Risk Hedging Research Articles

Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets

This paper studies cross-country risk spillovers through C-vine copula quantile regression. We find Both China's and the US markets can result in large risk spillovers to East Asian markets. Furthermore, their significant conditional spillovers indicate they can emit risk through an intermediary market. However, their distinctive dependency structures with East Asian markets reflect their differences in spillovers to the markets in magnitude. The risk spillovers from US are stronger than China in magnitude. Moreover, the risk spillover from China's stock market during its high-volatility period is weaker than the whole period, which is contrary to the US market. It may imply Chinese financial influences gradually increase with Chinese financial liberalization and regional integration. Our results have implications for macroprudential regulators adopt the effective supervision and regulation to deal with the cross-border risk spillovers, and for international investors in risk hedging, derivative valuation and investment.

Cryptocurrency technology revolution: are Bitcoin prices and terrorist attacks related?

As a financial innovation of the information age, cryptocurrency is a complex concept with clear advantages and disadvantages and is worthy of discussion. Exploring from a terrorism perspective, this study uses the time-varying parameter/stochastic volatility vector autoregression model to explore the risk hedging and terrorist financing capabilities of Bitcoin. Empirical results show that both terrorist incidents and brutality may explain Bitcoin price, but their effects are slightly different. Compared to terrorist brutality, terrorist incidents have a weaker impact on Bitcoin price, showing that Bitcoin investors are more concerned about the number of deaths than the frequency of terrorist attacks. In turn, the impact of Bitcoin price on terrorist attacks is negligible. Bitcoin is a potential means of financing terrorism, but it does not currently play an important role. Our research findings can help investors analyze and predict Bitcoin prices and help improve the theoretical system of anti-terrorist financing, helping to maintain world peace and security.

Production Planning with Risk Hedging Under a Conditional Value at Risk Objective

Effective management of demand risk is a central problem of production planning. In many applications, it is observed that demand often depends on certain asset prices in the financial market. This calls for a model that jointly optimizes the production decision along with a risk hedging policy, using the latter to compensate for loss of profit in scenarios of weak demand. In “Production Planning with Risk Hedging under a Conditional Value at Risk Objective,” Wang and Yao develop an integrated production and risk hedging model, where the risk hedging strategy is derived in explicit form and the production quantity is solved as a concave maximization problem. Furthermore, a complete characterization of the efficient frontier is provided, and the improvement over the production-only decision is quantified.

Connectedness between Currency Risk Hedging and Firm Value: A Deep Neural Network-based Evaluation

Connectedness between Currency Risk Hedging and Firm Value: A Deep Neural Network-based Evaluation

A Review of the Global Climate Finance Literature

This study conducts a bibliometric analysis and literature review of studies on climate finance. Since the Paris Agreement was adopted in December 2015, the academic community has paid closer attention to this emerging topic, as witnessed by a sharp increase in the number of publications. Our review lists this field’s most influential publications, authors, and journals, based on citations. The bibliometric analysis highlights the multidisciplinary nature of climate finance research, which spans environmental science, energy, economics, and finance. The citation analysis also reveals that, despite the exponential growth in publications related to climate finance, leading journals in finance and economics have so far published only a small number of articles in this literature. In addition, the citation analysis identifies four main themes in the knowledge domain: the financing of renewable energy; the impacts of climate change risks on the financial sector; investor preferences for green investments and the impact on corporations; and the pricing and hedging of climate change risk in financial markets.

Why do banks use credit default swaps (CDS)? A systematic review

AbstractCredit default swaps (CDS)—the fiercely discussed derivatives instrument since the explosion of the recent global credit crunch—are still subject to considerable theoretical and practical debate. More than a decade after significant developments in CDS literature, we currently lack a holistic understanding of the disparate strands of evidence, synthesizing analytical advancements in the field. We, therefore, conducted a systematic review of 143 publications (peer‐reviewed and first‐tier grey literature), focusing on three key areas: CDS characteristics and development, credit risk hedging, and determinants of CDS use, and performed the first bibliometric mapping for CDS. Our review makes the following contributions. First, measuring CDS characteristics and development gives a snapshot of how CDS remained a significant indicator for hedging corporate lending risk. Second, by mapping the research landscape, we provide insights into banks’ use of CDS; in particular, we show that banks use CDS to obtain capital relief, enhance liquidity and profitability, limit credit supply, and consequently mitigate their NPLs’ level. Moreover, the use of CDS by lenders increases firms’ leverage and value. Leaving a fertile area for debates and future research, the outcomes of this review help provide policy guidance to regulators and financial institutions that make informed decisions to use CDS as a credit risk management instrument.

Estimating optimal hedging ratio and hedging efficiency in China's stock market

This paper examines the risk spillover mechanism between China's stock market and international commodity markets using selected industry data series on soybean copper, gold, silver, sugar, and crude oil. Based on the results of this analysis, a DCC-GARCH model is used to describe the dynamic correlation, build a risk hedging model, calculate the risk hedging efficiency, and evaluate the risk hedging effect. According to the findings, the industrial and optional consumer industries are the primary risk receiving markets, while the energy and finance industries are the primary risk export markets. The stock market crash in 2015 and the COVID-19 epidemic in 2020 made the risk spillover between China’s stock market and international commodity markets surge. On average, the commodity copper is the most efficient hedge, followed by silver, while commodities such as sugar, gold and soybeans are less effective, and copper will continue to be a good hedge for the Chinese stock market in the coming months.

Forecast and hedging of risks in decision-making by an investigator and a judge

The study is aimed at determining the role and significance of forecasting in the professional activities of an investigator and a judge. Methodologically, the study is based on probability theory, signal theory, project management and risk management. The empirical basis of the study is criminal cases initiated against judges as well as against investigators and other law enforcement officials due to negligence. The data of judicial and criminal statistics are used. The author analyzes the empirical material and solves the problem of forecasting by applying the approach is due to the classification of investigative and judicial risks proposed by the author himself according to the nature and content of the consequences of their implementation on legal (formal and material) and social risks. A qualitative-quantitative methodology for assessing forensic and investigative risks developed by the author is proposed. The concept of hedging is introduced into scientific legal circulation as a system of ways to prevent or minimize the negative consequences of their occurrence. The main conclusion is made about the need for judges to master the scientific methods of forecasting and managing risks, as well as to establish clear criteria for liability for grave consequences as a result of gross judicial errors in forecasting.

PROBLEMS AND PROSPECTS OF FINANCIAL DERIVATIVES MARKET DEVELOPMENT

The article is devoted to the study of problems and prospects for the development of the financial derivatives market. The relevance of the chosen topic is explained by the fact that the globalization of the economic space contributes to the transformation of the stock market into the main source of capital allocation, but the current conditions of the derivatives market in Ukraine do not meet the needs of the development of the national economy, which requires strengthening the regulation of their activities in order to ensure the hedging of the risks of market participants. The object of research is financial derivatives as a source of attracting additional investments and globalization of financial flows. The purpose of the research is to study the features, advantages and disadvantages of derivative financial instruments, to evaluate the possibilities of their use in different price situations in order to increase the efficiency of the derivatives market in Ukraine. Research methods – method of system analysis, method of analysis and synthesis, method of statistical analysis and method of comparison. In the course of the study, the dynamics of derivatives trading on the global stock market were analyzed and the dynamics of global exchange trading of financial derivatives were assessed, and the turnover of OTC derivative financial instruments in the EU countries was analyzed. Dynamic changes in the sums paid under the terms of the contracts for derivative securities in the world in terms of terms of validity, regions and sectors were also investigated; dynamics of options and futures trading on the global stock market. In the financial market of Ukraine, an analysis of the volumes of derivatives trade was carried out, the volume of trades on the exchange and over-the-counter markets was estimated, the dynamics of the volumes of exchange contracts and the share of trades in financial instruments on the securities market were given. Factors restraining the development of the derivative securities market in Ukraine have been identified, namely: deficiencies in legislation, the level of development of the infrastructure of the derivative securities market, as well as the current state of development of the underlying asset markets. Based on the analysis of the derivative financial instruments market, prospects for its development have been developed. Conclusions – the main measures regarding the future development of the financial derivatives market in Ukraine should be: comprehensive regulation of the functioning of the derivatives market, ensuring the operation of regulated markets and developing their infrastructure, introducing appropriate tools for the protection of participants and risk hedging. On the basis of taking into account the international experience of the use of derivatives in Ukraine, it is necessary to create an effective developed financial market, and such a segment of it as the derivatives market, in order to become a worthy competitor on the global financial market.

РАЗРАБОТКА АЛГОРИТМА ХЕДЖИРОВАНИЯ ПРОЦЕНТНЫХ И ВАЛЮТНЫХ РИСКОВ

Given the continuing level of uncertainty and volatility in the foreign exchange market, as well as the interest rate market, risk hedging plays a special role in the organization’s activities. However, the question of choosing an effective hedging instrument still remains open. In this article, the authors proposed an algorithm that, based on the VAR calculation model using historical data, selects the appropriate derivative financial instrument. All stages of the algorithm are considered. Using the considered algorithm allows companies to reduce uncertainty, as well as choose a tool that will allow them to get the highest profitability.

Scientific Investing in the Real World: Unifying the Extremes: Randomness Determinism Causality : Black Swan & Tail Risk Hedging Black Swan, Tail Risk Hedging, Convexity, Causality, Dynamics in Financial Market Causal Adjusted Randomized Factor Investing

Scientific Investing in the Real World: Unifying the Extremes: Randomness Determinism Causality : Black Swan & Tail Risk Hedging Black Swan, Tail Risk Hedging, Convexity, Causality, Dynamics in Financial Market Causal Adjusted Randomized Factor Investing

Through analyzing differences between four risk hedge methods to help companies choose a suitable strategy in different financial situation

Hedging risk is an essential section of finance for all investors, especially in the times where uncertainty occurs every time. covid-19 has hit the global market heavily since 2020, promoting the importance of hedging risk significantly. This essay generally introduces 4 fundamental methods of hedging risk, including the Arbitrage strategy, alpha strategy, neutral strategy and event-driven strategy. It mainly focusses on their origins, the economics and finance theory of each format and the reality problems occurred in application. At the same time, the advantages and drawback of each methods have been discussed with full detail. General speaking , in different scenarios there might be different methods that are suitable. Alpha strategy is desirable in stable market and neutral strategy is the most secure one but requires lots of calculation. Event-driven strategy and arbitrary strategy hugely depends on the executive of managers.This essay is fairly helpful for the learner who just started to learn about hedging risks to generally study the fundamental risk hedging.

Multilateral climate change financing in the developing world: challenges and opportunities for Africa

The Paris Agreement has highlighted the worldwide significance of adaptation. Many investors are considering the effects of climate change and resource scarcity when making decisions. Even while the whole amount of the environmental harm caused by climate change is yet unknown, recent scientific evidence is more frightening, and many governments are taking substantial measures to avert a calamity. The financial innovations and mechanisms created to ease the transition to a low-carbon economy will have far-reaching effects on markets, firms, intermediaries, and investors. Although economists have been working on the subject for decades, financial-economics professionals have only recently become interested in climate change. There has been a growing body of empirical and theoretical contributions in recent years that analyse the influence of climate risks on investment decisions for firms, financial intermediaries, and national governments, as well as the pricing and hedging of climate change risks. This study seeks to establish the role of multilateral climate change financing in the developing world vis-à-vis challenges and opportunities for Africa. Five determinants of the multilateral climate fund were established and they are namely; Reduction of Greenhouse gas emissions, Enabling Environments, Poverty and development linkages, Private investment and Public climate finance.

The moderating role of informatization between country risks and international tourism: A cross-country panel analysis.

Informatization plays an increasingly important role in the tourism industry, while its effectiveness in alleviating tourism risks remains to be verified. This research aims to explore the effects of country risks on the international tourism and the moderating role of informatization between the two. This study firstly measures country risks based on the ICRG database, quantifies international tourism by tourism revenue, tourism expenditure, and tourist arrival, and calculates informatization level from informatization facilities, informatization applications, and informatization skills. A dynamic SYS-GMM model is then adopted to verify the research hypotheses based on the panel data of 138 countries from 2000 to 2019. The research results show that the composite country risk, political risk, economic risk, and financial risk all show a negative impact on the international tourism indicators regardless of different time periods, regions, or income levels. However, the effects are more obvious before the global financial crisis in 2008 and regions and countries with lower income levels. In addition, informatization is found to positively mitigate the adverse impacts of country risks on international tourism, especially for economic and financial risks. The research findings indicate the risk hedge potential of informatization in the tourism industry, which provides a profound reference for destination risk management.

Theoretical Aspects of Hedge Accounting in Non-Financial Institutions: Problematic Field and Potential Effects

The paper contains the results of a study of problematic aspects and potential effects associated with the use of hedge accounting by non- financial institutions. The relevance of the study is because hedge accounting allows to ensure that income and expenses for the object and hedging instrument match but its use is the choice of the organization. Therefore, the works’s aim is to conduct a comprehensive study of the effects and problems associated with the use of hedge accounting and develop recommendations for assessing the need for usage in non-financial organizations. The author identified the following tasks for this goal achievement: studying the practice of applying hedge accounting by Russian companies; analysis of potential effects from the use of this toolkit; consideration of problematic aspects related to the application of hedge accounting; method development for determining the need for its use in non-fi institutions. The theoretical and methodological basis of the study are the provisions of IFRS and US GAAP in terms of accounting for derivatives and hedging, fair value assessment and disclosure, literature on their practical application, as well as reporting by Russian companies compiled in conformity with IFRS. In the work’s course, the author revealed that only half of the hedger companies from the considered sample apply hedge accounting. For understanding motives of organizations to use this toolkit or abandon it, the author identified the potential positive effects associated with it and problematic aspects. Also, they proposed a methodology for determining the need for its use, which would be useful for consulting companies when they provide services in risk hedging.

Option pricing and risk hedging for Visa

As the core of the option transaction, the option price changing with the supply and demand in the market is a variable which affects the profit and loss of both trading sides directly. In the 20th century, multitudinous econometric pricing models proposed lacked universal recognition until the Black Scholes Merton model came out. This paper focuses on the stocks and options from Visa Inc. to do the article consisting of calibration, option pricing and hedging using fundamental Black Scholes Merton model and the extensive jump model mainly under the seldom used method. The article demonstrates that calibrated parameters in Black Scholes Merton model perform better than that of the jump diffusion model with the same method, and the hedging portfolio based on the Black Scholes Merton model do keeps the profit and loss at a steady level though it should not be a preference at the certain circumstance. The results in this paper are beneficial for investors to forecast the price of option with the optimal model and describes the nature for option selection.

Option pricing and risk hedging for Apple

The Black Sholes Merton (BSM) model is one of the fundamental stochastics models in quantitative finance and the Merton Jump diffusion (MJ) model. This paper examines how BSM, and MJ behave on the European pricing based on 10 options chosen for Apple Inc, with BSM using RRS, SSE, and Historical Volatility, and MJ using SSE as calibration methods. Then delta-neutral hedging strategy is performed using the BSM on the historical data collected from the concessive 10 days. The BSM with RRS and SSE when pricing should be preferred, and the results are similar. The MJ and the BSM using Historical Volatility, however, do not work well when pricing. The delta-neutral hedging strategy is not ideal in this case, since it results in lower profits. The result possesses valuable insights for quantitative finance that calibration methods can significantly influence the accuracy of pricing, and the hedging method can limit the maximum profit.

Risk hedging properties of infrastructure: a quantile regression approach

PurposeThis paper aims to examine the hedge, diversifier and safe haven properties of the global listed infrastructure sector and subsector indices against two traditional asset classes, stocks and bonds, and four alternative asset classes, including commodities, real estate, private equity and hedge funds during extreme negative stock market movements.Design/methodology/approachUsing dynamic conditional correlation and quantile regression, the authors analyze a data set of 12 indices comprising listed infrastructure and traditional asset classes from 2010 to 2019.FindingsOverall, the findings indicate that listed infrastructure acts as an effective diversifier but not as a strong safe haven or hedge when considered in a multiasset context. With minor exceptions, listed infrastructure cannot be concluded as a safe haven against other asset classes under investigation.Practical implicationsThe present study has implications for institutional investors looking to incorporate infrastructure in their multiasset portfolios for increased portfolio diversification benefits.Originality/valueDespite the increased influence of infrastructure as an asset class, to the best of the authors’ knowledge, this is the first study to investigate the hedge, safe haven and diversifying properties of infrastructure in a multi-asset context.

Modelling and Forecasting of EUR/USD Exchange Rate Using Ensemble Learning Approach

Abstract The aim of the study is to obtain an accurate result from forecasting the EUR/USD exchange rate. To this end, high-performance machine learning models using CART Ensembles and Bagging method have been developed. Key macroeconomic indicators have been also examined including inflation in Europe and the United States, the index of unemployment in Europe and the United States, and more. Official monthly data in the period from December 1998 to December 2021 have been studied. A careful analysis of the macroeconomic time series has shown that their lagged variables are suitable for model’s predictors. CART Ensembles and Bagging predictive models having been built, explaining up to 98.8% of the data with MAPE of 1%. The degree of influence of the considered macroeconomic indicators on the EUR/USD rate has been established. The models have been used for forecasting one-month-ahead. The proposed approach could find a practical application in professional trading, budgeting and currency risk hedging.

Risk-based multistage stochastic mixed-integer optimization for biofuel supply chain management under multiple uncertainties

CO2 emissions from the transportation sector account for 22% of global emissions. Blending biofuels with fossil fuels is a promising method for reducing these emissions and ensuring energy security. One of the most important and challenging aspects of the biofuel production process is the design of supply chains that integrate various types of biomasses under multiple uncertainties. The aim of this study is to address this issue by proposing a multi-stage stochastic program for strategic and tactical planning in multi-feedstock biofuel supply chain networks under uncertainties of biomass supply and biofuel demand. The proposed model minimizes the total annualized cost by selecting raw materials, positioning production facilities, placing storage facilities, and defining deferral paths for each feedstock. In addition, a new dynamic method of the conditional value at risk is adopted to consider the risk hedge. Deterministic, stochastic, and risk-based models are compared, and case studies based on the South Korean context show the effectiveness of the model and the algorithm. Computational results indicate that considering risk can increase biofuel expected production cost by up to 88%. It also shows that biomass transportation is the most affected part of the supply chain in risk assessment. Furthermore, it indicates that a value of 0.5 is the most effective risk aversion factor.