Artificial Intelligence Approach to Momentum Risk-Taking

We propose a mathematical model of momentum risk-taking, which is essentially real-time risk management focused on short-term volatility. Its implementation, a fully automated momentum equity trading system, is systematically discussed in this paper. It proved to be successful in extensive historical and real-time experiments. Momentum risk-taking is one of the key components of general decision-making, a challenge for artificial intelligence and machine learning. We begin with a new mathematical approach to news impact on share prices, which models well their power-type growth, periodicity, and the market phenomena like price targets and profit-taking. This theory generally requires Bessel and hypergeometric functions. Its discretization results in some tables of bids, basically, expected returns for main investment horizons, the key in our trading system. A preimage of our approach is a new contract card game. There are relations to random processes and the fractional Brownian motion. The ODE we obtained, especially those of Bessel-type, appeared to give surprisingly accurate modeling of the spread of COVID-19.

Illiquidity risk and equity trading performance: A statistical analysis

Subject. The article considers the development of special statistical methods for estimating and analyzing the liquidity risk. Objectives. The purpose is to improve the methodology for statistical appraisal and analysis of risk in equity trading. Methods. The study rests both on well-known methods for equity risk analysis and my own development results (calculation of equity annual illiquidity ratio, formation of illiquidity risk factor). The data analyzed in this paper come from the Moscow Exchange (MOEX) and cover January 2011 to May 2021. The sample included all common stocks traded on MOEX and issuers’ financial statements. I also apply analysis and synthesis, induction and deduction, and methods of comparison and grouping. Results. I calculated monthly illiquidity factor as zero-investment long-short portfolio. I examined the impact of illiquidity risk on the return dynamics of size, book-to-market ratio sorted portfolios. Conclusions. The study shows that expected equity returns are related cross-sectionally to the illiquidity factor. The evidence strongly supports the hypothesis that the illiquidity risk factor is priced. The premium for this risk is positive and offers higher expected returns in equities with strong illiquidity. However, for liquid equities no significant premium is revealed. The offered approach to the factor equity risk analysis based on illiquidity risk enables a true picture of how the risks impact the equity trading performance and how they can be improved in the future.

Blockchain Equity System Transaction Method and System Research Based on Machine Learning and Big Data Algorithm

With the development of machine learning and big data, traditional equity trading system methods can no longer meet the current trading needs, and there are still problems such as low operating efficiency and serious homogeneity. Blockchain technology has the characteristics of decentralization and can also complete transactions through smart contracts, innovating the way of equity system transactions. The purpose of this paper is to build an equity trading system in combination with blockchain in the context of machine learning and big data and provide innovative trading methods, so as to provide reference and reference significance for the construction of my country’s equity market. This article uses literature data method, comparative analysis method, factor analysis method, and other methods to carry out research, in-depth study of machine learning and big data, blockchain-related concepts, system composition, application situation, etc., and discusses the allocation of equity trading market The functions of resources, risk diversification, risk transfer, price determination, etc., have built a blockchain equity trading system, designed a consensus mechanism, block generation protocol, block verification, decentralization, and smart contract platform, and finally conducted a national equity transaction the background of the market is analyzed, and the experimental results, simulation indicators, transaction time, transmission consumption, and other content of the system constructed in this article are analyzed. In the single-node test, the CPU usage of the PoW consensus mechanism algorithm reached 100%, but the improved PBFT consensus mechanism was only 16%, which saved a lot of computing power and improved computing performance.

Impact of Private Equity Trading Platforms on Firm Value and Corporate Governance

This study presents a theoretical model to analyze the effect of private equity trading platforms, which have recently experienced rapid growth, on the investment decisions of unlisted companies. As the value of unlisted companies has soared, demand for these stocks has increased. Accordingly, platforms for the brokerage of private stock transactions are being activated. We find that these platforms increase the liquidity in the unlisted stock market by easing regulations on trading of these stocks, further enhancing the firm values and corporate governance of the corresponding firms. In addition, a significant number of unlisted companies are family-owned, in which a manager is also a blockholder. Our study therefore constructs a framework based on a market microstructure model to analyze the impact of unlisted stock trading platforms. In the case of an unlisted firm, a potential dual agency problem exists where the manager, who is also a blockholder, invests less than the external shareholders’ profit-maximizing levels. We find that managers have the incentives to increase firms’ investment when the liquidity in the unlisted stock market improves with the growth of the private equity trading platform, implying that these platforms potentially enhance corporate governance of unlisted companies and promote their growth.

United States

This technical note considers the regulation and supervision of fund management and equity and derivatives trading in the United States (U.S.). As one of the main destinations for household savings and a key provider of funding to U.S. corporates, investment funds play a major role in the U.S. financial system. Distortions to equity trading could cause significant loss of confidence in markets, while international post-crisis reforms for OTC derivatives have underlined the importance of greater transparency and the value of central clearing. U.S. companies have also traditionally raised more finance through equity and other capital markets than through bank lending, and so capital markets are of greater structural significance in the U.S. than in some other jurisdictions.

Herding in Chile: the case of equity trading in the Chilean pension fund market

The phenomena of ‘herding’ or herd behavior can have important effects when it manifests in equity markets as co-movement in trades of institutional money managers. On one hand, the assetsunder management are so large in comparison with the size of themarket that the trades of these managers affect asset prices, evenmore so if many managers trade in the same direction. On the otherhand, commissions and fees paid by investors are supposedly leviedin exchange for an expert management of the investors’ capital.Thus, a manager that simply imitates the behavior of others does notadd value with her work. The present study is the first to report theresults of two measures of herding used to study this phenomenon inthe equity portions of Chilean AFP (pension) funds. One measure isthe widely used Lakonishok, Vishny y Shleifer (1992) metric, theother is a relatively newer measure presented in Sias (2004). Using adataset of monthly fund trades during the period 2003-2011, bothmeasures find herding in the Chilean market which, while moderatein intensity, is still higher than that reported in the stock markets ofdeveloped countries. More interesting is the asymmetry of results:herding is stronger during times of market crisis, and almostdisappears during periods when the economy expands. These resultshave important implications for performance evaluation and valueadded of the pension funds managed by the AFPs, as well as theimpact of their trades in the stability of the stock market.