act as a safe haven asset was presented by Baur and Lucey (2009)....
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TL;DR: This paper used a dynamic conditional correlation model to examine whether Bitcoin can act as a hedge and safe haven for major world stock indices, bonds, oil, gold, the general commodity index and the US dollar index.
854 citations
Cites background from "Is Gold a Hedge or a Safe Haven? an..."
...The principles of Bitcoin are explained by Dwyer (2015) and at bitcoin....
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...The principles of Bitcoin are explained by Dwyer (2015) and at bitcoin.org. Since its introduction in 2009, the value of Bitcoin grew rapidly to more than US$6 billion at the end of 2015 (coinmarketcap.com). In parallel, there has been a growing interest in research addressing the economics and finance of Bitcoin. Rogojanu and Badea (2014) compare Bitcoin to alternative monetary systems....
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...Brandvold et al. (2015) and Ciaian et al. (2016) focus on price discovery in the Bitcoin market....
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...Bouri et al. (2016) concentrate on the role of trading volume in explaining Bitcoin return and volatility....
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...As gold has been traditionally considered a hedge and a safe haven, these concepts have previously been applied mostly to gold (Baur and Lucey, 2010)....
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TL;DR: In this article, the authors use the daily internet search volume from millions of households to reveal market-level sentiment, by aggregating the volume of queries related to household concerns (e.g. "recession", "unemployment" and "bankruptcy") and construct a Financial and Economic Attitudes Revealed by Search (FEARS) index as a new measure of investor sentiment.
Abstract: We use the daily internet search volume from millions of households to reveal market-level sentiment. By aggregating the volume of queries related to household concerns (e.g. "recession", "unemployment" and "bankruptcy"), we construct a Financial and Economic Attitudes Revealed by Search (FEARS) index as a new measure of investor sentiment. Between 2004 and 2011, we find increases in FEARS lead to return reversals: although high FEARS are associated with low returns today, they predict high returns over the following two days. In the cross-section of stocks, the reversal effect is strongest among stocks which are attractive to noise traders and hard to arbitrage. FEARS also coincide with excess volatility and predict daily mutual fund flow. When FEARS increase, investors are more likely to pull money out of equity mutual funds and put it into bond funds. Taken together, the results are broadly consistent with theories of investor sentiment.
774 citations
Cites result from "Is Gold a Hedge or a Safe Haven? an..."
...relationship between searches for “gold” and market returns, consistent with the evidence in Baur and Lucey (2010), who argue that gold represents a “safe haven” in times of distress, at least in view of retail investors who are most likely to be affected by sentiment....
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TL;DR: In this paper, the authors compared the conditional variance properties of Bitcoin and gold as well as other assets and found differences in their structure and concluded that Bitcoin and Gold feature fundamentally different properties as assets and linkages to equity markets.
520 citations
TL;DR: It is shown that Bitcoin does not act as a safe haven, instead decreasing in price in lockstep with the S&P 500 as the crisis develops, and cast doubt on the ability of Bitcoin to provide shelter from turbulence in traditional markets.
519 citations
Cites background from "Is Gold a Hedge or a Safe Haven? an..."
..., 2004) and may prompt investors to seek out safe haven investments such as gold (Conlon et al., 2018; Bredin et al., 2015; Baur and Lucey, 2010)....
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References
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Book•
01 Jan 1974TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Abstract: This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
31,082 citations
TL;DR: Cumulative prospect theory as discussed by the authors applies to uncertain as well as to risky prospects with any number of outcomes, and it allows different weighting functions for gains and for losses, and two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting function.
Abstract: We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows different weighting functions for gains and for losses. Two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting functions. A review of the experimental evidence and the results of a new experiment confirm a distinctive fourfold pattern of risk attitudes: risk aversion for gains and risk seeking for losses of high probability; risk seeking for gains and risk aversion for losses of low probability. Expected utility theory reigned for several decades as the dominant normative and descriptive model of decision making under uncertainty, but it has come under serious question in recent years. There is now general agreement that the theory does not provide an adequate description of individual choice: a substantial body of evidence shows that decision makers systematically violate its basic tenets. Many alternative models have been proposed in response to this empirical challenge (for reviews, see Camerer, 1989; Fishburn, 1988; Machina, 1987). Some time ago we presented a model of choice, called prospect theory, which explained the major violations of expected utility theory in choices between risky prospects with a small number of outcomes (Kahneman and Tversky, 1979; Tversky and Kahneman, 1986). The key elements of this theory are 1) a value function that is concave for gains, convex for losses, and steeper for losses than for gains,
13,433 citations
TL;DR: In this article, a new class of multivariate models called dynamic conditional correlation models is proposed, which have the flexibility of univariate generalized autoregressive conditional heteroskedasticity (GARCH) models coupled with parsimonious parametric models for the correlations.
Abstract: Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.
5,695 citations
"Is Gold a Hedge or a Safe Haven? an..." refers methods in this paper
...In order to examine whether the hedge ratio is potentially constant we estimate the dynamic conditional correlations model (DCC) of Engle (2002) and compute time-varying betas....
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...the dynamic conditional correlations model (DCC) of Engle (2002) and compute time-varying...
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Posted Content•
TL;DR: Prospect Theory as mentioned in this paper is an alternative theory of individual decision making under risk, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights.
Abstract: Analysis of decision making under risk has been dominated by expected utility theory, which generally accounts for people's actions. Presents a critique of expected utility theory as a descriptive model of decision making under risk, and argues that common forms of utility theory are not adequate, and proposes an alternative theory of choice under risk called prospect theory. In expected utility theory, utilities of outcomes are weighted by their probabilities. Considers results of responses to various hypothetical decision situations under risk and shows results that violate the tenets of expected utility theory. People overweight outcomes considered certain, relative to outcomes that are merely probable, a situation called the "certainty effect." This effect contributes to risk aversion in choices involving sure gains, and to risk seeking in choices involving sure losses. In choices where gains are replaced by losses, the pattern is called the "reflection effect." People discard components shared by all prospects under consideration, a tendency called the "isolation effect." Also shows that in choice situations, preferences may be altered by different representations of probabilities. Develops an alternative theory of individual decision making under risk, called prospect theory, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights. The theory has two phases. The editing phase organizes and reformulates the options to simplify later evaluation and choice. The edited prospects are evaluated and the highest value prospect chosen. Discusses and models this theory, and offers directions for extending prospect theory are offered. (TNM)
4,185 citations
TL;DR: In this article, a multinomial logistic regression model is proposed to evaluate contagion in financial markets, which captures the coincidence of extreme return shocks across countries within a region and across regions.
Abstract: This article proposes a new approach to evaluate contagion in financial markets. Our measure of contagion captures the coincidence of extreme return shocks across countries within a region and across regions. We characterize the extent of contagion, its economic significance, and its determinants using a multinomial logistic regression model. Applying our approach to daily returns of emerging markets during the 1990s, we find that contagion is predictable and depends on regional interest rates, exchange rate changes, and conditional stock return volatility. Evidence that contagion is stronger for extreme negative returns than for extreme positive returns is mixed.
879 citations