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On the correlation between stocks and art market returns
Abstract
We estimate the correlation between the returns of an S&P 500-based portfolio and Renoir paintings. Unlike previous studies that relied on single-point estimates of the correlation to explore the merits of adding art assets to a portfolio of stocks, we rely on a wild bootstrap algorithm to determine confidence intervals for the correlation estimates. We find that these confidence intervals are so wide (a situation not peculiar to our example) that it seems impossible to make absolute remarks about the merits of adding art-related assets to stocks portfolios. Moreover, our results suggest that previous conclusions regarding the correlation between art and stocks should be taken with some scepticism.
... The following findings suggest that in the art market, prices do not fully reflect all available information, thereby offering opportunities for speculators to capitalize on predictable momentum trends (see Figure 2 and 3). In general, numerous studies have explored the relations between stock market performance and art market trends (such as Baumol 1986;Quattrocchi and Strati 2014;Chanel 1995;Mandel 2009;Renneboog and Spaenjers 2012;David, Oosterlinck, and Szafarz 2013;Charlin and Cifuentes 2017a;Higgs and Andrew C. 2004), the relationship between wealth and art prices (Goetzmann, Renneboog, and Spaenjers 2011;Goetzmann 1993) as well as the technical definition of art market returns (Charlin and Cifuentes 2017b;Bocart, Ghysels, and Hafner 2020). However, results regarding efficiency in the art market remain diverse (see Çevik, Atukeren, and Korkmaz 2013, Kra ussl, Lehnert, and Martelin 2016, Aye et al. 2017, Assaf et al. 2021, Pe nasse and Renneboog 2022. ...
I investigate the presence of time series momentum in the market of five highly rated living artists by considering a different approach that follows a pure investment purpose: Is this index investable? I shall test for time series predictability and then examine the profitability of two different trading strategies: speculative and passive.
... As they were gauged characteristically aimed at educational as well as business applications, it also exhibited the concern that ought to be exercised in understanding the hedonics PI of substandard investments. [36] gauged the correlation betwixt the returns of S&P 500-centered portfolio as well as Renoir paintings. They counted upon a wild bootstrap algorithm for ascertaining the confidence intervals aimed at the correlation estimations contrasting the studies on single-point estimations of the correlation to discover the advantages of including art assets to a portfolio of stocks. ...
Alternative Investments (AI) turns out to be helpful in the case where the investors trying to avoid Stock Market (SM). The gain that the long-term investors get as of the SM is not very propitious or enough for their patience or risk tolerance, which is the pretext for taking such a step. Thus, art can be an alternative asset class as it can proffer prodigious returns with diversification; yet it is an unplumbed area caused by ignorance. The goal of this paper is to render a perception into the awareness level and the prevailing attitude concerning art investment in India. In addition to that, it also explores the reasons for the same through the ideas along with opinions of individual investors, financial managers, together with financial advisors. Also, it provides an inclusive view of investment avenues together with their performance in the past with useful insights of understanding the reasons for under-development and non-popularity of art investments among Indian potential investors. Lastly, art along with other asset classes' outcomes of returns in addition to return-risk portfolios are analyzed.
... For example, a number of authors have promoted the idea that art is lowly correlated with more conventional assets, such as stocks and bonds, simply by computing correlations over a fixed time frame (Campbell 2008). They have not paid attention to how unstable and time-dependent these correlations are, and more important, to the error associated with these correlation estimates, a topic that only a handful of authors have paid attention to (Charlin and Cifuentes 2016;Renneboog and Spaenjers 2013;Spaenjers 2010). Other authors have relied on the capital asset pricing model (CAPM) to showcase the merits of art investments (Edwards 2004;Hodgson and Vorkink 2004;Kraeussl and Lee 2010;Mei and Moses 2002;Stein 1977). ...
This article presents a new framework to evaluate the merits of an art investment that differs substantially from previous studies. First, it assumes that the investor already holds a portfolio consisting of more traditional assets and is planning to add art to it. This is far more realistic than the usual academic set up in which it is assumed that the investor is planning to deploy a given amount of cash among many assets, one of which is art. Second, the approach departs from the traditional Markowitz’s mean-variance framework in two important ways: (i) the efficient frontier is constructed based on cumulative returns, rather than average returns, and risk is assessed via potential losses and not volatility; and (ii) it relies on a semi-parametric approach to generate synthetic data based on the Gaussian copula and historic returns. Finally, an alternative risk metric, based on losses and not volatility, is introduced. The usefulness of this framework is demonstrated with an example based on art sales auction data.
... Charlin i Cifuentes (2017) 40 analizując współczynniki korelacji dla indeksu S&P 500 oraz stóp zwrotu dzieł dwóch artystów (Picassa i Renoira) oraz dwóch kierunków malarskich (Surrealistów i Impresjonistów) w okresie marzec 1985grudzień 2014 z wykorzystaniem technik bootstrapingu dla oszacowania przedziałów ufności dla oszacowanych współczynników korelacji, skonkludowali, że przedziały te były na tyle szerokie, że nie było możliwym ustalenie faktu, czy dodanie dzieł sztuki do portfela złożonego z akcji i obligacji podnosiłoby jego efektywność. ...
Inwestycje alternatywne, a zwłaszcza w obrębie sztuki cieszą się dużym zainteresowaniem inwestorów, szczególnie w okresie zawirowań na rynku akcji. Mniejsza niż jeden wartość współczynnika korelacji stóp zwrotu na rynku sztuki ze stopami zwrotu na rynku inwestycji klasycznych (akcji, obligacji), pozwala na budowę portfela bardziej efektywnego w rozumieniu teorii Markowitza. O ile kalkulacja stóp zwrotu na bazie pojedynczych transakcji na rynku sztuki budzi wiele kontrowersji, o tyle posługiwanie się indeksami rynku sztuki, głównym i sektorowymi pozwala na przeprowadzenie bardziej dokładnych porównań z rynkiem akcji czy obligacji. W artykule przedstawione zostały obliczenia stóp zwrotu, ryzyka (odchylenie standardowe), współczynnika zmienności (ryzyko/dochód) dla ogólnego indeksu sztuki Global Art Index oraz pięciu indeksów sektorowych (Old Masters, 19th Century, Modern Art, Post War Art i Contemporary Art) i skonfrontowane zostały one z wynikami uzyskanymi dla akcji i obligacji. Ponadto w artykule zamieszczono obliczenia współczynników korelacji stóp zwrotu analizowanych indeksów rynku sztuk oraz stóp zwrotu na rynku inwestycji klasycznych (akcji i obligacji).
... The comparison of art market returns and stocks is a widespread tool of analysis among researchers. The recent study of [21] provides evidence that the confidential intervals for correlation between art returns and S&P 500 are too wide, so, the merits of adding art assets to stock portfolios as a way of diversification are doubtful. Such inference does not contradict the pattern we demonstrate above. ...
... Art-related assets trade infrequently (not continuously), art transaction costs are very high (BS assumes they are negligible), art returns do not follow a normal distribution (they tend to be very skewed and with fat tails), and artworks cannot be shorted. Additionally, art returns are difficult to estimate with good accuracy (Charlin & Cifuentes 2017). And finally, art returnseven in the best case-are marred by a problem not occurring with other assets: they reflect the return of an "average" painting, not the specific painting that is to be auctioned. ...
Auction-house guarantees are becoming a common feature in the art market. We analyze these guarantees within the framework of financial options. This approach allows us to derive analytical (closed-form) expressions to value these positions, considering both, the case in which the painting is sold, and the case in which the painting goes unsold (“bought in”). In addition, we present several risk metrics that are useful to describe from an intuitive viewpoint the exposure of the auction house, and that of a third party (in case the auction house decides to layoff, fully or partially, the risk associated with offering such guarantees). We demonstrate that the expressions we derive satisfy the put-call parity relationship, and we further validate these formulas with a Monte Carlo simulation applied to a realistic example. We also show that the risk associated with such guarantees is lower than what is commonly believed by market practitioners, and we expose the dangers of relying on the Black-Scholes model to value such guarantees. Finally, having explicit expressions to assess the risk involved in these guarantees helps to bring more transparency to a notoriously opaque segment of the art market.
... Additional studies have explored the correlation between the market for paintings and that of stocks, bonds and commodities (e.g. Campbell, 2010;Charlin and Cifuentes, 2017;Kraeussl and Lee, 2010). ...
The relationship between prices of paintings at public auctions and their attributes has received much attention in recent years. However, the effects of color have been mostly absent from these studies. The present study explored the relationship between price and color in Rothko’s post 1950 paintings, which were dominated by color rather than figurative elements. We characterized the color features of the paintings in terms of their dominant hues and luminosity. In addition, we developed two additional metrics to evaluate color contrast, and palette diversity. We found that in general the market favored diverse color compositions, and preferred reds over greens, blues over yellows, and lighter-colored paintings. We also identified two distinct price regimes in the period studied: a first period, dominated by enthusiasm for the artist, regardless of the painting’s characteristics; and a second period, driven by color-related attributes.
The purpose of the article: The art market becomes very popular among investors, when there is strong turbulence on the stock market. In times of calm, the art market is used by investors to diversify risk and build more efficient investment portfolios according to the Markovitz’s theory. The aim of this paper is to: (i) present the peculiarity of investment on the art market, represented by art market indexes in comparison to traditional investments in other financial market segments (money market, equity indexes and commodity market), (ii) to verify the hypothesis of normality of the distribution of rates of return of the analyzed art market indices as well as (iii) to analyze calendar effects occurrence on the art market.
Methodology: Comparison of rates of return on the stock, bond, commodity and money markets with rates on the art market in four different time intervals. For each of the analyzed periods, an income-risk map was presented, taking into account the spectrum of financial instruments, including six art indexes: Old Masters, 19th Century, Modern art, Post War art, Contemporary art and Global art. The hypothesis of normality of the distribution of rates of return of the art market indices for four analyzed periods was verified with the use of Jarque-Bera test.
Results of the research: Comparison of rates of return on the stock market and art market leads to the conclusion that their relationship depends on the period chosen. For two of the analyzed periods, the rates of return on the stock market were higher than on the art market, but for others periods, the opposite. The distribution of quarterly rates of return resulted to be a normal distribution for almost all of analyzed indices and time periods. Calendar effects were observed in the case of four analyzed indexes.
The purpose of the article: The art market becomes very popular among investors, when there is strong turbulence on the stock market. In times of calm, the art market is used by investors to diversify risk and build more efficient investment portfolios according to the Markovitz’s theory. The aim of this paper is to: (i) present the peculiarity of investment on the art market, represented by art market indexes in comparison to traditional investments in other financial market segments (money market, equity indexes and commodity market), (ii) to verify the hypothesis of normality of the distribution of rates of return of the analyzed art market indices as well as (iii) to analyze calendar effects occurrence on the art market.
Methodology: Comparison of rates of return on the stock, bond, commodity and money markets with rates on the art market in four different time intervals. For each of the analyzed periods, an income-risk map was presented, taking into account the spectrum of financial instruments, including six art indexes: Old Masters, 19th Century, Modern art, Post War art, Contemporary art and Global art. The hypothesis of normality of the distribution of rates of return of the art market indices for four analyzed periods was verified with the use of Jarque-Bera test.
Results of the research: Comparison of rates of return on the stock market and art market leads to the conclusion that their relationship depends on the period chosen. For two of the analyzed periods, the rates of return on the stock market were higher than on the art market, but for others periods, the opposite. The distribution of quarterly rates of return resulted to be a normal distribution for almost all of analyzed indices and time periods. Calendar effects were observed in the case of four analyzed indexes.
Esta investigación estima el comportamiento del valor de obras de artistas colombianos durante el período 1989-2015 mediante el cálculo de un índice hedónico. Para ello, se utilizan datos de subastas internacionales del portal Artprice.com y la metodología de precios hedónicos; se incorpora, además, el modelo de selección de Heckman con el fin de evitar sesgo de selección. Los resultados muestran cómo la rentabilidad de la inversión en estas obras de arte ha sido inferior al rendimiento de los principales indicadores de renta variable, pero constituye una alternativa de diversificación dentro de un portafolio de inversión.
We analyze the guarantees that art-auction houses offer from an options viewpoint. This approach allows us to derive analytical expressions to value the positions involved in such arrangements. We further validate these formulas with a Monte Carlo simulation applied to a realistic example. Finally, we show that the risk associated with such guarantees is lower than what is commonly believed by market practitioners, we also expose the dangers of relying on the Black-Scholes model to value such guarantees, and we introduce a simple risk-reward metric that has intuitive appeal.
The comparatively poor performance of traditional asset classes in recent years has driven the search for greater returns via alternative asset classes. The desire to reap higher risk adjusted returns from diversification into assets which offer low and even negative correlation with equities and bonds is extremely desirable. There has been a huge growth in the traditional alternative investments such as real estate, commodity futures, private equity and hedge fund investments. Additionally, a number of funds specialising in art have recently emerged. These also appear to offer a highly beneficial diversification strategy with extremely low correlation with traditional asset classes. It is important for investors to understand the risk and return characteristics of this new alternative asset class. In this paper we take a closer look at art as an alternative asset, and look specifically at how this new alternative asset is expected to perform, also during bear markets, when the benefits of diversification are most needed. We look at the risk and return characteristics of art using art market indices, and the prospects for portfolio diversification in the art market using a variety of data across art market sectors, including the Old Master, European Impressionist, Modern and Contemporary art markets. Due to the low correlation of art with other asset classes, we find opportunities for portfolio diversification across art markets and across asset classes. The results hold, even allowing for the high transaction costs, which are encountered when trading art, when spread over a longer time horizon.
In this paper we are interested in inference based on heteroskedasticity consistent covariance matrix estimators, for which the appropriate bootstrap is a version of the wild bootstrap. Simulation results, obtained by a new very efficient methos, show that all wild bootstraps tests exhibit substantial size distortion if the error terms are skewed and strongly heteroskedastic.
Bootstrap methods are a collection of sample re-use techniques designed to estimate standard errors and confidence intervals. Making use of numerous samples drawn from the initial observations, these techniques require fewer assumptions and offer greater accuracy and insight than do standard methods in many problems. After presenting the underlying concepts, this introduction focuses on applications in regression analysis. These applications contrast two forms of bootstrap resampling in regression, illustrating their differences in a series of examples that include outliers and heteroscedasticity. Other regression examples use the bootstrap to estimate standard errors of robust estimators in regression and indirect effects in path models. Numerous variations of bootstrap confidence intervals exist, and examples stress the concepts that are common to the various approaches. Suggestions for computing bootstrap estimates appear throughout the discussion, and a section on computing suggests several broad guidelines.
In regression models, appropriate bootstrap methods for inference robust to heteroskedasticity of unknown form are the wild bootstrap and the pairs bootstrap. The finite sample performance of a heteroskedastic-robust test is investigated with Monte Carlo experiments. The simulation results suggest that one specific version of the wild bootstrap outperforms the other versions of the wild bootstrap and of the pairs bootstrap. It is the only one for which the bootstrap test always gives better results than the asymptotic test.
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances. We show that, in one very specific case, perfect bootstrap inference is possible, and a substantial reduction in the error in the rejection probability of a bootstrap test is available much more generally. However, the version of the wild bootstrap with this desirable property is without the skewness correction afforded by the currently most popular version of the wild bootstrap. Simulation experiments show that this does not prevent the preferred version from having the smallest error in rejection probability in small and medium-sized samples.
This paper provides a simple and empirically plausible model of artworks as investment vehicles. It reconciles the observation that average financial returns for collectibles are low and volatile with the theory of consumption-based asset pricing. Art assets are appealing both for their ability to transfer consumption over time and for their use as signals of wealth, as in the literature on the demand for luxuries. Adding art value to utility, returns also reflect this "conspicuous consumption" dividend; as a result, average financial returns are low. Risk premia for artworks are predicted to be modest or even negative. (JEL G11, Z11)
It is shown in this article that the classical i.i.d. bootstrap remains a valid procedure for estimating the sampling distributions of certain symmetric estimators of location, as long as the random observations are independently drawn from distributions with (essentially) a common location. This may be viewed as a robust property of the classical i.i.d. bootstrap. Also included is a study of the second order properties of a different bootstrap procedure proposed by Wu in the context of heteroscedasticity in regression.
Hedonic methods are currently considered state-of-the-art for handling quality changes when compiling consumer price indices. The present article proposes first a mathematical description of characteristics and of elementary aggregates. In a following step, a hedonic econometric model is formulated and hedonic elementary population indices are defined. These indices extend from simple indices based on some average quality to universal formulae that incorporate the full quality spectrum of the respective elementary aggregate. We emphasise that population indices are unobservable economic parameters that need to be estimated by suitable sample indices. It is shown that most of the hedonic elementary index formulae used in practice are sample versions of particular hedonic elementary population indices.
Hedonic methods are currently considered state-of-the-art for handling quality changes when compiling consumer price indices. The present article proposes first a mathematical description of characteristics and of elementary aggregates. In a following step, a hedonic econometric model is formulated and hedonic elementary population indices are defined. These indices extend from simple indices based on some average quality to universal formulae that incorporate the full quality spectrum of the respective elementary aggregate. We emphasise that population indices are unobservable economic parameters that need to be estimated by suitable sample indices. It is shown that most of the hedonic elementary index formulae used in practice are sample versions of particular hedonic elementary population indices.
In Davidson and MacKinnon (1981), two of the present authors proposed a novel and very simple procedure for testing the specification of a nonlinear regression model against the evidence provided by a non-nested alternative. In this paper we extend their results in several directions. First, we relax a number of the assumptions of the previous paper; we admit the possibility that the nonlinear regression functions may depend on lagged dependent variables, and we do not require that the error terms be normally distributed. Second, we show how the earlier procedure may straightforwardly be generalized to the case where the two non-nested models involve different transformations of the dependent variable. Finally, we propose a simple procedure for testing non-nested linear regression models which have endogenous variables on the right-hand side, and have therefore been estimated by two-stage least squares.
Estimation Biases in Quality-Adjusted Hedonic Price Indices. Rotterdam: Rotterdam School of Management, Erasmus University
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Art as an Investment: The Top 500 Artists. Amsterdam: Department of Finance
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Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties
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Art as an Investment and the Underperformance of Masterpieces
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Buying Beauty: On Prices and Returns in the Art Market
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