A Volatility Estimator of Stock Market Indices Based on the Intrinsic Entropy Model

Grasping the historical volatility of stock market indices and accurately estimating are two of the major focuses of those involved in the financial securities industry and derivative instruments pricing. This paper presents the results of employing the intrinsic entropy model as a substitute for estimating the volatility of stock market indices. Diverging from the widely used volatility models that take into account only the elements related to the traded prices, namely the open, high, low, and close prices of a trading day (OHLC), the intrinsic entropy model takes into account the traded volumes during the considered time frame as well. We adjust the intraday intrinsic entropy model that we introduced earlier for exchange-traded securities in order to connect daily OHLC prices with the ratio of the corresponding daily volume to the overall volume traded in the considered period. The intrinsic entropy model conceptualizes this ratio as entropic probability or market credence assigned to the corresponding price level. The intrinsic entropy is computed using historical daily data for traded market indices (S&P 500, Dow 30, NYSE Composite, NASDAQ Composite, Nikkei 225, and Hang Seng Index). We compare the results produced by the intrinsic entropy model with the volatility estimates obtained for the same data sets using widely employed industry volatility estimators. The intrinsic entropy model proves to consistently deliver reliable estimates for various time frames while showing peculiarly high values for the coefficient of variation, with the estimates falling in a significantly lower interval range compared with those provided by the other advanced volatility estimators.

On Spillover Effect of Systemic Risk of Listed Securities Companies in China Based on Extended CoVaR Model

Based on the daily data from January 2, 2019, to September 30, 2020, this paper uses the extended CoVaR model to measure the spillover effect of systemic risk among top 10 securities companies by market value in China, All Share Brokerage Index, All Share Financials Index, All Share Insurance Index, and CSI Banks Index. The conclusions are as follows: (1) there are risk spillover effects among 10 securities companies, which are asymmetric and bidirectional and highly volatile in a short period of time; (2) the spillover effect of systematic risk of securities companies is not necessarily related to the market value of securities companies but has a strong relationship with the stock market; (3) there are risk spillover effects between the sample securities companies and the four major indexes, but there are significant differences in the size of the spillover effects; (4) the securities industry has a great risk spillover effect on the financial industry, but the risk spillover effect of other financial sectors on the securities industry is very small. Finally, we put forward countermeasures and suggestions.

Study of Anonymity and Supervision Based on Negotiable Securities Information System

The financial services industry continues to innovate, every day the face of complex trading environment, risk-based supervision has become a serious and important work, how to use technology to enhance the efficiency of supervision and financial regulation capacity, reduce fraud and regulatory costs, effectively guard against financial risk management mechanism. This study takes this concept as the starting point and uses the framework and process of securities industry transactions to be divided into 8 stages: registration stage, account issuance stage, order placement stage, order confirmation stage, transaction return stage, report business stage, data query and supervision and inspection stage, combined with ElGamal play algorithm to meet the requirements of the securities regulatory process, propose a set can have stealth, can not be tampered with, security mechanism and double-blind and other securities regulatory system.

An Empirical Research Survey of the Productivity and Efficiency of the Securities Industry

This paper provides a review of the approaches that have been used to evaluate the productivity and efficiency of the securities industry (financial ratios, econometric techniques, data envelopment analysis-DEA, and the estimation of stochastic frontiers). In undertaking this it identifies some of the organisational structure characteristics of securities companies that are associated with high levels of operational efficiency, particularly regarding the impact of regulation, the structure of ownership, and economies of scope and scale. The findings are that from the limited number of studies that have to date been undertaken it appears that the industry does have economies of scale, benefits from deregulation and performs better with foreign and bank ownership.

COVID-19 considerations for SEC cybersecurity guidance, disclosure, enforcement, and parallel proceedings: navigating the new normal

Purpose To examine the COVID-19 pandemic’s effects on regulated entities within the context of cybersecurity, US Securities and Exchange Commission (SEC) compliance, and parallel proceedings. Design/methodology/approach Describes the SEC’s ability to conduct its operations within the telework environment, its commitment and ability to monitor the securities market, its enhanced monitoring of the adverse effects of SEC-regulated companies from COVID-19, its guidance to public companies of disclosure obligations related to cybersecurity risks and incidents, the SEC Office of Compliance and Examinations’s (OCIE’s) focus on broker-dealers’ and investment advisories’ cybersecurity preparedness, the role and activities of the SEC Division of Enforcement’s Cyber Unit, and parallel proceedings on cyberbreaches and incidents by different agencies, branches of government or private litigants. Findings SEC-regulated entities face many challenges in trying to maintain their ongoing business operations and infrastructure due to severe financial pressures, the threat of infection to employees and customers, and cybersecurity risks posed by remote operations from hackers and fraudsters. The SEC has reemphasized that its long-standing focus on cybersecurity and resiliency within the securities industry will continue, including ongoing vigilance over companies’ efforts to identify, assess, and address the inherent, heightened cybersecurity risks of teleworking and the resource reallocation that business need to sustain their operations until a safe and effective vaccine is developed for COVID-19. Originality/value Expert analysis and guidance from experienced lawyers with expertise in securities, litigation, government enforcement, information technology, data protection, privacy and cybersecurity.

The demographic profile of victims of investment fraud: an update

Purpose This study aims to examine the demographic factors of investors, contributing to financial victimization that occurs in Canada from June of 2008 to December of 2019. Design/methodology/approach In all 235 cases disclosing the details of financial crime victims are collected from the Industry Regulatory Organization of Canada (IIROC) enforcement platform between June of 2009 and December of 2019 for the analysis. The study used a descriptive analysis to showcase the demographic characteristics of investors who have been victims of financial crimes in Canada. Findings The findings indicate that these investors of age 60 and above were more likely to fall prey to various types of financial crime. The results also disclosed that retirees and investors with limited investment knowledge increase the probability of being vulnerable to the perpetrators than others. Research limitations/implications Overall, the study helps regulators in the securities industry gain insights into demographic portraits of the more vulnerable investors. Hence, more precautionary measures could pitch into these concerns to protect specific subsets of investors from investment fraud. Originality/value Individuals who are more vulnerable to investment fraud might not be entirely comparable with the stereotypical victims that most studies portray. The research gap could cause individual investors who appear to be at lower risk to unconsciously fall prey to investment fraud. The IIROC study, detailing the demographic factors of victims, can fill the gap and improve understanding of the tendency of victims.

A Blockchain Prediction Model on Time, Value, and Purchase Based on Markov Chain and Queuing Theory in Stock Trade

With the continuous development of the blockchain, it has brought a subversive impact on the blossom of all fields with its characteristics of decentralization, trust-free, and tampering, especially in the financial field. It is of great significance to research the application of blockchain technology in the financial field. As an important part of the financial market, stock has the crucial influence, and the combination of stock and blockchain is becoming a growing trend. In recent years, many studies have focused on the prediction of the stock value, but they have not fully considered the combination of time, value, and purchase. To solve the above problem, we propose a preemption queuing model for multipriority service objects in the blockchain financial architecture according to different service priority. Meanwhile, a queuing-based resource scheduling model is established by using the Markov chain to find the optimal solution. The method in this paper can greatly improve the efficiency of the system and provide a basis for future scientific research in the healthy and sustainable development of the securities industry.