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The goal of this work is to determine whether Bitcoin behaves as a safe-haven asset. In order to do so, the influence of Economic Policy Uncertainty (EPU) on Bitcoin returns and volatility was studied.

It is evaluated whether, when compared with the evolution of EPU, Bitcoin's returns and volatility show behaviours typical of safe havens or rather, those of conventional speculative assets. When faced with an increase in EPU, safe havens – such as gold – can be expected to increase their returns and volatility, while conventional speculative assets will increase their volatility and reduce their returns. This study uses simple linear regression and quantile regression models on a daily data sample from 19 July 2010 to 11 April 2019, to analyse the influence of EPU on the returns and volatility of Bitcoin and gold.

Bitcoin's returns and volatility increase during more uncertain times, just like gold, showing that Bitcoin acts not only as a means of exchange but also shows characteristics of investment assets, specifically of safe havens. These findings provide useful information to investors by allowing Bitcoin to be considered as a tool to protect savings in times of economic uncertainty and to diversify portfolios.

This study complements and expands current research by aiming to answer the question of whether Bitcoin is a simple speculative asset or a safe haven. The most significant contribution is to show that Bitcoin is not a mere speculative asset but behaves like a safe haven.

本研究旨在確定比特幣是不是避難所資產。為達這目的，研究人員探討了經濟政策不確定性對比特幣的回報及波動性的影響。

研究評估比特幣的回報和波動性，若與經濟政策不確定的進化作比較，會顯示資金避難所的典型行為，抑或顯示傳統投機資產的行為。當面對經濟政策不確定的增加時，資金避難所 - 如黃金－會被預期有回報及波動性的上升。但傳統投機資產則其波動性會增加及其回報會減少。本研究使用簡單線性迴歸及分位數迴歸模型，根據從2010年7月19曰至2019年4月11日期間每天的數據樣本，來分析經濟政策不確定對比特幣和黃金的回報及波動性所產生的影響。

像黃金一樣，在較不明朗的時期，比特幣的回報和波動會增加，這顯示比特幣不單是一個交易工具，它也表現投資資產的特性，特別是資金避難所的特性。這研究結果為投資者提供有用的資訊，讓他們在經濟不明朗時考慮以比特幣作為保障存款的工具，及以比特幣作為使其投資組合更多元化的工具。

本研究旨在探索比特幣是一簡單的投機資產、抑或是一資金避難所，這補足及擴展了目前的研究。本研究最重要的貢獻、在於顯示了比特幣不單純是一種投機資產，它的行為實像資金避難所一樣。

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the purpose of this paper is to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios.

The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios.

The authors provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios.

This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows to compare optimal portfolios in early/recent subsamples, and during the pre-/post-cryptocurrency crisis periods.

As cryptocurrencies continue to gain viability as an asset class, institutional investors and publicly traded firms have started taking investment positions in digital currencies. What firms may not be considering, however, is the effect these assets may have on their risk profiles. This study aims to (1) measure the effect of cryptocurrencies on the risk and return characteristics of publicly traded companies; (2) decipher the motives behind holding cryptocurrencies as an asset class; and (3) determine whether one reason for holding is more effective than another. To conduct this research, the four largest publicly traded holders of cryptocurrency as well as four of the most prominent cryptocurrencies are explored.

The cross-sectional analysis approach has been used to analyze the daily returns, volatility, betas and Sharpe Ratios of firms during periods without cryptocurrency strategies and during periods with cryptocurrency strategies.

The impact of the cryptocurrency asset class on common stock performance and corporate disclosures are documented. The importance of risk disclosures on cryptocurrency holdings is emphasized: Firms must better inform their stakeholders through comprehensive disclosures in financial statements. Firms utilize cryptocurrencies for various reasons such as treasury management tools or as direct sources of income. Consequently, the impact on returns and risks varies substantially.

To the best of the authors’ knowledge, this is one of the first studies on cryptocurrency investments in the treasury departments of publicly traded companies. The study contributes to the literature by extracting relevant information regarding company risk reporting and cryptocurrency risk at firms. The conclusions also promote firm transparency with detailed reporting of cryptocurrency holding risks.

This paper examined the volatility models for exchange rate return, including Random Walk model, AR model, GARCH model and extensive GARCH model, with Normal and Student-t distribution assumption as well as nonparametric specification test of these models. We fit these models to Bangladesh foreign exchange rate index from January 1999 to December 31, 2012. The return series of Bangladesh foreign exchange rate are leptokurtic, significant skewness, deviation from normality as well as the returns series are volatility clustering as well. We found that student t distribution into GARCH model improves the better performance to forecast the volatility for Bangladesh foreign exchange market. The traditional likelihood comparison showed that the importance of GARCH model in modeling of Bangladesh foreign market, but the modern nonparametric specification test found that RW, AR and the model with GARCH effect are still grossly mis-specified. All these imply that there is still a long way before we reach the adequate specification for Bangladesh exchange rate dynamics.

Purpose: This chapter examines the effect of COVID-19 on the stock market volatility (SMV) in the Colombo Stock Exchange (CSE), Sri Lanka.

Need for the Study: The study is necessary to understand investor behaviour, market efficiency, and risk management strategies during a global crisis.

Methodology: Utilising daily All Share Price Index (ASPI) data from 2 January 2018 to 31 August 2021, the data are divided into subsamples corresponding to the pre-pandemic period, the pandemic period, and distinct waves of the pandemic. The impact of the pandemic is investigated using the Mann–Whitney U test, the Kruskal–Wallis test, and the Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) model.

Findings: The pandemic considerably affected CSE – the Mann–Whitney U test produced different market returns during the pre-COVID and COVID eras. The Kruskal–Wallis test improved performance during COVID-19 but did not continue to do so across COVID-19 waves. The EGARCH model detected increased volatility and risk during the first wave, but the second and third waves outperformed the first. COVID-19 had a minimal overall effect on CSE market results. GARCH and Autoregressive Conditional Heteroskedasticity (ARCH) models identified long-term variance memory and volatility clustering. The News Impact Curve (NIC) showed that negative news had a more significant impact on market return volatility than positive news, even if the asymmetric term was not statistically significant.

Practical Implications: This study offers significant insight into how Sri Lanka’s SMV is affected by COVID-19. The findings help create efficient mitigation strategies to mitigate the negative consequences of future events.

In recent years, with the gradual differentiation of economic and financial cycles, it has been increasingly difficult for monetary policies to remain balanced in stabilizing both economy and finance. Taking the period of 1999–2017 as a sample, the purpose of this paper is to find whether the synergy between the growth cycle and the price cycle is constantly improving in the economic cycle is more appropriate.

The key to stabilizing the economic cycle lies in the monetary policy and it should abandon the goal of boosting growth in a timely manner and turn into the goal of maintaining steady growth. At present, quantitative monetary policy is still more effective than price-oriented monetary policy in smoothing the economic cycle.

The impact of quantitative regulation on the financial cycle is more neutral, whereas price regulation will increase the volatility of price and financial cycles in the course of smoothing the growth cycle. In view of the continuous differentiation between the economic and financial cycles, it is realistic and reasonable to accelerate the establishment of a sound dual-pillar regulatory framework of “monetary policy and macro-prudential policy.”

The macro-prudential policy is specially used to smooth the financial cycle, so as to reduce the burden and increase the efficiency of the monetary policy on regulating economic cycle. Moreover, the transformation of monetary policy to price-oriented regulation must keep pace with the construction of the dual-pillar regulation framework and complement each other to prevent undesirable consequences in the financial sector. On the other hand, monetary policy still needs to rely on quantitative regulation in the future. The research in this paper also provides a new perspective for understanding the internal and external reform of China’s monetary policy in recent years.

As of March 2021, the National Pension Service (NPS) is the world’s 3rd largest pension fund with 872.5tn won (KRW) in management. Recently, the NPS proposed a policy to gradually reduce the proportion of domestic stocks in the portfolio in the future. This change in the asset allocation strategy is related to the NPS’s exit strategy for domestic stocks. This study aims to examine the market impact cost asymmetry between buys and sells of the NPS and suggest a trading strategy for mitigating the market impact cost. The results are as follows. First, there is an asymmetry between buys and sells in the market impact cost of the NPS. The market impact cost of the NPS is gradually increasing over time. In particular, the market impact cost from selling has increased significantly in recent years. Second, past returns, volatility, liquidity and trading intensity can be found as external factors affecting the asymmetric market impact cost of the NPS. Although there is no difference between the buying and selling ratios of the NPS, the market impact cost from sells is relatively higher than that from buys. Third, after controlling for the order execution size of the NPS, the longer the trade execution period, the lower the market impact cost. This result implies that the strategy of splitting orders as a way to reduce the market impact cost is effective. The trading behavior of the NPS directly or indirectly affects other investors. If the sell of the NPS incurs excessive market impact cost, the negative impact on the stock price will be further exacerbated. Therefore, it is necessary for the NPS to reduce the market impact cost through split trading in executing orders in the domestic stock market. Findings of this study provide implications for countermeasures and long-term management strategies that can minimize the market impact cost of the NPS in the process of reducing the proportion of domestic stocks in the future.

This paper aims to examine the performance of Islamic and conventional stocks listed at the Pakistan Stock Exchange by using both parametric and non-parametric approaches. The motivation is to do risk-return analysis of Islamic stock prices and conventional stock prices.

It uses various measures of performance, e.g. Sharpe ratio, Treynor ratio, Jensen's alpha, beta, generalized auto-regressive conditional heteroskedasticity and stochastic dominance. Using the Karachi Meezan Index-30 (KMI-30) and the Karachi Stock Exchange Index-30 (KSE-30) as proxies for Islamic and conventional stock prices, respectively, it examines the performance of Islamic and conventional stocks. The daily data of KMI-30 and KSE-30, covering period from June 9, 2009 to June 20, 2020 are used.

The results show that the overall KMI-30 outperforms the KSE-30. The returns of the KMI-30 are greater than the KSE-30. However, the risk and volatility of the KMI-30 and KSE-30 are similar. Further, the KMI-30 has higher excess returns per unit of total risk than the KSE-30. But both indexes have similar excess returns per unit of systematic risk. Moreover, the KMI-30 returns have stochastically dominance over the KSE-30 returns. These results reveal that the Islamic index performs better than the conventional index.

The findings provide several practical implications in financial and investment decisions making by investors, managers and policymakers such as strategies for asset allocation and investment. Further, in risk management, it provides guidance for allocating portfolios and managing risk. The investment in Islamic stocks may mitigate potential risk within asset portfolios.

This research is unique in its approach to the analysis of the performance comparison of conventional and Islamic stock by using comprehensive parametric and non-parametric estimation techniques. Such research has not been undertaken in the Pakistan's equity market since.

The purpose of this paper is to examine the volatility transmission between migration policy uncertainty indices (MI) of France, Germany, UK and the USA, and respective stock markets of these countries. Therefore, the author’s major intention is to understand whether MI is a critical factor affecting company valuations and investor sentiment.

The author proxies volatility via EGARCH (1,1) for all series and employs Diebold–Yilmaz (2012) methodology to test the spillover, which is a simple yet very intuitive procedure. This method allows one to analyze the numerical amount of spillover, as well as the direction.

Findings propose that volatility transmission is from migration index to stock markets for the UK and US markets, but similar findings are not applicable for France and Germany. However, when cross-market transmissions are analyzed, it is observed that migration policy uncertainty of US spills significant volatility to all European stock markets. Hence, the findings underline the central role of US markets.

Given the increasing worries about migration across the USA and Europe, the author tries to cast light on whether investor sentiment alters by migration policies. The literature is recently building and best of the author’s knowledge; the paper is the first to investigate the cross-country spillover between MIs, which has not been performed before.