Time series properties of an artificial stock market

This paper presents results from an experimental computer simulated stock market. In this market artificial intelligence algorithms take on the role of traders. They make predictions about the future, and buy and sell stock as indicated by their expectations of future risk and return. Prices are set endogenously to clear the market. Time series from this market are analyzed from the standpoint of well-known empirical features in real markets. The simulated market is able to replicate several of these phenomenon, including fundamental and technical predictability, volatility persistence, and leptokurtosis. Moreover, agent behavior is shown to be consistent with these features, in that they condition on the variables that are found to be significant in the time series tests. Agents are also able to collectively learn a homogeneous rational expectations equilibrium for certain parameters giving both time series and individual forecast values consistent with the equilibrium parameter values.     

The stock–bond comovements and cross-market trading

We propose an asset pricing model with heterogeneous agents allocating capital to the stock and bond markets to optimize their portfolios, utilizing the dynamic interaction between the two markets. While some agents focus on the stock market and have more expertise in it, the others specialize in the bond market. Based on their comparative advantages in a particular market, heterogeneous agents constantly revise their investment portfolios by taking into account the time-varying stock–bond return comovements and the changing market conditions. Agents׳ collective investment behavior shapes the stock–bond interlinkage, which feedbacks on their subsequent capital allocations. Using monthly US stock and bond data from January 1990 to June 2014, we estimate the vector autoregression model with threshold and Markov switching mechanisms. We find evidence in support of flight-to-quality and show that it is mainly driven by the technical traders who actively sell stocks and buy bonds during periods of high market uncertainty.     

Does Mad Money make the market go mad?

Empirical studies of numerous popular investment advisory services find statistically significant abnormal returns at the time of their broadcast or published investment recommendations. Our analysis of returns and trading volume around stock recommendations aired on charismatic host Jim Cramer's Mad Money program reveals statistical evidence of response to both his buy and sell opinions, with most of the full-day return following an on-air buy recommendation captured by that day's opening price. Trading strategy analysis suggests that individuals with limited funds should be wary of short-term trading to exploit the show's suggestions, while professional investors may be able to exploit buy picks with a contra strategy.     

“Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet

The cryptocurrencies with small market capitalization are often overlooked despite they can potentially be the source of shocks to other cryptocurrencies in the market. To address this caveat, this paper attempts to investigate the spillover effects among 14 cryptocurrencies by employing transfer entropy. Our results suggest that among different types of cryptos, Bitcoin is still the most appropriate instrument for hedging, while Tether (USDT) which have a strong anchor with the US dollar is significantly volatile. Interestingly, we document that the small coins are more likely to be shock creators in the cryptocurrency market. Using the same approach, we further explored the link between gold prices and cryptocurrency prices. The results show that gold could be a good hedging instrument for cryptocurrencies due to its independence. In light of empirical results, it is advisable to carefully consider the coins with small capitalization. Further, investors should conduct portfolio rebalancing by including gold to hedge against the unexpected movement in the cryptocurrency market. Our paper not only contributes in terms of the application of advanced empirical methodology but also provides evidence on idiosyncratic features of the cryptocurrency market.     

Quoted spreads and trade imbalance dynamics in the European Treasury bond market

Using high-frequency transaction data for the three largest European markets (France, Germany and Italy), this paper documents the existence of an asymmetric relationship between market liquidity and trading imbalances: when quoted spreads rise (fall) and liquidity falls (increases) buy (sell) orders tend to prevail. Risk-averse market-makers, with inventory-depletion risk being their main concern, tend to quote wider (narrower) spreads when they think bond appreciation is more (less) likely to occur. It is also found that the probability of being in a specific regime is related to observable bond market characteristics, stock market volatility, macroeconomic releases and liquidity management operations of the monetary authorities.     

Is the secondary loan market valuable to borrowers?

In recent years, the secondary loan market has developed into an over-the-counter market where loans are not only sold but also subsequently traded. This shift away from traditional banking is altering the business of lending. Loan sales are valuable to banks because they free up capital, generate fee-based income and facilitate risk management; but they may be costly to borrowers because they negatively affect bank monitoring incentives. In this paper, however, we argue that there is another potential benefit to borrowers from loan sales. Borrowers with trading loans, in particular those with liquid loans, may “demand” a share of bank benefits from loan sales when they take out new loans as it will be easier for banks to sell these loans afterwards. We investigate this potential benefit of the secondary loan market by comparing the interest rates borrowers pay before their loans start to trade with the interest rates they pay on loans originated post-trading. Our results show that, on average, borrowers pay higher spreads on the loans they take out after the onset of trading on their loans. Importantly, our results also show that borrowers with liquid trading loans are able to borrow at lower interest rates after the onset of trading on their loans. Thus, while the banks’ decision to sell loans may initially impose a cost on borrowers, those whose loans enter the secondary loan market and become liquid benefit from an interest rate discount on their subsequent loans.     

Herding behavior in the cryptocurrency market during COVID-19 pandemic: The role of media coverage

This paper examines herding behavior in the cryptocurrency market during the COVID-19 pandemic using daily data and based on static and regime-switching models. Furthermore, we investigate whether herding behavior is affected by the coronavirus media coverage. Based on a sample of the top-43 cryptocurrencies in terms of market capitalization between 2013 and 2020, we find significant evidence of herding for the entire sample period only during high volatility state. Moreover, during the COVID-19 crisis, results suggest that investors in the cryptocurrency market follow the consensus. Finally, the impact of coronavirus media coverage is significant on herding among investors, explaining such behavior in the cryptocurrency market during the COVID-19 crisis. Our findings explain herding determinants that may help investors avoid such comportment, mainly during the crisis.     

Distribution of stock ratings and analyst recommendation revision

With the implementation of NASD Rule 2711 in 2002, each brokerage firm is now required to publicly disseminate the distribution of stock ratings in each research report. Hence, this paper investigates the relationship between the percentage of buy recommendations and probability of deciding to downgrade or drop coverage of stocks. Our findings suggest that the percentage of buy recommendations can enhance the probability of deciding to downgrade stock ratings and drop coverage of stocks. Furthermore, we find that analysts tend to revise their recommendations downward to hold instead of an unfavorable level. In addition, we find the market tends to heed downgrade decisions of analysts with a higher percentage of buy ratings. This finding is consistent with Barber, Lehavy, McNichols, and Trueman (2006) by applying data at the broker level.This study further investigates the changing dynamic in buy ratio of analysts by partitioning pre and post regulatory reform period. We show that analysts are more likely to revise their ratings to hold and less likely to revise their ratings to sell; in particular after post regulatory reform. Moreover, we observe one key coefficient in the post-Rule period with superior performance in contrast to the pre-Rule period. Compared to the results in the pre-Rule period, the results show that analysts are more likely to revise their ratings to hold and less likely to revise ratings to sell, and more likely to drop coverage of stocks in the post-Rule period. Overall, our findings suggest that the implementation of Rule 2711 will contribute to reduce analysts’ optimistic stock ratings.     

Network analysis on Bitcoin arbitrage opportunities

Many studies have shown that investment in Bitcoin could serve to diversify the stock market. The existing literature offers insight into how arbitrage trading may diminish the risks associated with cryptocurrencies. Using arbitrage data and a novel methodology, this paper uncovers pertinent insights for investors interested in hedging against losses. Evidence points to the dsx, kraken, and bitstamp exchanges as the most attractive for buying Bitcoin and the cexio, bitmarketlt, and coindeal exchanges as the most attractive for selling Bitcoin. We employ network analysis to explore the interrelationships in thirteen cryptocurrency exchanges, providing evidence that kraken and bitstamp are leaders in market-forming trends, while coindeal and dsx serve as intermediary exchanges. Overall, these findings show that investors can mitigate their trading risks by knowing precisely where to buy and sell Bitcoin and which exchanges offer arbitrage opportunities. Using these results, investors can develop long-term and algorithmic trading strategies.     

Illiquidity,transaction cost,and optimal holding period for real estate: Theory and application

Choosing the optimal holding period is an important part of real estate investment decisions, because “when to sell” affects “whether to buy”. This paper presents a theoretical model for such decision making. Our model indicates that the optimal holding period is affected by both systematic and non-systematic factors—market conditions (illiquidity and transaction cost) and property performance (return and return volatility). Other things being equal, higher illiquidity and transaction costs lead to longer holding periods, while higher return volatility implies shorter holding periods. Our empirical application suggests that the optimal holding period based on our model is quite consistent with previous empirical findings. In addition, we find that when illiquidity risk is incorporated the true real estate risk is significantly higher than the conventional risk estimate. Therefore, the current practice of real estate valuation, which is naively borrowed from finance theory, substantially underestimates real estate risk.     

Direct Marketing in Oligopoly

We consider a game in which symmetric manufacturers decide whether to set up sites (e.g., web sites) where consumers can buy their products directly. Following this decision, the manufacturers choose quantities to sell to the retailers, and then the manufacturers with direct‐sales sites and retailers choose quantities to sell to the consumers. We show that since an increase in the number of retailers may drive the direct‐selling manufacturers from the retail market, it may raise the retailers’ profit and reduce social welfare. Finally, we discuss two cases: an oligopolistic wholesale market and a market with price competition and differentiated products.     

中国商业地产的商业模式现状分析

国内的商业地产的商业模式具体分为以下五种,即:整体租赁不售产权的模式,分零租赁不售产权的模式、整体租赁经营零售产权的返租模式、分零租赁经营零售产权的模式、零售零租与整租不售的商业模式等,接下来对这些模式一一进行分析。     

Lottery-like momentum in the cryptocurrency market

Following the methodology of Bali et al. (2011), we construct the lottery-like portfolio based on the maximum return. First, we find that a higher maximum return leads to a higher future return among 64 cryptocurrencies. This phenomenon is called the lottery-like momentum. Controlling for the momentum effect, the lottery-like momentum still exists in the cryptocurrency market. In addition, we find that the major cryptocurrencies—Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC)—are less likely to have extreme positive returns. And the absence of extreme positive returns is persistent.     

Efficiency of temporary equilibria

A temporary equilibrium model of a production economy with various capital markets in which producers maximize the expected utility of cash flows in various periods is considered. Without restricting the price expectation of producers, it is shown that, if contracts to buy or sell goods at future periods can be trated in a market and if the producer's utility functions are increasing in the cash flow of the first period, then the temporary equilibrium allocations are technically efficient. Also, production is technically efficient even in the presence of some quantity constraints on sales of futures contracts which are sufficient for existence of an equilibrium.     

A wavelet-based assessment of market risk: The emerging markets case

The measurement of market risk poses major challenges to researchers and different economic agents. On one hand, it is by now widely recognized that risk varies over time. On the other hand, the risk profile of an investor, in terms of investment horizon, makes it crucial to also assess risk at the frequency level. We propose a novel approach to measuring market risk based on the continuous wavelet transform. Risk is allowed to vary both through time and at the frequency level within a unified framework. In particular, we derive the wavelet counterparts of well-known measures of risk. One is thereby able to assess total risk, systematic risk and the importance of systematic risk to total risk in the time-frequency space. To illustrate the method we consider the emerging markets case over the last twenty years, finding noteworthy heterogeneity across frequencies and over time, which highlights the usefulness of the wavelet approach.     

A non-Walrasian labor market in a monetary model of the business cycle

This paper investigates to what extent a new Keynesian, monetary model with the addition of a microfounded, non-Walrasian labor market solely based on union bargaining is able to replicate key aspects of the business cycle. The presence of a representative union offers an explanation for two features of the cycle. First, it generates an endogenous mechanism which produces persistent responses to both supply and demand shocks. Second, labor unionization reduces the elasticity of marginal costs to output. This leads to lower inflation volatility. Model simulations show that the unionized framework can better reproduce European business cycle data than can a model with a competitive labor market.     

一种电子商务的设计与实现

文章系统论述了世纪惠佳科技有限公司电子商务的设计与实现,该电子商务既支持B-B模式,又满足B-C的要求,实现了客户、供应商和合作伙伴之间的在线交易,相互协作和价值交换,除了在网上交易市场中销与购的活动外,强调交易流程的整体效率与效益的提升。     

我国投资基金业绩的持续性分析

基金业绩的持续性是指业绩优秀的基金以后一段时间继续保持优秀的业绩,而业绩差的基金继续表现出差的业绩。如果基金具有持续性,对于投资者来讲,他们可以买进前期业绩优秀的基金,而卖出前期业绩差的基金,来获取超额收益,投资者不必耗费大量的资金和时间去评价和选择基金经理。本文就基金业绩持续性的研究理论方法进行阐述,并对我国投资基金作实证分析。     

Factor market effects upon product market equilibrium

Conventional duopoly models typically assume agents possess specific conjectures concerning other agents’ behavior. In this paper equilibrium conjectures are endogenous and are a result of a joint factor market and product market equilibrium. Factor markets affect product markets since potential managers or owners of firms engage in product market competition and compete for corporate control in labor or capital markets. The resulting factor and product market joint equilibrium (FPE) endogenizes conjectures and can thus potentially endogenize market structure. This approach provides economic rationales for both Stackelberg and consistent conjectural equilibria. Copyright © 1999 John Wiley & Sons, Ltd.