TECHNICAL ANALYSIS AND ITS THEORETICAL BASIS FOR TRADING ACTIVITY MANAGEMENT

Research background: In today's era of modern technology, traditional and new methods as well as processes and technologies increasingly contrast. In the first chapter, we focused on a detailed description of the first historical changes in the emergence of trade and financial derivatives. We also identified and described the emergence of specialised trading and stock exchange locations. We continued with a description of the basic methods of analysis and focused on the basics of technical analysis. In the next chapter, we evaluated the current state of research in this area and, based on previous research, we classified and structured individual studies. Purpose of the article: The aim of our contribution is to examine, in detail, the basics and current research in the field of technical analysis. Methods: We consider the inconsistent results of the studies analysed to be very interesting. We consider the unsystematic and inconsistent methodology of the assessment of individual studies to be a major problem. As we mentioned in the article, in many instances the studies analysed focused only on individual aspects of technical analysis and evaluated the final results of the business process. Findings & Value added: In other cases, the results were skewed, mainly due to the nonacceptance of transaction costs or due to risk abstraction. However, despite such results, technical analysis as such can be a valuable tool for predicting price movements. Subsequently, we described our findings, interpreted them, and identified their limitations. We consider the aim of the study to have been met, and believe that it will be beneficial in the field of research on this issue.

Nonlinear differential equations based on the B-S-M model in the pricing of derivatives in financial markets

The pricing and hedging of financial derivatives have become one of the hot research issues in mathematical finance today. In the case of non-risk neutrality, this article uses the martingale method and probability measurement method to study the pricing method and hedging strategy of financial derivatives. This paper also further studies the hedging strategy of financial derivatives in the incomplete market based on the BSM model and converts the solution of this problem into solving a vector on the Hilbert space to its closure. The problem of space projection is to use projection theory to decompose financial derivatives under a given martingale measure. In the imperfect market, the vertical projection theory is used to obtain the approximate pricing method and hedging strategy of financial derivatives in which the underlying asset follows the martingale process; the projection theory is further expanded, and the pricing problem of financial derivatives under the mixed-asset portfolio is obtained. Approximate pricing of financial derivatives; in the discrete state, the hedging investment strategy of financial derivatives H in the imperfect market is found through the method of variance approximation.

A Performance Comparison of Various Bootstrap Methods for Diffusion Processes

In this paper, we compare the finite sample performances of various bootstrap methods for diffusion processes. Though diffusion processes are widely used to analyze stocks, bonds, and many other financial derivatives, they are known to heavily suffer from size distortions of hypothesis tests. While there are many bootstrap methods applicable to diffusion models to reduce such size distortions, their finite sample performances are yet to be investigated. We perform a Monte Carlo simulation comparing the finite sample properties, and our results show that the strong Taylor approximation method produces the best performance, followed by the Hermite expansion method.

Combined Custom Hedging: Optimal Design, Noninsurable Exposure, and Operational Risk Management

Optimal Design of Combined Contingent Claims: Theory and Applications. In “Combined Custom Hedging: Optimal Design, Noninsurable Exposure, and Operational Risk Management”, Paolo Guiotto and Andrea Roncoroni develop a normative framework for the optimal design, value assessment, and operations management integration of financial derivatives. Most business and operating revenues entail a mix of financially insurable and noninsurable risk. A risk-averse firm may face them by positioning in a pair of financial derivatives with optimal bespoke payoff functions; one claim is written on the insurable term, and the other claim is written on any observable index exhibiting correlation to the noninsurable term. On a theoretical ground, the authors 1) state the problem in a general setup and prove existence and uniqueness of the optimal pair of combined claims, 2) show that the optimal payoff functions satisfy a Fredholm integral equation, and 3) assess the incremental benefit the firm obtains by switching from the optimal single-claim custom hedge to the optimal combined custom hedge they propose. On an experimental ground, they show that 1) the optimal combined custom hedge would be empirically relevant for a highly risk-averse firm facing a market shock shown during the first period of the COVID-19 pandemic in 2020, 2) integration with the optimal procurement in a generalized newsvendor model leads to a significant improvement in both risk and return, and: 3) this gain can be traded off for a substantial enhancement in operational flexibility.