Financial Derivatives Research Articles

The Role of International Accounting Standard 39 in Disclosing Financial Derivatives/ Financial Instruments in the Financial Statements of Jordanian Banks Listed on the Amman

This study objective to know the nature of financial derivatives of both types (stocks and bonds) and the role of International Accounting Standard (39) in disclosing them in the financial statements, in addition to identifying their problems, how they are dealt with, and what is the mechanism for disclosing them in accordance with international accounting standards. The study used the content analysis method to determine the volume of disclosure of financial derivatives in the financial statements of a number of Jordanian banks registered on the Amman Stock Exchange. The descriptive analytical method was also used in the theoretical aspect The study showed through the conclusions that the financial reports of Jordanian banks have dealings with financial instruments and that the banks have applied the standard, but only partially and in accordance with the standard (39 Financial Instruments: Recognition and Measurement), which led to a significant improvement in the measurement and disclosure of financial instruments (stocks and bonds). Thus, the auditor is able to give an impartial technical opinion The study presented several recommendations, the most important of which are: the need to pay attention to applying Accounting Standard 39 completely and not partially for the purpose of being able to compete internationally and not just at the local level through developing and qualifying employees/and resorting to foreign companies specialized in the field of applying international accounting standards.

A Girsanov transformed Clark-Ocone-Haussmann type formula for $$L^1$$-pure jump additive processes and its application to portfolio optimization

AbstractWe derive a Clark-Ocone-Haussmann (COH) type formula under a change of measure for $$ L^1 $$ L 1 -canonical additive processes, providing a tool for representing financial derivatives under a risk-neutral probability measure. COH formulas are fundamental in stochastic analysis, providing explicit martingale representations of random variables in terms of their Malliavin derivatives. In mathematical finance, the COH formula under a change of measure is crucial for representing financial derivatives under a risk-neutral probability measure. To prove our main results, we use the Malliavin-Skorohod calculus in $$ L^0 $$ L 0 and $$ L^1 $$ L 1 for additive processes, as developed by Di Nunno and Vives (2017). An application of our results is solving the local risk minimization (LRM) problem in financial markets driven by pure jump additive processes. LRM, a prominent hedging approach in incomplete markets, seeks strategies that minimize the conditional variance of the hedging error. By applying our COH formula, we obtain explicit expressions for locally risk-minimizing hedging strategies in terms of Malliavin derivatives under the market model underlying the additive process. These formulas provide practical tools for managing risks in financial market price fluctuations with $$L^1$$ L 1 -additive processes.

On the pricing of vulnerable Parisian options

Parisian options, serving as substitutes for barrier options, are frequently embedded in complex financial derivatives. Despite the considerable mathematical challenges in pricing, their significant applications in finance and insurance have generated extensive studies in the literature. However, the impact of counterparty risk has not been taken into account so far. To address this gap, we develop a closed-form pricing framework for vulnerable Parisian options. Utilizing the Laplace transform and measure-change technique, we derive closed-form pricing formulas of Parisian options incorporating counterparty credit risk. Finally, we conduct numerical analyses to verify our pricing formulas’ accuracy and efficiency.

Random Processes and Their Applications in Financial Mathematics

Random processes are fundamental tools in modern financial mathematics, widely applied in fields such as financial derivatives pricing, risk management, and interest rate models. This paper systematically introduces the basic theory of random processes, including definitions and classifications, Brownian motion and geometric Brownian motion, and stochastic differential equations. Furthermore, the paper explores specific applications of random processes in financial mathematics, focusing on financial derivatives pricing, risk management and portfolio optimization, and applications in interest rate models and credit risk. Through theoretical and empirical research, this paper reveals the significant role and development prospects of random processes in financial mathematics, providing new ideas and methods for risk management and pricing models in financial markets.

Enhancing the Financial Derivatives Market in Kenya: Challenges, Opportunities and Strategic Recommendations

Enhancing the Financial Derivatives Market in Kenya: Challenges, Opportunities and Strategic Recommendations

Quantum computational finance for martingale asset pricing in incomplete markets

A derivative is a financial asset whose future payoff is a function of underlying assets. Pricing a financial derivative involves setting up a market model, finding a martingale (“fair game”) probability measure for the model from the existing asset prices, and using that probability measure to price the derivative. When the number of underlying assets and/or the number of market outcomes in the model is large, pricing can be computationally demanding. In this work, we first formulate the pricing problem in a linear algebra setting, including the realistic setting of incomplete markets where derivatives do not have a unique price. We show that the problem can be solved with a variety of quantum techniques such as quantum linear programming and the quantum linear systems algorithm. While in previous works the martingale measure is assumed to be given, here it is extracted from market variables akin to bootstrapping, a common practice among financial institutions. We discuss the quantum zero-sum game algorithm and the quantum simplex algorithm as viable subroutines. For quantum linear systems solvers, we formalize a new market assumption milder than market completeness, which allows the potential for large speedups. Towards prototype use cases, we conduct numerical experiments motivated by the Black–Scholes–Merton model.

Assessing the Impact of Derivatives on the 2008 Financial Crisis and the Effectiveness of Subsequent Regulatory Reforms

The 2008 financial crisis was a global financial catastrophe that reflected the misuse of financial derivatives in financial markets, such as credit default swaps, asset-backed securities and collateralized debt obligations, exposing significant weaknesses in the global financial system. These financial instruments were designed to hedge against debt risk, but their lack of transparency and massive misuse ultimately led to the accumulation of systemic risk that accelerated the financial crisis. Since then, regulatory authorities around the world have realized the necessity for stronger regulatory frameworks, and a series of significant reforms have been implemented, such as the Dodd-Frank Wall Street Reform and Consumer Protection Act in the United States, the European Market Infrastructure Regulation in the European Union, and the Basel III international regulatory framework, with the objectives of increasing transparency in financial markets and improving the risk management measures of financial institutions. This paper will explore the role of derivatives in the 2008 financial crisis and examine the effectiveness of these regulatory measures introduced after the crisis in enhancing stability of financial system.

Research on the Pricing Model of Financial Derivatives

Based on the importance of the pricing model of financial derivatives, this paper points out the defects and risks of the current model and proposes some possible solutions. The research method is mainly to summarize the framework of the existing model by searching the academic literature and commercial examples related to the pricing model. The final conclusion is that an obvious flaw of the pricing model is that it is based on an idealized market state and cannot predict hidden market trends, but through random volatility, consideration of market friction, and the development of mathematical technology, the market can refine the pricing model. Research and forecast risk premium, market liquidity and asset price changes in advance when considering pricing. In addition, the market is also supported to consider the application of large machines in the portfolio as well as the issue of options panels, so as to deepen the understanding of the movement of financial products.

Exploring Financial Risk Management: A Qualitative Study on Risk Identification, Evaluation, and Mitigation in Banking, Insurance, and Corporate Finance

The research aims to analyze existing scholarly works to gain insights into risk identification, evaluation, and mitigation strategies. The methodology involves a comprehensive literature search using academic databases such as PubMed, JSTOR, Scopus, and Google Scholar. Inclusion and exclusion criteria are applied to filter relevant sources, and data collection involves reading and critically appraising each selected source. Thematic analysis is employed to identify key findings, themes, and theoretical frameworks. The synthesized findings reveal the importance of risk identification as a fundamental step in effective risk management, encompassing various risks such as credit, market, liquidity, operational, and systemic risks across different sectors. Risk evaluation techniques, including quantitative methods such as value-at-risk modeling and scenario analysis, are crucial for assessing risk impact and likelihood. Risk mitigation strategies, such as financial derivatives, reinsurance, and corporate governance mechanisms, are essential for minimizing risk exposure and enhancing organizational resilience. Challenges such as cybersecurity threats, regulatory complexities, and climate change risks present significant obstacles to risk management. The study highlights the need for integrated risk management approaches that consider emerging threats and uncertainties, promote regulatory cooperation, and leverage technological innovations.

Neural network empowered liquidity pricing in a two-price economy under conic finance settings

In the article at hand neural networks are used to model liquidity in financial markets, under conic finance settings, in two different contexts. That is, on the one hand this paper illustrates how the use of neural networks within a two-price economy allows to obtain accurate pricing and Greeks of financial derivatives, enhancing computational performances compared to classical approaches such as (conic) Monte Carlo. The methodology proposed for this purpose is agnostic of the underlying valuation model, and it easily adapts to all models suitable for pricing in conic financial markets. On the other hand, this article also investigates the possibility of valuing contingent claims under conic assumptions, using local stochastic volatility models, where the local volatility is approximated by means of a (combination of) neural network(s). Moreover, we also show how it is possible to generate hybrid families of distortion functions to better fit the implied liquidity of the market, as well as we introduce a conic version of the SABR model, based on the Wang transform, that still allows for analytical bid and ask pricing formulae.

Stock exchange operations in an anti-crisis management system of the enterprise

Today, in the process of building an effective system of anti-crisis management of the enterprise, more attention should be paid to such less common, but highly effective tools as stock transactions. Anti-crisis management is a certain set of strategic measures and tactical actions aimed at identifying, preventing and overcoming crisis phenomena in the company's activities, as well as impulses that potentially threaten the development of crisis phenomena in the future. The main directions of action are the following: development of the general anti-crisis strategy of the enterprise, ensuring the financial stability of the enterprise, implementation of the risk management system, restructuring of the enterprise and its business processes, personnel and communications management, increasing the efficiency of the marketing system, etc. Speaking about the place of stock exchange operations in the system of anti-crisis management of the enterprise, it should be noted that they can be considered as a tool in the middle of some of the above measures, namely optimization of business processes, improvement of the level of communications and activation of marketing. In all these aspects, the use of exchange operations can be effective. In our opinion, transactions with goods and derivative financial instruments require the main attention. Speaking about the optimization of business processes, the following advantages of cooperation with stock exchange institutions can be distinguished: guaranteed replenishment of production stocks with raw materials and materials of the required quality and quantity due to the conclusion of term exchange agreements for their supply, the forecast level of prices for raw materials and materials, which is fixed during the conclusion of exchange agreements , clearly defined conditions of supply. Access to the stock market also has a positive effect on the level of business communications, because it is the stock exchange that maximally concentrates all interested parties regarding specific types of goods, which contributes to the intensification of business activity. Exchange operations can also be considered as a highly effective tool for activating the marketing activities of the enterprise. In addition to the purchase of raw materials on the stock exchange for your activity, you can use the stock market for the sale of goods manufactured by the enterprise. In this way, the company can guarantee itself future sales in a certain forecasted price range, and accordingly, reasonable planning of the company's performance indicators, cash flows is possible, therefore, it becomes possible to manage insolvency, which is the main crisis impulse for the company.

Navigating the labyrinth of smart contract financial derivatives: Unraveling technical detail and application

This research paper delves into the intricate world of smart contract derivatives, aiming to unravel the technical intricacies and explore their applications. Smart contract derivatives represent a burgeoning intersection of blockchain technology and financial instruments, providing decentralized and automated solutions for derivative trading. The paper navigates through the complex landscape of smart contract derivatives, addressing both the technical aspects of their implementation and the diverse range of applications they unlock. Through a comprehensive review of existing literature, case studies, and real-world examples, this research aims to provide a holistic understanding of the challenges, opportunities, and implications associated with smart contract derivatives. By comprehensively addressing both the technical intricacies and practical applications of smart contract derivatives, this study contributes valuable insights into the rapidly evolving field of decentralized finance.

Research on the Impact of Economic Development on Financial Derivatives

This paper aims to further investigate the impact of economic growth on the demand for financial derivatives, provide effective support to financial market participants and investors, and promote the stable development of financial markets. Firstly, time series analysis models, including autoregressive, mixed autoregressive, and moving average regression, are established by considering various factors in the financial market. Secondly, the basic characteristics of financial derivatives are thoroughly analyzed, and relevant variables are selected for explanation. Finally, the paper elucidates the fundamental functions of financial derivatives and their role in economic growth. The empirical results show that the correlation coefficient between non-financial institution derivatives and enterprise value is 0.2049, and the impact of enterprise economic growth on derivatives demand is 0.0003. Through time series analysis, the study reveals the impact mechanisms of economic cycles, business fluctuations, and other factors on the financial derivatives market, providing effective support for investors and participants.

Who gets the flow? Financial globalisation and wealth inequality

This paper studies whether the advent of financial globalisation has contributed to increasing wealth inequality in the United States, France, and the United Kingdom. I find that (i) positive changes in the benchmark measure of financial globalisation are associated with a positive change in the top 1% and 10% wealth shares and a negative change in the wealth share of the bottom 50% of the distribution. This is equivalent to an average gain of $1 trillion for the top 10% and $1.6 trillion for the top 1%, over the period of interest. (ii) Portfolio equities and financial derivatives appear to be the driving components behind the increase in wealth shares. (iii) The implied change in wealth shares is driven by the accumulation of new financial wealth (flow) rather than the valuation of existing one. (iv) The dynamic is strengthened when a banking crisis hits the economy, possibly because people at the top of the distribution can recover their lost wealth faster than people at the bottom. The main finding is robust to an expanded country sample, albeit reducing the historical context beyond the scope of this paper.

Neural Networks and the Nonlinear Feynman–Kac Theorem Applied to Financial Options Pricing

The classic financial market model proposed by Black and Scholes allows solving, under a series of simplifying assumptions, the problem of valuing financial derivatives. However, these assumptions deviate from the reality of global markets, particularly assuming perfect liquidity. In this work, a financial market model is proposed in which the illiquidity of the risky asset is stochastic, described by a mean-reversion process. The dynamics of the asset price in this context are established alongside the valuation PDE for derivatives. Additionally, as an approximation method to the solution of this PDE, the implementation of the extension of the Feynman–Kac representation theorem to the nonlinear case using deep neural networks is proposed.

SARIMA Model-Based Monte Carlo Simulation of Option Contract Design for Maize Seasonal Heavy Precipitation in Shenyang

Agricultural production is highly dependent on weather conditions such as temperature, light, water and heat. The huge loss caused by extreme disaster weather makes the global insurance and reinsurance market overwhelmed, and seriously affects the enthusiasm of agricultural investment and the development of agricultural economy. With unique topography and vast territory, China is vulnerable to complex and diverse climate disasters. In recent years, the annual average economic loss caused by extreme weather disasters has reached about 200-300 billion yuan, among which floods caused by extreme heavy rainfall are the main agricultural disasters in China. In order to enhance the "farmer - insurance company - government" interest association to resist the risk of flood disaster caused by extreme heavy rainfall, financial hedging derivatives of weather disaster risk have gradually become a new hedging tool besides traditional insurance and reinsurance. This paper takes Shenyang, the main grain producing area in northeast China, as the sample of the study area, and uses the SARIMA model to obtain the distribution characteristics of seasonal rainfall time series. Different seasonal rainfall index option products (call option and put option contracts) are designed respectively, and the final option pricing is obtained by Monte Carlo stochastic simulation. The seasonal rainfall call option and put option contracts have opened up a new hedging model of agricultural extreme weather catastrophe outside the insurance and reinsurance market, which has enriched the varieties of weather financial derivatives market in China, reduced the severe impact of extreme weather disasters on agriculture, and enhanced the ability of agricultural stakeholders to resist the risk of extreme weather disasters.

Hedging Market Risk with the Index: Experiment Based on Chinese Stock Market

The index can be seen as a reflection of the market. Index futures, also known as stock index futures, are financial derivatives whose value is based on the performance of the whole market. As a consequence, investors can hedge the market risk by longing or shorting some specific value of index futures. Based on the idea, the paper tried to hedge the market risk and have a deeply look into whether it works and what characteristics it has. The paper chooses 10 stocks from those who are the components of the three main Index in China. The results show that with all the hedging strategies, volatility is effectively reduced and the ROI significantly increased during the period with acute value changes. The paper refined the whole experiment by randomly choosing the stocks with python and comparing the stock selection within the industry. The experiment verify the feasibility and the effectiveness of the hedging strategies based on the Index.

Contagion and interdependencies between BRICS-plus Countries on the Markets of Commodities and Derivative Financial Instruments

Purpose: This study was started on the main macroeconomic data (2010-2019), coming from the countries of the BRICS-plus group. While a significant contribution of these emerging economies to global economic output has generally been observed, this has also been accompanied by persistent domestic imbalance. Design/Methodology/Approach: Regarding the model, we state and contextualize the (long-term) risk co-incidence of the set of macroeconomic variables for this coalition of countries. Particular attention was paid to a valuation, description and forecasting model based on the calculation of the Dynamic Conditional Correlation (DCC) in a Generalized AutoRegressive Conditional Heteroscedasticity (GARCH) process on the time series of credit default swaps (CDS). Findings: The empirical analysis and calculations carried out have verified the significance of the parameters and confirmed the conditional dynamic correlation between the economies of the Brics “expanded”, especially in the presence of shocks, which also involve mutual contagion (temporary increase in DCC) and even interdependence (increasing DCC leads to new, less unstable levels). Implications/Originality/Value: The research offers a look at the most current trends in terms of international economic balances and the entire global system, focusing on commodity markets, financial derivatives and the impacts of trade at the dawn of the new BRICS-plus coalition.

Empirical Study of Monte Carlo Simulation in SSE 50 ETF Options Pricing

Option is one of the most basic financial derivatives, and the pricing of option has always been a significant research topic in financial engineering. Reasonable pricing of options is the premise of options to play an important role in the financial market, for avoiding market risks, stabilizing the financial market, sustainable development of the derivatives market has vital practical significance. Monte Carlo Simulation is an important simulation method in option pricing and it based on probability theory and mathematical statistics, by simulating the path of asset prices to predict a complete average return and obtain an option price estimate. In this paper, the Monte Carlo simulation is used to make an empirical analysis of China's financial derivative SSE 50 ETF option, and the simulation price is compared with prices simulating by other models, and finally compared with the current price of SSE 50 ETF option. The results show that the SSE 50 ETF call option is recommendable to be bought, and has strong feasibility.

Evolution of option pricing models: From Black-Scholes to Heston and beyond

This essay explores the evolution of option pricing models, tracing their development from the foundational Black-Scholes model to more advanced frameworks such as the Heston model and beyond. Beginning with an introduction to option pricing theory, the essay discusses the origins of the Black-Scholes model and its assumptions, as well as the challenges and limitations it faces. It then examines the extension of the Black-Scholes model, so-called the Black-Scholes-Merton model. It incorporates dividends, and lays the groundwork for further research into options pricing and financial derivatives. Then various stochastic volatility models emerge, and the essay chooses the Heston model as a typical example for analysis, highlighting its advantages and applications in option pricing. Furthermore, the essay compares the Heston model with other option pricing models, including the SABR model and Bates model. At the end of the essay, recent advances and future directions in option pricing are introduced and discussed. Through this comprehensive exploration, readers can gain a deeper understanding of the evolution of option pricing models and their significance in modern finance.