Financial Engineering Applications Research Articles

Application of Financial Engineering in Quantitative Investment Strategy

This paper mainly discusses the application of financial engineering in quantitative investment strategy. Firstly, the importance and function of financial engineering in quantitative investment strategy are introduced, and then the principle and technology of quantitative investment strategy are expounded. Then, the application of financial engineering in quantitative investment strategy is analyzed in detail, including stock market analysis, financial risk management, portfolio optimization, market liquidity analysis and financial innovation. Finally, the contribution of financial engineering in quantitative investment strategy and its future development trend are summarized.

Deep calibration with random grids

We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. [Deep learning volatility: A deep neural network perspective on pricing and calibration in (rough) volatility models. Quant. Finance, 2021, 21(1), 11–27]. with the pointwise two-stage calibration of Bayer and Stemper [Deep calibration of rough stochastic volatility models. Working Paper, arXiv:1810.03399, 2018] and Liu et al. [A neural network-based framework for financial model calibration. J. Math. Ind., 2019, 9(1), 1–28]. Our methodology inherits robustness from the former while not suffering from the need for interpolation/extrapolation techniques, a clear advantage ensured by the pointwise approach. The crucial point to the entire procedure is the generation of implied volatility surfaces on random grids, which one dispenses to the network in the training phase. We support the validity of our calibration technique with several empirical and Monte Carlo experiments for the rough Bergomi and Heston models under a simple but effective parametrization of the forward variance curve. The approach paves the way for valuable applications in financial engineering—for instance, pricing under local stochastic volatility models—and extensions to the fast-growing field of path-dependent volatility models.

Finance Must Be Defended: Cybernetics, Neoliberalism and Environmental, Social, and Governance (ESG)

In the last decade, interest in environmental, social, and governance (ESG) surged dramatically. This article contends that corporate perspectives on ESG—as managing risk and/or returning expected value—are insufficient to account for developments presently unfolding in the ESG finance space. There, novel derivative tools are being developed and deployed, promising to flip the sustainability market on its head. Unlike other sustainability metrics or strategies, ESG derivatives do not attempt to price a given firm’s risk profile in light of the environment, but rather seek to price the risk profile of environmental catastrophe itself. What this translocation of risk prophesies is the direct application of financial engineering to the climate. In this article, re-visiting the late work of Friedrich Hayek and tracing his legacy in Michel Foucault’s lectures on neoliberalism frames my argument that the modern financial system from which these derivatives spring is best understood as a cybernetic one. Cybernetic systems are ones that endeavor to negate entropy and maintain organization by means of information feedback loop-based learning; in finance, this takes the form of Hayekian price discovery. With ESG derivatives, the system of cybernetic finance is presently setting to work converting climate uncertainty into pricing efficiency. Because derivatives such as these represent the polity’s most advanced media for the meaningful sensation of threats, what emerges about the environment from the trade of these products will soon be fed backwards as a powerful set of inputs to governance, shaping how the climate is brought into representation and what responses to its associated crises are possible.

Discussion on the Role of Finance in Financial Innovation and Its Application


 The ever-changing financial environment at home and abroad not only puts forward new requirements for financial engineering innovation, but also provides favorable conditions for its further development. Compared with traditional finance, financial engineering is a relatively new discipline, which plays an irreplaceable role in promoting financial innovation and development based on data analysis and operational research. The application of financial engineering can give full play to its great advantages, predict the risks involved in finance in advance and emphasize finance. The timeliness and expandability of management have obvious effect on preventing financial risks, and at the same time avoid the bad development of national finance. This paper discusses the problems faced by financial engineering in financial innovation, the application of financial engineering in financial innovation and the role of financial engineering in financial innovation.

Research on the Application of Financial Engineering in The Risk Management and Control of Internet Financial Innovation

The article introduces the application advantages of financial engineering in Internet financial risk management and control in detail. Through investigation and research, it finds out the main risks in Internet financial innovation, and proposes effective measures to optimize risk control, such as building a risk management and control system, enhancing Internet finance. Taking an Internet financial enterprise as an example to explore the practical application of financial engineering in its risk management and control, so as to improve the risk control level of Internet finance.

The application of financial engineering in marketing trend analysis

With the continuous expansion of the influence of the new economic era, China's competition in marketing is increasingly fierce. If an enterprise wants to occupy a place in the fierce competition, it must constantly innovate its marketing strategy. This paper takes Shanghai Liangxin Electric Co., Ltd. as an example, combining with financial engineering analysis technology, analyzes the trend of the company's business situation in the next three years. First of all, we use Python to check and process the data. As a creative way, the main financial indicators of the balance sheet of the enterprise in 2015-2017 are analyzed in terms of the ring comparison analysis method, which shows that the operation status of the enterprise in the next three years is getting better and better. This method can effectively promote enterprises to improve their own economic benefits and has a good marketing analysis trend.

Blockchain Based Retail Sukuk for Infrastructure Development and Financial Inclusion in Pakistan

Developments around new technology are opening new avenues for business, commerce, and management. From instantaneous, low-cost transaction processing, clearing, and settlement to the management of government & commercial banking ledgers, disruptive technologies like blockchain has numerous applications in financial engineering and innovative product development. Distributed ledger technology can be used to develop innovative Shariah-compliant products including financial instruments that are beneficial for the growth and development of the Islamic finance industry along with the achievement of Sustainable Development Goals (SDGs). In this paper, blockchain technology is proposed to develop Sukuk to finance development infrastructure projects in Pakistan. With adequate governance, innovative products along with legal and regulatory support, Islamic finance has the potential to make a reasonable contribution towards the development of infrastructure along with the rising standard of living for people, eventually supporting Sustainable Development Goals (SDGs) set by the United Nations General Assembly in 2015 for the year 2030. Rigorous infrastructure is the key to the successful implementation and achievement of Sustainable Development Goals (SDGs).

Exact simulation of Ornstein–Uhlenbeck tempered stable processes

AbstractThere are two types of tempered stable (TS) based Ornstein–Uhlenbeck (OU) processes: (i) the OU-TS process, the OU process driven by a TS subordinator, and (ii) the TS-OU process, the OU process with TS marginal law. They have various applications in financial engineering and econometrics. In the literature, only the second type under the stationary assumption has an exact simulation algorithm. In this paper we develop a unified approach to exactly simulate both types without the stationary assumption. It is mainly based on the distributional decomposition of stochastic processes with the aid of an acceptance–rejection scheme. As the inverse Gaussian distribution is an important special case of TS distribution, we also provide tailored algorithms for the corresponding OU processes. Numerical experiments and tests are reported to demonstrate the accuracy and effectiveness of our algorithms, and some further extensions are also discussed.

On the Practical Application of Financial Engineering in Corporate Financial Management

<p align="justify">The proportion of income and operating expenses will be out of balance once there is no appropriate financial management on the basic finance of corporate operation. The improving of corporate financial management has become the focus of many companies, especially for modern enterprises of strong competitiveness. However, many Chinese companies still adopt traditional financial management techniques, and their effects of risk management are obviously decreasing. Financial engineering is beneficial to the implementation of company’s new management plans. It is essential and plays a critical role in all aspects of business operations. Improvement and innovation should also be made with effort in the process of application.</p>

Analysis on Corporate Financial Engineering and Financial Management Innovation

Corporate financial engineering refers to the use of advanced mathematical and communication techniques to solve financial problems for the maximization of company’s own interests. The techniques are used for innovative designs regarding financial tools and means, and also for devising and implementing financial products. As for corporate financial management, it is the basic guarantee for operating a company. For both the company and its internal and external activities, the support from financial management is inseparable. Financial management is an important link to balance the benefits and costs generated in the process of corporate operation. This article analyzes and explores the effects of the application of financial engineering in financial management.

First Passage Problems of a Reflected Hyper-Exponential Jump Diffusion Process: A Unified Computational Approach

The extant literature on first passage problems of reflected hyper-exponential jump diffusion processes (RHEPs) lacks efficiently computable formulae for the Laplace transform of the joint distribution of the RHEP and its first passage time, cumulative distribution function of the overshoot, expected cumulative value of the discounted increments of the local time up to the first passage time, expected cumulative discounted value of the RHEP up to the first passage time, and expectation of the first passage time. We combine numerical solutions to ordinary integro-differential equations and martingale methods in a novel manner to derive such expressions. For some of these quantities, our approach can deal with the subtle case in which both the RHEP's overall drift and the discount rate equal zero. As a by-product, we obtain a formula for the Laplace transform of the RHEP transition density. We illustrate the numerical performance of our methodology through a few examples. We observe that when the RHEP's overall drift and the discount rate are very close to zero rounding errors can make the evaluation of some of our formulae unreliable. In these situations our exact expression for the case of both zero RHEP's overall drift and discount rate can be an effective approximation for the quantities in question that is substantially more efficient than reliably calculating them using their exact expressions and ``Multiprecision Computing. Our research has applications in financial engineering, insurance, economics, and queueing.

Overcoming the curse of dimensionality in the approximative pricing of financial derivatives with default risks

Parabolic partial differential equations (PDEs) are widely used in the mathematical modeling of natural phenomena and man made complex systems. In particular, parabolic PDEs are a fundamental tool to determine fair prices of financial derivatives in the financial industry. The PDEs appearing in financial engineering applications are often nonlinear and high dimensional since the dimension typically corresponds to the number of considered financial assets. A major issue is that most approximation methods for nonlinear PDEs in the literature suffer under the so-called curse of dimensionality in the sense that the computational effort to compute an approximation with a prescribed accuracy grows exponentially in the dimension of the PDE or in the reciprocal of the prescribed approximation accuracy and nearly all approximation methods have not been shown not to suffer under the curse of dimensionality. Recently, a new class of approximation schemes for semilinear parabolic PDEs, termed full history recursive multilevel Picard (MLP) algorithms, were introduced and it was proven that MLP algorithms do overcome the curse of dimensionality for semilinear heat equations. In this paper we extend those findings to a more general class of semilinear PDEs including as special cases semilinear Black-Scholes equations used for the pricing of financial derivatives with default risks. More specifically, we introduce an MLP algorithm for the approximation of solutions of semilinear Black-Scholes equations and prove that the computational effort of our method grows at most polynomially both in the dimension and the reciprocal of the prescribed approximation accuracy. This is, to the best of our knowledge, the first result showing that the approximation of solutions of semilinear Black-Scholes equations is a polynomially tractable approximation problem.

On the Optimal Design of the Randomized Unbiased Monte Carlo Estimators

In recent literature, a new class of unbiased Monte Carlo estimators have been proposed, which is based on truncating a telescopic representation of the expectation of a functional of the stochastic process at an independent random level. The generality of the method lies in that it can translate any sequence of asymptotically unbiased estimators into a truly unbiased estimator. However, since any independent truncation level can lead to an unbiased estimator, its optimal choice is crucial for the successful implementation of this unbiased Monte Carlo method in financial engineering applications. We develop a novel efficient algorithm to locate the optimal distribution of the random truncation level in general, which answers positively an open question posted in Rhee and Glynn (2015), and we rigorously establish the convergence and optimality of the algorithm and derive its exact complexity. Our algorithm has a much lower complexity as compared to the literature, and numerical examples confirm our findings. The proposed algorithm is shown to be also applicable to optimization problems arising in contextual areas of supply chain management.

FINANCIAL ENGINEERING AS A TOOL FOR THE DEVELOPMENT OF CORPORATE BOND MARKET IN EASTERN EUROPE ON THE EXAMPLE OF UKRAINE

In the context of the gap between the financial and real sectors of the Ukrainian economy, there is a problem of the absence of financial instruments able to solve the issue of financing the development of the national economic system on a long-term basis. At the current stage of the stock market development, financial engineering has a significant potential for the effective application since it can become an instrument that meets the current needs of the market. The purpose of this article is to study the current dynamics of development and features of the corporate bond market in Ukraine, as well as to develop the parameters of the new profit-bonds with the help of financial engineering, which takes into account investors’ inquiries in the formation of an investment portfolio and supposed to be a profitable form of attracting financial resources for issuers. Methodology. Materials of periodicals, analytical market reviews, resources of the Internet are the informational and methodological basis of the investigation. The research is based on general scientific and special methods, such as: comparison, systematic approach factor analysis, economic and mathematical methods. A comparative analysis of the parameters of financial instruments has been carried out that allowed determining the investors’ inquiries, investment trends and features of the choice of financial instruments by investors and accordingly to offer competitive debt securities according to the parameters of payment, maturity, security, repayment order, issue of currency. The results of the study indicate that there is the necessity of reformation of the stock market in terms of expanding the range of financial instruments based on financial engineering. The introduction of profit-bonds will allow offering participants of the Ukrainian market competitive conditions for the issue of securities, which are based on the modelled parameters of bonds. A schematic algorithm for the implementation of profit bonds is developed; it joins a complex of interrelated stages of implementation, which are sensitive to internal and external factors of influence. Practical implications. Directions for improving financial instruments on the basis of financial engineering can be applied by the participants of the stock market that will increase the general level of economic activity in the national economy and permit to accumulate financial resources on the profitable terms. Value/originality. The article reveals the development of the domestic market for corporate bonds as an important segment of the stock market through the application of financial engineering and the use of new financial products created to address the issue of attracting the necessary financial resources to the real sector. The introduction of financial engineering as a tool for the development of Ukrainian corporate bond market and its schematic algorithm of the implementation will allow an investor to react in time to the market changes. The creation of the State Fund for the Guaranteeing of Income of the Investors Market Act, which is formed at the state level by analogy with the existing Guarantee Fund for Individual Deposits, will allow the fulfilment of the security parameter that will classify profit bonds as long-term debt instruments with a high credit rating.

Ordering scalar products with applications in financial engineering and actuarial science

Abstract In this paper we build the increasing convex (concave) order for the scalar product of random vectors with an upper (lower) tail permutation decreasing joint density. As applications, we revisit allocations of portfolio risks in financial engineering and of coverage limits and deductibles in insurance. Some related results in the literature are substantially updated.

Explore the Application of Financial Engineering in the Management of Exchange Rate Risk

In the background where the domestic enterprises commonly have a weak protection consciousness against the exchange rate risk, this article makes a deep analysis based on the definition of exchange rate risk and its cause. By comparison of the traditional management method of exchange rate risk with another one based on financial engineering tools, it also deeply analyzes the method to use the financial engineering technology in the management of exchange rate risk, and concludes the primary purpose of exchange rate risk management is for hedging. This article proposes an optimal analysis method in two aspects, namely the minimum risk and maximum efficiency, for the forward-based optimal hedging, and proposes an optimal analysis method of dynamic hedging for the optimal hedging of option-based tools. Based on the description of the application of financial tools in foreign exchange futures, forward contract, currency exchange and foreign exchange option, it makes an empirical analysis on the management of foreign exchange risk by taking an assumed T company as the carrier and based on the trading tools of forward foreign exchange and currency option, which describes the operation procedure of financial tools in a more direct way and proves the efficiency of the optimal analysis method of this article.

A Two-Sided Laplace Inversion Algorithm with Computable Error Bounds and its Applications in Financial Engineering

Transform-based algorithms have wide applications in applied probability, but rarely provide computable error bounds to guarantee the accuracy. We propose an inversion algorithm for two-sided Laplace transforms with computable error bounds. The algorithm involves a discretization parameter C and a truncation parameter N. By choosing C and N using the error bounds, the algorithm can achieve any desired accuracy. In many cases, the bounds decay exponentially, leading to fast computation. Therefore, the algorithm is especially suitable to provide benchmarks. Examples from financial engineering, including valuation of cumulative distribution functions of asset returns and pricing of European and exotic options, show that our algorithm is fast and easy to implement.

A Two-Sided Laplace Inversion Algorithm with Computable Error Bounds and its Applications in Financial Engineering

Transform-based algorithms have wide applications in applied probability, but rarely provide computable error bounds to guarantee the accuracy. We propose an inversion algorithm for two-sided Laplace transforms with computable error bounds. The algorithm involves a discretization parameterCand a truncation parameterN. By choosingCandNusing the error bounds, the algorithm can achieve any desired accuracy. In many cases, the bounds decay exponentially, leading to fast computation. Therefore, the algorithm is especially suitable to provide benchmarks. Examples from financial engineering, including valuation of cumulative distribution functions of asset returns and pricing of European and exotic options, show that our algorithm is fast and easy to implement.

Localization and Exact Simulation of Brownian Motion-Driven Stochastic Differential Equations

Generating sample paths of stochastic differential equations (SDE) using the Monte Carlo method finds wide applications in financial engineering. Discretization is a popular approximate approach to generating those paths: it is easy to implement but prone to simulation bias. This paper presents a new simulation scheme to exactly generate samples for SDEs. The key observation is that the law of a general SDE can be decomposed into a product of the law of standard Brownian motion and the law of a doubly stochastic Poisson process. An acceptance-rejection algorithm is devised based on the combination of this decomposition and a localization technique. The numerical results corroborates that the mean-square error of the proposed method is in the order of O(t−1/2), which is superior to the conventional discretization schemes. Furthermore, the proposed method also can generate exact samples for SDE with boundaries which the discretization schemes usually find difficulty in dealing with.

Brownian meanders, importance sampling and unbiased simulation of diffusion extremes

Computing expected values of functions involving extreme values of diffusion processes can find many applications in financial engineering. Conventional discretization simulation schemes often converge slowly. We propose a Wiener-measure-decomposition based approach to construct unbiased Monte Carlo estimators. Combined with the importance sampling technique and the Williams path decomposition of Brownian motion, this approach transforms simulating extreme values of a general diffusion process to simulating two Brownian meanders. Numerical experiments show this estimator performs efficiently for diffusions with and without boundaries.