We study dynamic conditional correlations of Central Bank Digital Currency (CBDC) uncertainty and attention indices with US dollar futures, 1-year US government bond, and gold futures. We find that USD futures hedges CBDC uncertainty, while the US bond hedges the CBDC uncertainty index subsequent to 2019. Interestingly, gold does not hedge CBDC uncertainty. The CBDC attention index exerts a negative effect on the other assets. These results are important for portfolio management.

In this paper, we examine the time-varying tail risks transmission among the agricultural, precious metals, and energy commodities markets, and explore how climate change concerns affect this connectedness. Using the Conditional Autoregressive Value-at-Risk (CAViaR) model and the time-varying parameter vector autoregressive (TVP-VAR) connectedness model, our empirical analysis reveals several key findings. First, our tail risk-based approach shows that tail risks transmission rises during crisis periods such as the GFC of 2007 and the Covid period of 2020. Second, climate risks, in particular climate transitions risks, play an important role in commodity tail risk connectedness. These findings are important for investors, practitioners, and policymakers. Our results are robust to a number of robustness tests.

This paper examines the effects of economic uncertainty (idiosyncratic vis-à-vis common uncertainty) on equity, bond and housing returns across both developed and developing countries. Building on International/Intertemporal Capital Asset Pricing Model (ICAPM), we find that economic uncertainty exerts negative effects on equity, bond and housing returns. When we decompose economic uncertainty into two parts: idiosyncratic and common economic uncertainty, we find that ‘idiosyncratic uncertainty’ affects equity, bond and housing returns more negative and pronounced than ‘common’ uncertainty, where investors do not demonstrate differences in responses to the different dimensions of uncertainty. Moreover, there are weak lagged effects of economic uncertainty on asset returns. Additionally, we find negative uncertainty premium for equity more persistently in bullish rather than bearish market conditions. Our results are also robust for low frequency data and inclusion of covid period in the analysis. Our findings have implications for policy makers in both developed and emerging markets regarding clear communication of economic policies.

ABSTRACT: Extant literature investigates on the determinants of NPL (non-performing loan) many a time, however, little is known on the relationship between economic uncertainty and NPL for any developing country. Historically, Bangladesh is suffering from high level of NPL in the banking sector. In addition to that, Bangladesh observes high level of macroeconomic uncertainty as characterized by high and volatile Gross Domestic Products and inflation, continuous exchange rate devaluations, and shallow financial markets. Motivated by this, we investigate the nexus between economic uncertainty and NPL for Bangladesh. Based on the data availability, we use the annual dataset covering 1990–2018. Furthermore, we use autoregressive distributed lag (ARDL) model considering its benefit accommodating both I(0) and I(1) variables. The empirical results show that there is positive relationship between economic uncertainty and NPL in the long run. The results are robust to the alternative measures of economic uncertainty and specifications. Consistent with the expectation, financial development carries a negative sign on the asset quality albeit the effect of economic uncertainty is actually pronounced (both the size and significance changes) in the augmented models. Key policy implication of this study is that government should formulate well anchored, rule-based policies to reduce inflation and interest related uncertainties. With a rule-based policy (for example, inflation targeting), people believe that central bank can achieve its targets. Government should adopt floating exchange rate regime that will adjust the external shocks well via exchange rates. In addition to this, government can monitor, and regulate stock market so that uncertainty in stock market is reduced. Finally, monetary and fiscal policies should be communicated well to the people. Thus, it is possible to reduce asymmetric information among the people, which may reduce economic uncertainty, and thus reduce NPL.

As global biodiversity declines, market participants are increasingly attentive to the financial implications of biodiversity risks. We study the effects of biodiversity risks on commodities futures returns using a novel biodiversity risk index over 2005-2022. Biodiversity risks can’t predict commodities returns, suggesting risk underestimation. Using dynamic conditional correlations (DCCs), we further show that precious metals offer diversification against biodiversity risks, while energy commodities can serve as a hedge or safe haven. However, agricultural commodities don’t provide protection against biodiversity risks, potentially increasing investors exposure to these risks. Our findings are significant for investors and regulators interested in addressing biodiversity risks.

In this paper, we study the impact of news and sentiments related to covid-19 on United Kingdom (UK)'s stock returns from February 4, 2020 to December 7, 2020. Our results show that covid-19 daily cases exert a significant negative effect on stock returns whereas covid-19 daily deaths have a significant positive impact. These findings hold when covid-related news and sentiments indices are controlled with the 2nd wave data, and when the US policies and equity market volatilities from infectious diseases are used as controls. The magnitude of the effect of covid cases and deaths indicates that the pandemic is not very harmful to the UK stock market.

We examine the relationship between oil price volatility and firm performance, and the moderating role of organization capital on this relationship. Using U.S. firm-level data during the period of 1986-2017, our analysis reveals several key findings. Consistent with the real option theory, we find that oil price volatility negatively affects firm performance. However, this adverse effect of oil price volatility is reduced for firms with high levels of organization capital. Interestingly, this moderating effect of organization capital is more pronounced for firms with large cash holdings. Overall, our findings substantiate the idea that firms with high levels of organization capital can hedge oil price related volatilities effectively. Findings from several robustness tests support our key results.

This paper uses the global vector autoregressive (GVAR) modelling approach to study (1) the effects of negative output shocks on Bangladesh's following trading partners on Bangladesh's economy: the United States, China, Eurozone, India and Saudi Arabia (2) positive global oil price shocks. To represent Bangladesh's macroeconomics, the GVAR model contains four key macroeconomic variables as endogenous variables. They are (1) real gross domestic product (GDP), (2) real exchange rate, (3) short-term interest rates, and (4) inflation. The specified GVAR model is estimated using quarterly data from 32 countries/regions from 1993Q4 to 2016Q4. The findings of this paper are consistent with theoretical predictions that external shocks can and will be transmitted to an open economy operating under a fixed or managed floating exchange rate system. For example, quantitatively, if the real output of Bangladesh's trading partners' falls by 1%, its output will fall by 0.39%, while the inflation rate of Bangladesh's trading partners' rises by 1%, and Bangladesh's inflation rate will increase by 1.38%. Although the negative output shock of the US economy will not significantly affect the Bangladeshi economy, the negative output shock of the Chinese economy will have a negative and significant effect on the Bangladeshi economy. The negative output shock on the US economy has caused the real exchange rate of Bangladesh's currency to appreciate and raised its short-term interest rate, although it is not statistically significant. Contrarily, a negative output shock to China or other economies devalues the real exchange rate of the Bangladeshi currency, although it is not statistically significant. However, Bangladesh's interest rates have not responded to negative output shocks from its trading partners (except the United States and Saudi Arabia), and they are not statistically significant. One policy implication of Bangladesh's inflation being overly sensitive to external inflation shocks is that Bangladesh can and should make its currency exchange rate more flexible to protect its economy from external price shocks. Unexpectedly, the external oil price shock did not seem to have a significant impact on the Bangladeshi economy. One explanation is that the impact of foreign inflation on Bangladesh's economy may have reflected the impact of oil prices.

Recent literature extensively studies the safe-haven properties of different asset classes in crisis periods. The magnitude of the economic policy uncertainty index (EPU) and the geopolitical risk (GPR) increases significantly during extreme crisis periods such as covid crisis, but the earlier literature ignores how both risk measures impact on different asset classes during severe economic downturns. In this paper, we contribute by examining the hedging and safe-haven properties of gold, oil, equities, and foreign exchange rates against the United States (US) EPU and GPR by utilizing OLS regression, quantile regression and the quantile connectedness approach for pre-covid (October 1, 2013–March 10, 2020) and post-covid data (March 11, 2020–August 27, 2021). OLS results suggest that only the stock market has positive risk premium for both uncertainty measures. With quantile regression analysis for the pre-covid period, we find that asset returns provide no hedge (hedge) across bearish (bullish) market conditions. Importantly, safe-haven properties suggest that gold is a safe-haven asset at the extreme stress condition (at higher level of USEPU shocks). Other assets also exhibit safe-haven characteristics during extreme uncertain periods with heterogeneity in safe-haven effectiveness across bearish to bullish markets. With the post-covid data, we show that S&P500 stocks and EURO hedge EPU and GPR in bullish market condition, while Oil, S&P500, Great Britain Pound, EURO, Japanese Yen display safe-haven properties at the 99% quantile of USEPU. Specifically, gold lost its safe-haven features during covid. Interestingly, results from quantile connectedness suggest that selected asset returns have the potential to diversify against uncertainty measures considering low volatility transmissions between them across the lower and higher quantiles. Our findings are important for investors and asset managers who aim to hedge EPU and GPR during the stress period.

Given the recent evolution of green bonds as hedging tool on the face of climate change and green energy transitions, as well as cryptocurrencies’ popularity as portfolio diversifier, prior literature could focus on the potential impacts of environmental concerns in conjunction with cryptocurrencies on the performance of green financial assets. Against this backdrop, we analyse the impact of cryptocurrency environment attention index (ICEA) on clean energy stocks and green bonds using a range of econometric methods. Specifically, we use OLS, and quantile-based regression, quantile connectedness approach, and dynamic conditional correlations (DCC)-GJR-GARCH model to analyse the data. Quantile regression results suggest that ICEA exerts positive effects on S&P500 stocks in bearish market conditions and on water stocks in normal to bullish market conditions. Interestingly, clean energy stocks and green bonds have insignificant relationship with the ICEA based on OLS and quantile regression results. While, quantile connectedness results show that connectedness among the assets is low (high) at lower (higher) quantiles. Additionally, ICEA transmits (receives) weak spillovers to (from) other assets at lower quantiles, thus there is potential for diversification with clean energy stocks and green bonds in the portfolio against ICEA in bearish market conditions. Our DCC – GARCH based analysis shows that gold has positive relationship with the ICEA. DCCs also show that clean energy stocks have consistently positive relationship with ICEA, specifically during the period of high spikes of ICEA in 2017–2021, but green bonds failed to maintain consistent positive correlations with ICEA during such period. Finally, covid period reveals higher connectedness and changes in direction of contagion among assets, and lack of significant relationship between ICEA and asset returns. Our findings have important implications for the investors in the construction of optimal portfolio with carbon free assets in different markets states.

This paper investigates the inflation-hedging properties of three asset classes, namely common stocks, bonds and real estate, for thirty-one selected countries which are at different stages of development. Quarterly data for these countries over the period 1973-2017 are deployed for estimation purposes. Empirical results obtained for most countries in the sample do not show any positive or significant relationship between the actual, expected or unexpected inflation and stock returns. In contrast, consistent with the extant literature, results show an anomalous or puzzling negative relationship between inflation and stock returns. Unlike the stock returns, the bond returns are found to respond positively and significantly to expected inflation, but not much to unexpected inflation. This finding suggests that unlike common stocks, the bonds can be considered a better hedge against expected inflation. These findings suggest that in so far as unexpected inflation is concerned, neither common stocks nor bonds qualify as inflation hedges. However, unlike the stock returns and bond returns, real-estate (housing) returns are found to respond positively and significantly to actual, expected and unexpected inflation. This outcome suggests that real estate qualifies as an inflation hedge irrespective of actual, expected or unexpected inflation. The findings could be useful to design an asset management strategy in the context of high and volatile, and hence unexpected, inflation in developing countries.

There is a large body of literature on which assets are a good hedge against inflation. Most of these studies are concentrated on US or other developed countries. The present study has a wider focus; it examines the inflation hedging properties of three asset classes, namely common stocks, bonds and real estates for 45 countries, both developed and developing. The empirical results suggest that all the three classes of assets are not equally good as a hedge against inflation. Common stocks are found not a good hedge against inflation. As expected, bond returns are negatively associated with inflation, implying that they are also not a good hedge against inflation. However, contrary to the expectations, real estate is not found to be an inflation hedge in most countries. Further investigation of the issue with expected, rather than actual inflation, measured by ARIMA-based and Treasury-bill based models, provides mixed results. Overall, there is lack of significant and positive relationship between actual or expected inflation and asset returns.

This paper investigates the effect of inflation and inflation uncertainty on equity returns for the data of 41 countries. A GARCH based measure of volatility is used to model inflation uncertainty. The empirical results shows that the effects are not statistically significant in most of the cases, which implies equity investors are not sensitive to inflation and inflation uncertainty. Consistent to existing findings, equity is not a hedge against inflation (and inflation uncertainty) in developed countries; further, emerging and frontier countries are not exception. Inflation uncertainty exerts a negative influence in equity returns. The results are robust to alternative measurements. These results have important implications for asset manager’s diversification purpose and monetary policymaking.

The question whether an asset class is a good hedge against inflation is extensively investigated in the finance and economics literature; however, most of these are concentrated on stock returns from developed countries perspectives with little or no evidence on either from alternative asset classes or emerging and developing countries context. Inflation and inflation volatility have a feedback relationship, which affect investor’s real return. Despite of that literature is also scare on the relationship of inflation uncertainty and asset returns. Against this backdrop, using Fisher hypotheses as benchmark, this paper investigates whether asset return is hedge against inflation and inflation uncertainty for data of 41 developed, emerging and developing countries for 3 asset classes namely, stocks, bonds and real estate. Given varied monetary, exchange rate policies and institutional arrangement across developed and developing countries, the main argument in this paper is that stock and real estate are better inflation hedges than bonds because they constitute claims against real or physical asset and better adjust with inflation shocks, While for bonds higher, inflation reduces the price of bonds through increase in discount rate and hence decrease bonds returns. Our econometric analysis finds support for real estate not for stocks. As anticipated, investors will not be able to hedge inflation by investing in bonds.

This paper aims at examining the validity of purchasing power parity (PPP) both in absolute and relative terms with reference to the long run behavior of the real exchange rate of Bangladesh Taka relative to USA dollar. In doing so, the paper tests the presence of mean-reversion in the real exchange rate by using the unit root test approach i.e. Augmented Dickey-Fuller,DF-GLS, Zivot-Andrews tests. The paper verifies the long run relationship on co-integration and VAR framework. Using monthly data (01/2007-06/2013) and annual data (1986-2014), the paper finds support for both absolute and relative PPP. While the paper finds the evidence of structural change (Quandt-Andrew test and CUSUM test) only monthly data. VECM has been applied on monthly data, as there exists co-integrating equations for only monthly data (by using Johansen test ). Unit root test indicates that the real exchange rate is I (1), that is real exchange rate of Bangladesh is not stationary.

The paper studies the dependence pattern between stock market and foreign exchange market of three South Asian countries; namely Bangladesh, India and Sri Lanka by using five copula functions, to reveal asymmetric dependence structure. This paper focuses South Asia because of its promise as portfolio investment destination. The dependence structure between stock market and foreign exchange market assists MNCs, private equity firms, international portfolio managers and policy makers in international investment decision making. The paper also studies tail dependence (upper and lower). Markets crash together rather boom together, which can be traced by tail dependence parameter. Correlation, Kendall’s tau and Spearman’s rho reveal linear dependence. However, Copulas reveal non-linear dependence between non-normal distributions. In this paper, Copula functions are applied between marginal distributions of stationary uni-variate return series. Using daily return series for the period of July 31, 2009 to July 31, 2013, ARMA-GARCH type model are applied to obtain marginal distributions of return series. The results from marginal models indicate that volatility dies immediately after a crisis; meanwhile positive news creates more volatility than negatives. The results from copula models indicate existence of asymmetric dependence, with upper tail dependence for all pairs, implying dependence increases in bull market situation (price increase in financial instruments). Both Bangladeshi and Indian pairs provide some diversification possibility, against no diversification for investing in Sri Lankan market. Moreover, Bangladesh and India demonstrated as promising investment destination in terms of risk –return criteria. Foreign investors are recommended to employ proper risk and investment management strategy in order to earn capital gain, by following diversification strategy. Conversely, investment recipient countries are recommended to establish a stable, well regulated stock market, with high stock market capitalization to GDP. Besides, monetary policy should stabilize the exchange rate of currency to attract foreign investors. Copula based dependence measures assist foreign investors and investment recipient countries to change their related strategies and policies; subsequently they will be able to maximize their utility functions.

This paper uses generalized method of moments (GMM) panel estimator, proposed by Arellano-Bond and Blundell-Bond, to examine the relationship between FDI and environment for the period of 2000-2010 for a sample of 16 emerging countries. The effect of financial development, institutional quality and macroeconomic policy related variables are controlled for from the macroeconomic literature. The OLS based regression results reveal that environmental quality is not significant in explaining FDI inflows in emerging countries. However, based on dynamic panel data analysis, environmental quality is significant in explaining FDI. Using a number of controls it is found that stock market capitalisation to GDP, gross saving to GDP, gross capital stock to GDP, market size , and economic freedom (institutional quality) exercised by the host countries are important determinants in FDI inflows. However, the influence of such determinants is mixed in direction and magnitude at different significance levels. Thus, climate change and its mitigation strategy and overall environment policy have important implications for attracting FDI in the countries in question. In addition, the results highlight the role of institutional quality and financial development in attracting FDI.

Using HIES 2000 data, the paper presents asset based poverty information so that it is possible to provide incentives in the form of social benefit and fiscal support to the group of people who needs it most. While income based measurements and other methods are available to characterise households under poverty, asset based measurements provide a new insight into poverty and related welfare studies. By applying fractional polynomial regression, it is found that there is a significant relationship between total asset and income. We also find significant results for asset income, profit from enterprises, other assets (including financial asset, jewelry), house value and other income (rent, dividend, interest) in total asset. Meanwhile, variables such as religion, gender of the household head and agricultural income do not significantly affect total asset. People accumulate asset starting from the age of around 20 years which continues until the age of 80 years. The education level of head of the household ranges between class V and class X, when such households move on to higher assets. Except for a few outliers, both asset and income are invested and managed effectively by households to derive return from such investment.

The paper aims at constructing an optimal portfolio by applying Sharpe’s single index model of capital asset pricing in different scenarios, one is ex ante stock price bubble scenario and stock price bubble and bubble burst is second scenario. Here we considered beginning of year 2010 as rise of stock price bubble in Dhaka Stock Exchange. Hence period from 2005 -2009 is considered as ex ante stock price bubble period. Using DSI (All share price index in Dhaka Stock Exchange) as market index and considering daily indices for the March 2005 to December 2009 period, the proposed method formulates a unique cut off point (cut off rate of return) and selects stocks having excess of their expected return over risk-free rate of return surpassing this cut-off point. Here, risk free rate considered to be 8.5% per annum (Treasury bill rate in 2009). Percentage of an investment in each of the selected stocks is then decided on the basis of respective weights assigned to each stock depending on respective ‘β’ value, stock movement variance representing unsystematic risk, return on stock and risk free return vis-à-vis the cut off rate of return. Interestingly, most of the stocks selected turned out to be bank stocks. Again we went for single index model applied to same stocks those made to the optimum portfolio in ex ante stock price bubble scenario considering data for the period of January 2010 to June 2012. We found that all stocks failed to make the pass Single Index Model criteria i.e. excess return over beta must be higher than the risk free rate. Here for the period of 2010 to 2012, the risk free rate considered to be 11.5 % per annum (Treasury bill rate during 2012).