Monetary Policy Response in the Republic of North Macedonia and the Republic of Albania for Coping with the Pandemic COVID-19 in 2020

This study aims to analyse how the monetary policies of the Republic of North Macedonia and the Republic of Albania, as one of the two critical macroeconomic policies, have reacted in response to COVID-19 for the year 2020. Last year, the year 2020, the pandemic caused these two countries to react through monetary policy. This research examines how central banks of both countries have changed traditional monetary policy tools for tackling the pandemic, starting with open market operations, required reserve ratio, the overnight loans interest rate, and the available deposits interest rate. The research continues with analyzing whether they were used and what non-traditional tools were applied in that period. The study analysis concludes which monetary policies have been pursued in the Republic of North Macedonia and the Republic of Albania, whether there have been non-traditional tools and how the scope for interbank interest rate volatility has changed. Our study revealed that both countries had pursued an expansive monetary policy, there were also non-traditional tools, and the scope for interbank interest rate volatility has shifted towards narrowing. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

The Determinants of Net Interest Margin: An Empirical Study of Indonesia Category-IV Banks for the Period of 2014-2017

Bank’s Net Interest Margin (NIM) is a key indicator on how bank performs its intermediary function and necessary for the financial system stability. NIM is influenced by both internal and external determinants. This study aims to analyze these internal and external determinants of NIM for Indonesia’s Category-IV banks in the period of 2014 to 2017. The internal determinants used as independent variables are Loan to Deposit Ratio (LDR), Operating Efficiency Ratio (OER), and Capital Adequacy Ratio (CAR). Meanwhile, the external determinants used as independent variables are Interest Rate volatility and Inflation. This study uses four Indonesia’s Category-IV banks which were chosen by purposive sampling methodology based on criteria set with quarterly time horizon. These 4 commercial banks are those listed as ‘Category-IV’ or BUKU 4 during the study’s time frame. The statistical approach being used is panel least square fixed effect model. This study reveals that Loan to Deposit Ratio (LDR), Operating Efficiency Ratio (OER), and Inflation have positive significant influence toward NIM. In contrast, Capital Adequacy Ratio (CAR) shows negative significant influence, while Interest Rate volatility contributes insignificantly to NIM. The overall findings underlined that contribution of internal factors are consistent in influencing the value of NIM in a significant way.

The Impact of Interest Rate Volatility on Stock Returns Volatility: Empirical Evidence from Pakistan Stock Exchange

Apprehension pertaining to Stock return volatility always has been producing the appreciable significance in the various current research works and it has been lucrative to many researchers for forecasting stock market volatility. This study is about the forecasting of stock returns volatility on the basis of interest rate volatility in the well established Pakistan Stock Exchange (PSX). The stock returns are calculated on the basis of KSE 100 index and interest rate volatility is calculated on the basis of monthly treasury bills rate during a period of 1994 to 2016. Various volatility models like Auto Regressive Conditional Heteroscedasticity (ARCH) and Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) were used to predict stock return volatility on the basis of interest rate volatility in Pakistan. ARCH model is one of the well known methods to forecast the error term in the data and which will certain our forecast regarding stock prices. In the Pakistan Stock Exchange the ARCH (1, 1) has been statistically significantly proved. The GARCH (1, 1) model is also used to estimate the stock volatility. This model shows the short run volatility affect the lagged stock returns and is contributing to the overall volatility. The sum of α and β is less than 1 so the short run volatility is positively related to the overall stock volatility. The GARCH (1, 1) model has outperformed the other volatility models in the case of Pakistan Stock Exchange.

The Impact of Financial Risks on Financial Investment in Infrastructure: Based on a Two-Factor Stochastic Differential Equation

Financial risks, such as inflation and interest rate changes, significantly affect the costs and benefits of infrastructure projects. Nevertheless, there is a dearth of research concerning financial investment (government subsidies) for infrastructure projects in the context of inflation and interest rate changes. Accordingly, this study builds a stochastic differential equation model based on inflation rate and interest rate, through which the expression of government subsidies in public-private partnership is optimised. Specifically, the Monte Carlo simulation was used to undertake a calculation of the present value of operating loss subsidy and risk-sharing subsidy for the N City Metro Line 3. Subsequently, the effect of inflation, nominal interest rates, interest rate volatility, as well as inflation volatility, on the present value of operating loss subsidies was investigated. It was established that the dynamic random discount rate based on inflation rate and interest rate may effectively simulate the effect of inflation rate and interest rate changes on project operating loss. Moreover, it is feasible to calculate the present value of the risk-adjusted operating loss subsidy and the present value of the risk-sharing subsidy. Inflation rate, inflation volatility, and interest rate volatility are positively correlated with the present value of operating loss subsidies, whereas the interest rate is negatively correlated with the present value of inflation-adjusted operating loss subsidies. Inflation volatility has the greatest effect on the present value of subsidies, followed by interest rate volatility and inflation rate. Ultimately, this paper provides an effective tool for quantitative simulation of and risk-sharing in public-private partnership projects, which can facilitate a regional economy’s sustainable development.

A UNIFIED MARKET MODEL FOR SWAPTIONS AND CONSTANT MATURITY SWAPS

Internal-rate-of-return (IRR) settled swaptions are the main interest rate volatility instruments in the European interest rate markets. Industry practice is to use an approximation formula to price IRR swaptions based on Black model, which is not arbitrage-free. We formulate a unified market model to incorporate both swaptions and constant maturity swaps (CMS) pricing under a single, self-consistent framework. We demonstrate that the model is able to calibrate to market quotes well, and is also able to efficiently price both IRR-settled and swap-settled swaptions, along with CMS products. We use the model to illustrate the difference in implied volatilities for IRR-settled payer and receiver swaptions, the pricing of zero-wide collars and in-the-money (ITM) swaptions, the implication on put-call parity, and the issue of negative vega. These findings offer important insights to the ongoing reform in the European swaption market.

Interest Rate Volatility and No-Arbitrage Affine Term Structure Models

Within the affine framework, many have observed a tension between matching conditional first and second moments in dynamic term structure models (DTSMs). Although the existence of this tension is generally accepted, less understood is the mechanism that underlies it. We show that no arbitrage along with the rich information in the cross section of yields has strong implications for both the dynamics of volatility and the forecasts of yields. We show that this link implied by the absence of arbitrage—and not the factor structure per se—underlies the tension between first and second moments found in the literature. Adding to recent research that has suggested that no-arbitrage restrictions are nearly irrelevant in Gaussian DTSMs, our results show that no-arbitrage restrictions are potentially relevant when there is stochastic volatility. This paper was accepted by Gustavo Manso, finance.

Why is bank credit in Brazil the most expensive in the world?

The article reviews the scientific literature about the determinants of credit spreads in Brazil. Econometric evidence shows that market concentration, a proxy for (un)competitive behavior, is statistically significant for all studies surveyed. We posit that that higher concentration is part of a well-defined strategy by the Brazilian Central Bank that favors prudence over efficiency. Other variables that help explain why spread in Brazil is among the highest in the world include market microstructure, operating costs, credit risk, opportunity costs, managerial quality, nominal interest rates (SELIC), market concentration, interest rate volatility, earmarked credit, and GDP.

Valuation discrepancies in money market funds during market disruptions: evidence from Egypt

Money market funds (MMFs) are generally considered safe investment vehicles, but the 2008 global financial crisis showed their vulnerability during market disruptions resulting in increased regulatory oversight across developed markets to protect investors. This paper examines the effect of MMF accounting regulation on investors in an emerging market context. It hypothesizes that the continued use of amortized cost methods to account for MMFs’ Net Asset Value (NAV) during market disruptions can result in unfair treatment of investors. The Egyptian money market provided a unique laboratory to test this hypothesis over a prominent economic crisis that combined high levels of interest rate volatility with a redemption-only structure for MMFs. A model that measures the discrepancies between the amortized and floating market NAVs per certificate for various money market portfolios (MMPs) simulating MMFs of different durations is tested using the Egyptian data. A sharp rise in interest rates is found to lead to significant discrepancies between the amortized NAV per certificate relative to their floating value. Serial investor redemptions of the certificates compound the discrepancies, but only certificate holders remaining in the funds bear the accumulated losses, which are augmented for portfolios with higher durations. The results suggest that emerging market regulators consider introducing the rules that switch to floating NAV calculations for MMFs during such periods to promote equality across all investors.

Evidence of customer sophistication behaviour in deposit markets: the case of Qatar

PurposeThe paper investigates the interest rate policy transmission mechanism and the role of market structure of the banking industry in Qatar.Design/methodology/approachCompetitiveness indexes are used to measure the degree of market power in the banking industry in Qatar. The momentum threshold autoregressive model is applied over the monthly period from January 2005 to June 2018 to examine the magnitude of intermediation and adjustment to disequilibria in the deposit market. In addition, to model interest rate volatility and overcome the problem of heteroscedastic errors in the error correction standard models, an asymmetric EC-EGARCH-M model is applied.FindingsThe findings suggest incomplete pass-through and asymmetric response to monetary shocks. The asymmetric adjustment mechanism is found to be downward rigid which suggests a high degree of customer sophistication and an elastic supply of deposits. The results of the EC-EGARCH-M show that the impact of monetary policy shocks has a significant positive impact on deposit interest rates and that negative monetary shocks trigger more conditional interest rate volatility in the next period than positive monetary shocks for a short maturity rate.Originality/valueThe paper is the first to highlight the behaviour of the interest rate pass through channel and measures the degree of competitiveness of the banking industry for the case of a small, rich country. In addition, using recent data, the paper applies different econometric methodologies and overcomes the problem of heteroskedastic errors by modelling the interest rate volatility using the EC-EGARCH-M model.