Journal of Risk and Financial Management

Research

12 pages, 474 KiB

Open AccessArticle

A Deep Learning Integrated Cairns-Blake-Dowd (CBD) Sytematic Mortality Risk Model

by Joab Odhiambo, Patrick Weke and Philip Ngare

J. Risk Financial Manag. 2021, 14(6), 259; https://doi.org/10.3390/jrfm14060259 - 8 Jun 2021

Cited by 4 | Viewed by 3843

Many actuarial science researchers on stochastic modeling and forecasting of systematic mortality risk use Cairns-Blake-Dowd (CBD) Model (2006) due to its ability to consider the cohort effects. A three-factor stochastic mortality model has three parameters that describe the mortality trends over time when [...] Read more.

Many actuarial science researchers on stochastic modeling and forecasting of systematic mortality risk use Cairns-Blake-Dowd (CBD) Model (2006) due to its ability to consider the cohort effects. A three-factor stochastic mortality model has three parameters that describe the mortality trends over time when dealing with future behaviors. This study aims to predict the trends of the model,

k_{t}^{(2)}

by applying the Recurrent Neural Networks within a Short-Term Long Memory (an artificial LSTM architecture) compared to traditional statistical ARIMA (p,d,q) models. The novel deep learning (machine learning) technique helps integrate the CBD model to enhance its accuracy and predictive capacity for future systematic mortality risk in countries with limited data availability, such as Kenya. The results show that Long Short-Term Memory network architecture had higher levels of precision when predicting the future systematic mortality risks than traditional methods. Ultimately, the results can be implemented by Kenyan insurance firms when modeling and forecasting systematic mortality risk helpful in the pricing of Annuities and Assurances. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Figure 1

12 pages, 447 KiB

Open AccessArticle

Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach

by Ioannis E. Tsolas

J. Risk Financial Manag. 2021, 14(5), 214; https://doi.org/10.3390/jrfm14050214 - 10 May 2021

Viewed by 2203

Abstract

This paper employs a cross-sectional research design to collect quantitative data for a group of Greek pharmaceutical companies in order to evaluate their credit risk. The data are processed using a variety of quantitative approaches, including series two-stage data envelopment analysis (DEA) combined [...] Read more.

This paper employs a cross-sectional research design to collect quantitative data for a group of Greek pharmaceutical companies in order to evaluate their credit risk. The data are processed using a variety of quantitative approaches, including series two-stage data envelopment analysis (DEA) combined with bootstrap and hierarchical clustering. The results of the two-stage DEA bootstrapped analysis indicate that the key problem with the firms’ performance is a lack of effectiveness rather than operating efficiency. The lack of a correlation between operating efficiency and effectiveness indicates that the firms’ performance metrics are unrelated. As a result, a bootstrapped DEA-based synthetic indicator is developed to be used with the other performance metrics as inputs to hierarchical clustering to divide sample firms into credit risk clusters. The series two-stage DEA bootstrapped approach used in this study could aid firms in evaluating their performance and increasing their competitive advantages. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Figure 1

20 pages, 385 KiB

Open AccessArticle

An Analytic Approach for Pricing American Options with Regime Switching

by Leunglung Chan and Song-Ping Zhu

J. Risk Financial Manag. 2021, 14(5), 188; https://doi.org/10.3390/jrfm14050188 - 21 Apr 2021

Cited by 8 | Viewed by 2570

Abstract

This paper investigates the American option price in a two-state regime-switching model. The dynamics of underlying are driven by a Markov-modulated Geometric Wiener process. That means the interest rate, the appreciation rate, and the volatility of underlying rely on hidden states of the [...] Read more.

This paper investigates the American option price in a two-state regime-switching model. The dynamics of underlying are driven by a Markov-modulated Geometric Wiener process. That means the interest rate, the appreciation rate, and the volatility of underlying rely on hidden states of the economy which can be interpreted in terms of Markov chains. By means of the homotopy analysis method, an explicit formula for pricing two-state regime-switching American options is presented. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Figure 1

13 pages, 231 KiB

Open AccessArticle

Information Frictions and Stock Returns

by Xiaolou Yang

J. Risk Financial Manag. 2020, 13(7), 140; https://doi.org/10.3390/jrfm13070140 - 1 Jul 2020

Cited by 1 | Viewed by 2083

Abstract

The purpose of this paper is to assess the impact of ambiguity on financial analyst forecast incentives and the associated abnormal stock returns. I present a model incorporating ambiguity aversion into a two-period Lucas tree model. The resulting model confirms the role of [...] Read more.

The purpose of this paper is to assess the impact of ambiguity on financial analyst forecast incentives and the associated abnormal stock returns. I present a model incorporating ambiguity aversion into a two-period Lucas tree model. The resulting model confirms the role of ambiguity in the determination of asset returns. In particular, the model with ambiguity aversion generates a lower price and a higher required rate of returns compared to the classical model without ambiguity concern. I construct a measure of ambiguity and provide empirical evidence showing that the incentive of analysts to misrepresent information is a function of ambiguity. Analysts are more likely to bias their forecasts when it is more difficult for investors to detect their misrepresentation. Under ambiguity, analysts’ optimistic forecasts for good/bad news tend to deteriorate. Moreover, stock returns are positively related with ambiguity. Under ambiguity neither good nor bad news is credible. Investors systematically underreact to good news forecast and overreact to bad news forecast when ambiguity exists. Full article

(This article belongs to the Special Issue Quantitative Risk)

24 pages, 370 KiB

Open AccessArticle

Modeling Portfolio Credit Risk Taking into Account the Default Correlations Using a Copula Approach: Implementation to an Italian Loan Portfolio

by Annalisa Di Clemente

J. Risk Financial Manag. 2020, 13(6), 129; https://doi.org/10.3390/jrfm13060129 - 17 Jun 2020

Cited by 2 | Viewed by 3794

Abstract

This work aims to illustrate an advanced quantitative methodology for measuring the credit risk of a loan portfolio allowing for diversification effects. Also, this methodology can allocate the credit capital coherently to each counterparty in the portfolio. The analytical approach used for estimating [...] Read more.

This work aims to illustrate an advanced quantitative methodology for measuring the credit risk of a loan portfolio allowing for diversification effects. Also, this methodology can allocate the credit capital coherently to each counterparty in the portfolio. The analytical approach used for estimating the portfolio credit risk is a binomial type based on a Monte Carlo Simulation. This method takes into account the default correlations among the credit counterparties in the portfolio by following a copula approach and utilizing the asset return correlations of the obligors, as estimated by rigorous statistical methods. Moreover, this model considers the recovery rates as stochastic and dependent on each other and on the time until defaults. The methodology utilized for coherently allocating credit capital in the portfolio estimates the marginal contributions of each obligor to the overall risk of the loan portfolio in terms of Expected Shortfall (ES), a risk measure more coherent and conservative than the traditional measure of Value-at-Risk (VaR). Finally, this advanced analytical structure is implemented to a hypothetical, but typical, loan portfolio of an Italian commercial bank operating across the overall national country. The national loan portfolio is composed of 17 sub-portfolios, or geographic clusters of credit exposures to 10,500 non-financial firms (or corporates) belonging to each geo-cluster or sub-portfolio. The outcomes, in terms of correlations, portfolio risk measures and capital allocations obtained from this advanced analytical framework, are compared with the results found by implementing the Internal Rating Based (IRB) approach of Basel II and III. Our chief conclusion is that the IRB model is unable to capture the real credit risk of loan portfolios because it does not take into account the actual dependence structure among the default events, and between the recovery rates and the default events. We underline that the adoption of this regulatory model can produce a dangerous underestimation of the portfolio credit risk, especially when the economic uncertainty and the volatility of the financial markets increase. Full article

(This article belongs to the Special Issue Quantitative Risk)

26 pages, 694 KiB

Open AccessArticle

The Influence of Domestic and Foreign Shocks on Portfolio Diversification Gains and the Associated Risks

by Seema Narayan

J. Risk Financial Manag. 2019, 12(4), 160; https://doi.org/10.3390/jrfm12040160 - 10 Oct 2019

Cited by 5 | Viewed by 3602

Abstract

This paper evaluates the influence of foreign or domestic stock market return and return of volatility shocks on dynamic conditional correlations (DCCs) between international stock markets and correlation volatility, respectively. The correlations between markets have implications for the gains from portfolio diversification, while [...] Read more.

This paper evaluates the influence of foreign or domestic stock market return and return of volatility shocks on dynamic conditional correlations (DCCs) between international stock markets and correlation volatility, respectively. The correlations between markets have implications for the gains from portfolio diversification, while correlation volatilities can be seen as risks to portfolio diversification. Meanwhile, domestic shocks are sourced from the return and return volatility from 24 developed, emerging, and frontier stock markets. The US stock market is the source of foreign shocks. The domestic and foreign shocks are derived using market-based returns and under bearish market conditions. We estimate multivariate exponential generalized autoregressive conditional heteroskedasticity (E-GARCH) models using daily and monthly MSCI based stock price data of selected developed, emerging, and frontier markets over 1993:1–2014:1. Our key results are as follows. Domestic market shocks were significant drivers of gains from portfolio diversification most of the time, although the US market effects were relatively stronger. On the other hand, the US, in terms of the number of significant cases as well as the size effects of shocks, dominated as a determinant of correlation volatility (or risks to portfolio diversification). Further, under bear market conditions, adjustments in correlations and correlation volatilities are found to be mostly US-induced. Bearish shocks, rather than market return based shocks, show strong evidence of the leverage effect. Signs of persistence of shocks are mainly noticed under bearish conditions. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Figure 1

29 pages, 7823 KiB

Open AccessArticle

Empirical Credit Risk Ratings of Individual Corporate Bonds and Derivation of Term Structures of Default Probabilities

by Takeaki Kariya, Yoshiro Yamamura and Koji Inui

J. Risk Financial Manag. 2019, 12(3), 124; https://doi.org/10.3390/jrfm12030124 - 23 Jul 2019

Cited by 3 | Viewed by 4717

Abstract

Undoubtedly, it is important to have an empirically effective credit risk rating method for decision-making in the financial industry, business, and even government. In our approach, for each corporate bond (CB) and its issuer, we first propose a credit risk rating (Crisk-rating) system [...] Read more.

Undoubtedly, it is important to have an empirically effective credit risk rating method for decision-making in the financial industry, business, and even government. In our approach, for each corporate bond (CB) and its issuer, we first propose a credit risk rating (Crisk-rating) system with rating intervals for the standardized credit risk price spread (S-CRiPS) measure presented by Kariya et al. (2015), where credit information is based on the CRiPS measure, which is the difference between the CB price and its government bond (GB)-equivalent CB price. Second, for each Crisk-homogeneous class obtained through the Crisk-rating system, a term structure of default probability (TSDP) is derived via the CB-pricing model proposed in Kariya (2013), which transforms the Crisk level of each class into a default probability, showing the default likelihood over a future time horizon, in which 1545 Japanese CB prices, as of August 2010, are analyzed. To carry it out, the cross-sectional model of pricing government bonds with high empirical performance is required to get high-precision CRiPS and S-CRiPS measures. The effectiveness of our GB model and the S-CRiPS measure have been demonstrated with Japanese and United States GB prices in our papers and with an evaluation of the credit risk of the GBs of five countries in the EU and CBs issued by US energy firms in Kariya et al. (2016a, b). Our Crisk-rating system with rating intervals is tested with the distribution of the ratings of the 1545 CBs, a specific agency’s credit rating, and the ratings of groups obtained via a three-stage cluster analysis. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Graphical abstract

15 pages, 403 KiB

Open AccessArticle

Default Risk and Cross Section of Returns

by Nusret Cakici, Sris Chatterjee and Ren-Raw Chen

J. Risk Financial Manag. 2019, 12(2), 95; https://doi.org/10.3390/jrfm12020095 - 6 Jun 2019

Cited by 4 | Viewed by 3226

Abstract

Prior research uses the basic one-period European call-option pricing model to compute default measures for individual firms and concludes that both the size and book-to-market effects are related to default risk. For example, small firms earn higher return than big firms only if [...] Read more.

Prior research uses the basic one-period European call-option pricing model to compute default measures for individual firms and concludes that both the size and book-to-market effects are related to default risk. For example, small firms earn higher return than big firms only if they have higher default risk and value stocks earn higher returns than growth stocks if their default risk is high. In this paper we use a more advanced compound option pricing model for the computation of default risk and provide a more exhaustive test of stock returns using univariate and double-sorted portfolios. The results show that long/short hedge portfolios based on Geske measures of default risk produce significantly larger return differentials than Merton’s measure of default risk. The paper provides new evidence that mediates between the rational and behavioral explanations of value premium. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Figure 1

19 pages, 453 KiB

Open AccessArticle

Tax Competitiveness of the New EU Member States

by Askoldas Podviezko, Lyudmila Parfenova and Andrey Pugachev

J. Risk Financial Manag. 2019, 12(1), 34; https://doi.org/10.3390/jrfm12010034 - 14 Feb 2019

Cited by 9 | Viewed by 4665

Abstract

This paper investigates tax competitiveness among the EU member countries. The tax competition of countries causes both positive and negative effects on macroeconomic processes such as the effectiveness of government spending, the rationality of supply of externalities, and the length and amplitudes of [...] Read more.

This paper investigates tax competitiveness among the EU member countries. The tax competition of countries causes both positive and negative effects on macroeconomic processes such as the effectiveness of government spending, the rationality of supply of externalities, and the length and amplitudes of business cycles. A considerable reduction of corporate tax in the EU is related to increased tax competition after new members entered the EU. Multiple criteria methods were chosen for the quantitative evaluation of EU countries from different regions of the EU. Criteria of evaluation were chosen and structured into a hierarchy. The convergence process of the new members of the EU is reinforced with the increasing tax competitiveness of such countries. Results of the multiple criteria evaluation revealed both the factors that increased the tax competitiveness of new members of the EU, and outlined the factors that hampered such competition. Full article

(This article belongs to the Special Issue Quantitative Risk)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Quantitative Risk

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (9 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI