Search results

The authors investigate whether the effects of stock buyback announcements on credit default swap (CDS) spread changes for US firms depend on macroeconomic conditions. The authors find that abnormal CDS spreads increase for small-sized firms announced to repurchase a higher share ratio during the normal period. In contrast, abnormal CDS spreads decrease for big-sized firms regardless of the magnitude of the repurchase ratio during the crisis period. The results of this study suggest that the wealth transfer effect dominates the signaling effect for small-sized firms with higher target ratios during the normal period. In contrast, the signaling effect is stronger for bondholders of big-sized firms during the crisis period.

This study aims to quantify the cost of rebalancing Sharīʿah-compliant indexes, both economically and statistically.

An empirical approach is employed where the rebalanced Sharīʿah-compliant index is calculated numerous times with different lags in rebalancing, and the number of stocks and their cost across time are determined in order to identify the optimal rebalancing frequency.

This paper finds that annual Sharīʿah rebalancing does not lead to significant differences in portfolio returns, even though it does bring some advantages in cumulative wealth starting from the third year onwards and brings about better risk-return characteristics measured in terms of the Sharpe ratio. However, these advantages involve an average annual shifting between 30 and 60% of the portfolio market capitalization, which would be costly at any level of transaction costs.

A private investor may be better off holding a constant portfolio and only rebalancing in three-year intervals since this was shown to possess similar portfolio returns and cumulative wealth results. Any advantages of annual rebalancing in terms of risk-return characteristics may be offset by transaction costs of rebalancing. Sharīʿah scholars and practitioners are to determine when the correct time for rebalancing really is, taking into consideration the cost of rebalancing vis-à-vis the advantages in cumulative wealth and risk-return characteristics of the portfolio.

Predictions that Islamic indexes will perform well during financial crises, such as the COVID-19 pandemic, miss the cost of frequent rebalancing. This paper addresses this issue in an empirical manner learning from the previous crisis in 2008.

Considering the relationship between the central bank balance sheet and unconventional monetary policy after the 2008 financial crisis, it is crucial to see how the unconventional monetary policy, given near-zero interest rates, affects future stock market performance. This paper analyzes the impact of the Fed's balance sheet size on stock market performance.

To analyze the Fed's balance sheet size's long-term stock market implications, this paper uses the asset pricing framework of market return predictability such as Ordinary least squares (OLS) and Generalized method of moments (GMM) analysis.

Findings in this paper suggest that the Fed's balance sheet size, deflated by asset market wealth, presents evidence of return predictability during 1926–2015 that is robust against standard controls. These results can be explained through the redistribution of risk and the wealth channels of monetary policy transmission. The changing balance sheet size of a central bank (1) affects systemic risk, yields and expectations and (2) signals the future direction of monetary policy and thus economic outlook.

The main implication of these findings is that policymakers should avoid a severe imbalance between a central bank's balance sheet size and assets market wealth.

The empirical evidence in this paper documents a century-old relation between the Fed's balance sheet size and US stock market return using the Fed's balance sheet data for the last 100 years and stock market returns from the Center for research in security prices (CRSP) database.

Homeownership provides shelter and is a vital component of wealth, and house purchase signifies a lifetime achievement for many households. For South Africa confronted with social and structural challenges, homeownership by the low and lower middle-income household is pivotal for its structural transformation process. In spite of these potential benefits, research on the affordable housing market in the context of South Africa is limited. This study aims to contribute to this knowledge gap by answering the question “do changes in household income per capita have a symmetric or asymmetric effect on affordable house prices?”

A survey of the international literature on house prices and income revealed that linear modelling that assumes symmetric reaction of macroeconomic variables dominates the empirical strategy. This linearity assumption is restrictive and fails to capture possible asymmetric dynamics inherent in the housing market. The authors address this empirical limitation by using asymmetric non-linear autoregressive distributed lag models that can test and detect the existence of asymmetry in both the long and short run using data from 1985Q1 to 2016Q3.

The results revealed the presence of an asymmetric long-run relationship between affordable house prices and household income per capita. The estimated asymmetric long-run coefficients of logIncome[+] and logIncome[−] are 1.080 and −4.354, respectively, implying that a 1% increase/decrease in household income per capita induces a 1.08% rise/4.35% decline in affordable house prices everything being equal. The positive increase in affordable house prices creates wealth, helps low and middle-income household climb the property ladder and can reduce inequality, which provides support for the country’s structural transformation process. Conversely, a decline in affordable house prices tends to reduce wealth and widen inequality.

This paper recommends both supply- and demand-side policies to support affordable housing development. Supply-side stimulants should include incentives to attract developers to affordable markets such as municipal serviced land and tax credit. Demand-side policy should focus on asset-based welfare policy; for example, the current Finance Linked Income Subsidy Programme (FLISP). Efficient management and coordination of the FLISP are essential to enhance the affordability of first-time buyers. Given the enormous size of the affordable property market, the practice of mortgage securitization by financial institutions should be monitored, as a persistent decline in income can trigger a systemic risk to the economy.

The study results illustrate the importance of homeownership by low- and middle-income households and that the development of the affordable market segment can boost wealth creation and reduce residential segregation. This, in turn, provides support to the country’s structural transformation process.

The affordable housing market in South Africa is of strategic importance to the economy, accounting for 71.4% of all residential properties. Homeownership by low and lower middle-income households creates wealth, reduces wealth inequality and improves revenue collection for local governments. This paper contributes to the empirical literature by modelling the asymmetric behaviour of affordable house prices to changes in household income per capita and other macroeconomic fundamentals. Based on available evidence, this is the first attempt to examine the dynamic asymmetry between affordable house prices and household income per capita in South Africa.

The purpose of this research is to study the impact of divestitures on shareholder wealth. This study covers selloffs of publicly traded companies in Germany, Austria and Switzerland (DACH region) during the period 2002–2018. It aims to understand the overall effect of selloffs on shareholder wealth as well as the impact of important influencing factors.

This study is part of capital market studies which investigate shareholder wealth effects (abnormal returns) using event study methodology. To determine the significance of abnormal returns, a standardized cross-sectional test as suggested by Boehmer et al. (1991) was applied. The sample consists of 393 selloffs of publicly traded companies with a deal value of at least EUR 10m.

The findings confirm the overall positive impact of selloffs on shareholder wealth. The average abnormal return on the announcement day of the sample companies amounts to 1.33%. The type of buyer, the relative size of the transaction as well as the financial situation of the seller in particular seem to influence abnormal returns positively.

This study investigates shareholder wealth creation through selloffs in the DACH region, a largely neglected region in divestiture research, but now very relevant due to increasing pressure of active foreign investors. Sophisticated statistical methods were used to generate robust findings, which are in line with the results of similar studies for the US and the UK.

This paper examines the role of illiquidity and duration factor in understanding the momentum profit in the Korean stock market. We find that the foreigner/institutional illiquidity factor explains the momentum effect. In addition, this paper finds that duration factor defined as the difference in returns of short-duration and long-duration stocks captures well the momentum profits. That is, a two-factor model with the market and duration factor performs much better than competing asset pricing models in explaining the momentum effect. Finally, when controlling for the duration factor, the explanatory power of the foreign/institutional illiquidity factor on the momentum profits disappears. In sum, our empirical finding indicates that the duration factor is the most important ingredient in understanding the momentum effect in the Korean stock market.

The purpose of this paper is to examine, in a global perspective, the oil, gold, US dollar and stock prices interdependencies and to identify instantaneously direct and indirect linkages among them.

A methodology based on simultaneous equations system was used to identify direct and indirect linkages for the period 1995-2015. The authors try initially to find theoretical answers to main question of the study by discussing causal bilateral relationships while focusing on multilateral interactions.

The results show significant interactions between all markets. The authors found a negative relation between oil and stock prices but oil price is significantly and positively affected by gold and USD. Oil price is also affected by oil futures prices and by Chinese oil gross imports. Gold rate is concerned by changes in oil, USD and stock markets. The US dollar is negatively affected by stock market and significantly by oil and gold price. Indirect effects always exist which confirm the presence of global interdependencies and involve the financialization process of commodity markets.

Motivation of this research paper is the substantial implications of price movements on real economy and financial markets. Understanding that co-movement has great value for investors, policy makers and portfolio managers. This paper differs from previous studies in several aspects. First, most of the research papers focus on bilateral linkages solely, while the authors’ investigation was implemented on all the four markets simultaneously. Second, the study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

In this paper, we view an individual's annuitization decision as an American style call option whose underlying asset is financial wealth, which controls the distance to annuitization. We then derive a certain threshold of wealth over which the individual is optimal to annuitize all of her wealth. We particularly focus on the effects of liquidity constraints on the individual's optimal annuitization decision, concerning their effects on the optimal investment and consumption strategies. We show that the annuitization decision can be significantly affected by the extent to which individual borrowing is constrained. More specifically, the optimal decision is for the individual to annuitize earlier with the tighter liquidity constrains she is exposed to than initially planned. This is particularly relevant to today's pandemic situation especially with the growing concern about cutting credit limits.

The current study aims to investigate the impacts of two behavioral biases, namely, loss aversion and overconfidence on the performance of US companies. First, the impact of loss aversion on the economic performance of companies was assessed. Second, the impact of overconfidence on market performance was discussed.

This study used around 6,777 quarterly observations on the population of US-insured industrial and services companies over the 2006-2016 period. Ordinary least squares (OLS) regression in two panel data models were used to test the hypotheses formulated for the study.

It was documented that the loss-aversion bias negatively affects the economic performance of companies and this is achieved for both sectors. In contrast, the findings suggest that overconfidence positively affects market performance of industrial firms but negatively affects market performance in service firms. Further robust evidence was found that overconfidence bias seems to be dominant, and hence, investors may tend to be more overconfident rather than more loss-averse.

This research can be extended by focusing on the following question: What is the impact of the contradictory (positive and negative) effects of an investor's loss aversion and overconfidence on the US company performance in case of realization of a stock market crisis or stock market crash?

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.