A data mining approach to financial time series modelling and forecasting

This paper describes one of the relatively new data mining techniques that can be used to forecast the foreign exchange time series process. The research aims to contribute to the development and application of such techniques by exposing them to difficult real-world (non-toy) data sets. The results reveal that the prediction of a Radial Basis Function Neural Network model for forecasting the daily $US/$NZ closing exchange rates is significantly better than the prediction of a traditional linear autoregressive model in both directional change and prediction of the exchange rate itself. We have also investigated the impact of the number of model inputs (model order), the number of hidden layer neurons and the size of training data set on prediction accuracy. In addition, we have explored how the three different methods for placement of Gaussian radial basis functions affect its predictive quality and singled out the best one. Copyright © 2001 John Wiley & Sons, Ltd.     

Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis

This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.     

A framework for analyzing financial reporting cases

Accounting educators have called for greater emphasis on both conceptual and case teaching material in the curriculum. In this paper, an approach to delivering such materials in a financial accounting course is presented and discussed.     

A framework for assessing financial stability?

I worked as a consultant in the Financial Stability Department (FSD) of the Bank of England for several years (2002–2004). In this paper I reflect on issues relating to the work of such an FSD, starting with the difficulty of defining or measuring ‘financial stability’. Stress tests are commonly used, but, for an FSD, should relate to the system as a whole, not just to individual institutions. FSDs need to assess the probability, virulence and speed of occurrence of potential shocks. There is a need to develop appropriate analytical models. The focus on capital adequacy has diverted attention from concern about having sufficient liquidity.     

A structural framework for modelling contingent capital

This paper develops a structural model of contingent capital. In contrast to existing approaches we explicitly link the firm’s total payout to its cost of debt, leading to a total payout that is linear in—as opposed to proportional to—asset value. In the special case that asset value evolves as affine geometric Brownian motion we derive closed-form expressions for limiting (i.e. perpetual) bond values. The proposed model is flexible, so that it can be used to gauge the relative merits of different variations of contingent capital, and parsimonious, so that it is relatively easy to implement in practice. An empirical example using data from the Canadian banking sector is provided that illustrates how the model can generate insights into problems that are of interest to both regulators and issuers of contingent capital (e.g. what range of conversion prices would be consistent with regulatory guidelines, and how expensive is contingent debt over this range).     

A builder's guide to agent-based financial markets

This paper is intended to guide researchers interested in building their own agent-based financial markets. Key design questions are outlined, along with some of the major controversies about which directions to take.     

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.     

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.     

A note on the no arbitrage condition for international financial markets

We consider an international financial market model that consists ofN currencies. The purpose is to derive a no arbitrage condition which is not affected by the choice of numéraire between theN currencies. As a result, we show that a finiteness condition for an arbitrary chosen currency and the no arbitrage condition for the basket currency are necessary and sufficient for the no arbitrage property of all theN currencies. Research supported in part by Nomura Foundation for Social Science and by the European Community Stimulation Plan for Economic Science contract Number SPES-CT91-0089. The authors thank an anonymous FEJM referee for helpful comments.     

Optimal liberalization of financial markets

As financial markets become completely liberalized, countries gain from improved risk sharing, but less wealthy countries can no longer profit from borrowing abroad at the lower rate and reinvesting at home at the higher rate. With decreasing rather than constant returns to capital, the gain from risk sharing is more likely to dominate the loss of the difference between the borrowing rate abroad and the decreasing reinvestment rate at home. Complete liberalization is likely to be optimal for less wealthy countries unless their labor endowment is large, their productivity is large, or holdings by foreigners are small, as in China.     

A general HJM framework for multiple yield curve modelling

We propose a general framework for modelling multiple yield curves which have emerged after the last financial crisis. In a general semimartingale setting, we provide an HJM approach to model the term structure of multiplicative spreads between FRA rates and simply compounded OIS risk-free forward rates. We derive an HJM drift and consistency condition ensuring absence of arbitrage and, in addition, we show how to construct models such that multiplicative spreads are greater than one and ordered with respect to the tenor’s length. When the driving semimartingale is an affine process, we obtain a flexible and tractable Markovian structure. Finally, we show that the proposed framework allows unifying and extending several recent approaches to multiple yield curve modelling.     

Diversification in financial and crypto markets

This article investigates the conditional value at risk (CVaR) of two portfolio optimiza- tion approaches containing assets from the financial and crypto markets. We first catch the conditional interdependence structure among each variable through the vine-copula-GARCH model before merging it with the Mean-CVaR model. We then optimize each portfolio and find out the optimal allocation while evaluating the precise risk. The results indicate that the D-Vine copula is more suitable for both portfolios and that, when different conditional stock indices information are being taken into consideration, the crypto-market components can act as a weak hedge/safe haven against financial market indices. Furthermore, as CVaR is found to outperform the mean-variance of Markowitz in both portfolios, both risk measures similarly show that when including cryptocurrencies in a portfolio, the S&P 500 shall not be included. Additionally, the inclusion of Ethereum in a portfolio already containing Bitcoin does not boost the return.     

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.     

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.     

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.