Option Trading Research Articles

To Change or Not to Change: The Informativeness of REIT Annual Reports

Increasingly similar corporate disclosures may fail to provide potential investors with adequate information about a company to facilitate astute, informed, and/or rational decision making. In light of this repeatedly expressed SEC concern, the current investigation uses a sample of 1,910 annual report (10-k) filings by 234 separate equity REITs from 2000-2020 to examine the impact of year-over-year linguistic similarity on the perceived information content of corporate disclosures. Consistent with the aforementioned concerns, we document a significant increase in the degree of REIT annual report similarity over time. Despite this trend, we find that innovations in annual report disclosures remain directly related to observable changes in both the operational complexity and financial position of the firm. Furthermore, these innovations engender significant market reactions including changes in options trading activity, annual report readability, and the firm’s cost of equity capital. Lastly, these findings are both robust to the inclusion of alternative information channels and are significantly more pronounced within informationally opaque market settings. In sum, we find REIT annual reports remain a value-relevant source of information for market participants.

Option trading activity and capital reallocation efficiency: Evidence from corporate restructurings

We examine whether option trading enables firms to restructure more efficiently and thus achieve better economic outcomes. We find that more option trading is associated with greater operating performance and higher firm value in the years following restructuring, after controlling for other determinants of performance and value. The central findings survive the consideration of endogeneity. Our results suggest that option trading produces a feedback effect that allows for a more economically efficient allocation of capital.

Synthetic long stock and option trading: Evidence from stock splits

AbstractWe theoretically and empirically identify synthetic long stock as an alternative driver of option trading. Our model proves that the use of synthetic long stocks by capital‐constrained traders contributes to at‐the‐money (ATM) option trading. Using an event study based on stock splits, we document empirical evidence consistent with the model's predictions. ATM option trading declines after stock splits, and these declines are more pronounced for stock splits with higher stock split factors and for more illiquid stocks but are less pronounced for more illiquid options. Our study implies that option trading can occur even without information or opinion dispersion.

Multi-perspective option price forecasting combining parametric and non-parametric pricing models with a new dynamic ensemble framework

This article introduces a dynamic ensemble framework that integrates parametric and non-parametric pricing models. Within this framework, we propose a time-varying parametric pricing model optimized using artificial intelligence algorithms. Additionally, we construct a non-parametric pricing model using a 2-dimensional convolutional neural network (2D-CNN) to capture the interactions among options, enhancing the existing non-parametric pricing model. Validation using China's SSE 50 ETF options trading data reveals several key findings: Firstly, the dynamic integration method proposed in this study not only improves prediction accuracy but also enhances stability. Secondly, previous parametric pricing models do not effectively utilize their pricing performance, while our proposed time-varying parametric pricing model significantly enhances accuracy. Lastly, the 2D-CNN model, which considers interactions among options trades, proves to be reasonable and effective, outperforming common non-parametric pricing models. The dynamic ensemble framework proposed in this study effectively combines the strengths of both parametric and non-parametric pricing models. This research serves as an important reference for risk managers, institutional investors, and other stakeholders. Furthermore, it provides valuable research ideas for future scholars in the field.

Options illiquidity in an over-the-counter market

This article reveals that the intensity of search determines whether illiquid currency options trade at premia or at discounts. For options in a standalone search market, illiquidity leads to price premia, as intermediating dealers, who are presumably short in the equilibrium, demand additional compensation. With the presence of listed options at exchanges, illiquidity results in price discounts, as dealers provide concessions for customers’ alternative trading opportunities. The presence of substitutes changes the market outcome. Illiquidity premia and discounts coexist in a sufficiently one-sided market.

The role of options markets in corporate social responsibility

We explore the relationship between options trading and corporate social responsibility (CSR). We find that options trading can enhance CSR by (i) fostering shareholder activism, as indicated by increased long-term and socially responsible institutional ownership and CSR proposals and (ii) intensifying product market competition, which spurs green innovation and product-related CSR initiatives. The positive effects are more pronounced in well-governed firms but diminished in firms with managerial entrenchment. Moreover, CSR improvements driven by options trading positively influence firm value, with notable enhancements in environmental performance. Our results underscore that options markets play a crucial role in promoting responsible corporate practices.

React Financial Analysis with Interactive Pay-Off Graph and Options Data

Abstract: We propose a System which represents a web-based financial application designed for managing options trading strategies. Developed using React, it offers an intuitive user interface for strategy selection, parameter configuration, and visualization of profit and loss via payoff graphs. The application provides real-time market data, P&L grid views, and insights into option Greeks. It integrates with AWS services for backend processing, handles order placement and status monitoring, and efficiently manages external services and a database. This system architecture is structured for scalability and high-performance in options trading, serving as a comprehensive tool for traders and investors.

Menelaah Keabsahan Kontrak Binary Option pada Unsur Pidana Perjudian

The rapid development and advancement of technology had made everything easy, including accessing the internet. The economy is one of the many fields that have experienced rapid development as a result of technological developments, and investment is no exception. One of the investments that is currently being discussed is the binomo platform. But in reality, binomo is not an investment but a platform that provides binary option services for potential investors. The element of agreement is the most important element in determining whether binary options are included in gambling applications or not. This research aims to examine the validity of the agreement on binomo in determining whether the binary option is included in the gambling application or not. This research uses a normative juridical method with a conceptual approach. The results of this study explain that the validity of the futures contract on the binomo platform in terms of the Civil Code contradicts several articles in the Civil Code, when referring to the valid terms of the agreement in article 1320 of the Civil Code, binomo does not meet when viewed from the 3rd valid requirement, namely a certain thing and the 4th valid requirement, namely a lawful legal cause. the Binary Option Trading mechanism has fulfilled the elements of gambling in accordance with Article 303 Paragraph 3 of the Criminal Code, so that the Binary Option Trading affiliator can also be subject to Article 27 Paragraph 2 of the ITE Law Jo. Article 45 Paragraph 1 of the ITE Law.

Review of Recent Research Directions and Practical Implementation of Low-Frequency Algorithmic Trading

Financial trading has undergone substantial technological evolution, with automation taking center stage, leading to approximately 80% of US market trades being executed by computer systems, predominantly by large financial institutions. The rise of algorithmic trading, poised to engage smaller entities, international markets, and individual traders, drives this article’s exploration of research in this field. Providing a comprehensive overview, it outlines the evolution of trading practices and defines algorithmic trading as a computer-powered tool aiding investment decisions. The article details the steps involved in algorithmic trading, covering opportunity identification, quantitative research, implementation, testing phases, and continuous monitoring. It also examines prevalent programming languages and open-source platforms facilitating algorithm development. Focusing on trading frequencies across financial instruments, it delves into high-frequency trading as a subset, alongside methodologies like technical and fundamental analysis, time series analysis, option trading strategies, and machine learning techniques used in algorithm creation. Categorized by trading frequencies, analytical approaches, involved financial instruments, and analysis objectives, the reviewed papers contribute insights into algorithmic trading’s diverse landscape and methodologies, offering valuable perspectives for industry participants and researchers alike.

Numerical Methods for Option Pricing

Nowadays, financial markets have become more complex and have given rise to more research opportunities, one of which focuses on research related to the pricing of various financial instruments used in options trading. In this essay, a gradual process of reflection is used to deepen the option pricing theory. Firstly, an effective mathematical method for pricing option contracts is using the binomial tree model, a relatively straightforward way of calculating the value of an option. However, it has only two upward and downward trends and has limitations that are the most different from the actual market conditions. That is why the study will have to continue in-depth to get as close as possible to the real situation in the market. The next step is to make the model more in line with market reality by adding a possible rate of change, resulting in the Trinomial Tree Model. The model incorporates the possibility of future price increases, decreases, or stabilization (the third change). The Trinomial Tree Model follows the no-arbitrage principle and removes the assumption of a risk-free market opportunity. This paper derives a method for constraining market prices under risk-neutral conditions. This is crucial for investors seeking profitable outcomes in options trading. The main objective of this research-based paper is to develop a complete theory of option pricing in a one-step trinomial tree model.

Options trading and firm investment efficiency

AbstractWe examine the effect of options trading on an optioned firm's investment decisions. We find that active options trading improves an optioned firm's investment efficiency, and that this effect holds under several alternative empirical specifications and identification strategies, including fixed‐effects models, different matching methods, an instrumental variable approach, a Granger causality test and a quasi‐natural experiment based on the listing decisions of the options exchanges. This relation is mediated by two factors, namely, information asymmetry and uncertainty, consistent with the notion that options trading improves investment efficiency by providing information that facilitates external monitoring and managerial learning. The results of cross‐sectional analyses indicate that the effect of options trading on investment efficiency increases with firms’ tendency to overinvest or underinvest, and with managers’ risk‐taking and learning incentives. We also demonstrate that the effect of options markets on investment efficiency is distinct from the effect of stock markets. Overall, our findings suggest that options trading plays a nonnegligible role in improving an optioned firm's investment efficiency.

A machine learning approach to predict the S&P 500 absolute percent change

Models of the stock market often focus on predicting the direction of the stock market. Instead of following this approach, we created a model to predict the daily absolute percent change of the S&P 500. An accurate model of this metric would greatly increase profitability of option trading strategies such as straddles and iron condors. In this project, novel features were created based on historical data and fed to machine learning algorithms such as Decision Trees, Rule Based Classifiers, K-mean Clusters, and Kernels. Based on our findings, Decision Trees and Kernels showed an accuracy of 80% when predicting absolute percent change, while Rule Based Classifiers had an accuracy of 88%.

Do Credit Rating Agencies Learn from the Options Market?

Do credit rating agencies (CRAs) learn from the options market? We examine this question by exploring the relation between options trading activity and credit rating accuracy. We find that as options trading volume increases, credit ratings become more responsive to expected credit risk and exhibit greater ability to predict future defaults. We also find that CRAs rely more on the options market as a source of ratings-related information when firm default risk is higher, options trading is more informative, manager-provided information is of lower quality, and firm uncertainty is higher. Our results are robust to a number of sensitivity tests, including alternative measures of options trading and credit rating accuracy. We reach similar inferences using various approaches to address endogeneity issues, including difference-in-difference analyses and an instrumental variables approach. Overall, our findings are consistent with the view that CRAs incorporate unique information from the options market into their rating decisions which, in turn, improves credit rating accuracy. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.4980 .

Martingale defects in the volatility surface and bubble conditions in the underlying

AbstractThe martingale theory of bubbles enables testing for asset price bubbles by analyzing option prices. As recently shown by Piiroinen et al. (Asset price bubbles: an option-based indicator, 2018), the SABR model is a strict local martingale when its parameterization implies a positive correlation between stock and option prices. We operationalize this theoretical result and analyze stock price bubbles in 2576 stocks over 26 years. Martingale defect conditions are absorbed quickly by options markets, but identify high proportions in significant and permanent changes in distribution of price returns, option trading activity, short interest in the underlying, and institutional ownership. These results confirm many common assumptions about stock price bubbles. These bubbles are temporally clustered, and tend to occur in periods of positive market development. Martingale defects are rare in market corrections, which indicates that they are a result of overoptimistic speculation.

Quantum Uncertainty and the Black-Scholes Formula

The publication of the Black-Scholes formula in 1973 appeared for the first time to put the pricing of financial options onto a rational and objective basis. Its adoption transformed the perception of option pricing from a form of gambling to scientific risk management, and led to a huge increase in options trading. However while the formula revolutionised the world of finance, and remains the industry-standard pricing model today, its proof relies on a number of assumptions about price behaviour which are often contested, such as that log prices follow a random walk with constant volatility, and that one can constantly buy or sell stocks and options without incurring transaction fees. This paper presents an alternative approach to option pricing, based on a quantum oscillator model of stock prices. In the quantum model, the bid/ask spread between buy and sell prices is treated as a fundamental measure of uncertainty, and volatility is not constant but exhibits a smile-like dependence on strike. We show how the Black-Scholes model and its assumptions lead to a systematic mispricing of commonly-traded options, while results can be improved by adopting the quantum model.

Binary options trading: A deep dive into user perspective and satisfaction

This study delves into the realm of binary options trading, a high-risk investment strategy, through the lens of user perspectives and satisfaction with the Binomo app. Binary options trading, characterized by its simplicity and potential for high returns, has seen a surge in popularity with the advent of online trading platforms. However, it also carries significant risks and legal implications. Through an analysis of 14,341 reviews of the Binomo app, this research uncovers key areas of user concern and interest, including aspects related to money, time, trading, and app functionality. The study reveals a prevalence of negative sentiments, highlighting potential issues of fraud, withdrawal problems, and overall dissatisfaction. Despite the high rating, the study underscores the need for prospective traders to understand the inherent risks and legal implications of binary options trading. The findings provide valuable insights for improving user experience, enhancing transparency and security, and fostering trust among users.

Options Trading and Firm Investment Efficiency

Options Trading and Firm Investment Efficiency

Analisis Juridis terhadap Disparitas Putusan Hakim dalam Tindak Pidana Transaksi Elektronik dan Pencucian Uang (Studi Putusan Nomor :1240/Pid.Sus/2022/PN. Tng dan Putusan Nomor: 576/ Pid,Sus/2022/PN. Blb.)

This article focuses on the crime of electronic transactions and money laundering. This focus was motivated by reports from victims of fraud by Indra Kenz and Doni Salman via videos circulating on social media regarding the investment business. This uses the Binomo and Quotex applications. During the examination at the Tangerang and Bale District Courts, Bandung, there was a disparity in the sentences imposed by the judges in decision Number: 1240/Pid.Sus/2022/PN.Tng and Decision Number: 576/Pid,Sus/2022/PN.Blb. Indra was sentenced to 6 years and Doni to 4 years. Based on this, this article wants to analyze the reasons that the judge considered in deciding the criminal case of electronic transactions and money laundering for the two perpetrators with different sentences for the two perpetrators. This is because the criminal acts committed by the two perpetrators have similarities. This research uses a normative juridical method with a case approach. Sources of legal research materials used consist of judge's decisions, cases to be analyzed, legislation, books (literature) and scientific journals related to writings and data from news articles. The data collection procedure was carried out by searching data on the internet related to the writing topic. All data collected will be compiled and analyzed using theory or expert opinion. Then, this theory is linked to the reasons or legal considerations (ratio decidendi) used by the judge in making his decision. This study concluded that the disparity in sentences imposed on the two perpetrators was due to the lack of clear regulations prohibiting binary option trading affiliates. Apart from that, there are differences in regulations regarding the spread of fake news that harm consumers in the ITE Law and the Consumer Protection Law.

Energy-conservation model of inter-provincial cooperation that accounts GDP and social benefits

With rapid development of the global economy, economic growth is increasingly dependent on energy consumption, and the world faces the associated problems of environmental pollution and depletion of energy sources. This creates a challenge: Our ability to achieve these goals is severely constrained by the current governance based on non-cooperative energy conservation. To improve energy conservation in China, we developed an energy-conservation model based on market mechanisms. The model has three parts: (1) a two-objective (GDP and social benefits) optimization model; (2) a model that determines the optimal trading volume for energy conservation quotas in each province, including division of provinces into quota buyers and sellers and a cooperative game model for energy conservation quotas; and (3) a Nash distribution model for inter-provincial cooperation to fairly distribute the benefits from cooperation. We then used Shandong, Zhejiang, and Jiangsu provinces for an empirical analysis of the cooperative model. With the current territorial management approach, the social benefits of the inter-provincial cooperation based on option trading increased by 2.79 %, and GDP increased by 273.636 × 109 CNY. After a reasonable distribution of the benefits, each province benefited from the cooperation. This demonstrates that our model can improve China's current energy conservation governance.

A Comparative Study of Options with Reference to ICICI Bank, SBI and Axis Bank

Options trading is a dynamic and sophisticated field that shapes investment strategies for big banking organizations in the complex world of financial markets. With a focus on three major participants in the Indian banking industry—ICICI Bank, State Bank of India (SBI), and Axis Bank—this study conducts a thorough comparative analysis. The study aims to dissect and compare the complex tactics, positions in the market, and general performance of these banks in the field of options trading. It provides a thorough analysis of market positioning and competitiveness as well as deep insights into the complex strategies used by each bank. Additionally, it looks to pinpoint the crucial elements of success as well as the difficulties these financial organizations face in the intricate world of options trading. Insightful comparative studies, the discovery of original tactics, an assessment of market positioning, and comprehensive insights into the elements determining success or difficulties faced by ICICI Bank, SBI, and Axis Bank in the ever-changing world of options trading are among the anticipated results. For investors, financial analysts, and regulators who want to understand the intricacies of options trading in the banking industry, this might be a useful tool.