Risk-adjusted Return On Capital Research Articles

The Risk Management And Usage Of The Net Present Value-At-Risk To Evaluate Indonesian Toll Road

This study evaluates the financial feasibility and risk management of toll road infrastructure so as characteristics of toll road projects prone to risks and uncertainties. The study was conducted using case study and qualitative methods. The parameters used to determine the fair value of the project through parameters such as NPV, IRR, Payback Period, NPV at risk, and Risk Adjusted Return on Capital (RAROC) for financial and risk-based feasibility evaluation. This study also conducted a risk assessment in risk management analysis. The study provides various illustrations of possible outputs (NPV) and risk variability so that it can provide a more communicative and varied offer and recommendation, especially for investors as a consideration in making investment decisions. The results of the risk assesment process showed a low to the very high-risk level that requires different treatment. This study contributes understanding the investment in Indonesia toll road project

Determinasi RAROC Bank menggunakan Faktor Internal dan Faktor Eksternal Bank serta Size sebagai Variabel Moderasi

This study aims to explore the influence of internal and external company factors on bank profitability with size as a moderating variable. The company's financial ratios and macroeconomic variables are used to determine bank profitability, specifically the Risk-Adjusted Return on Capital (RAROC). A panel data model is employed to determine the RAROC in Indonesia for the period 2014 to 2023. This study finds that Non-Performing Loans, Electricity Consumption, Oil Prices, Exchange Rate, and FED Rate do not affect RAROC. However, Net Interest Margin and Total Assets have a significantly negative effect on RAROC, while Market Power has a significantly positive effect on RAROC. Additionally, Total Assets strengthen the negative effect of Non-Performing Loans and Net Interest Margin on RAROC, while Total Assets strengthen the positive effect of Market Power, Electricity Consumption, Oil Prices, Exchange Rate, and FED Rate on RAROC.

The impact of revenue diversification on profitability, capital, and risk in US banks by size

This study examines the influence of US banks’ revenue diversification on profitability, capital, and credit risk by size. By a simple decomposition of Return On Capital (ROC) I show how popular revenue diversification measures reflect both the ROC and risk-adjusted ROC. I find substantial differences between size groups concerning the impact of revenue diversification measures on: profitability, capital, and credit risk both in comparative statics and dynamically along the business cycles. Profitability, capital, and credit risk in medium size banks reflect insensitivity to these measures compared to other size groups; large and small alike. A similar ‘smile’ pattern has also been found regarding the respective pairwise conditional correlations between profitability, capital, and credit risk.

Financial Asset Risk Measurement Based on Smart Sensor Big Data Security Analysis and Bayesian Posterior Probability Model

Following the speeding up of a process of financial globalization, the risks faced by financial markets have become more complex and diversified. Correlated patterns among financial assets exhibit characteristics of nonlinearity, asymmetry, and tail correlation. The original linear correlation analysis method is no longer suitable, but relevant information describing financial risks. In order to confirm whether an asset is safe, the key is to study and master its volatility, and this is based on our mastery of volatility measurement skills. This article is based on smart sensor big data security analysis and Bayesian analysis. The risk measurement of financial assets based on the empirical probability model is studied. The GARCH-t(1,1) model is selected according to the Akaike information criterion (AIC) after the generalized autoregressive conditional heteroskedasticity (GARCH) model is established by the EViews software. According to the results of probability integral transformation, a series of correlation coefficients and degrees of freedom oft-copula are obtained by the maximum likelihood estimation method. This paper uses the risk-adjusted return on capital (RAROC) method to evaluate the risk performance of financial assets. Financial institutions can only retain and absorb the financial market risks that cannot be avoided and transferred. The edge user node sends the service request to the edge server node. The edge server uses the model proposed in this paper to evaluate the user’s trust and selects the corresponding service level according to the trust level corresponding to the calculated credibility results. The data show that the edge calculation takes 0.2581 seconds, while the linear search takes about 64 seconds. The results show that intelligent edge computing improves the accuracy and efficiency of financial asset risk measurement.

Optimizing balance sheet performance: Advanced asset and liability management strategies for financial stability

Optimizing balance sheet performance is critical for financial institutions seeking to enhance profitability, maintain liquidity, and ensure long-term stability. Asset and Liability Management (ALM) plays a central role in achieving these objectives by aligning the management of assets, liabilities, and capital to mitigate risks associated with interest rates, liquidity, and credit. This review explores advanced ALM strategies designed to optimize the balance sheet while navigating complex financial environments. Key strategies include interest rate risk management through duration gap analysis, hedging instruments, and interest rate swaps; liquidity management techniques leveraging cash flow matching, stress testing, and scenario planning; and capital optimization using risk-adjusted return on capital (RAROC) models. Additionally, managing leverage ratios, diversifying funding sources, and optimizing the cost of funding are highlighted as critical to enhancing financial resilience. The integration of technology, particularly data analytics, artificial intelligence, and automation tools, is increasingly important in enhancing ALM practices. These technologies enable predictive modeling, real-time monitoring, and efficient reporting, thereby improving decision-making and risk management. The review also presents case studies of successful ALM implementations, demonstrating how institutions have effectively managed interest rate and liquidity risks during periods of market volatility. Lastly, the discussion extends to future trends, such as the impact of regulatory shifts, the rise of green finance, and the integration of digital innovations in financial management. By adopting a proactive and integrated ALM approach, financial institutions can optimize balance sheet performance, reduce risk exposure, and adapt to evolving economic and regulatory landscapes, ultimately achieving sustainable financial stability.

RISIKO DAN PENGEMBALIAN HASIL PADA INVESTASI DEPOSITO MUDHARABAH BANK SYARIAH

The research objective is to determine the risk of mudharabah deposit investment in Islamic banking measured by the VaR approach and to determine the rate of return on bank investment using mudharabah bank deposit funds measured by the RAROC approach. This type of research is a quantitative study and uses the VaR and RAROC measurement techniques. It is indicated that long-term investment using mudharabah deposits is more risky than short-term investments, this is indicated by the level of change in monthly returns that fluctuates significantly. But customers prefer long-term investments in mudharabah deposits marked by the amount of 12-month deposit funds that reach 35.63% of the total mudharabah deposit funds managed by the bank. This indicates that the customer chooses a long-term risk in order to get the maximum benefit. Risk Adjusted Return On Capital (RAROC) analysis describes the level of income earned by Islamic banks that has been adjusted to the risks that will occur, this shows that the income earned by the bank has not been able to cover the possible potential losses that will occur. The RAROC result shows the following figures for each year 20, -19, -4. The RAR value shows a positive overall number, which indicates that the bank is considered capable of controlling risks that can erode bank capital.

Risk Capital: Theory and Applications

After a brief review of the current theory and practice of risk capital by financial firms, the authors define the concept of risk capital and identify the costs and benefits of using more or less of it. Next, they present their procedure for allocating risk capital to assets and lines of business on the basis of marginal default values, and in a way designed to prevent risk shifting and internal arbitrage. Then, they show how allocations of risk capital are likely to be affected by, and in turn influence, a financial firm's decisions about both the scale and composition of its portfolio of businesses. Finally, the authors present a number of applications and consider their implications for maximizing the value of financial firms.In so doing, the authors also show how their method produces very different allocations of risk capital than those based on two measures that have long been widely used by financial firms: value at risk (VaR) and risk‐adjusted return on capital (RAROC). Moreover, the adjusted present value (APV) rule for evaluating investment opportunities is shown to be workable for nonfinancial as well as financial firms.

Optimal planning strategy of energy internet zones based on risk adjusted return on capital

With the spread of energy internet concept, energy internet zones (EIZs) have been widely constructed and operated. EIZs supply thermal power, cooling power and some other kinds of energy to customers in addition to electricity. In EIZs, all kinds of energy are coupled together by energy converters like electric heaters. The operation of thermal power system can influence the electricity system by the electricity consumption for heating. This paper discussed a risk-averse planning problem for EIZs considering the coupling relationships of electricity, thermal power and cooling power. Because the uncertainties of load demands, renewable power and electricity prices are inevitable and have great effects on the EIZs’ economy, Conditional Value-at-Risk (CVaR) and Risk Adjusted Return on Capital (RAROC) have been introduced to the planning strategy for risk management. According to the CVaR, EIZs can determine the economic capital reserved to withstand the huge losses in extreme events. The RAROC defines the tradeoff relationships between profit and risk with economic meanings. The proposed planning model maximizes the expected annual profits with the RAROC threshold constraint for risk management. An EIZ in Shanghai has been adopted as case study to prove the validity of the proposed models.

Assessment of the Effect of CAMELS Indicators on Risk-Adjusted Return on Capital (RAROC) in the Banks listed in Iran’s Stock Market

در این پژوهش بازده سرمایه تعدیل‌شده به ریسک (RAROC) به‌عنوان یک شاخص سنجش عملکرد اقتصادی و تعدیل‌شده به ریسک تبیین و برای اولین‌بار براساس روش جدید مبتنی بر مطالعات اخیر برای همه بانک‌های پذیرفته‌شده در بورس اوراق بهادار تهران و فرابورس ایران در بازه زمانی سالهای 1391 الی 1398 محاسبه گردید. روش محاسبه این شاخص در این پژوهش یکی از وجوه تمایز آن به شمار می‌رود. در گام بعد ضمن معرفی شاخص‌های کملز (CAMELS) و تبیین اهمیت آن‌ها، اثرشان بر بازده سرمایه تعدیل‌شده به ریسک بر اساس مدل رگرسیون خطی چند متغیره و رویکرد پانل دیتا، مورد سنجش قرار گرفت. بر اساس یافته‌های پژوهش، بسیاری از بانک‌ها علی‌رغم افشای سودخالص درصورت-های مالی خود، از حیث این شاخص در وضعیت مناسبی قرار ندارند. همچنین براساس مدل اجراشده، اثر کفایت سرمایه، کیفیت مدیریت، کیفیت سود و کیفیت نقدینگی بر بازده سرمایه تعدیل‌شده به ریسک در بانک‌ها معنی‌دار تلقی شد، بدین معنا که با بهبود این شاخص‌ها می‌توان RAROC را نیز بهبود بخشید. از طرف دیگر رابطه‌ای بین کیفیت دارایی‌ها و حساسیت نسبت به ریسک بازار با این شاخص یافت نشد.

ANALISIS RISIKO DAN PENGEMBALIAN HASIL TERHADAP PEMBIAYAAN MUDARABAH PADA BANK PEMBIAYAAN RAKYAT SYARIAH (BPRS)

This study examines the risk and return that effect mudarabah financing at Islamic Rural Banks. The study uses the Value at Risk (VaR) method to measure risk and for Return using the Risk Adjusted Return on Capital (RAROC) method. The data used are secondary data were gathered from the 2016-2018 Monthly from Financial Reports that published on the Financial Services Authority website. The results of the analysis show that risk affects mudarabah financing, whereas the return of results does not affect mudarabah financing. Meanwhile, simultaneously it shows that the risk and return affect mudarabah financing financing at Islamic Rural Banks

A Raroc Valuation Scheme for Loans and Its Application in Loan Origination

In this article, a risk-adjusted return on capital (RAROC) valuation scheme for loans is derived. The critical assumption throughout the article is that no market information on a borrower’s credit quality like bond or CDS (Credit Default Swap) spreads is available. Therefore, market-based approaches are not applicable, and an alternative combining market and statistical information is needed. The valuation scheme aims to derive the individual cost components of a loan which facilitates the allocation to a bank’s operational units. After its introduction, a theoretical analysis of the scheme linking the level of interest rates and borrower default probabilities shows that a bank should only originate a loan, when the interest rate a borrower is willing to accept is inside the profitability range for this client. This range depends on a bank’s internal profitability target and is always a finite interval only or could even be empty if a borrower’s credit quality is too low. Aside from analyzing the theoretical properties of the scheme, we show how it can be directly applied in the daily loan origination process of a bank.

A RAROC Valuation Scheme for Loans and its Application in Loan Origination

In this article, a RAROC (risk-adjusted return on capital) valuation scheme for loans is derived. The critical assumption throughout the article is that no market information on a borrower’s credit quality like bond or credit default swap spreads is available. Therefore, market-based approaches are not applicable, and an alternative combining market and statistical information is needed. The valuation scheme aims to derive the individual cost components of a loan which facilitates the allocation to bank?s operational units. After its introduction, a theoretical analysis of the scheme linking the level of interest rates and borrower default probabilities shows that a bank should only originate a loan when the interest rate the borrower is willing to accept is inside the profitability range for this client. This range depends on a bank’s internal profitability target and is always a finite interval only or could even be empty if a borrower’s credit quality is too low. Aside from analyzing the theoretical properties of the scheme, we show how it can be directly applied in the daily loan origination process of a bank.

Using Economic Value Added in Ex-Ante Profitability Calculation of Bank´s Medium-Sized Clients

This article deals with the calculation of bank´s medium-sized enterprises clients´ ex-ante profi- tability and the possibility to use Economic Value Added (EVA) tools in such calculation instead of, currently in bank sector, widely used measure of Risk Adjusted Return on Capital (RAROC). Using a sample of medium-sized enterprises clients to whom a credit exposure was approved in one of the banks operating on the bank´s market within a country belonging to the European Union, the expected profitability of these clients was compared by using firstly RAROC and then compared the results to the profitability calculation using EVA tool on the same set of data. Although both measures (RAROC and EVA) are based on the same initial variables, the results of profitability measure show different outcomes in terms of clients´ profitability level and thus their contribution to the total clients´ portfolio profitability. Using EVA tool instead of RAROC measurement thus could help bank´s relationship managers and branch managers focus on those clients creating larger value added than others.

Minimal required rate of return for ex-ante profitability calculation of bank medium-sized enterprises clients

This article summarises and analyses various approaches for determination of minimal rate of return that should be required from provided credit exposures to bank clients in order for a value added for the bank shareholders to be created. The most widely used measurement for the so called ex-ante profitability calculation of bank's clients is currently Risk Adjusted Return on Capital (RAROC), which is then compared to the required rate of return. The article shows, on a hypothetical example, one of the ways of this target return estimation that could be applicable in practice, is its determination through forecast Economic Value Added (EVA). On the sample of medium-sized enterprise clients of a bank operating on the market in the Czech Republic, the article shows that using EVA for ex-ante profitability calculation can be of more informative value than using RAROC.

The Risk Measurement of China’s Insurance Fund Investment—Based on VaR Model

Since the 19th National Congress of CPC (the Communist Party of China), China has put forward more stringent requirements for the prevention and control of risks in the insurance industry. In order to measure the risk and performance of four main investment types of China’s insurance fund (bank deposit, bond investment, stock investment, fund investment), the paper first introduces the development and present situation of the insurance fund investment in China, and then uses the VaR model to measure the risk of each investment type. Finally, the performance evaluation of each investment type is carried out through the RAROC (Risk Adjusted Return on Capital) method. The result shows that China’s insurance industry still has problems such as asset-liability mismatch, hidden liquidity risk and increased credit risk. Additionally, it also reveals that there is still room for improvement in the investment structure of China’s insurance fund investment. This result not only provides relevant policy suggestions for risk management in China’s insurance industry, but also fills the blank of research in this field in recent years.

Pricing Mechanism for Inventory Finance Business under the RAROC Criterion

Risk Adjusted Return On Capital (RAROC) is a loan-pricing criterion that has become increasingly prevalent in the banking industry since the 1990s. Under RAROC, a bank sets the loan term such that a certain rate of return is achieved on the regulatory capital required by the Basel capital regulation. The amount of regulatory capital for each loan is calculated either under the standardized approach (standardized banks, the regulatory capital equals to a fixed proportion of the loan amount) or the internal rating-based (IRB) approach (IRB banks, the regulatory capital is related to the Value-at-Risk (VaR) of the loan). Using a model in which the bank first sets the loan terms and the newsvendor-type retailer then decides the order quantity and the borrowing amount, this paper quantifies the impact of the adoption of the RAROC criterion and the specific approach used to calculate regulatory capital on the bank's loan-pricing decision and the retailer's inventory decision. We find that among the loan terms that satisfy the bank's RAROC criterion, the one that benefits the retailer the most requires the bank to specify an inventory advance rate in addition to the interest rate. Under this Pareto dominant loan term, the retailer's inventory level decreases with the bank's cost of capital and regulatory capital adequacy ratio. Further, the order quantity is more sensitive to his asset level when facing an IRB bank compared to a standardized bank. For the retailer with high (low) initial asset, the retailer's profit and inventory level are higher under the IRB (standardized) loan. For the retailer with medium initial asset, an IRB loan leads to a higher retailer profit but a lower consumer welfare due to a lower inventory level. When the interest rate that the bank can charge is capped by regulation, retailers borrowing from a standardized bank are more likely to be influenced by the interest rate cap than those borrowing from an IRB bank. Under strong empire-building incentives, e.g., the bank will offer loan terms to maximize the size of the loan instead of the retailer's profit, while low-risk retailers still prefer IRB loans, retailers with medium initial asset level shift their preference from IRB banks to standardized banks.

Exploring a Risk Adjusted Return on Capital Model for the Performance and Persistence of the Indian Equity Mutual Funds

Assisting fund investors in making better investment decisions when faced with market climate change is an important subject. For this purpose, the author adopts a genetic algorithm (GA) to search for an optimal decay factor for an exponential weighted moving average model, which is used to calculate the value at risk combined with risk-adjusted return on capital (RAROC). The author then proposed a GA-based RAROC model. Next, using the model to find the optimal decay factor and investigate the performance and persistence of 31 Indian open-end equity mutual funds over the period from November 2012 to October 2015, divided into three periods: November 2012- October 2013, November 2013- October 2014, and November 2014- October 2015, which includes the global financial crisis. The author finds that for three periods, the optimal decay factors are 0.999, 0.951 and 0.990, respectively. The rankings of funds between bull and bear markets are quite different. Moreover, the proposed model improves performance persistence. That is, a fund's past performance will continue into the future.

Managing and Pricing Contingent Liquidity within a Banking Operation Using the COLA Framework

Following the financial crisis, the cost of liquidity became prevalent and effectively required banks to take such costs into account in client pricing. A common place practice is still yet to emerge. As such, in this note, we present the Costs of Liquid Assets (COLA) framework. A bank implementing such a framework would be able to provide a genuine incentive for each client towards the types of products that minimize the corresponding contingent liquidity (HQLA).We treat the portfolio of high-quality liquid assets (HQLA) as a scarce resource – in the same way that the bank’s equity is treated as a scarce resource in the Risk-adjusted Return on Capital (RAROC) framework. Via the Liquidity Coverage Ratio (LCR) ratio, the HQLA are linked to the balance sheet items (assets as well as liabilities) that produce the liquidity and funding risk. This connection is defined in a proportional way, i.e. assets and liabilities with a higher contribution to the LCR receive a higher allocation of HQLA. HQLA represent a loss of opportunity for the bank; this is referred to as the Cost of Liquid Assets (COLA). By defining a required profit margin on the allocated HQLA – the %COLA hurdle – the framework produces a natural incentive for BUs to manage their business towards a limited contribution to the LCR and make sure to obtain appropriate compensation for the amount of HQLA allocated to the BU.We apply the COLA framework to a hypothetical bank with a stylized balance sheet consisting of a few BUs. Although, we see this framework primarily as a mechanism to allocate HQLA and corresponding COLA on BU level, the framework could be extended to client portfolios, industry classes or even individual clients separately.

BARRIERS TO IMPLEMENTATION OF INTEGRATED MODELS FOR EFFICIENCY AND RISK EVALUATION

The main aim of this article is to identify and present barriers to the implementation of integrated models for evaluation of efficiency and risk. Considerations were carried out on the example of the RAROC (Risk-Adjusted Return On Capital) model implementation in a commercial bank. At the beginning integrated models were presented, with particular emphasis on RAROC model, the manner of its determination and application possibilities. Then, important assumptions and barriers to implementation of the integrated model were shown. The evolutionary and adaptive conception of implementation of such models were outlined.

ANALISA RISIKO DAN KEUNTUNGAN INVESTASI SAHAM BATU BARA DI BURSA EFEK INDONESIA (Tahun 2010-2014)

This research was motivated by the increasing value of the production and consumption of coal from year to year, but is not offset by an increase in new investment in this sector. Each selection of investment decisions certainly linked to the degree of risk and benefit ratio, in order to know how much future investment results that will be obtained with the level of risk to a minimum. The purpose of this study was to measure the level of risk and benefit ratio of shares in a coal mining company listed on the Stock Exchange during the study period 2010-2014. Calculation of the level of risk in this study was measured by VaR (Value at Risk) and the profit rate is measured with RAROC (Risk Adjusted Return on Capital). The results of this study indicate that the coal mining stocks are a potential value loss (high risk low return). The highest VaR value during the study period experienced by PKPK of 0.64300 or 64.30% in 2010. The market value of the highest RAROC during the observation period by ITMG in 2010 amounted to 0.4304 or 43%.