Research articles for the 2020-02-26
A Call on Art Investments
SSRN
The art market has seen a sustained growth over the last years, but participation has been reserved for just a few investors. The paper proposes to overcome this problem by introducing a call option on an art index which is derived from one of the most comprehensive data sets of art market transactions. The option allows investors to optimize their exposure to art. For pricing purposes, nontradability of the art index is acknowledged, and a fundamental PDE for the option value and its closed form solution are derived, if one assumes the underlying to be correlated with an existing asset. A lower bound for the option value is also given when no such correlated asset exists.
SSRN
The art market has seen a sustained growth over the last years, but participation has been reserved for just a few investors. The paper proposes to overcome this problem by introducing a call option on an art index which is derived from one of the most comprehensive data sets of art market transactions. The option allows investors to optimize their exposure to art. For pricing purposes, nontradability of the art index is acknowledged, and a fundamental PDE for the option value and its closed form solution are derived, if one assumes the underlying to be correlated with an existing asset. A lower bound for the option value is also given when no such correlated asset exists.
A Model of Presidential Debates
arXiv
arXiv
Presidential debates are viewed as providing an important public good by revealing information on candidates to voters. We consider an endogenous model of presidential debates in which an incumbent and a challenger (who is privately informed about her own quality) publicly announce whether they are willing to participate in a public debate, taking into account that a voter's choice of candidate depends on her beliefs regarding the candidates' qualities and on the state of nature.It is found that in equilibrium a debate occurs or does not occur independently of the challenger's quality and therefore the candidates' announcements are uninformative. This is because opting-out is perceived to be worse than losing a debate and therefore the challenger never refuses to participate.
A Model of Trading in the Art Market
SSRN
We present an infinite-horizon model of endogenous trading in the art auction market. Agents make purchase and sale decisions based on the relative magnitude of their private use value in each period. Our model generates endogenous cross-sectional and time-series patterns in investment outcomes. Average returns and buy-in probabilities are negatively correlated with the time between purchase and resale (attempt). Idiosyncratic risk does not converge to zero as the holding period shrinks. Prices and auction volume increase during expansions. Our model finds empirical support in auction data and has implications for selection biases in observed prices and transaction-based price indexes.
SSRN
We present an infinite-horizon model of endogenous trading in the art auction market. Agents make purchase and sale decisions based on the relative magnitude of their private use value in each period. Our model generates endogenous cross-sectional and time-series patterns in investment outcomes. Average returns and buy-in probabilities are negatively correlated with the time between purchase and resale (attempt). Idiosyncratic risk does not converge to zero as the holding period shrinks. Prices and auction volume increase during expansions. Our model finds empirical support in auction data and has implications for selection biases in observed prices and transaction-based price indexes.
Art Investment Vehicles and the Challenges of the Alternative Investment Fund Manager Directive (AIFMD)
SSRN
As interest in art as an alternative asset class has grown in recent years so has the emergence of art investment vehicles. These vehicles seek to capitalize on the inherent inefficiencies of the art market and provide the potential to identify, create and execute transactions in works of art at highly attractive terms. Art fund managers seek to approach art investment in the same manner as any collective portfolio manager such as UCITSD management companies or AIFMs. Proven techniques and disciplines common to the management of every asset class are employed and modern portfolio theory, sophisticated risk management tools, and quantitative and qualitative analysis forms the basis for investment strategy and process. This paper briefly discusses challenges for art fund managers under the AIFMD.
SSRN
As interest in art as an alternative asset class has grown in recent years so has the emergence of art investment vehicles. These vehicles seek to capitalize on the inherent inefficiencies of the art market and provide the potential to identify, create and execute transactions in works of art at highly attractive terms. Art fund managers seek to approach art investment in the same manner as any collective portfolio manager such as UCITSD management companies or AIFMs. Proven techniques and disciplines common to the management of every asset class are employed and modern portfolio theory, sophisticated risk management tools, and quantitative and qualitative analysis forms the basis for investment strategy and process. This paper briefly discusses challenges for art fund managers under the AIFMD.
Art and Money
SSRN
This paper investigates the impact of equity markets and top incomes on art prices. Using a newly constructed art market index, we demonstrate that equity market returns have had a significant impact on the price level in the art market over the last two centuries. We also find evidence that an increase in income inequality may lead to higher prices for art. Finally, the results of Johansen cointegration tests strongly suggest the existence of a long-run relation between top incomes and art prices.
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This paper investigates the impact of equity markets and top incomes on art prices. Using a newly constructed art market index, we demonstrate that equity market returns have had a significant impact on the price level in the art market over the last two centuries. We also find evidence that an increase in income inequality may lead to higher prices for art. Finally, the results of Johansen cointegration tests strongly suggest the existence of a long-run relation between top incomes and art prices.
Art as Collateral
SSRN
High market values and the recognition of its investment potential make art a potential source of collateral for loans. Recently, firms specializing in art lending have emerged to serve this market. This study explores the effect of regional variations in economic and financial conditions on art-backed lending activities. We show that demand for art loans increases when the economy experiences a downturn and the liquidity need is high. We also compare the demand for art-secured loans with home equity loans and test a pecking order theory for the borrowing of high net worth individuals. The findings suggest that art as a substitute collateral is increasingly used when home equity loans are difficult to obtain.
SSRN
High market values and the recognition of its investment potential make art a potential source of collateral for loans. Recently, firms specializing in art lending have emerged to serve this market. This study explores the effect of regional variations in economic and financial conditions on art-backed lending activities. We show that demand for art loans increases when the economy experiences a downturn and the liquidity need is high. We also compare the demand for art-secured loans with home equity loans and test a pecking order theory for the borrowing of high net worth individuals. The findings suggest that art as a substitute collateral is increasingly used when home equity loans are difficult to obtain.
Art as an Asset: Evidence from Keynes the Collector
SSRN
The risk-return characteristics of art as an asset have previously been studied through aggregate price indexes. By contrast, we examine the long-run buy-and-hold performance of an actual portfolio, namely the collection of John Maynard Keynes. We find that its performance has substantially exceeded existing estimates of art market returns. Our analysis of the collection identifies general attributes of art portfolios crucial in explaining why investor returns can diverge substantially from market returns: transaction-specific risk, buyer heterogeneity, return skewness, and portfolio concentration. Furthermore, our findings highlight the limitations of art price indexes as a guide to asset allocation or performance benchmarking.
SSRN
The risk-return characteristics of art as an asset have previously been studied through aggregate price indexes. By contrast, we examine the long-run buy-and-hold performance of an actual portfolio, namely the collection of John Maynard Keynes. We find that its performance has substantially exceeded existing estimates of art market returns. Our analysis of the collection identifies general attributes of art portfolios crucial in explaining why investor returns can diverge substantially from market returns: transaction-specific risk, buyer heterogeneity, return skewness, and portfolio concentration. Furthermore, our findings highlight the limitations of art price indexes as a guide to asset allocation or performance benchmarking.
Art as an Investment and the Underperformance of Masterpieces
SSRN
This paper constructs a new data set of repeated sales of artworks and estimates an annual index of art prices for the period 1875-2000. Contrary to earlier studies, we find art outperforms fixed income securities as an investment, though it significantly under-performs stocks in the US. Art is also found to have lower volatility and lower correlation with other assets, making it more attractive for portfolio diversification than discovered in earlier research. There is strong evidence of underperformance of masterpieces, meaning expensive paintings tend to under-perform the art market index. The evidence is mixed on whether the "law of one price" holds in the New York auction market.
SSRN
This paper constructs a new data set of repeated sales of artworks and estimates an annual index of art prices for the period 1875-2000. Contrary to earlier studies, we find art outperforms fixed income securities as an investment, though it significantly under-performs stocks in the US. Art is also found to have lower volatility and lower correlation with other assets, making it more attractive for portfolio diversification than discovered in earlier research. There is strong evidence of underperformance of masterpieces, meaning expensive paintings tend to under-perform the art market index. The evidence is mixed on whether the "law of one price" holds in the New York auction market.
Art as an Investment and the Underperformance of Masterpieces
SSRN
This paper constructs a new data set of repeated sales of artworks and estimates an annual index of art prices for the period 1875-2000. Contrary to earlier studies, we find art outperforms fixed income securities as an investment, though it significantly under-performs stocks in the US. Art is also found to have lower volatility and lower correlation with other assets, making it more attractive for portfolio diversification than discovered in earlier research. There is strong evidence of underperformance of masterpieces, meaning expensive paintings tend to under-perform the art market index. The evidence is mixed on whether the "law of one price" holds in the New York auction market.
SSRN
This paper constructs a new data set of repeated sales of artworks and estimates an annual index of art prices for the period 1875-2000. Contrary to earlier studies, we find art outperforms fixed income securities as an investment, though it significantly under-performs stocks in the US. Art is also found to have lower volatility and lower correlation with other assets, making it more attractive for portfolio diversification than discovered in earlier research. There is strong evidence of underperformance of masterpieces, meaning expensive paintings tend to under-perform the art market index. The evidence is mixed on whether the "law of one price" holds in the New York auction market.
Art-Backed Lending: Implied Spreads and Art Risk Management
SSRN
The increasing portion of individuals' wealth in art sets the stage for art-backed lending services. Considering widely used credit default swaps, the paper applies the structure to art-backed loans and develops an extensive pricing model for the derivatives contract, explicitly taking art market characteristics into account. Using a CDS pricing methodology sheds light on current lending spreads and provides a risk management tool for art-backed lending institutions. At the same time, an introduced art credit default swap would offer an ability to transfer the lender's risk with respect to the art price. The results suggest that credit risk accounts for at most 50% of current art-backed lending spreads.
SSRN
The increasing portion of individuals' wealth in art sets the stage for art-backed lending services. Considering widely used credit default swaps, the paper applies the structure to art-backed loans and develops an extensive pricing model for the derivatives contract, explicitly taking art market characteristics into account. Using a CDS pricing methodology sheds light on current lending spreads and provides a risk management tool for art-backed lending institutions. At the same time, an introduced art credit default swap would offer an ability to transfer the lender's risk with respect to the art price. The results suggest that credit risk accounts for at most 50% of current art-backed lending spreads.
Banking on the Lawyers
SSRN
This Article is the first to analyze an unexplored but critical change in how modern banks are governed: the rise of lawyers as bank directors. That rise has been precipitous, raising the question of why lawyer-directors now sit on most bank boards. Using novel empirical evidence, we show that lawyer-directors at banks are associated with efficient changes in risk management and significant increases in bank value. In particular, banks with lawyer-directors assume more risk in ordinary (non-crisis) circumstances and less risk when a crisis arises, in each case in a way that makes banks more valuable. Lawyer-directors do this by drawing on advocacy skills to critically analyze opposing points of view, an essential quality in managing the risks banks face today. They are also more likely to make complex information, sourced from multiple experts, more accessible to a bank’s board as part of its decision-making process. Finally, lawyer-directors are skilled at assessing litigation and regulatory risks, which have grown significantly in recent years.Risk management failures were a primary cause of the 2008 financial crisis, prompting two principal regulatory responses: stricter capital requirements and enhanced governance. Their effectiveness remains hotly debated. Our findings have two important implications. First, we challenge the notion that stricter regulation is sufficient for efficient risk management. Rather, to manage a bank, directors must have the skills to think critically about risk. Second, we underscore the value of director expertise, showing that more is needed than simply the director’s independence now mandated by law.
SSRN
This Article is the first to analyze an unexplored but critical change in how modern banks are governed: the rise of lawyers as bank directors. That rise has been precipitous, raising the question of why lawyer-directors now sit on most bank boards. Using novel empirical evidence, we show that lawyer-directors at banks are associated with efficient changes in risk management and significant increases in bank value. In particular, banks with lawyer-directors assume more risk in ordinary (non-crisis) circumstances and less risk when a crisis arises, in each case in a way that makes banks more valuable. Lawyer-directors do this by drawing on advocacy skills to critically analyze opposing points of view, an essential quality in managing the risks banks face today. They are also more likely to make complex information, sourced from multiple experts, more accessible to a bank’s board as part of its decision-making process. Finally, lawyer-directors are skilled at assessing litigation and regulatory risks, which have grown significantly in recent years.Risk management failures were a primary cause of the 2008 financial crisis, prompting two principal regulatory responses: stricter capital requirements and enhanced governance. Their effectiveness remains hotly debated. Our findings have two important implications. First, we challenge the notion that stricter regulation is sufficient for efficient risk management. Rather, to manage a bank, directors must have the skills to think critically about risk. Second, we underscore the value of director expertise, showing that more is needed than simply the director’s independence now mandated by law.
Cascading Losses in Reinsurance Networks
arXiv
arXiv
We develop a model for contagion in reinsurance networks by which primary insurers' losses are spread through the network. Our model handles general reinsurance contracts, such as typical excess of loss contracts. We show that simpler models existing in the literature--namely proportional reinsurance--greatly underestimate contagion risk. We characterize the fixed points of our model and develop efficient algorithms to compute contagion with guarantees on convergence and speed under conditions on network structure. We characterize exotic cases of problematic graph structure and nonlinearities, which cause network effects to dominate the overall payments in the system. We lastly apply our model to data on real world reinsurance networks. Our simulations demonstrate the following: (1) Reinsurance networks face extreme sensitivity to parameters. A firm can be wildly uncertain about its losses even under small network uncertainty. (2) Our sensitivity results reveal a new incentive for firms to cooperate to prevent fraud, as even small cases of fraud can have outsized effect on the losses across the network. (3) Nonlinearities from excess of loss contracts obfuscate risks and can cause excess costs in a real world system.
Corrupted Multidimensional Binary Search: Learning in the Presence of Irrational Agents
arXiv
arXiv
Standard game-theoretic formulations for settings like contextual pricing and security games assume that agents act in accordance with a specific behavioral model. In practice however, some agents may not prescribe to the dominant behavioral model or may act in ways that are arbitrarily inconsistent. Existing algorithms heavily depend on the model being (approximately) accurate for all agents and have poor performance in the presence of even a few such arbitrarily irrational agents. \emph{How do we design learning algorithms that are robust to the presence of arbitrarily irrational agents?}
We address this question for a number of canonical game-theoretic applications by designing a robust algorithm for the fundamental problem of multidimensional binary search. The performance of our algorithm degrades gracefully with the number of corrupted rounds, which correspond to irrational agents and need not be known in advance. As binary search is the key primitive in algorithms for contextual pricing, Stackelberg Security Games, and other game-theoretic applications, we immediately obtain robust algorithms for these settings.
Our techniques draw inspiration from learning theory, game theory, high-dimensional geometry, and convex analysis, and may be of independent algorithmic interest.
Crowdfunding Under Market Feedback, Asymmetric Information And Overconfident Entrepreneur
SSRN
This article is the first one that considers a model of the choice between the different types of crowdfunding, which contains elements of the asymmetric information approach and behavioral finance (overconfident entrepreneurs). The model provides several implications, most of which have not yet been tested. Our model predicts that equity-based crowdfunding is more profitable than reward-based crowdfunding when an entrepreneur is overconfident. This is because the entrepreneur learns from the sale of shares before making production decisions. The model also predicts that an equilibrium can exist where some firms use equity-based crowdfunding, which contrasts the results of traditional theories (which have rational managers), for example the pecking-order theory. It also contrasts traditional behavioral finance literature (e.g. Fairchild 2005) where equity is not issued in equilibrium.
SSRN
This article is the first one that considers a model of the choice between the different types of crowdfunding, which contains elements of the asymmetric information approach and behavioral finance (overconfident entrepreneurs). The model provides several implications, most of which have not yet been tested. Our model predicts that equity-based crowdfunding is more profitable than reward-based crowdfunding when an entrepreneur is overconfident. This is because the entrepreneur learns from the sale of shares before making production decisions. The model also predicts that an equilibrium can exist where some firms use equity-based crowdfunding, which contrasts the results of traditional theories (which have rational managers), for example the pecking-order theory. It also contrasts traditional behavioral finance literature (e.g. Fairchild 2005) where equity is not issued in equilibrium.
Crowdfunding in a Competitive Environment
SSRN
Crowdfunding has mostly been used to finance very unique projects. Recently, however, companies have begun using it to finance more traditional products where they compete against other sellers of similar products. Major crowdfunding platforms, Kickstarter and Indiegogo, as well as Amazon have launched several projects consistent with this trend. This paper offers a model where two competing firms can use crowdfunding prior to direct sales. The model provides several implications that have not yet been tested eg.: 1) Firms can use crowdfunding strategically to signal a high level of demand for their products; 2) (reward-based) Crowdfunding is procyclical; 3) A higher platform fee may lead to higher firm profits in equilibrium; 4) Competition increases the chances of using crowdfunding compared to the monopoly case; 5) A non-monotonic relationship exists between the risk of crowdfunding campaign failure and firm profit.
SSRN
Crowdfunding has mostly been used to finance very unique projects. Recently, however, companies have begun using it to finance more traditional products where they compete against other sellers of similar products. Major crowdfunding platforms, Kickstarter and Indiegogo, as well as Amazon have launched several projects consistent with this trend. This paper offers a model where two competing firms can use crowdfunding prior to direct sales. The model provides several implications that have not yet been tested eg.: 1) Firms can use crowdfunding strategically to signal a high level of demand for their products; 2) (reward-based) Crowdfunding is procyclical; 3) A higher platform fee may lead to higher firm profits in equilibrium; 4) Competition increases the chances of using crowdfunding compared to the monopoly case; 5) A non-monotonic relationship exists between the risk of crowdfunding campaign failure and firm profit.
Digital Transformation in the Hedge Fund and Private Equity Industry
SSRN
The digital transformation is disrupting the financial sector. Venture capital, private equity and hedge funds are also affected. We see more and more firms implement emerging technologies in their investment process. There are several common trends. Big Data analytics and the use of artificial intelligence in the initial stages of the investment process significantly reduce the information asymmetries and even offer more accurate predictions of the probability of success than human analysts. At the same time, emerging technologies help democratize investment decisions. Consider the ability of emerging technologies to close the expertise gap and create a level playing field for all types of investors. Moreover, technology has the potential to make the hedge fund, private equity, and venture capital industries accessible to retail investors. Crypto markets emerged only recently, but their instantaneous success highlights the demand for alternative investment assets and opportunities across different investor groups.
SSRN
The digital transformation is disrupting the financial sector. Venture capital, private equity and hedge funds are also affected. We see more and more firms implement emerging technologies in their investment process. There are several common trends. Big Data analytics and the use of artificial intelligence in the initial stages of the investment process significantly reduce the information asymmetries and even offer more accurate predictions of the probability of success than human analysts. At the same time, emerging technologies help democratize investment decisions. Consider the ability of emerging technologies to close the expertise gap and create a level playing field for all types of investors. Moreover, technology has the potential to make the hedge fund, private equity, and venture capital industries accessible to retail investors. Crypto markets emerged only recently, but their instantaneous success highlights the demand for alternative investment assets and opportunities across different investor groups.
Do Press Announcements of Corporate Downsizing Predict Actual Downsizing?
SSRN
We investigate the determinants of actual downsizing following corporate press announcements of downsizing and find that some announcements are followed by lower growth rates in assets and employees and some are not. Our analysis indicates that the downsizing announcement sometimes implies net downsizing and sometimes implies strategic re-alignment of assets. Firms with increased asset and employee growth rates have higher market to book, a proxy for investment opportunities. In contrast, ex-post decreases in growth occur for firms with lower operating performance. Further we find that during a normal economy, board independence is also associated with lower ex-post growth, but not during a period of economic decline. This suggests relatively more board involvement in asset restructuring during normal or boom times. The results provide new evidence on the nature of information contained in announcements of asset downsizing and employee layoffs.
SSRN
We investigate the determinants of actual downsizing following corporate press announcements of downsizing and find that some announcements are followed by lower growth rates in assets and employees and some are not. Our analysis indicates that the downsizing announcement sometimes implies net downsizing and sometimes implies strategic re-alignment of assets. Firms with increased asset and employee growth rates have higher market to book, a proxy for investment opportunities. In contrast, ex-post decreases in growth occur for firms with lower operating performance. Further we find that during a normal economy, board independence is also associated with lower ex-post growth, but not during a period of economic decline. This suggests relatively more board involvement in asset restructuring during normal or boom times. The results provide new evidence on the nature of information contained in announcements of asset downsizing and employee layoffs.
Does It Pay to Play? A Multi-Perspective on Follow-On Funding, Funding Structure and Investment Profitability in a Venture Capital Context
SSRN
Within this paper, I propose a comprehensive modelling framework to evaluate venture capital (VC) investment decisions from an individual investors' portfolio perspective.The approach integrates the perspective of different shareholding parties and allocation of rights usually determined via shares in each one's portfolio.Using a basic model implementation of the modelling framework, I focus on the feasibility of follow-on funding of investment projects given underlying investment profitability. In particular, I evaluate the minimum levels of profitability of the investment, where funding is feasible.Based on the model, I propose alternative explanations on observed phenomena in VC such as underinvestment (non funding of positive net present value investments) and funding of negative net present value projects which are ultimately rooted in common practice of venture funding structure.In a first model extension, I also consider the effectiveness of pay-to-play rights on the minimum levels of profitability. Based on the model's result, I conclude that pay-to-play rights effectiveness is eventually limited by the investment approval of shareholders.
SSRN
Within this paper, I propose a comprehensive modelling framework to evaluate venture capital (VC) investment decisions from an individual investors' portfolio perspective.The approach integrates the perspective of different shareholding parties and allocation of rights usually determined via shares in each one's portfolio.Using a basic model implementation of the modelling framework, I focus on the feasibility of follow-on funding of investment projects given underlying investment profitability. In particular, I evaluate the minimum levels of profitability of the investment, where funding is feasible.Based on the model, I propose alternative explanations on observed phenomena in VC such as underinvestment (non funding of positive net present value investments) and funding of negative net present value projects which are ultimately rooted in common practice of venture funding structure.In a first model extension, I also consider the effectiveness of pay-to-play rights on the minimum levels of profitability. Based on the model's result, I conclude that pay-to-play rights effectiveness is eventually limited by the investment approval of shareholders.
Econometric issues with Laubach and Williams' estimates of the natural rate of interest
arXiv
arXiv
Holston, Laubach and Williams' (2017) estimates of the natural rate of interest are driven by the downward trending behaviour of `other factor' $z_{t}$. I show that their implementation of Stock and Watson's (1998) Median Unbiased Estimation (MUE) to determine the size of $\lambda_{z}$ is unsound. It cannot recover the ratio of interest $\lambda _{z}=a_{r}\sigma _{z}/\sigma _{\tilde{y}}$ from MUE required for the estimation of the full structural model. This failure is due to their Stage 2 model being incorrectly specified. More importantly, the MUE procedure that they implement spuriously amplifies the estimate of $\lambda _{z}$. Using a simulation experiment, I show that their MUE procedure generates excessively large estimates of $\lambda _{z}$ when applied to data simulated from a model where the true $\lambda _{z}$ is equal to zero. Correcting their Stage 2 MUE procedure leads to a substantially smaller estimate of $\lambda _{z}$, and a more subdued downward trending influence of `other factor' $z_{t}$ on the natural rate. This correction is quantitatively important. With everything else remaining the same in the model, the natural rate of interest is estimated to be 1.5% at the end of 2019:Q2; that is, three times the 0.5% estimate obtained from Holston et al.'s (2017) original Stage 2 MUE implementation. I also discuss various other issues that arise in their model of the natural rate that make it unsuitable for policy analysis.
Emerging Art Markets
SSRN
This paper analyzes the performance and risk-return characteristics of three major emerging art markets: Russia, China, and India. According to three national art market indices, built by hedonic regressions based on auction sales prices, the geometric annual returns are 10.00%, 5.70%, and 42.20% for Russia (1985-2008), China (1990-2008), and India (2002-2008), respectively. The Russian art market exhibits positive correlations with most common financial assets and a positive market beta, whereas the Chinese art market demonstrates a negative correlation overall and a negative market beta, and the Indian art index reveals a negative market beta and varying correlation results. Portfolio optimization under a power utility framework suggests limited diversification potential, but with a downside beta of 0.43, investing in Chinese art offers hedging potential during financial market downswings. Investigating the linkages between art and the economy through co-integration and causality analyses proves that emerging art markets share a significant long-term relation with other financial market instruments, but the short-term relations are largely absent.
SSRN
This paper analyzes the performance and risk-return characteristics of three major emerging art markets: Russia, China, and India. According to three national art market indices, built by hedonic regressions based on auction sales prices, the geometric annual returns are 10.00%, 5.70%, and 42.20% for Russia (1985-2008), China (1990-2008), and India (2002-2008), respectively. The Russian art market exhibits positive correlations with most common financial assets and a positive market beta, whereas the Chinese art market demonstrates a negative correlation overall and a negative market beta, and the Indian art index reveals a negative market beta and varying correlation results. Portfolio optimization under a power utility framework suggests limited diversification potential, but with a downside beta of 0.43, investing in Chinese art offers hedging potential during financial market downswings. Investigating the linkages between art and the economy through co-integration and causality analyses proves that emerging art markets share a significant long-term relation with other financial market instruments, but the short-term relations are largely absent.
Empirical Analysis of Basel Effects on the Interest Rate of Public and Private Banks: A Case Study of SBI and ICICI Bank
SSRN
The purpose of this working paper is to analyze the effect of Basel norms on the interest rate structure of both public and private bank of Indian banking industry by taking the time series data of two leading banks i.e. State bank of India and Industrial Credit and Investment Corporation of India from 2000 to 2015.The study used both qualitative and quantitative approaches and to analyze the data linear regression model is used for interest rate structure. To study the effect on interest rate this paper includes independent variable based on CAMEL approach. The ratio which are taken into consideration are Capital adequacy ratio, Asset management (Net Asset to loan given), Managerial Efficiency (Total advances to total deposit), Earning Ratio (Net interest income to total fund), and Liquidity Ratio (Liquid Asset to deposit ratio. The result of regression model summary statistics for average interest rate on loans shows that interest rate of loan has a strong correlation with explanatory variables that we used in this model. Explanatory variable explains 78.8 percent (public bank SBI) and 83.3 percent (private bank ICICI) of dependent variable and this can be concluded that the model is proper and fit. The empirical result shows the independent variables have a significant effect on the interest rate of the Indian Banking Industry.
SSRN
The purpose of this working paper is to analyze the effect of Basel norms on the interest rate structure of both public and private bank of Indian banking industry by taking the time series data of two leading banks i.e. State bank of India and Industrial Credit and Investment Corporation of India from 2000 to 2015.The study used both qualitative and quantitative approaches and to analyze the data linear regression model is used for interest rate structure. To study the effect on interest rate this paper includes independent variable based on CAMEL approach. The ratio which are taken into consideration are Capital adequacy ratio, Asset management (Net Asset to loan given), Managerial Efficiency (Total advances to total deposit), Earning Ratio (Net interest income to total fund), and Liquidity Ratio (Liquid Asset to deposit ratio. The result of regression model summary statistics for average interest rate on loans shows that interest rate of loan has a strong correlation with explanatory variables that we used in this model. Explanatory variable explains 78.8 percent (public bank SBI) and 83.3 percent (private bank ICICI) of dependent variable and this can be concluded that the model is proper and fit. The empirical result shows the independent variables have a significant effect on the interest rate of the Indian Banking Industry.
Empirical Analysis of Investments on the Fine Art Market
SSRN
In conditions of the stock market instability the art assets could be considered as an attractive investment. However, due to the heterogeneity of the fine art market's goods and the absence of the systematic information about the sales, researchers do not come to the same opinion about the merits of the art assets conducting studies on single segments of the market. We make an attempt to investigate attractiveness of the fine art market for investors. Extensive data was collected to obtain a complete pattern of the market analyzing it within different segments. We construct hedonic art price indexes using parametric and semi-parametric methodologies and assess the risk via CAPM model. The artworks in the high price sector are the potentially most profitable assets on the market, but the investments in paintings are associated with high risk.
SSRN
In conditions of the stock market instability the art assets could be considered as an attractive investment. However, due to the heterogeneity of the fine art market's goods and the absence of the systematic information about the sales, researchers do not come to the same opinion about the merits of the art assets conducting studies on single segments of the market. We make an attempt to investigate attractiveness of the fine art market for investors. Extensive data was collected to obtain a complete pattern of the market analyzing it within different segments. We construct hedonic art price indexes using parametric and semi-parametric methodologies and assess the risk via CAPM model. The artworks in the high price sector are the potentially most profitable assets on the market, but the investments in paintings are associated with high risk.
Experience and Brokerage in Asset Markets: Evidence from Art Auctions
SSRN
Focusing on the art market, where auction houses act as brokers between art sellers and buyers, we investigate whether more experienced brokers achieve better performance as information providers. We use a unique data set of auctions of Italian paintings in various houses around the world, and we measure experience as the number of times an auctioneer has auctioned the artworks of a certain artist in a given location. We find that more experienced auction houses (i) are more likely to sell and (ii) provide more precise pre-sale estimates. These findings suggest that experience plays an important role for brokers to reduce illiquidity and opacity in markets with asymmetric information.
SSRN
Focusing on the art market, where auction houses act as brokers between art sellers and buyers, we investigate whether more experienced brokers achieve better performance as information providers. We use a unique data set of auctions of Italian paintings in various houses around the world, and we measure experience as the number of times an auctioneer has auctioned the artworks of a certain artist in a given location. We find that more experienced auction houses (i) are more likely to sell and (ii) provide more precise pre-sale estimates. These findings suggest that experience plays an important role for brokers to reduce illiquidity and opacity in markets with asymmetric information.
Fast Lower and Upper Estimates for the Price of Constrained Multiple Exercise American Options by Single Pass Lookahead Search and Nearest-Neighbor Martingale
arXiv
arXiv
This article presents fast lower and upper estimates for a large class of options: the class of constrained multiple exercise American options. Typical options in this class are swing options with volume and timing constraints, and passport options with multiple lookback rights. The lower estimate algorithm uses the artificial intelligence method of lookahead search. The upper estimate algorithm uses the dual approach to option pricing on a nearest-neighbor basis for the martingale space. Probabilistic convergence guarantees are provided. Several numerical examples illustrate the approaches including a swing option with four constraints, and a passport option with 16 constraints.
Firms Default Prediction with Machine Learning
arXiv
arXiv
Academics and practitioners have studied over the years models for predicting firms bankruptcy, using statistical and machine-learning approaches. An earlier sign that a company has financial difficulties and may eventually bankrupt is going in \emph{default}, which, loosely speaking means that the company has been having difficulties in repaying its loans towards the banking system. Firms default status is not technically a failure but is very relevant for bank lending policies and often anticipates the failure of the company. Our study uses, for the first time according to our knowledge, a very large database of granular credit data from the Italian Central Credit Register of Bank of Italy that contain information on all Italian companies' past behavior towards the entire Italian banking system to predict their default using machine-learning techniques. Furthermore, we combine these data with other information regarding companies' public balance sheet data. We find that ensemble techniques and random forest provide the best results, corroborating the findings of Barboza et al. (Expert Syst. Appl., 2017).
Hedging the Art Market: Creating Art Derivatives
SSRN
A number of inefficiencies in the art market stress the fact that art remains a highly risky investment. The art market is characterized by high illiquidity, inefficient market information, high transaction costs, long transaction time and the absence of a hedging mechanism. Therefore, unlike investments in other sectors, investors cannot calculate the risk and return profile of art. More importantly, this currently makes it very difficult to hedge, or protect against possible losses. Applying a hedging strategy to art will bring the liquidity and regulation needed as well as stimulate future investment.
SSRN
A number of inefficiencies in the art market stress the fact that art remains a highly risky investment. The art market is characterized by high illiquidity, inefficient market information, high transaction costs, long transaction time and the absence of a hedging mechanism. Therefore, unlike investments in other sectors, investors cannot calculate the risk and return profile of art. More importantly, this currently makes it very difficult to hedge, or protect against possible losses. Applying a hedging strategy to art will bring the liquidity and regulation needed as well as stimulate future investment.
How does Regulatory Pressure Shock Affect Firms’ Risk-Taking Behavior? Theory and Evidence
SSRN
We explore the impact of regulatory pressure shock on the risk-taking behavior of financial institutions. We develop a portfolio-choice model to investigate the relationship between firm’s capital adequacy and risk-taking under a risk-based (or non-risk-based) capital regulation and examine how a regulatory reform influences this relationship. The model predicts that either all financial institutions reduce their risk-taking, or there exists a capital-adequacy threshold below which risk-taking increases as regulation becomes stricter. The Chinese risk-oriented solvency regulatory reform in the insurance sector provides a unique natural experiment to test our theory. In 2015, each insurer in China was required to report its solvency ratios under both the original non-risk-based and the new risk-based regulatory systems. The difference between the two solvency ratios produces an exogenous and insurer-specific measure of the change in regulatory pressure that occurred due to the reform. Consistent with our theoretical predictions, we find that increasing regulatory pressure induces greater risk-taking for less capital-adequate insurers, an unintended consequence of the regulatory reform. We show that increasing the penalties of insolvency, increasing the risk sensitivity of capital requirements, and reinforcing the qualitative risk assessment are effective remedies for this backfiring problem.
SSRN
We explore the impact of regulatory pressure shock on the risk-taking behavior of financial institutions. We develop a portfolio-choice model to investigate the relationship between firm’s capital adequacy and risk-taking under a risk-based (or non-risk-based) capital regulation and examine how a regulatory reform influences this relationship. The model predicts that either all financial institutions reduce their risk-taking, or there exists a capital-adequacy threshold below which risk-taking increases as regulation becomes stricter. The Chinese risk-oriented solvency regulatory reform in the insurance sector provides a unique natural experiment to test our theory. In 2015, each insurer in China was required to report its solvency ratios under both the original non-risk-based and the new risk-based regulatory systems. The difference between the two solvency ratios produces an exogenous and insurer-specific measure of the change in regulatory pressure that occurred due to the reform. Consistent with our theoretical predictions, we find that increasing regulatory pressure induces greater risk-taking for less capital-adequate insurers, an unintended consequence of the regulatory reform. We show that increasing the penalties of insolvency, increasing the risk sensitivity of capital requirements, and reinforcing the qualitative risk assessment are effective remedies for this backfiring problem.
How to Deal with Small Data Sets in Machine Learning: An Analysis on the CAT Bond Market
SSRN
This study compares state-of-the-art regression-based models to machine learning methods in terms of forecasting performance in asset pricing on a small data set. The performance comparison is conducted on the market for CAT bonds, where we use a large sample of CAT bond issues to forecast risk premia. First, we evaluate the performance of regression models based on the literature. We then test whether the accuracy of those models can be improved through different variable selection algorithms or penalization methods. Afterwards, we use the machine learning methods random forest and neural networks to forecast CAT bond premia. We obtain three main results. First, the application of selection and penalization methods to linear regression models yields only minor differences in forecasting performance. Second, random forest outperforms regression models in terms of forecasting performance. Third, machine learning methods perform quite well on a relatively small data set.
SSRN
This study compares state-of-the-art regression-based models to machine learning methods in terms of forecasting performance in asset pricing on a small data set. The performance comparison is conducted on the market for CAT bonds, where we use a large sample of CAT bond issues to forecast risk premia. First, we evaluate the performance of regression models based on the literature. We then test whether the accuracy of those models can be improved through different variable selection algorithms or penalization methods. Afterwards, we use the machine learning methods random forest and neural networks to forecast CAT bond premia. We obtain three main results. First, the application of selection and penalization methods to linear regression models yields only minor differences in forecasting performance. Second, random forest outperforms regression models in terms of forecasting performance. Third, machine learning methods perform quite well on a relatively small data set.
ICO vs. Equity Financing Under Imperfect, Complex and Asymmetric Information
SSRN
This paper offers a model of a firm that raises funds for financing an innovative business project and choses between ICO (initial coin offering) and equity financing. The model is based on information problems associated with both ICO and equity financing well documented in literature. The model provides several implications that have not yet been tested. For example we find that the message complexity can be benefitial for firms conducting ICOs. Also high-quality projects can use ICO as a signal of quality. Thirdly the average size of projects undertaking equity financing is larger than that of firms conducting ICO.
SSRN
This paper offers a model of a firm that raises funds for financing an innovative business project and choses between ICO (initial coin offering) and equity financing. The model is based on information problems associated with both ICO and equity financing well documented in literature. The model provides several implications that have not yet been tested. For example we find that the message complexity can be benefitial for firms conducting ICOs. Also high-quality projects can use ICO as a signal of quality. Thirdly the average size of projects undertaking equity financing is larger than that of firms conducting ICO.
Institutional Holdings, Investment Opportunities and Dividend Policy
SSRN
This paper examines the relationship between institutional holdings and dividend policy by jointly considering investment style and firms’ growth opportunities. It helps to resolve the apparent low-dividend-preference puzzle in which institutional investors have higher holdings in dividend-paying firms, but among dividend payers, prefer firms that pay low dividends. We find that, controlling for style, institutional investors’ preferences for dividends are based on whether payout levels are consistent with firms’ needs to fund growth opportunities. High payout is preferred for firms with low growth opportunities, and low or no payout is preferred for firms with high growth opportunities. The results enhance our understanding of payout preferences of institutions by demonstrating the interactions of investment opportunities and investing style with respect to institutional investors’ payout preferences.
SSRN
This paper examines the relationship between institutional holdings and dividend policy by jointly considering investment style and firms’ growth opportunities. It helps to resolve the apparent low-dividend-preference puzzle in which institutional investors have higher holdings in dividend-paying firms, but among dividend payers, prefer firms that pay low dividends. We find that, controlling for style, institutional investors’ preferences for dividends are based on whether payout levels are consistent with firms’ needs to fund growth opportunities. High payout is preferred for firms with low growth opportunities, and low or no payout is preferred for firms with high growth opportunities. The results enhance our understanding of payout preferences of institutions by demonstrating the interactions of investment opportunities and investing style with respect to institutional investors’ payout preferences.
Interest and Credit Risk Management in German Banks: Evidence From a Quantitative Survey
SSRN
Using unique data of a survey among small and medium-sized German banks, we analyze various aspects of risk management over a short-term and medium-term horizon. We especially analyze the effect of a 200-bp increase in the interest level. We find that, in the first year, the impairments of banks' bond portfolios are much larger than the reductions in their net interest income, that banks attenuate the resulting write-downs by liquidating hidden reserves and that banks which use interest derivatives have lower impairments in their bond portfolios. In addition, we find that banks' exposures to interest rate risk and to credit risk are remunerated, that banks' try to stabilize the mid-term net interest margin with exposure to interest rate risk and that they act as if they have a risk budget which they allocate either to interest rate risk or credit risk.
SSRN
Using unique data of a survey among small and medium-sized German banks, we analyze various aspects of risk management over a short-term and medium-term horizon. We especially analyze the effect of a 200-bp increase in the interest level. We find that, in the first year, the impairments of banks' bond portfolios are much larger than the reductions in their net interest income, that banks attenuate the resulting write-downs by liquidating hidden reserves and that banks which use interest derivatives have lower impairments in their bond portfolios. In addition, we find that banks' exposures to interest rate risk and to credit risk are remunerated, that banks' try to stabilize the mid-term net interest margin with exposure to interest rate risk and that they act as if they have a risk budget which they allocate either to interest rate risk or credit risk.
Investment Returns and Economic Fundamentals in International Art Markets
SSRN
Works of art are neither easily tradable across borders, nor evaluated according to globally identical standards. We examine geographical segmentation and its effects on price formation and returns in the international art auction market. We find (i) a close connection between the country of sale and the type (e.g., nationality) of artworks sold; (ii) substantial international variation in average returns to art investments over the period 1971-2007; (iii) an impact of both global and local GDP growth and equity returns on national art market returns. Local fundamentals have not lost importance over time, despite increased economic integration (especially between the EU countries). Yet, country-specific economic factors matter less in determining the auction outcomes for high-end art. Our findings suggest the continuing importance of international demand differences in shaping the global art market, at least outside the top segment.
SSRN
Works of art are neither easily tradable across borders, nor evaluated according to globally identical standards. We examine geographical segmentation and its effects on price formation and returns in the international art auction market. We find (i) a close connection between the country of sale and the type (e.g., nationality) of artworks sold; (ii) substantial international variation in average returns to art investments over the period 1971-2007; (iii) an impact of both global and local GDP growth and equity returns on national art market returns. Local fundamentals have not lost importance over time, despite increased economic integration (especially between the EU countries). Yet, country-specific economic factors matter less in determining the auction outcomes for high-end art. Our findings suggest the continuing importance of international demand differences in shaping the global art market, at least outside the top segment.
L\'evy-Ito Models in Finance
arXiv
arXiv
We propose a class of financial models in which the prices of assets are L\'evy-Ito processes driven by Brownian motion and a dynamic Poisson random measure. Each such model consists of a pricing kernel, a money market account, and one or more risky assets. The Poisson random measure is associated with an $n$-dimensional L\'evy process. We show that the excess rate of return of a risky asset in a pure-jump model is given by an integral of the product of a term representing the riskiness of the asset and a term representing the level of market risk aversion. The integral is over the state space of the Poisson random measure and is taken with respect to the L\'evy measure associated with the $n$-dimensional L\'evy process. The resulting framework is applied to a variety of different asset classes, allowing one to construct new models as well as non-trivial generalizations of familiar models.
Manager Sentiment, Deal Characteristics, and Takeover Performance
SSRN
Literature has presented extensive discussion about the driving forces of takeover activities including investor sentiment, liquidity, and fundamental shocks. We examine how manager sentiment constructed on the basis of textual analysis of 10-Ks and 10-Qs, affect takeover characteristics and long-term performance. We find that manager sentiment has a strong positive predictive power for takeover waves. Firms with high manager sentiment tend to acquire large and private targets, complete deals with large size, complex payment structure, and high bidding premium. Manager sentiment decreases the quality of takeover deals and long-term performance.
SSRN
Literature has presented extensive discussion about the driving forces of takeover activities including investor sentiment, liquidity, and fundamental shocks. We examine how manager sentiment constructed on the basis of textual analysis of 10-Ks and 10-Qs, affect takeover characteristics and long-term performance. We find that manager sentiment has a strong positive predictive power for takeover waves. Firms with high manager sentiment tend to acquire large and private targets, complete deals with large size, complex payment structure, and high bidding premium. Manager sentiment decreases the quality of takeover deals and long-term performance.
Nonperforming Loans in BRICS Nations: Determinants and Macroeconomic Impact
SSRN
The issue of Nonperforming loan is considered as a serious threat towards the banking soundness of a country. Nonperforming loans are those loans which cease to generate principle and interest and create a negative impact on the performance of banks. There are host of factors which effect nonperforming loans which include both banking and macroeconomic variables. This study tries to study the impact of macroeconomic determinants on the Nonperforming loans of BRICS countries covering the period from 2000-2016. BRICS bloc is considered for study as various previous studies shows that trading blocs also get affected by inter countries nonperforming loans issues. This study uses dynamic panel data approach for analysis using Fully Modified Ordinary least square model along with Co integration analysis and for robustness checks this model incorporates fixed and random ordinary least square method. The outcome of this paper shows that unemployment has a positive relation with nonperforming loans whereas growth and financial soundness of a country has a negative relation with nonperforming loans. Savings by household also has an inverse relation with nonperforming loans like inflation rate which shows a negative relation with default loans.
SSRN
The issue of Nonperforming loan is considered as a serious threat towards the banking soundness of a country. Nonperforming loans are those loans which cease to generate principle and interest and create a negative impact on the performance of banks. There are host of factors which effect nonperforming loans which include both banking and macroeconomic variables. This study tries to study the impact of macroeconomic determinants on the Nonperforming loans of BRICS countries covering the period from 2000-2016. BRICS bloc is considered for study as various previous studies shows that trading blocs also get affected by inter countries nonperforming loans issues. This study uses dynamic panel data approach for analysis using Fully Modified Ordinary least square model along with Co integration analysis and for robustness checks this model incorporates fixed and random ordinary least square method. The outcome of this paper shows that unemployment has a positive relation with nonperforming loans whereas growth and financial soundness of a country has a negative relation with nonperforming loans. Savings by household also has an inverse relation with nonperforming loans like inflation rate which shows a negative relation with default loans.
Pitching Research for Engagement and Impact â€" A Simple Tool and Illustrative Examples
SSRN
Using Faff’s (2015, 2019) pitching research template as a base (first-phase scholarly pitch), Faff and Kastelle (2016) develop a research pitch tool targeting non-academic external stakeholders/end users. The “pitching research for engagement and impact†(PR4EI) second-phase pitch augments the original tool, retaining its underlying philosophy. The current paper formally presents the PR4EI framework and illustrates the approach with four paired examples from diverse settings, namely: international finance; business model evolution; auditing; and organisational behaviour.
SSRN
Using Faff’s (2015, 2019) pitching research template as a base (first-phase scholarly pitch), Faff and Kastelle (2016) develop a research pitch tool targeting non-academic external stakeholders/end users. The “pitching research for engagement and impact†(PR4EI) second-phase pitch augments the original tool, retaining its underlying philosophy. The current paper formally presents the PR4EI framework and illustrates the approach with four paired examples from diverse settings, namely: international finance; business model evolution; auditing; and organisational behaviour.
Public Comment on IOSCO Report: Leverage
SSRN
Following the IOSCO studies, the metrics that identify leverage, for also addressing the comparability of certain indicators across funds, subset of funds and at a global level, depend on the goals of the analysis and on the accounting principles and standards. For comparison purposes, leverage should also be able to consider: (i) the granularity of the assets, the concentration of the holdings and the percentage of long and short positions that allow the derivation of the Net Asset Value; (ii) the effects of changes in market factors; (iii) the historical correlations of the future price movements for the related instruments or underlying reference assets, also in times of stress for some market factors.
SSRN
Following the IOSCO studies, the metrics that identify leverage, for also addressing the comparability of certain indicators across funds, subset of funds and at a global level, depend on the goals of the analysis and on the accounting principles and standards. For comparison purposes, leverage should also be able to consider: (i) the granularity of the assets, the concentration of the holdings and the percentage of long and short positions that allow the derivation of the Net Asset Value; (ii) the effects of changes in market factors; (iii) the historical correlations of the future price movements for the related instruments or underlying reference assets, also in times of stress for some market factors.
Random Walk Theory and the Weak-Form Efficiency of the US Art Auction Prices
SSRN
We perform variance ratio tests based on non-parametric methods to detect the size of the random walk component of the US art auction prices. The past 134 years of the US art prices exhibit large transitory component (72%) and based on this, the random walk hypothesis does not hold. However, possibly due to sparse data before 1935 or due to institutional changes of the art market after World War II, we detect structural breakpoints and find that the random walk hypothesis and the weak-form efficiency of the US art market cannot be rejected at least for the past 64 years.
SSRN
We perform variance ratio tests based on non-parametric methods to detect the size of the random walk component of the US art auction prices. The past 134 years of the US art prices exhibit large transitory component (72%) and based on this, the random walk hypothesis does not hold. However, possibly due to sparse data before 1935 or due to institutional changes of the art market after World War II, we detect structural breakpoints and find that the random walk hypothesis and the weak-form efficiency of the US art market cannot be rejected at least for the past 64 years.
Real-Time Forecasts of Auction Prices
SSRN
This paper investigates the informational content of aggregate prices in the fine arts auction market. A Mixed Data Sampling (MIDAS) modeling approach is proposed to forecast year-end art prices, using higher frequency variables related to the stock and bond markets and to art market sentiment. It takes about six months for art prices to incorporate information contained in the price of Sotheby's stock. Market sentiment variables such as trading volume have better explanatory power in the short-term. These findings suggest that art market participants react with a delay to information contained in stock market returns, so that information diffuses only slowly into art prices.
SSRN
This paper investigates the informational content of aggregate prices in the fine arts auction market. A Mixed Data Sampling (MIDAS) modeling approach is proposed to forecast year-end art prices, using higher frequency variables related to the stock and bond markets and to art market sentiment. It takes about six months for art prices to incorporate information contained in the price of Sotheby's stock. Market sentiment variables such as trading volume have better explanatory power in the short-term. These findings suggest that art market participants react with a delay to information contained in stock market returns, so that information diffuses only slowly into art prices.
Reconsidering Psychic Return in Art Investments
SSRN
Measuring the psychic return of art investments is a debated issue in Cultural economics. Several works suggest Jensen’s alpha as a measure of the psychic return. Since the Jensen’s alpha is defined in the CAPM framework, its uncritical application as a measure of the psychic return may be problematic when the CAPM hypotheses do not hold. Applying an opportunity cost framework and the analytical tools of portfolio theory, we propose a new psychic return measure, which is not affected by the same issues as Jensen’s alpha. Psychic return estimates based on our measure are provided for several art market indexes as an empirical application.
SSRN
Measuring the psychic return of art investments is a debated issue in Cultural economics. Several works suggest Jensen’s alpha as a measure of the psychic return. Since the Jensen’s alpha is defined in the CAPM framework, its uncritical application as a measure of the psychic return may be problematic when the CAPM hypotheses do not hold. Applying an opportunity cost framework and the analytical tools of portfolio theory, we propose a new psychic return measure, which is not affected by the same issues as Jensen’s alpha. Psychic return estimates based on our measure are provided for several art market indexes as an empirical application.
Residential Real Estate Return, Risk and Portfolio Building in Chinese Cities
SSRN
In this paper, we build up a portfolio in the Chinese residential real estate market. We separate 35 big cities in China into 3 groups with different criteria. Then we build portfolios for these groups, by comparing the efficient frontier and Sharpe ratio with the portfolio of full samples. We find out the most suitable criteria to be the Real Housing Price Increase Rate. Then we choose cities in the different groups together to find out the portfolio which has a high Sharpe Ratio with limited cities number. This means the real estate company could invest in limited cities to get a similar portfolio performance with the full area. We test if this method in other parts of China, and the result shows this method could also work well. Our research has valuable meaning for both investors and policymakers.
SSRN
In this paper, we build up a portfolio in the Chinese residential real estate market. We separate 35 big cities in China into 3 groups with different criteria. Then we build portfolios for these groups, by comparing the efficient frontier and Sharpe ratio with the portfolio of full samples. We find out the most suitable criteria to be the Real Housing Price Increase Rate. Then we choose cities in the different groups together to find out the portfolio which has a high Sharpe Ratio with limited cities number. This means the real estate company could invest in limited cities to get a similar portfolio performance with the full area. We test if this method in other parts of China, and the result shows this method could also work well. Our research has valuable meaning for both investors and policymakers.
SHIFT: A Highly Realistic Financial Market Simulation Platform
arXiv
arXiv
This paper presents a new financial market simulator that may be used as a tool in both industry and academia for research in market microstructure. It allows multiple automated traders and/or researchers to simultaneously connect to an exchange-like environment, where they are able to asynchronously trade several financial assets at the same time. In its current iteration, this order-driven market implements the basic rules of U.S. equity markets, supporting both market and limit orders, and executing them in a first-in-first-out fashion. We overview the system architecture and we present possible use cases. We demonstrate how a set of automated agents is capable of producing a price process with characteristics similar to the statistics of real price from financial markets. Finally, we detail a market stress scenario and we draw, what we believe to be, interesting conclusions about crash events.
Sentiment and Art Prices
SSRN
We hypothesize the existence of a slow-moving fad component in art prices. Using unique panel survey data on art market participants’ confidence levels in the outlook for a set of artists, we find that sentiment indeed predicts short-term returns.
SSRN
We hypothesize the existence of a slow-moving fad component in art prices. Using unique panel survey data on art market participants’ confidence levels in the outlook for a set of artists, we find that sentiment indeed predicts short-term returns.
Social Inclusion and Financial Inclusion: International Evidence
SSRN
This paper investigates the association between social inclusion and financial inclusion. Social inclusion and financial inclusion are two major development policy agenda in many countries, and the association between them has received little attention in the policy and academic literature. Using correlation analysis, the findings reveal a positive and significant correlation between social inclusion and financial inclusion for Asian countries, Middle Eastern countries and African countries while the correlation between social inclusion and financial inclusion is negative for European countries. The findings also show that European and Asian economies experience higher levels of social inclusion and account ownership in a formal financial institution while African countries and Middle Eastern countries experience lower levels of social inclusion and account ownership. The implication of the findings is that some socially inclusive societies tend to enjoy greater financial inclusion while other socially inclusive societies may experience lower financial inclusion. The study provides insights for researchers, decision makers, and practitioners to understand the association between financial and social inclusion.
SSRN
This paper investigates the association between social inclusion and financial inclusion. Social inclusion and financial inclusion are two major development policy agenda in many countries, and the association between them has received little attention in the policy and academic literature. Using correlation analysis, the findings reveal a positive and significant correlation between social inclusion and financial inclusion for Asian countries, Middle Eastern countries and African countries while the correlation between social inclusion and financial inclusion is negative for European countries. The findings also show that European and Asian economies experience higher levels of social inclusion and account ownership in a formal financial institution while African countries and Middle Eastern countries experience lower levels of social inclusion and account ownership. The implication of the findings is that some socially inclusive societies tend to enjoy greater financial inclusion while other socially inclusive societies may experience lower financial inclusion. The study provides insights for researchers, decision makers, and practitioners to understand the association between financial and social inclusion.
Speculative Trading and Bubbles: Evidence from the Art Market
SSRN
The art market is subject to booms and busts in both prices and volume, which are difficult to reconcile with models where agents trade to consume. This paper shows that: (i) a high trading volume coincides with higher prices and more speculative trades, (ii) a high volume predicts negative returns, especially in the most volatile art schools, (iii) a substantial increase in transaction costs decreases art prices and can destroy the return-volume relation, and (iv) short-term transactions underperform and are riskier than long-term transactions. The evidence is consistent with a resale option model of speculative trading where the impossibility to sell short embeds a bubble component in prices. This paper suggests that speculative trading can generate significant price bubbles, even when trading costs are huge.
SSRN
The art market is subject to booms and busts in both prices and volume, which are difficult to reconcile with models where agents trade to consume. This paper shows that: (i) a high trading volume coincides with higher prices and more speculative trades, (ii) a high volume predicts negative returns, especially in the most volatile art schools, (iii) a substantial increase in transaction costs decreases art prices and can destroy the return-volume relation, and (iv) short-term transactions underperform and are riskier than long-term transactions. The evidence is consistent with a resale option model of speculative trading where the impossibility to sell short embeds a bubble component in prices. This paper suggests that speculative trading can generate significant price bubbles, even when trading costs are huge.
Star Artists and Herding in Fine Arts’ Market: Theory and Empirical Evidence
SSRN
This paper uses information cascades theory to analyze the art market. It focus on the art stars, explaining the phenomenon that in the art market a small fraction of artists accounts for most of the trade and dominate the financial activity. We analyze fine art auction data. In particular, we draw a Lorenz-curve for the distribution of auction volume (number of works times auction price) in three art market segments. Our auction data demonstrates that a relatively small fraction of artists account for a large portion of the art auction volume. We provide empirical evidence for our theory of herding behavior in fine arts markets. Our data shows that historical auction performance of an artist is significantly more influential in determining the artist’s success than the quality of her work. In particular, our theory and empirical evidence suggests that contemporary artists and less-established ones are subject to more herding behavior than 400 highest ranked artists.
SSRN
This paper uses information cascades theory to analyze the art market. It focus on the art stars, explaining the phenomenon that in the art market a small fraction of artists accounts for most of the trade and dominate the financial activity. We analyze fine art auction data. In particular, we draw a Lorenz-curve for the distribution of auction volume (number of works times auction price) in three art market segments. Our auction data demonstrates that a relatively small fraction of artists account for a large portion of the art auction volume. We provide empirical evidence for our theory of herding behavior in fine arts markets. Our data shows that historical auction performance of an artist is significantly more influential in determining the artist’s success than the quality of her work. In particular, our theory and empirical evidence suggests that contemporary artists and less-established ones are subject to more herding behavior than 400 highest ranked artists.
The Art Market: What Do We Know About Returns?
SSRN
We examine the annual returns based on auction data for two groups of artists (Surrealists and Impressionists) and two individual artists (Picasso and Renoir) using hedonic pricing models in combination with a wild bootstrap statistical technique. With this approach we estimate confidence intervals for such returns; we also estimate confidence intervals for the correlations with returns of other type of assets, and risk-return metrics.
SSRN
We examine the annual returns based on auction data for two groups of artists (Surrealists and Impressionists) and two individual artists (Picasso and Renoir) using hedonic pricing models in combination with a wild bootstrap statistical technique. With this approach we estimate confidence intervals for such returns; we also estimate confidence intervals for the correlations with returns of other type of assets, and risk-return metrics.
The Capital Asset Pricing Model (CAPM) Applied to Paintings
SSRN
The Capital Asset Pricing Model (CAPM) has been used in a number of studies to explore the features of the art market (or individual artists). We claim that such studies have been based on unsuitable estimates of art market returns in the context of the CAPM methodology. The CAPM calls for employing total returns whereas most art-related studies rely on return estimates based on the time-dummies of hedonic pricing models. This choice is conceptually flawed since it is based on an ideal or average painting whose characteristics do not change overtime, and therefore, it does not capture total returns. We also claim that most indexes used in previous studies as proxy for the market are not able to capture the dynamics of the art market. These two observations call into question at least some of the findings of earlier researchers. Finally, we illustrate these points with several examples using actual auction prices for a group of surrealist artists. We also advance some proposals to overcome the above-mentioned shortcomings.
SSRN
The Capital Asset Pricing Model (CAPM) has been used in a number of studies to explore the features of the art market (or individual artists). We claim that such studies have been based on unsuitable estimates of art market returns in the context of the CAPM methodology. The CAPM calls for employing total returns whereas most art-related studies rely on return estimates based on the time-dummies of hedonic pricing models. This choice is conceptually flawed since it is based on an ideal or average painting whose characteristics do not change overtime, and therefore, it does not capture total returns. We also claim that most indexes used in previous studies as proxy for the market are not able to capture the dynamics of the art market. These two observations call into question at least some of the findings of earlier researchers. Finally, we illustrate these points with several examples using actual auction prices for a group of surrealist artists. We also advance some proposals to overcome the above-mentioned shortcomings.
The Iconic Boom in Modern Russian Art
SSRN
Motivated by the fast growth of personal wealth in emerging economies like Russia, we investigate the investment performance of modern Russian art. A hedonic analysis of more than 50,000 art transactions results in a geometric average return of 3.97%, in real USD terms, between 1967 and 2007. Our Russian art index shows an impressive annualized return of 12.37% since 1997. This is roughly double the average yearly appreciation of a global art market index over the same period. Especially art from the nineteenth century has performed well. The returns on Russian art correlate positively with the returns on global equities, gold, and (especially) London real estate. Also, they seem to be affected more by trends in oil prices than are global art prices. Our results illustrate how the new wealth created in fast-developing economies has its impact on the demand for art from these countries, which reflects a home bias in taste.
SSRN
Motivated by the fast growth of personal wealth in emerging economies like Russia, we investigate the investment performance of modern Russian art. A hedonic analysis of more than 50,000 art transactions results in a geometric average return of 3.97%, in real USD terms, between 1967 and 2007. Our Russian art index shows an impressive annualized return of 12.37% since 1997. This is roughly double the average yearly appreciation of a global art market index over the same period. Especially art from the nineteenth century has performed well. The returns on Russian art correlate positively with the returns on global equities, gold, and (especially) London real estate. Also, they seem to be affected more by trends in oil prices than are global art prices. Our results illustrate how the new wealth created in fast-developing economies has its impact on the demand for art from these countries, which reflects a home bias in taste.
The Impact of Skin in the Game on Bank Behavior in the Securitization Market
SSRN
Based on European RMBS deals with 24 million quarterly loan observations, we examine the effect of risk retention on bank behavior. Using OLS, propensity score matching, and instrumental variable regressions, we examine why retention deals perform better. Analyzing monitoring effort and the workout process, we find that the probability of rating updates or collateral revaluations is higher, and the rating quality is better. Retention loans have a lower probability of becoming non-performing, a lower delinquency amount, and a shorter time in arrears. Moreover, non-performing and defaulted retention loans are more likely to recover. We observe that total losses are lower for deals with retention, which are driven by lower default rates, lower exposures at default, and higher recovery rates. Overall, our results suggest that retention reduces moral hazard and incentivizes banks to exert higher effort, which results in superior securitized asset performance.
SSRN
Based on European RMBS deals with 24 million quarterly loan observations, we examine the effect of risk retention on bank behavior. Using OLS, propensity score matching, and instrumental variable regressions, we examine why retention deals perform better. Analyzing monitoring effort and the workout process, we find that the probability of rating updates or collateral revaluations is higher, and the rating quality is better. Retention loans have a lower probability of becoming non-performing, a lower delinquency amount, and a shorter time in arrears. Moreover, non-performing and defaulted retention loans are more likely to recover. We observe that total losses are lower for deals with retention, which are driven by lower default rates, lower exposures at default, and higher recovery rates. Overall, our results suggest that retention reduces moral hazard and incentivizes banks to exert higher effort, which results in superior securitized asset performance.
The Myth of Machine Learning Overfitting (Seminar Slides)
SSRN
Scientific disciplines have successfully applied Machine Learning (ML) methods for decades. In recent years, investment managers have begun to replace or complement classical statistical methods (e.g., Econometrics) with modern statistical methods (e.g. ML).A popular belief is that ML is more prone to overfitting than Econometrics. In reality, Econometric methods are more likely to overfit due to their: (a) reliance on train-set error estimates, and (b) assumption that only one trial has taken place.Econometric overfitting is a leading cause of the current “false discoveries†crisis. When used properly, ML techniques are designed to prevent overfitting.
SSRN
Scientific disciplines have successfully applied Machine Learning (ML) methods for decades. In recent years, investment managers have begun to replace or complement classical statistical methods (e.g., Econometrics) with modern statistical methods (e.g. ML).A popular belief is that ML is more prone to overfitting than Econometrics. In reality, Econometric methods are more likely to overfit due to their: (a) reliance on train-set error estimates, and (b) assumption that only one trial has taken place.Econometric overfitting is a leading cause of the current “false discoveries†crisis. When used properly, ML techniques are designed to prevent overfitting.
The Winner's Curse on Art Markets
SSRN
We investigate the effect of overreaction in the fine art market. Using a unique sample of auction prices of modern prints, we define an overvalued (undervalued) print as a print that was bought for a price above (below) its high (low) auction pricing estimate. Based on the overreaction hypothesis, we predict that overvalued (undervalued) prints generate a negative (positive) excess return at a subsequent sale. Our empirical findings confirm our expectations. We report that prints that were bought for a price 10 percent above (below) its high (low) pricing estimate generate a positive (negative) excess return of 12 percent (17 percent) after controlling for the general price movement on the prints market. The price correction for overvalued (undervalued) prints is more pronounced during recessions (expansions).
SSRN
We investigate the effect of overreaction in the fine art market. Using a unique sample of auction prices of modern prints, we define an overvalued (undervalued) print as a print that was bought for a price above (below) its high (low) auction pricing estimate. Based on the overreaction hypothesis, we predict that overvalued (undervalued) prints generate a negative (positive) excess return at a subsequent sale. Our empirical findings confirm our expectations. We report that prints that were bought for a price 10 percent above (below) its high (low) pricing estimate generate a positive (negative) excess return of 12 percent (17 percent) after controlling for the general price movement on the prints market. The price correction for overvalued (undervalued) prints is more pronounced during recessions (expansions).
Theories of Financial Inclusion
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This article presents several theories of financial inclusion. Financial inclusion is the ease of access to, and the availability of, basic financial services to all members of the population. Financial inclusion means that individuals and businesses have access to useful and affordable financial products and services that meet their needs in a responsible and sustainable way. Financial inclusion practices vary from country to country, and there is need to identify the underlying principles or propositions that can explain the observed variation in financial inclusion practices. These set of principles or propositions are called theories. Financial inclusion theories are explanations for observed financial inclusion practices. The study shows that the ideas and perspectives on financial inclusion can be grouped into theories to facilitate meaningful discussions in the literature. The theories are intended to be useful to researchers, academics and practitioners. The resulting contributions to theory development are useful to the problem-solving process in the global financial inclusion agenda.
SSRN
This article presents several theories of financial inclusion. Financial inclusion is the ease of access to, and the availability of, basic financial services to all members of the population. Financial inclusion means that individuals and businesses have access to useful and affordable financial products and services that meet their needs in a responsible and sustainable way. Financial inclusion practices vary from country to country, and there is need to identify the underlying principles or propositions that can explain the observed variation in financial inclusion practices. These set of principles or propositions are called theories. Financial inclusion theories are explanations for observed financial inclusion practices. The study shows that the ideas and perspectives on financial inclusion can be grouped into theories to facilitate meaningful discussions in the literature. The theories are intended to be useful to researchers, academics and practitioners. The resulting contributions to theory development are useful to the problem-solving process in the global financial inclusion agenda.
Uncertainty, Disagreement and Expert Price Estimates in Art Markets
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The purpose of this study is to test whether the size of the pre-sale price estimate range affects art auction prices and, if so, in what direction. We find that auction house art experts' relative estimate range positively affects realized prices. The effect is robust across the mid- low- and high-end segments of the international sculpture market. Interpreting the art experts' price estimate range as a proxy for the prevailing divergence of investor opinion in the art market, the findings are consistent with disagreement models. This evidence is contradictory to the predictions of the General Auction model and does not lend support to the interpretation of the price estimate range as a proxy only for uncertainty. Moreover, the study gives insight into the price determinants of sculpture using a unique large data set of over 65,000 sculpture sales at international auctions.
SSRN
The purpose of this study is to test whether the size of the pre-sale price estimate range affects art auction prices and, if so, in what direction. We find that auction house art experts' relative estimate range positively affects realized prices. The effect is robust across the mid- low- and high-end segments of the international sculpture market. Interpreting the art experts' price estimate range as a proxy for the prevailing divergence of investor opinion in the art market, the findings are consistent with disagreement models. This evidence is contradictory to the predictions of the General Auction model and does not lend support to the interpretation of the price estimate range as a proxy only for uncertainty. Moreover, the study gives insight into the price determinants of sculpture using a unique large data set of over 65,000 sculpture sales at international auctions.
Unconscionability as a Sword: The Case for an Affirmative Cause of Action
SSRN
Consumers are drowning in a sea of one-sided fine print. To combat contractual overreach, consumers need an arsenal of effective remedies. To that end, the doctrine of unconscionability provides a crucial defense against the inequities of rigid contract enforcement. However, the prevailing view that unconscionability operates merely as a “shield†and not a “sword†leaves countless victims of oppressive contracts unable to assert the doctrine as an affirmative claim. This crippling interpretation betrays unconscionability’s equitable roots and absolves merchants who have already obtained their ill-gotten gains. But this need not be so. Using California consumer credit law as a backdrop, this Note argues that the doctrine of unconscionability must be recrafted into an offensive sword that provides affirmative relief to victims of unconscionable contracts. While some consumers may already assert unconscionability under California’s Consumers Legal Remedies Act, courts have narrowly construed the Act to exempt many forms of consumer credit. As a result, thousands of debtors have remained powerless to challenge their credit terms as unconscionable unless first sued by a creditor. However, this Note explains how a recent landmark ruling by the California Supreme Court has confirmed a novel legal theory that broadly empowers consumersâ€"including debtorsâ€"to assert unconscionability under the State’s Unfair Competition Law. Finally, this Note argues that unconscionability’s historical roots in courts of equityâ€"as well as its treatment by the Uniform Commercial Code and the Restatementsâ€"reveal that courts already possess an inherent equitable power to fashion affirmative remedies against unconscionable contracts under the common law, even absent statutory authorization.
SSRN
Consumers are drowning in a sea of one-sided fine print. To combat contractual overreach, consumers need an arsenal of effective remedies. To that end, the doctrine of unconscionability provides a crucial defense against the inequities of rigid contract enforcement. However, the prevailing view that unconscionability operates merely as a “shield†and not a “sword†leaves countless victims of oppressive contracts unable to assert the doctrine as an affirmative claim. This crippling interpretation betrays unconscionability’s equitable roots and absolves merchants who have already obtained their ill-gotten gains. But this need not be so. Using California consumer credit law as a backdrop, this Note argues that the doctrine of unconscionability must be recrafted into an offensive sword that provides affirmative relief to victims of unconscionable contracts. While some consumers may already assert unconscionability under California’s Consumers Legal Remedies Act, courts have narrowly construed the Act to exempt many forms of consumer credit. As a result, thousands of debtors have remained powerless to challenge their credit terms as unconscionable unless first sued by a creditor. However, this Note explains how a recent landmark ruling by the California Supreme Court has confirmed a novel legal theory that broadly empowers consumersâ€"including debtorsâ€"to assert unconscionability under the State’s Unfair Competition Law. Finally, this Note argues that unconscionability’s historical roots in courts of equityâ€"as well as its treatment by the Uniform Commercial Code and the Restatementsâ€"reveal that courts already possess an inherent equitable power to fashion affirmative remedies against unconscionable contracts under the common law, even absent statutory authorization.
University rankings from the revealed preferences of the applicants
arXiv
arXiv
A methodology is presented to rank universities on the basis of the lists of programmes the students applied for. We exploit a crucial feature of the centralised assignment system to higher education in Hungary: a student is admitted to the first programme where the score limit is achieved. This makes it possible to derive a partial preference order of each applicant. Our approach integrates the information from all students participating in the system, is free of multicollinearity among the indicators, and contains few ad hoc parameters. The procedure is implemented to rank faculties in the Hungarian higher education between 2001 and 2016. We demonstrate that the ranking given by the least squares method has favourable theoretical properties, is robust with respect to the aggregation of preferences, and performs well in practice. The suggested ranking is worth considering as a reasonable alternative to the standard composite indices.
Using Reinforcement Learning in the Algorithmic Trading Problem
arXiv
arXiv
The development of reinforced learning methods has extended application to many areas including algorithmic trading. In this paper trading on the stock exchange is interpreted into a game with a Markov property consisting of states, actions, and rewards. A system for trading the fixed volume of a financial instrument is proposed and experimentally tested; this is based on the asynchronous advantage actor-critic method with the use of several neural network architectures. The application of recurrent layers in this approach is investigated. The experiments were performed on real anonymized data. The best architecture demonstrated a trading strategy for the RTS Index futures (MOEX:RTSI) with a profitability of 66% per annum accounting for commission. The project source code is available via the following link: this http URL
Valuation of Auction Guarantees in the Art Market
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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.
SSRN
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.
Wealth Management for Collectors
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Most high-net-worth individuals hold a portion of wealth in residential real estate and some collecting category. Art is the predominate collecting category of high-net-worth individuals, and this paper investigates the general effects of incorporating art as well as the particular effects of incorporating a client’s art holdings when making wealth-management decisions. New indexes based on transparent like-object market transactions and replicable quantitative methodologies allow for comparisons of the returns from collections and other assets. Individual asset class risks and the correlation of returns among asset classes are important criteria that can be derived from these indexes. We use the Mei Moses® family of fine art indexes as proxies for art-market financial performance. We also include the effects of the S&P/Case-Shiller U.S. Residential Real Estate Index.
SSRN
Most high-net-worth individuals hold a portion of wealth in residential real estate and some collecting category. Art is the predominate collecting category of high-net-worth individuals, and this paper investigates the general effects of incorporating art as well as the particular effects of incorporating a client’s art holdings when making wealth-management decisions. New indexes based on transparent like-object market transactions and replicable quantitative methodologies allow for comparisons of the returns from collections and other assets. Individual asset class risks and the correlation of returns among asset classes are important criteria that can be derived from these indexes. We use the Mei Moses® family of fine art indexes as proxies for art-market financial performance. We also include the effects of the S&P/Case-Shiller U.S. Residential Real Estate Index.
