Financial Deepening,Asset Price Inflation,and Economic Convergence: Empirical Analysis Based on China’s Experience

Abstract

In this study, we test for convergence in financial development and economic growth in China’s financial deepening reform process by using system GMM method. The results show strong evidence of the mutually interactive and systematic relationship between financial development and economic growth, and the system is in a condition of long-run divergence. The main cause of divergence in the system changed after 2008 from financial depression to asset price expansion. This study provides evidence that the government should intensify financial deepening reforms and pay attention to financial resource flows to prevent excessive asset price expansion.     

Explaining Mortality Dynamics

Abstract

Using data for six OECD countries over the period 1950–2006, this paper studies the impact of macroeconomic fluctuations and cause of death trends on mortality dynamics in the Lee-Carter mortality forecasting model. The key results of this study are the following: (1) Periods can be identified in which the Lee-Carter mortality index k_t correlates significantly with macroeconomic fluctuations. (2) A few causes of death such as diseases of the circulatory system, influenza and pneumonia, and diabetes mellitus account for a large fraction of the variations in the Lee-Carter mortality index k_t . (3) Most cause-specific mortality rates show pronounced trends over the last few decades. These trends change the composition of deaths and alter how total mortality reacts to external factors such as macroeconomic fluctuations.     

The Application of Corporate Governance Indicators With XBRL Technology to Financial Crisis Prediction

ABSTRACT

The widespread adoption of eXtensible Business Reporting Language (XBRL) suggests that intelligent software agents can now use financial information disseminated on the Web with high accuracy. Financial data have been widely used by researchers to predict financial crises; however, few studies have considered corporate governance indicators in building prediction models. This article presents a financial crisis prediction model that involves using a genetic algorithm for determining the optimal feature set and support vector machines (SVMs) to be used with XBRL. The experimental results show that the proposed model outperforms models based on only one type of information, either financial or corporate governance. Compared with conventional statistical methods, the proposed SVM model forecasts financial crises more accurately.     

The double entry structural constraint on the econometric estimation of accounting variables

ABSTRACT

This paper develops a structural system for estimating accounting variables, within which the deterministic relationships inherent in financial statement articulation are clearly defined in the econometric model. The key proposition of the paper lies in the treatment of the financial statements as a matrix of codetermined information constrained by double entry, where the expected value of each of the individual items that comprise the financial statements will be mirrored elsewhere in the system with a different sign. Given that the change in net operating assets shares the same variation as the change in net financial claims, it is shown, by formally identifying the articulation, that empirical application will yield increased precision and improved efficiency by comparison to the more traditional methods that fail to specify the structural double entry property.     

Analyst Earnings Forecasts for Publicly Traded Insurance Companies

Several trends in the insurance and financial services industry, including demutualizationconsolidation, and deregulation, have attracted increasing attention from investors and financial analysts. This paper investigates the accuracy of the earnings forecasts of financial analysts for insurance companies. Our empirical results indicate that analyst forecasts outperform random walk time-series forecasts. Furthermore, we find that both disagreement over earnings forecasts among analysts and the relative forecasting error in the mean forecasts is smaller for life insurers than for property-casualty insurers, whereas the relative errors for forecasts for multiple-line insurers are in between the two. Forecasting error is a negative function of firm size and the number of analysts who are following a company, and is a positive function of the disagreement among analysts.Analyst forecasts have a timing advantage over the random walk model. Our results also suggest that the fair value reporting requirement (SFAS 115), which has been in effect since 1994, has enhanced the accuracy of analyst forecasts. The SFAS 115 has improved the superiority of analyst forecasts over the random walk forecasts for life insurers, but not for property-casualty insurers, and there is a weak improvement for multiple-line insurers. JEL Classification: G15     

Bayesian Risk Management for Equity-Linked Insurance

This paper describes how to apply Markov Chain Monte Carlo (MCMC) techniques to a regime switching model of the stock price process to generate a sample from the joint posterior distribution of the parameters of the model. The MCMC output can be used to generate a sample from the predictive distribution of losses from equity linked contracts, assuming first an actuarial approach to risk management and secondly a financial economics approach. The predictive distribution is used to show the effect of parameter uncertainty on risk management calculations. We also explore model uncertainty by assuming a GARCH model in place of the regime switching model. The results indicate that the financial economics approach to risk management is substantially more robust to parameter uncertainty and model uncertainty than the actuarial approach.     

Financial fragility in a general equilibrium model: the Brazilian case

This paper employs a general equilibrium approach to model the Brazilian financial system. We show that the model is able to replicate the main characteristics of the data and to predict short-term trends. We calibrate the model for the years of 2002–2006, which comprise a crisis period in Brazil’s financial system. Empirical results suggest that the financial system is improving in terms of financial stability over time. Furthermore, the model has been proven useful to model the Brazilian banking system and could be employed to evaluate the impact of changes in financial regulation on the banking system.     

A Hermite-spline model of post-retirement mortality

ABSTRACT

We present a model for post-retirement mortality where differentials automatically reduce with increasing age, but without the fitted mortality rates for subgroups crossing over. Selection effects are catered for, as are age-modulated time trends and seasonal variation in mortality. Central to the model are Hermite splines, which permit parsimonious modelling of complex risk factors in even modest-sized portfolios. The model is therefore suitable for the stand-alone analysis of experience data for reinsurance, bulk annuities and longevity swaps. We also illustrate the contrast between the statistical significance of a risk factor and its financial significance and discuss reasons why one might include risk factors like season that are not directly financially significant.     

Asymmetry and downside risk in foreign exchange markets

Abstract

This paper evaluates the double gamma distribution as a means of modelling asymmetry in the conditional distribution of financial data. To do this the model is applied to ten exchange rate series covering mature and emerging market countries. A second contribution of this paper is to highlight the link between the double gamma distribution and the measurement of the second lower partial moment (or semi-variance). The resulting empirical performance of the double gamma model is found to be mixed when compared to a symmetric GARCH-t model. Estimates of conditional downside risk based on the double gamma model are constructed for each series. The results for the Malaysian Riggit, Zimbabwe Dollar and the Korean Won demonstrate the extreme downside volatility experienced by these countries during the emerging markets currency crisis.     

Capital Structure Dynamics in the UK and Continental Europe

Abstract

This paper investigates empirically the effects of institutions and market characteristics on corporate capital structure dynamics. Based on the fact that firms may temporarily deviate from their optimal capital structure due to the existence of adjustment costs, a partial adjustment model is used that links these transaction costs to country-specific characteristics such as the development of the financial markets, legal system, and macroeconomic environment. The sample comprises data from 873 firms in France, Germany, Italy and the UK over the period from 1982 to 2002. The results support the hypotheses that more developed financial markets, greater efficiency of the legal system and better protection of shareholders all have a positive effect on the speed at which firms adjust their capital structure towards the target. Similarly, higher economic growth and a higher inflation rate positively affect the speed of adjustment to the optimal capital structure as well.     

Random matrix models for datasets with fixed time horizons

This paper examines the use of random matrix theory as it has been applied to model large financial datasets, especially for the purpose of estimating the bias inherent in Mean-Variance portfolio allocation when a sample covariance matrix is substituted for the true underlying covariance. Such problems were observed and modeled in the seminal work of Laloux et al. [Noise dressing of financial correlation matrices. Phys. Rev. Lett., 1999, 83, 1467] and rigorously proved by Bai et al. [Enhancement of the applicability of Markowitz's portfolio optimization by utilizing random matrix theory. Math. Finance, 2009, 19, 639–667] under minimal assumptions. If the returns on assets to be held in the portfolio are assumed independent and stationary, then these results are universal in that they do not depend on the precise distribution of returns. This universality has been somewhat misrepresented in the literature, however, as asymptotic results require that an arbitrarily long time horizon be available before such predictions necessarily become accurate. In order to reconcile these models with the highly non-Gaussian returns observed in real financial data, a new ensemble of random rectangular matrices is introduced, modeled on the observations of independent Lévy processes over a fixed time horizon.     

Time-consistent reinsurance and investment strategies for an AAI under smooth ambiguity utility

This paper investigates time-consistent reinsurance(excess-of-loss, proportional) and investment strategies for an ambiguity averse insurer(abbr. AAI). The AAI is ambiguous towards the insurance and financial markets. In the AAI's attitude, the intensity of the insurance claims' number and the market price of risk of a stock can not be estimated accurately. This formulation of ambiguity is similar to the uncertainty of different equivalent probability measures. The AAI can purchase excess-of-loss or proportional reinsurance to hedge the insurance risk and invest in a financial market with cash and an ambiguous stock. We investigate the optimization goal under smooth ambiguity given in Klibanoff, P., Marinacci, M., & Mukerji, S. [(2005). A smooth model of decision making under ambiguity. Econometrica 73, 1849–1892], which aims to search the optimal strategies under average case. The utility function does not satisfy the Bellman's principle and we employ the extended HJB equation proposed in Björk, T. & Murgoci, A. [(2014). A theory of Markovian time-inconsistent stochastic control in discrete time. Finance and Stochastics 18(3), 545–592] to solve this problem. In the end of this paper, we derive the equilibrium reinsurance and investment strategies under smooth ambiguity and present the sensitivity analysis to show the AAI's economic behaviors.     

Author’s Reply: Skewness and Stock Option Prices - Discussion by Terence Chan,Michel Jacques,Heinz H. Mu¨ller,Geérard Pafumi,Elias S.W. Shiu,and Serena Tiong,July 1997

Abstract

In recent years, the combined effects of deregulation in financial services, along with advances in telecommunications and information technology, are forcing far-reaching changes upon the insurance industry. The result is the industry is becoming more competitive. The emerging role of electronic commerce (e-commerce) is particularly important and interesting to study.

I offer a brief survey of the role of e-commerce in the insurance industry. The paper is organized in the following manner: Section 1 summarizes Internet trends and discusses various related public policy issues; Section 2 addresses online insurance supply and demand; Section 3 discusses the economics of disintermediation and reintermediation and explains how this applies to e-commerce in the insurance industry. Finally, Section 4 offers a set of concluding remarks.     

Asymptotic arbitrage and numéraire portfolios in large financial markets

This paper deals with the notion of a large financial market and the concepts of asymptotic arbitrage and strong asymptotic arbitrage (both of the first kind) introduced in Probab. Theory Appl. 39, 222–229 (1994) and in Finance Stoch. 2, 143–172 (1998). We show that the arbitrage properties of a large market are completely determined by the asymptotic behavior of the sequence of the numéraire portfolios related to small markets. The obtained criteria can be expressed in terms of contiguity, entire separation, and Hellinger integrals, provided that these notions are extended to sub-probability measures. As examples, we consider market models on finite probability spaces, semimartingale models, and diffusion models. We also examine a discrete-time infinite horizon market model with one log-normal stock. This work was supported by Southern Federal University, grant No. 26 “Mathematical Finance” and by RFBR, grant 07-01-00520.     

Intraday Empirical Analysis and Modeling of Diversified World Stock Indices

This paper proposes an approach to the intraday analysis of diversified world stock accumulation indices. The growth optimal portfolio (GOP) is used as reference unit or benchmark in a continuous financial market model. Diversified portfolios, covering the world stock market, are constructed and shown to approximate the GOP, providing the basis for a range of financial applications. The normalized GOP is modeled as a time transformed square root process of dimension four. Its dynamics are empirically verified for several world stock indices. Furthermore, the evolution of the transformed time is modeled as the integral over a rapidly evolving mean-reverting market activity process with deterministic volatility. The empirical findings suggest a rather simple and robust model for a world stock index that reflects the historical evolution, by using only a few readily observable parameters. Mathematics Subject Classification: (1991) primary 90A12, secondary 60G30,62P20 JEL Classification: G10, G13     

Financial Development and Total Factor Productivity Growth: Evidence from China

Abstract

In this article, we estimate the effect of China’s regional financial development on total factor productivity (TFP) growth using large provincial panel data for the years 1990 to 2009. Using the nonparametric stochastic frontier data envelopment approach, we analyze how financial development is related to efficiency improvement and technological progress, the two components of TFP. The study shows that Chinese financial development plays a significant role in promoting TFP growth via technological progress rather than efficiency change. The faster the financial development takes place, the better it could correct the mismatch of resource allocation, thus promoting TFP growth. The results imply that China needs to both further optimize the allocation of financial resources and perfect the regional financial system.     

Financial and Demographic Risks of a Portfolio of Life Insurance Policies with Stochastic Interest Rates

Abstract

We refer to a recent paper by G. Parker (1997) in which the risk of a portfolio of life insurance policies (namely the risk related to the entire contractual life) is studied by separating the demographic component from the financial component. In our paper, after making a brief summary of Parker’s model, we propose two additional contributions: 1. We first give the problem a different formalization, thus allowing a portfolio risk analysis by management periods and a study of the risk due to the interactions among years;

2. We elaborate on a powerful and flexible algorithm for calculating the probability distribution of the sum of random variables that proves useful to solve not only the problems discussed in this paper concerning the risk analysis but also various other problems.

In the paper, we also show, for both contributions, some applications made under the same financial and demographic assumptions taken by Parker; we also compare our results with Parker’s results.     

New development: Budgetary accounting in Colombia—arguments for a much-needed reform

ABSTRACT

Public financial management reforms are needed in Colombia to integrate the accrual-based accounting system with budgets. This would remove the need to make accounting variations through deficit measurement and would supply better information about the impact of public policies on the country’s financial situation. This article briefly explains why Colombia needs to integrate its accounting and budgeting systems.     

Government and Financial Institutional Determinants of Development in MENA Countries

ABSTRACT

This article aims to examine the causal impact of the Arab Spring (AS) and government institutions on the finance–growth nexus. The empirical analysis is implemented for extensive firm-level panel data combined with national data covering macroeconomic and institutional factors for the period 2005–2014, starting 6 years before and continuing after the AS. Using Difference-in-Difference method, we analyze the effect of the AS. Evidence points to financial development as a strong positive contributor to growth. The analysis also indicates that the AS dampens growth. These results seem to suggest that political instability adversely affects growth; nevertheless, a well-functioning financial system is a necessary but not a sufficient condition to enhance growth. Therefore, policies aiming at improving the efficiency and the operation of institutions such as a country’s legal system, citizen’s participation in selecting government, freedom of expression, and the stage of financial development should persist over an extended period of time, in order to bear fruition and achieve a significant success in boosting economic growth and reducing poverty.     

Estimating Beta-Coefficients of German Stock Data: A Non-Parametric Approach

Abstract

Although the consumption based asset pricing theory appears to be theoretically superior and more elegant than the beta pricing model, in practice the beta pricing model is more widely applied. Indeed, beta pricing models are one of the most widely adopted tools in financial analysis. They readily allow handling systematic risk as priced in financial assets. However, accurately estimating beta-coefficients is not as straightforward as implicitly suggested by Sharpe's standard market model, i.e. simply using the ordinary least-squares (OLS) regression. This is primarily because beta-coefficients cannot generally be assumed to be stable over time. In order to overcome this deficiency, we present and apply a non-parametric estimation technique that allows capturing this time effect and promises both more reliable estimates than obtained with an OLS regression as well as better manageability compared with the existing time-series approaches dealing with time-varying beta-coefficients. Estimation results for constant and time-varying betas are presented for portfolios of German industries.