Money and liquidity in financial markets

We argue that there is a connection between the interbank market for liquidity and the broader financial markets, which has its basis in demand for liquidity by banks. Tightness in the market for liquidity leads banks to engage in what we term “liquidity pull-back,” which involves selling financial assets either by banks directly or by levered investors. Empirical tests on the stock market are supportive. Tighter interbank markets are associated with relatively more volume in more liquid stocks; selling pressure, especially in more liquid stocks; and transitory negative returns. We control for market-wide uncertainty and in the process also contribute to the literature on portfolio rebalancing. Our general point is that money matters in financial markets.     

Adaptive learning in financial markets

We investigate adaptive or evolutionary learning in a repeatedversion of the Grossman and Stiglit (1980) model. We demonstratethat any process that is a monotonic selection dynamic willconverge to the rational expectations asset demands if the proportionof informed traders is fixed. We also show that these learningprocesses have a unique asymptotically stable fixed point atthe Grossman-Stiglitz (GS) equilibrium. The robustness of learningto noisy experimentation is studied using Binmore and Samuelson's(1999) deterministic drift approximation. Conditions on economicand learning process parameters for adaptive learning to leadto the GS rational expectations equilibrium are presented.     

Credit markets and financial information

The last decade has seen rapid growth in trading of credit instruments on secondary markets. The ensuing availability of a rich set of credit market data has created a novel environment for testing a variety of financial economic theories. In this discussion, we provide a simple framework for linking asset pricing research using equity and credit market data and offer some suggestions for future archival empirical research aiming to establish relations between financial information and credit markets. Credit instruments are intrinsically linked to equity instruments. The strength of this link varies temporally and cross-sectionally in measurable ways that can, and should be, used to guide future empirical research linking information to credit markets.     

Information provision in financial markets

We set up a rational expectations model in which investors trade a risky asset based on a private signal they receive about the quality of the asset, and a public signal that represents a noisy aggregation of the private signals of all investors. Our model allows us to examine what happens to market performance (market depth, price efficiency, volume of trade, and expected welfare) when regulators can induce improved information provision in one of two ways. Regulations can be designed that either provide investors with more accurate information by improving the quality of prior information, or that enhance the transparency of the market by improving the quality of the public signal. In our rational expectations equilibrium, improving the quality of the public signal can be interpreted as a way of providing information about the anticipations and trading motives of all market participants. We find that both alternatives improve market depth. However, in the limit, we show that improving the precision of prior information is a more efficient way to do so. More accurate prior information decreases asymmetric information problems and consequently reduces the informativeness of prices, while a more accurate public signal increases price informativeness. The volume of trade is independent of the quality of prior information and is increasing in the quality of the public signal. Finally, expected welfare can sometimes fall as prior information or the public signal become more precise.     

Diversification at financial institutions and systemic crises

It is widely believed that diversification at financial institutions benefits the stability of the financial system. This paper shows that it also entails a cost: even though diversification reduces each institution’s individual probability of failure, it makes systemic crises more likely. When systemic crises induce additional costs (over and above individual failures), full diversification is no longer desirable as a result and the optimal degree of diversification may be arbitrarily low. We show that the analysis can be extended beyond diversification, such as to interbank insurance and financial integration.     

A random forest-based model for crypto asset forecasts in futures markets with out-of-sample prediction

In this study, a price prediction model for futures markets of crypto assets is presented. Random Forest was used to study three scenarios as a function of input variables: technical indicators, candlestick patterns and both simultaneously. In turn, the model parameters, the time intervals, and the most suitable investment horizons were studied. In addition to showing the results from the model, a one-year out-of-sample prediction was simulated. The entire year of 2020 was chosen because the three possible stock market scenarios occurred in this year: a sideways market, a bear market resulting from the global pandemic and an end-of-year bull market. Last, this out-of-sample simulation was analyzed as a real operation, that is, by retraining the model after each new collection of data, so that the model had the maximum information at all times. In conclusion, using candlestick patterns instead of technical indicators, improves the efficiency of the results.     

Asymptotic arbitrage in large financial markets

A large financial market is described by a sequence of standard general models of continuous trading. It turns out that the absence of asymptotic arbitrage of the first kind is equivalent to the contiguity of sequence of objective probabilities with respect to the sequence of upper envelopes of equivalent martingale measures, while absence of asymptotic arbitrage of the second kind is equivalent to the contiguity of the sequence of lower envelopes of equivalent martingale measures with respect to the sequence of objective probabilities. We express criteria of contiguity in terms of the Hellinger processes. As examples, we study a large market with asset prices given by linear stochastic equations which may have random volatilities, the Ross Arbitrage Pricing Model, and a discrete-time model with two assets and infinite horizon. The suggested theory can be considered as a natural extension of Arbirage Pricing Theory covering the continuous as well as the discrete time case.     

Benchmarking in two price financial markets

No arbitrage for two price economies with no locally risk free asset implies that suitably benchmarked prices are nonlinear martingales. However, both the benchmarking asset and the measure change depend on the process being benchmarked. Further assumptions allow the nonlinear martingales in discrete time to become expectations with respect to a nonadditivity probability. Such nonlinear expectations are imminently reasonable given the lack of experience with tail events on both sides of the gain loss spectrum. Continuous time extensions employ measure distortions. The general valuation of economic activities and the leveraging of stability in benchmarked price processes is then addressed. Traditional asset pricing questions and investigations are then reopened for benchmarked prices. In particular, the analytics for benchmarked option pricing and the asset pricing theory for benchmarked prices in a limiting stationary state are developed.     

Measuring liquidity commonality in financial markets

This paper contributes to the literature by developing a new methodology, termed the beta index, for measuring liquidity commonality in financial markets which is derived from the dynamics of liquidity co-movements. We show that computing the beta index is a straightforward process. In addition, not only is the proposed beta index more efficient in controlling for confounding factors and addressing the associated statistical inference issues, but it will also enhance the accuracy of estimation. We apply the beta index to track liquidity commonality in the foreign exchange markets over the study period and to identify important financial and economic events that caused liquidity commonality. We detect periods of high and low liquidity commonalities that would especially benefit active market traders who frequently rebalance portfolios and require knowledge of liquidity commonality as an important early signal and indication of diversification benefit.     

CRM in intermediated financial services markets

A division of a major UK insurance company manufactures insurance products for wholesale clients to retail into their banking and building society customer bases. This paper discusses the CRM challenges of leveraging insurance business from existing partnership relationships, including issues of confidentiality between client portfolios, the strategic use of data marts rather than data warehouses and the sharing of information. It describes the issues involved in implementing CRM, such as rolling out customer contact management and call centre systems. The study concludes with an appraisal of lessons learned, which include a better understanding of who the customers are and which of them are profitable, together with the characteristics that contribute to them becoming profitable or unprofitable.     

全球金融市场在动荡中发展

2007年12月,国际清算银行发布了季度报告,对次贷危机威胁下的全球金融市场进行回顾,报告显示,市场遭受持续的信用恐慌打击,主要工业经济体的国债收益率显著下降,衍生品市场创下最繁忙记录,国际银行业跨境债权增长由急变缓（截至2007年6月末）。     

进一步扩大Shibor在金融市场上的运用

Shibor自2007年初在银行间市场正式推出以来,其作为货币市场基准利率的作用逐渐得到充分的发挥。文章介绍了Shibor在各类金融产品（如浮息金融债、企业债、金融衍生品、票据贴现业务等）以及银行内部定价机制中日益广泛的运用,指出了当前制约Shibor发展的主要问题,并从提高Shibor可交易性、理顺同业拆借业务框架等方面就推进Shibor建设提出建议。     

Measuring large comovements in financial markets

A general, copula-based framework for measuring the dependence among financial time series is presented. Particular emphasis is placed on multivariate conditional Spearman's rho (MCS), a new measure of multivariate conditional dependence that describes the association between large or extreme negative returns—so-called tail dependence. We demonstrate that MCS has a number of advantages over conventional measures of tail dependence, both in theory and in practical applications. In the analysis of univariate financial series, data are filtered to remove temporal dependence as a matter of routine. We show that standard filtering procedures may strongly influence the conclusions drawn concerning tail dependence. We give empirical applications to two large data sets of high-frequency asset returns. Our results have immediate implications for portfolio risk management, derivative pricing and portfolio selection. In this context we address portfolio tail diversification and tail hedging. Amongst other aspects, it is shown that the proposed modeling framework improves the estimation of portfolio risk measures such as the value at risk.     

Investor climate sentiment and financial markets

We propose to measure investor climate sentiment by performing sentiment analysis on StockTwits posts on climate change and global warming. In financial markets, stocks of emission (carbon-intensive) firms underperform clean (low-emission) stocks when investor climate sentiment is more positive. We document investors overreaction to climate change risk and reversal in longer horizons. Salient but uninformative climate change events, such as the release of a report on climate change and abnormal weather events, facilitate the investor learning process and correction of the mispricing.     

Volatility transmission in global financial markets

This paper considers the transmission of volatility in global foreign exchange, equity and bond markets. Using a multivariate GARCH framework which includes measures of realised volatility as explanatory variables, significant volatility and news spillovers are found to occur on the same trading day between Japan, Europe, and the United States. All markets exhibit significant degrees of asymmetry in terms of the transmission of volatility associated with good and bad news. There are also strong links between diffusive volatilities in all three markets, whereas jump activity is only important within the equity markets. The results of this paper deepen our understanding of how news and volatility are propagated through global financial markets.     

Equilibrium dominance in experimental financial markets

We examine the predictive power of equilibrium dominance inexperimental markets where firms with investment opportunitieshave an informational advantage over potential investors andare permitted to purchase a money-burning signal. Equilibriumdominance often fails to predict well when a Pareto-superiorsequential equilibrium is also available. Instead, equilibriumselection appears to be related to the potential earnings ofa more valuable firm that can signal its type successfully bydefecting from the sequential equilibrium.     

Herding behaviour and volatility clustering in financial markets

We propose a financial market model in which speculators follow a linear mix of technical and fundamental trading rules to determine their orders. Volatility clustering arises in our model due to speculators’ herding behaviour. In case of heightened uncertainty, speculators observe other speculators’ actions more closely. Since speculators’ trading behaviour then becomes less heterogeneous, the market maker faces a less balanced excess demand and consequently adjusts prices more strongly. Estimating our model using the method of simulated moments reveals that it is able to explain a number of stylized facts of financial markets quite well. Various robustness checks with respect to the model setup reveal that our results are quite stable.