Frankfurt Artificial Stock Market: a microscopic stock market model with heterogeneous interacting agents in small-world communication networks

We study the relationship between communication network topologies, namely the small-world networks introduced by Watts and Strogatz, and the simulation results of an artificial stock market, here the Frankfurt Artificial Stock Market. Heterogeneous interacting agents communicate their success and trading strategy to their nearest neighbors. A process of information diffusion arises through the adaptive behavior of agents when encountering more successful strategies in their direct neighborhood. We will show that an increasing rewiring probability of the small-world network will lead to higher volatility and distortion within our simulation model. It seems probable that the spatial position of traders within a communication network affects the price building process.     

Asset price and wealth dynamics in a financial market with heterogeneous agents

This paper considers a discrete-time model of a financial market with one risky asset and one risk-free asset, where the asset price and wealth dynamics are determined by the interaction of two groups of agents, fundamentalists and chartists. In each period each group allocates its wealth between the risky asset and the safe asset according to myopic expected utility maximization, but the two groups have heterogeneous beliefs about the price change over the next period: the chartists are trend extrapolators, while the fundamentalists expect that the price will return to the fundamental. We assume that investors’ optimal demand for the risky asset depends on wealth, as a result of CRRA utility. A market maker is assumed to adjust the market price at the end of each trading period, based on excess demand and on changes of the underlying reference price. The model results in a nonlinear discrete-time dynamical system, with growing price and wealth processes, but it is reduced to a stationary system in terms of asset returns and wealth shares of the two groups. It is shown that the long-run market dynamics are highly dependent on the parameters which characterize agents’ behaviour as well as on the initial condition. Moreover, for wide ranges of the parameters a (locally) stable fundamental steady state coexists with a stable ‘non-fundamental’ steady state, or with a stable closed orbit, where only chartists survive in the long run: such cases require the numerical and graphical investigation of the basins of attraction. Other dynamic scenarios include periodic orbits and more complex attractors, where in general both types of agents survive in the long run, with time-varying wealth fractions.     

价值分析者和技术分析者交互作用下的股市价格波动

运用市场上常用的基本价值分析策略和技术分析策略,以适应性信念系统模型为基础,构建了一个非线性演化的价格动力学模型。依此模型模拟的结果表明:基本价值分析策略和技术分析策略的交互行为产生波动集聚现象,适应性信念模型模拟的结果与我国股市实际的数据相似。     

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.     

Evolution of heterogeneous beliefs and asset overvaluation

I analyze a model in which different agents have different non-rational expectations about the future price and cash flows of a risky asset. The beliefs in the society evolve according to a very general class of evolution functions that are monotone; that is if one type has increased its share in the population then all types with higher profit should also have increased their shares. I show that the price of the risky asset converges to the risk-neutral fundamental price even though all agents in the economy are risk-averse. The risky asset thus becomes overvalued as compared to the equilibrium with rational expectations. The overvaluation is a result of the evolution of beliefs and does not rely on such asymmetric assumptions as short-sale constraints or optimistic bias.     

Asset price targeting in an open economy with cognitive limitations: The best for macroeconomic and financial stability?

The choices of policy targets and the formation of agent expectations have been critical issues addressed by monetary policy management since the financial crisis of 2008. This paper evaluates macroeconomic stability in a new Keynesian open economy in which agents experience both cognitive limitations and asset market volatility. The (im)perfect credibility of various monetary policies (e.g., a Taylor-type rule with- or without asset price targeting, strict domestic inflation targeting, strict CPI inflation targeting, and exchange rate peg) may lead agents to react according to their expectation rules, and thus create various degrees of booms and busts in output and inflation. Simulations confirm that a Taylor-type CPI inflation targeting including an asset price target is the best choice. In contrast, the business cycles induced by Keynesian “animal spirits” are enhanced by strict inflation targeting. Furthermore, a credible exchange rate pegging system with an international reserve pooling arrangement can improve social welfare and stability in an open economy, even though its absolute value of the loss function is slightly lower than a Taylor-type CPI inflation targeting including an asset price target.     

Rational asset pricing bubbles and debt constraints

Rational price bubble arises when the price of an asset exceeds the asset’s fundamental value, that is, the present value of future dividend payments. The important result of Santos and Woodford (1997) says that price bubbles cannot exist in equilibrium in the standard dynamic asset pricing model with rational agents facing borrowing constraints as long as assets are in strictly positive supply and the present value of total future resources is finite. This paper explores the possibility of asset price bubbles under endogenous debt constraints induced by limited enforcement of debt repayment. Equilibria with endogenous debt constraints are prone to have infinite present value of total resources. We show that asset price bubbles are likely to exist in such equilibria. Further, we demonstrate that there always exist equilibria with price bubbles on assets in zero supply.     

股票价格低于每股净资产的影响因素分析——来自中国A股上市公司的经验证据

破净指股票价格跌破每股净资产,是股票价格与每股净资产关系的一种极端表现。本文以1 059家A股上市公司为样本,采用修正的Ohlson模型,分组对股价破净的影响因素进行研究。结果发现:对于业绩为正的非ST企业而言,公司规模大、上市时间早、机构投资者持股比例低的国有企业容易破净;ST企业的股票价格虽下跌,但其重组捷径和壳资源改变了投资者的预期,使ST企业不破净或较少破净。     

Disaster risk and preference shifts in a New Keynesian model

In RBC models, disaster risk shocks reproduce countercyclical risk premia but generate an increase in consumption along the recession and asset price fall, through their effects on agents’ preferences (Gourio, 2012). This paper offers a solution to this puzzle by developing a New Keynesian model with such a small but time-varying probability of “disaster”. We show that price stickiness, combined with an EIS smaller than unity, restores procyclical consumption and wages, while preserving countercyclical risk premia, in response to disaster risk shocks. The mechanism then provides a rationale for discount factor first- and second-moment (“uncertainty”) shocks.     

The implications of financial frictions and imperfect knowledge in the estimated DSGE model of the U.S. economy

In this paper, I study how alternative assumptions about expectation formation can modify the implications of financial frictions for the real economy. I incorporate a financial accelerator mechanism into a version of the Smets and Wouters (2007) DSGE framework and explore the properties of the model assuming, on the one hand, complete rationality of expectations and, alternatively, several learning algorithms that differ in terms of the information set used by agents to produce the forecasts. I show that the implications of the financial accelerator for the business cycle may vary depending on the approach to modeling the expectations. The results suggest that the learning scheme based on small forecasting functions is able to amplify the effects of financial frictions relative to the model with Rational Expectations. Specifically, I show that the dynamics of real variables under learning is driven to a significant extent by the time variation of agents’ beliefs about financial sector variables. During periods when agents perceive asset prices as being relatively more persistent, financial shocks lead to more pronounced macroeconomic outcomes. The amplification effect rises as financial frictions become more severe. At the same time, a learning specification in which agents use more information to generate predictions produces very different asset price and investment dynamics. In such a framework, learning cannot significantly alter the real effects of financial frictions implied by the Rational Expectations model.     

Monetary policy and asset prices in an open economy

This paper examines whether central banks should respond to asset price fluctuations in a two-country sticky price model. We compare a monetary policy rule that targets both domestic asset prices and foreign asset prices with several alternative monetary policy rules. This paper shows that this policy rule can produce preferable outcomes because the domestic central bank incorporates important information that both domestic and foreign asset prices possess into its monetary policy. Our model suggests that central banks should consider both domestic and foreign asset prices in a two country framework with asset price fluctuations.     

Margin trade,short sales and financial stability

We model how leveraged trading activities constrained by dynamic funding availability affect financial stability. In the market, customers trade based on the fundamental value of the risky asset and make full payment for their transactions, while speculators take trading position based on margin, which is constantly adjusted by the financier, the fund provider, according to the price volatility. As a result of equilibrium price discontinuity triggered by dynamic margin requirements, trivial shocks to external supply, wealth or fundamental value can be transmitted into asset price crashes or jumps. We find that tightening margin requirements improves (mitigates) the market liquidity in the bull (bear) market, and that imposing short sale constraints helps prevent the price from falling further when the asset is sufficiently under-priced and accelerate price collapse when the asset is over-priced.

     

Information interaction,behavioral synchronization and asset market volatility

This paper focuses on the synchronization of trading behavior caused by interactions among traders. The study begins with an agent-based model in which most agents make investment decisions based on three types of information (neighbor, public and private information) according to their heterogeneous personal preferences. Considering the influence of the social relationship network in reality, traders in our model are connected by a complex network. We use four different types of networks. The simulated results of this model reproduce several stylized facts about the asset market. Simulated results show that when preference of traders for neighbor information increases, the level of trust among traders will gradually increase and then there will be a “leap” at a certain point. The mutual trust among traders is achieved through coupling effect in the network. Moreover, with the frequent synchronization of traders’ behavior, extreme phenomena in financial markets will emerge. In addition, our numerical simulations show that when the average degree of network is higher, behavioral synchronization will emerge at a lower level of dependence on neighbor information. The degree distribution of the network will also have a significant influence on the convergence processes of behavioral synchronization. The more heterogeneous the degree distribution is, the easier the behavioral synchronization process will occur. In our simulations, the mode of agent behavior expectation will also enhance the effect of network structure to behavioral synchronization. Finally, this paper affirms the important role of public information and learning mechanism (expectation formation mode) in the process of behavioral synchronization.     

Incorporating positions into asset pricing models with order-based strategies

The paper addresses the problem of agent-based asset pricing models with order-based strategies that the implied positions of the agents remain indeterminate. To overcome this inconsistency, two easily applicable risk aversion mechanisms are proposed which modify the original actions of a market maker and the speculative agents, respectively. Here the concepts are incorporated into the classical Beja–Goldman model. For the deterministic version of the thus enhanced model a four-dimensional mathematical stability analysis is provided. In a stochastic version it is demonstrated that jointly the mechanisms are indeed able to keep the agents’ positions within bounds, provided the corresponding risk aversion coefficients are neither too low nor too high. A similar result holds for the misalignment of the market price. We wish to thank two anonymous referees for their observations and detailed comments. Financial support from EU STREP ComplexMarkets, contract number 516446, is gratefully acknowledged.     

Learning to bid in sequential Dutch auctions

We propose an agent-based computational model to investigate sequential Dutch auctions with particular emphasis on markets for perishable goods and we take as an example wholesale fish markets. Buyers in these markets sell the fish they purchase on a retail market. The paper provides an original model of boundedly rational behavior for wholesale buyers׳ behavior incorporating learning to improve profits, conjectures as to the bids that will be made and fictitious learning. We analyze the dynamics of the aggregate price under different market conditions in order to explain the emergence of market price patterns such as the well-known declining price paradox and the empirically observed fact that the very last transactions in the day may be at a higher price. The proposed behavioral model provides alternative explanations for market price dynamics to those which depend on standard hypotheses such as diminishing marginal profits. Furthermore, agents learn the option value of having the possibility of bidding in later rounds. When confronted with random buyers, such as occasional participants or new entrants, they learn to bid in the optimal way without being conscious of the strategies of the other buyers. When faced with other buyers who are also learning their behavior still displays some of the characteristics learned in the simpler case even though the problem is not analytically tractable.     

News shocks and asset price volatility in general equilibrium

We study equity price volatility in general equilibrium with news shocks about future productivity and monetary policy. As West (1988) shows, in a partial equilibrium present discounted value model, news about the future cash flow reduces asset price volatility. We show that introducing news shocks in a canonical dynamic stochastic general equilibrium model may not reduce asset price volatility under plausible parameter assumptions. This is because, in general equilibrium, the asset cash flow itself may be affected by the introduction of news shocks. In addition, we show that neglecting to account for policy news shocks (e.g., policy announcements) can potentially bias empirical estimates of the impact of monetary policy shocks on asset prices.     

European quanto option pricing in presence of liquidity risk

In this paper, we study the pricing problems of the European quanto options in which the underlying foreign asset is in imperfectly liquid markets. First, we assume that the dynamics of the underlying foreign asset price are affected by market liquidity and propose a liquidity-adjusted quanto model. This allows for the effects of market liquidity on European quanto option pricing. And then we derive the analytical pricing formulas for four different types of European quanto options. Finally, we empirically investigate the pricing performance of our proposed model with a European quanto construction involving the SSE 50 ETF, as the underlying asset, and the CNY/HKD exchange rate. Empirical results demonstrate that the pricing accuracy of the proposed model is markedly superior to that of the Black-Scholes quanto model. In other words, allowing for liquidity risk in the framework of European quanto option pricing can make markedly improvements in fitting the real market data. Particularly, the improvement rate is high for medium-term and out-of-the-money options. Moreover, these results are robust for different liquidity measures.     

Economic uncertainty and national bitcoin trading activity

This study analyzes the dynamics between bitcoin trading, price activities, and economic surprise shocks from a broad and novel perspective on a national level. We start by estimating the response of bitcoin trading in terms of volume and volatility to economic surprises. Following this, we extend our framework by applying a Generalized AutoRegressive Conditional Heteroskedasticity model to get an indication of the volatility reaction of national bitcoin activities to economic surprise shocks. Our results show that local and global shocks affect local bitcoin activities and trading volatilities, confirming that economic events affect bitcoin markets. We argue that increased trading activity, coupled with a price reaction, indicates that bitcoin might be considered a hedge or safe haven asset against economic uncertainty. We find evidence that bitcoin is treated as a speculative asset against negative economic policy uncertainty shocks in Canada pre-Covid-19. These results change during the Covid-19 pandemic, leading to a significant structural break. Here, we find indications that bitcoin might be treated as a safe-haven asset in New Zealand and Australia. This shows that bitcoin behaves differently depending on the studied country, underlining the importance of country-level studies. It also shows that bitcoin is a new asset that is evolving rapidly and that the period in which it is studied is important.     

Price dynamics,financial fragility and aggregate volatility

Within a general equilibrium framework à la (Long and Plosser, 1983), we investigate the dynamics emerging from the interactions of households and firms that are adaptive price setters and financially constrained. Adaptive price-setting behavior induces micro-founded out-of-equilibrium dynamics along which agents become heterogeneous in terms of prices and wealth. The stringency of the financial constraints determines the regime into which the model settles: either an equilibrium one or a disequilibrium one conductive to financial fragility and aggregate volatility. In this setting, we investigate how the structure of the production network affects the emergence of aggregate volatility from micro-level price and financial shocks, hence providing a dynamical counterpart to recent results of Acemoglu et al. (2012).     

Do credit market imperfections justify a central bank׳s response to asset price fluctuations?

Do credit market imperfections justify a central bank׳s response to asset price fluctuations? This study addresses this question from the perspective of equilibrium determinacy. In the model we use, prices are sticky and the working capital of firms is subject to asset values because of a lack of commitment. If credit market imperfections exist to a small degree, the Taylor principle is a necessary and sufficient condition for equilibrium determinacy, and monetary policy response to asset price fluctuations is good from the perspective of equilibrium determinacy. However, if credit market imperfections exist to a large degree such that the collateral constraint is binding, then the Taylor principle no longer guarantees equilibrium determinacy, and monetary policy response to asset price fluctuations becomes a source of equilibrium indeterminacy. We find that the existence of credit market imperfections makes it unsuitable to initiate a monetary policy response to deal with asset price fluctuations. We also find that reductions in credit market imperfections can enlarge the indeterminacy region of the model parameters.