银保产品非正常退保风险管控及其监管

因金融危机等环境因素的影响,近年来国内投资收益率持续低迷,寿险公司的退保金额同比大幅增长（仅2012年退保金总额就高达1200亿元,同比增长超30％）,而以分红型、万能型产品为主的银行保险（简称银保）产品的退保问题尤为突出.     

终身寿险退保的利率敏感性分析——基于保单保障水平的测算

市场利率变化对于不分红终身寿险产品退保的影响很大,终身寿险保单不能够通过选择较长的缴费期来缓解市场利率变化引起的退保压力,调整预定利率能缓解退保压力;适当的分红政策能够大大缓解市场利率变化对分红型终身寿险退保的影响,但是经营效益差,分红水平低于市场预期的寿险公司产品可能会遭遇到更大的退保压力。     

国内银保业务发展分析

一、国内银行保险的总体状况银行保险业务指的是银行和保险公司在销售渠道、业务和机构等方面的相互融合。国内的银保业务开始于1995年,在保险公司的推动下,银行柜台尝试着销售一些养老金和定期寿险产品,由于产品的预期利率高于同期银行存款利率,得到公众认可。但是从1996年起,利率下调,银保产品销售不断下滑;1996年-1998年开始起步,主要在分公司层面进行合作,开展了有限的合作;在1999年后,银行保险突飞猛进,各家保险公司和几大国有银行纷纷开展银行保险业务;从2004年开始,银行保险显现逐步萎缩趋势;2005年,不同的公司具有不同策略的选择和…     

央行小幅加息对保险业影响不大

<正>一、加息不会导致退保潮和保险需求大幅下降许多人担心,保险公司实行预定利率,且该利率的上限为2.5%,加息后,一年期银行存款利率达到2.79%,保险产品相比较银行存款和其他投资型产品而言,收益率低,从而缺乏竞争优势,加息可能会引发退保潮。这种观点固然有它的道理,但是,要判断是否会出现退保潮,还必须对各险种进行综合分析,因为不同的险种有不同的特性,有的是利率敏感型,有的则不易受利率波动的影响,即使同是利率敏感型,有的会因利率上升而收益增加,而有的收益会减少。     

银保发展遇冷的深层次原因——基于资金运用效率的新视角

“银行保险”历来备受多方关注,近期中国保险市场的发展更是将“银保产品”再次推向风口浪尖。     

我国银行保险的问题及对策分析

<正>银行保险是金融合作的产物,是一种目前国际上流行的金融服务。我国银行保险销售模式由于银保双方利益难以统一、销售误导、银保自身的因素等原因,导致我国银行保险业存在不少问题,如银保合作松散、产品单一、销售队伍不专、退保金同比大幅上升、制度不完善等问题。针对这些制约银行保险发展的问题,本文提出了相应的对策。     

国外寿险领域银行保险的发展及对中国的启示

银行保险是目前国际上盛行的保险销售渠道,尤其是在寿险领域中成效显著。通过分析银行保险在寿险领域中的发展状况,研究了银行保险寿险产品的特征与趋势,以及影响银行保险在寿险领域中发展的相关因素。本文认为,我国保险公司在开展银行保险方面,应首先保证银行保险的低成本优势,同时依据现阶段的政策环境,顺应银行与客户的需求,开发新型的银保寿险产品。     

我国银行保险战略联盟模式选择与并购财富效应影响——基于AHP与Event study分析法的实证研究

本文以中国银行保险面临的困境为背景,针对银行保险发展趋势和研究现状,探讨了银保战略联盟选择模式,通过文献综述归纳总结,提出了并购为最优模式假设。为了检验假设,首先采用AHP层次分析法,研究银行保险战略联盟结构模型定性定量关系;其次对国内银行并购保险公司多样本案例运用事件分析法进行实证检验,研究发现:银行并购保险公司产生了显著的财富效应,但在不同银行间存在财富效应差异;最后,本文对银行保险发展模式进行了讨论,并对国内银行并购保险投资实践提出了可行性建议。     

国外寿险领域银行保险的发展及对中国的启示北大核心CSSCISSCI

银行保险是目前国际上盛行的保险销售渠道,尤其是在寿险领域中成效显著。通过分析银行保险在寿险领域中的发展状况,研究了银行保险寿险产品的特征与趋势,以及影响银行保险在寿险领域中发展的相关因素。本文认为,我国保险公司在开展银行保险方面,应首先保证银行保险的低成本优势,同时依据现阶段的政策环境,顺应银行与客户的需求,开发新型的银保寿险产品。     

内蒙古银行保险业务合作发展情况的调查分析

2012年以来,内蒙古银保业务扭转了去年底负增长的态势,实现低速增长,银保产品保障覆盖面进一步扩大,但银保新单保费出现小幅下降。银保产品竞争力不足,产品过多强调投资价值,未突出保险核心保障功能。市场竞争不规范,寿险市场分红险"一险独大",退保风险隐患较大等潜在的问题逐渐显现,迫切需要加强内外部监管。     

Is long memory necessary? An empirical investigation of nonnegative interest rate processes

This paper analyzes a class of nonnegative processes for the short-term interest rate. The dynamics of interest rates and yields are driven by the dynamics of the conditional volatility of the pricing kernel. We study Markovian interest rate processes as well as more general non-Markovian processes that display “short” and “long” memory. These processes also display heteroskedasticity patterns that are more general than those of existing models. We find that deviations from the Markovian structure significantly improve the empirical performance of the model. Certain aspects of the long memory effect can be captured with a (less parsimonious) short memory parameterization, but a simulation experiment suggests that the implied term structures corresponding to the estimated long- and short-memory specifications are very different. We also find that the choice of proxy for the short rate affects the estimates of heteroskedasticity patterns.     

International linkages and macroeconomic news effects on interest rate volatility — Australia and the US

We examine international linkages between daily time series of US and Australian 3-month treasury bills and 10-year government bonds from 1987–1995, paying particular attention to the effects of macroeconomic announcements in both countries. The two countries' interest rate data are modeled by a bivariate exponential generalized autoregressive conditional heteroscedasticity (EGARCH) formulation. The results suggest that market participants believed the Reserve Bank of Australia targeted the consumer price index (CPI), while the Federal Reserve targeted economic activity. Monetary policy announcements had significant effects on interest rates, as well as on their volatility in the short term. US macroeconomic activity announcements significantly moved Australian interest rates, particularly at the short end. Australian interest rates moved significantly in response to the previous day's US interest rate shocks. The conditional volatility of the Australian interest rate changes was also significantly influenced by lagged US interest rate shocks, as well as by surprises in US macroeconomic announcements. Some macroeconomic news announcements raised conditional volatilities, while others reduced them. Overall, there was a remarkable and complex array of linkages between the two countries.     

Are there nonlinearities in short‐term interest rates?

The present paper investigates the characteristics of short‐term interest rates in several countries. We examine the importance of nonlinearities in the mean reversion and volatility of short‐term interest rates. We examine various models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate. We find that different markets require different models. In particular, we find evidence of nonlinear mean reversion in some of the countries that we examine, linear mean reversion in others and no mean reversion in some countries. For all countries we examine, there is strong evidence of the need for the volatility of interest rate changes to be highly sensitive to the level of the short‐term interest rate. Out‐of‐sample forecasting performance of one‐factor short rate models is poor, stemming from the inability of the models to accommodate jumps and discontinuities in the time series data.     

Multi-Factor Cox-Ingersoll-Ross Models of the Term Structure: Estimates and Tests from a Kalman Filter Model

This paper presents a method for estimating multi-factor versions of the Cox-Ingersoll-Ross (1985b) model of the term structure of interest rates. The fixed parameters in one, two, and three factor models are estimated by applying an approximate maximum likelihood estimator in a state-space model using data for the U.S. treasury market. A nonlinear Kalman filter is used to estimate the unobservable factors. Multi-factor models are necessary to characterize the changing shape of the yield curve over time, and the statistical tests support the case for two and three factor models. A three factor model would be able to incorporate random variation in short term interest rates, long term rates, and interest rate volatility.     

Domestic variance and international comovement bonds tests of interest rates

This article demonstrates that long rates exhibit both domestic excess variance and international excess comovement compared to fundamental yields derived from short rates under the rational expectations theory of term structure. The results are consistent for all countries sampled: the US, UK, Canada, Germany, and Japan. Probing deeper, long rates are found to “overreact” to domestic expected future inflation and/or short real rates both of which are the underlying components of the short nominal rate according to the Fisher hypothesis. Since inflation rates as well as short real rates are highly correlated between countries, the excess volatility in long rates translates into excess covariance (“co-overreact”) internationally.     

Forecasting Surrender Rates Using Elliptical Copulas and Financial Variables

A multistage stochastic model to forecast surrender rates for life insurance and pension plans is proposed. Surrender rates are forecasted by means of Monte Carlo simulation after a sequence of GLM, ARMA-GARCH, and copula fitting is executed. The model is illustrated by applying it to age-specific time series of surrender rates derived from pension plans with annuity payments of a Brazilian insurer. In the GLM process, the only macroeconomic variable used as an explanatory variable is the Brazilian real short-term interest rate. The advantage of such a variable is that we can take future market expectation through the current term structure of interest rates. The GLM residuals of each age/gender group are then modeled by ARMA-GARCH processes to generate i.i.d. residuals. The dependence among these residuals is then modeled by multivariate Gaussian and Student's t copulas. To produce a conditional forecast on a stock market index, in our application we used the residuals of an ARMA-GARCH model fitted to the Brazilian stock market index (Ibovespa) returns, which generates one of the marginal distributions used in the dependence modeling through copulas. This strategy is adopted to explain the high and uncommon surrender rates observed during the recent economic crisis. After applying known simulation methods for elliptical copulas, we proceeded backwards to obtain the forecasted distributions of surrender rates by application, in the sequel, of ARMA-GARCH and GLM models. Additionally, our approach produced an algorithm able to simulate multivariate elliptical copulas conditioned on a marginal distribution. Using this algorithm, surrender rates can be simulated conditioned on stock index residuals (in our case, the residuals of the Ibovespa returns), which allows insurers and pension funds to simulate future surrender rates assuming a financial stress scenario with no need to predict the stock market index.     

A Two-Factor Model for Low Interest Rate Regimes

This paper derives a two-factor model for the term structure of interest rates that segments the yield curve in a natural way. The first factor involves modelling a non-negative short rate process that primarily determines the early part of the yield curve and is obtained as a truncated Gaussian short rate. The second factor mainly influences the later part of the yield curve via the market index. The market index proxies the growth optimal portfolio (GOP) and is modelled as a squared Bessel process of dimension four. Although this setup can be applied to any interest rate environment, this study focuses on the difficult but important case where the short rate stays close to zero for a prolonged period of time. For the proposed model, an equivalent risk neutral martingale measure is neither possible nor required. Hence we use the benchmark approach where the GOP is chosen as numeraire. Fair derivative prices are then calculated via conditional expectations under the real world probability measure. Using this methodology we derive pricing functions for zero coupon bonds and options on zero coupon bonds. The proposed model naturally generates yield curve shapes commonly observed in the market. More importantly, the model replicates the key features of the interest rate cap market for economies with low interest rate regimes. In particular, the implied volatility term structure displays a consistent downward slope from extremely high levels of volatility together with a distinct negative skew. 1991 Mathematics Subject Classification: primary 90A12; secondary 60G30; 62P20 JEL Classification: G10, G13     

Interest Rate Caps “Smile” Too! But Can the LIBOR Market Models Capture the Smile?

Using 3 years of interest rate caps price data, we provide a comprehensive documentation of volatility smiles in the caps market. To capture the volatility smiles, we develop a multifactor term structure model with stochastic volatility and jumps that yields a closed‐form formula for cap prices. We show that although a three‐factor stochastic volatility model can price at‐the‐money caps well, significant negative jumps in interest rates are needed to capture the smile. The volatility smile contains information that is not available using only at‐the‐money caps, and this information is important for understanding term structure models.     

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.