Adaptive Bayesian Networks for quantitative risk assessment of foreign body injuries in children

Injuries due to foreign body (FB) aspiration/ingestion/insertion represent a common public health issue in paediatric patients, which causes significant morbidity and mortality. The aim of this study is to present a Bayesian Network (BN) model for the identification of risk factors for FB injuries in children and provide their quantitative assessment. Combining a priori knowledge and observed data, a BN learning algorithm was used to generate the pattern of the relationships between possible causal factors of FB injuries. Finally, the BN was used for making inference on scenarios of interest, providing, for instance, the risk that an accident caused by a spherical object swallowed by a male child aged five while playing leads to hospitalization. BNs as a tool for quantitative risk assessment may assist in determining the hazard of consumer products giving an insight into their most influential specific features on the risk of experiencing severe injuries.     

投资性房地产公允价值计量的财务影响与决定因素:以北辰实业为例

以北辰实业为例,本文分析了企业在投资性房地产成本模式与公允价值计量模式之间选择的财务影响及其决定因素。与成本模式相比,投资性房地产公允价值计量将大幅提高其账面价值,加剧了企业当期净利润的波动。北辰实业在A股年报中采用成本模式,而在H股年报中采用公允价值计量,这主要源于以下因素:(1)香港会计准则与我国会计准则的差异;(2)两地监管机构对公允价值会计的态度不同;(3)两地投资性房地产信息披露的差异;(4)资本市场成熟度与投资者的理性程度的差异。最后我们总结了本案例对于企业选择公允价值计量模式、监管层推行公允价值会计与应对会计国际趋同三个方面的政策含义。     

运用贝叶斯网络量化和控制商业银行操作风险——一个基于实际业务流程的例子

操作风险量化是为降低和控制风险服务的。运用贝叶斯网络分析量化操作风险并改进控制,对提升商业银行的操作风险管理水平是一条有效途径。论文以我国银行的一个典型业务—远期结售汇为例,研究了实践中建立和运用贝叶斯网络来估计操作风险发生频率的具体方法。以流程分析和映射为基础,阐述了风险映射与节点识别、网络结构建立、网络节点描述、节点赋值的实施步骤,并说明了利用贝叶斯网进行因果推理和诊断推理的方法。     

Islamic and Conventional Equity Market Movements During and After the Financial Crisis: Evidence from the Newly Launched MSCI Indices

This paper examines the relationship between the Islamic and conventional equity indices by employing the newly launched MSCI Global Islamic Indices which began in 2008. We argue for the case of cointegration supported by fundamental, category and habitat theories, and against cointegration due to the fundamental difference between Islamic and conventional stocks in terms of debt ratio, accounts receivable and interest bearing securities. We find Islamic and conventional equity markets move together despite fundamental differences and given that market microstructure, dividends, capital gains, taxation and governance systems are different across the markets. Almost simultaneous movement of the permanent and cycle components of Islamic and mainstream equity indices has been supported by the application of the Beveridge Nelson (BN) time series decomposition technique. Theoretically, the volatility of Islamic equities should be lower due to their low leverage ratio. Surprisingly, permanent parts of the Islamic indices appear to be more volatile during the crisis period and less volatile during the post‐crisis period.     

The QLBS Q-Learner goes NuQLear: fitted Q iteration,inverse RL,and option portfolios

The QLBS model is a discrete-time option hedging and pricing model that is based on Dynamic Programming (DP) and Reinforcement Learning (RL). It combines the famous Q-Learning method for RL with the Black–Scholes (–Merton) (BSM) model's idea of reducing the problem of option pricing and hedging to the problem of optimal rebalancing of a dynamic replicating portfolio for the option, which is made of a stock and cash. Here we expand on several NuQLear (Numerical Q-Learning) topics with the QLBS model. First, we investigate the performance of Fitted Q Iteration for an RL (data-driven) solution to the model, and benchmark it versus a DP (model-based) solution, as well as versus the BSM model. Second, we develop an Inverse Reinforcement Learning (IRL) setting for the model, where we only observe prices and actions (re-hedges) taken by a trader, but not rewards. Third, we outline how the QLBS model can be used for pricing portfolios of options, rather than a single option in isolation, thus providing its own, data-driven and model-independent solution to the (in)famous volatility smile problem of the Black–Scholes model.     

Bank Leverage Cycles and the External Finance Premium

By combining the approaches of Gertler and Karadi (2011) (GK) and Bernanke, Gertler, and Gilchrist (1999) (BGG), I develop a Dynamic Stochastic General Equilibrium (DSGE) model with leverage constraints both in the banking and in the nonfinancial firm sector. I calibrate this “full model” to US data. The full model matches the relative volatility of the external finance premium and the procyclicality of bank leverage and thus outperforms both a BGG and a GK‐type model. For a reasonably calibrated combination of balance sheet shocks, the model reproduces a substantial share of the contraction (increase) of investment (the external finance premium) observed during the “Great Recession.”     

MARGIN TRADING: A RISK-RETURN ANALYSIS

This paper attempts to present an integrated valuation analysis of investment options involving margin trading. The analysis is based on valuation theories such as Modigliani and Miller's capital structure model, the capital asset pricing model and the option pricing model. It is shown (i) that in margin trading, the return on equity is given by the return on investment plus a risk premium which increases proportionally with the margin-trading rate; (ii) that both the total risk (variance) and systematic risk (beta) of the return on equity increases proportionally with those associated with the return on investment; and (iii) that, when the option pricing model is applied to the case of margin trading, a more precise valuation formula can be employed.     

An almost Markovian LIBOR market model calibrated to caps and swaptions

A new variant of the LIBOR market model is implemented and calibrated simultaneously to both at-the-money and out-of-the-money caps and swaptions. This model is a two-factor version of a new class of the almost Markovian LIBOR market models with properties long sought after: (i) the almost Markovian parameterization of the LIBOR market model volatility functions is unique and asymptotically exact in the limit of a short time horizon up to a few years, (ii) only minimum plausible assumptions are required to derive the implemented volatility parameterization, (iii) the calibration yields very good results, (iv) the calibration is almost immediate, (v) the implemented LIBOR market model has a related short-rate model. Numerical results for the two-factor case show that the volatility functions for the LIBOR market model can be imported into its short-rate model cousin without adjustment.     

Money and exchange rates in the Grossman-Weiss-Rotemberg model

We analyze the impact of monetary policy on inflation, interest rates and exchange rates in a model with segmented asset markets developed by Grossman and Weiss (1983) and Rotemberg (1984, 1985). We find parameters for which real and nominal exchange rates in this model are (1) much more volatile than interest rates, inflation rates, and money growth rates, (2) highly correlated with each other, and (3) highly persistent. While this model fails to match the data in other important respects, it illustrates a potentially useful approach to modelling exchange rate behavior.     

中国国债利率期限结构模型研究与实证分析

本文在概述国债利率期限结构模型的基础上,针对当前被发达国家广泛采用的NS和SV模型所存在的不足,通过扩展指数多项式的方法,构建出NSM模型。为了更好地估算利率期限结构模型中的参数,本研究针对目标函数优化求解,经分析比较多种优化算法后,确定选用GRG2非线性最优化算法。通过使用上海证券交易所2005.1.4～2007.11.30的国债每日交易数据对NS、SV、NSM三个模型的实证分析比较,表明NSM模型不仅保留了NS模型的经济含义,克服了SV模型参数估计依赖初值的缺点,能够反映出利率曲线多峰的情况;而且其在拟合精度、价格误差等多项指标上均优于NS模型和SV模型,并具有良好的适应性和稳健性,能够满足我国当前的国债市场需要。     

Asymmetric Price Movements and Borrowing Constraints: A Rational Expectations Equilibrium Model of Crises, Contagion, and Confusion

This study proposes a rational expectations equilibrium model of crises and contagion in an economy with information asymmetry and borrowing constraints. Consistent with empirical observations, the model finds: (1) Crises can be caused by small shocks to fundamentals; (2) market return distributions are asymmetric; and (3) correlations among asset returns tend to increase during crashes. The model also predicts: (1) Crises and contagion are likely to occur after small shocks in the intermediate price region; (2) the skewness of asset price distributions increases with information asymmetry and borrowing constraints; and (3) crises can spread through investor borrowing constraints.     

Implied volatility and skewness surface

The Homoscedastic Gamma (HG) model characterizes the distribution of returns by its mean, variance and an independent skewness parameter. The HG model preserves the parsimony and the closed form of the Black–Scholes–Merton (BSM) while introducing the implied volatility (IV) and skewness surface. Varying the skewness parameter of the HG model can restore the symmetry of IV curves. Practitioner’s variants of the HG model improve pricing (in-sample and out-of-sample) and hedging performances relative to practitioners’ BSM models, with as many or less parameters. The pattern of improvements in Delta-Hedged gains across strike prices accord with predictions from the HG model. These results imply that expanding around the Gaussian density does not offer sufficient flexibility to match the skewness implicit in options. Consistent with the model, we also find that conditioning on implied skewness increases the predictive power of the volatility spread for excess returns.     

General equilibrium pricing of currency and currency options

This paper presents a consumption-based general equilibrium model for valuing foreign exchange contingent claims. The model identifies a novel economic mechanism by exploiting highly but imperfectly shared consumption disaster with variable intensities which are the concerns to the representative investor under recursive utility. When applied to the data, the model simultaneously replicates (i) the moderate option-implied volatilities; (ii) substantial variations in the risk-neutral skewness of currency returns; (iii) the uncovered interest rate parity puzzle; and (iv) the first two moments of carry trade returns. Furthermore, the model rationalizes salient features of the aggregate stock, government bonds, and equity index options.     

Forecasting realised volatility: a Markov switching approach with time‐varying transition probabilities

This paper introduces a markov‐switching heterogeneous autoregressive (MS‐HAR) model with time‐varying transition probabilities (TVTP) for the realised volatility of Shanghai securities composite index returns. Its various extensions have been obtained by including negative returns outside trading hours in addition to the leverage effects and trading volume. The findings show asymmetries in the impact of explanatory variables on the realised volatility. Moreover, the out‐of‐sample results show that the benchmark MS‐HAR with TVTP model and its extensions consistently outperform the simple HAR model, MS‐HAR model with constant transition probabilities (CTP) and their extensions. These results are robust to alternative realised measurements, and have economic implications.     

New evidence on the price and liquidity effects of the FTSE 100 index revisions

We study the price and liquidity effects following the FTSE 100 index revisions. We employ the standard GARCH(1,1) model to allow the residual variance of the single index model (SIM) to vary systematically over time and use a Kalman filter approach to model SIM coefficients as a random walk process. We show that the observed price effect depends on the abnormal return estimation methods. Specifically, the OLS-based abnormal returns indicate that the price effect associated with the index revision is temporary, whereas both SIM with random coefficients and GARCH(1,1) model suggest that both additions and deletions experience permanent price change. Added (removed) stocks exhibit permanent (temporary) change in trading volume and bid-ask spread. The analysis of the spread components suggests that the permanent change associated with additions is a result of non-information-related liquidity. We interpret the permanent price effect of additions and deletions combined with the permanent (temporary) shift in liquidity of added (removed) stocks as evidence in favour of the imperfect substitution hypothesis with some non-information-related liquidity effects in the case of additions.     

Sticky Price Models,Durable Goods,and Real Wage Rigidities

The standard two‐sector New Keynesian model with durable goods is at odds with conventional wisdom and vector autoregression (VAR) evidence: Following a monetary shock, the model generates (i) either negative or no comovement across sectoral outputs and (ii) aggregate neutrality of money when durable goods' prices are flexible. We reconcile theory with evidence by incorporating real wage rigidities into the standard model: As long as durable goods' prices are more flexible than nondurable goods' prices, we obtain positive sectoral comovement and, thus, aggregate nonneutrality of money.     

Estimating the Dynamics of Mutual Fund Alphas and Betas

This article develops a Kalman filter model to track dynamicmutual fund factor loadings. It then uses the estimates to analyzewhether managers with market-timing ability can be identifiedex ante. The primary findings are as follows: (i) Ordinary leastsquares (OLS) timing models produce false positives (nonzeroalphas) at too high a rate with either daily or monthly data.In contrast, the Kalman filter model produces them at approximatelythe correct rate with monthly data; (ii) In monthly data, thoughthe OLS models fail to detect any timing among fund managers,the Kalman filter does; (iii) The alpha and beta forecasts fromthe Kalman model are more accurate than those from the OLS timingmodels; (iv) The Kalman filter model tracks most fund alphasand betas better than OLS models that employ macroeconomic variablesin addition to fund returns.     

CONVERTIBLE BOND VALUATION: AN EMPIRICAL TEST

This research applies the options pricing model to the valuation of convertible bonds. A numeric algorithm is used to obtain theoretical values for a sample of 103 convertible bond issues. When market prices are compared with model valuations, the means are not significantly different, and 90 percent of model predictions are within 10 percent of market values. As a further test, the sample is divided on the basis of whether the model prices are (1) greater or (2) less than market prices. Returns are compared over a subsequent three-year holding period. The results indicate that without risk adjustment, the returns for the subsample identified by the model as “undervalued” (model prices exceed market prices) are significantly greater than returns for the subsample identified by the model as “overvalued” (market prices exceed model prices).     

Shifting from the incurred to the expected credit loss model and stock price crash risk

Using a difference-in-differences (DID) design, this study examines the effect of shifting from the incurred credit loss model (ICL model) to the expected credit loss model (ECL model) on banks’ future stock price crash risk. We find that switching to the ECL model decreases the stock price crash risk of commercial banks. Inspired by Onali et al. (2021), we proceed with cross-sectional tests from the perspectives of opportunistic incentives, information environments, and compliance costs and find that the effect is more pronounced for (i) banks with less opportunistic incentives, proxied by state-owned property rights and managerial ownership; (ii) banks with opaque internal and external information environments, proxied by weak internal control, weak board governance, low analyst coverage, and short auditor tenure; and (iii) banks with lower implementation costs, proxied by less day-one impact and higher levels of accounting conservatism. Channel analyses show that banks increase their asset impairment provisions and the timeliness of loan loss recognition, and there is an increase in the value relevance of earnings and bank efficiency after the adoption of the ECL model. Overall, our evidence suggests that the flexibility of principle-based accounting standards influences banks’ stock price crash risk and provides implications that could be helpful to regulators and standard setters.