Binary Options Research Articles

Endoport-assisted microsurgical treatment for a ruptured posterior cerebral artery aneurysm: A technical note.

Posterior Cerebral Artery aneurysms are scarce, yet its territory is frequently associated to large and giant aneurysms. Treatment is mostly a binary option between microsurgical clipping and endovascular coiling. Hybrid approaches are an option too, whereas innovation with less frequent techniques such as endoscope-controlled and endoscope-assisted procedure may provide a safer surgical approach with same successful results. Hereby we report a case of a 53 years old male examined at the ER after presenting generalized seizures and altered state of consciousness. Upon arrival, neurological evaluation revealed homonymous right hemianopia. Computed tomography (CT) scan revealed a subarachnoid hemorrhage and left parieto-occipital intraparenchymal hemorrhage with intraventricular extension; computed tomography angiogram (CTA) revealed an aneurysm at the left posterior cerebral artery (PCA) in its P4 segment. We performed a vascular exploration with drainage of the occipital and intraventricular hematoma through a single endoscopic port through transulcal approach guided by neuronavigation, in addition to clipping and aneurysmectomy. The combination of microsurgical clipping with previous Endoport-guided endoscopic procedure may be a surgical-operative option that not only may facilitate the approach to the desired lesion, but also provides a safer surgical scenario.

FINANCIAL MODELING: PROBABILITY THEORETIC APPROACHES

Background. A large number of significant socio-economic events occur under the influence of unique factors. Formal application of probabilistic and statistical methods in such cases leads to analytical conclusions without sufficient scientific justification. Financial modeling reflects modern approaches to the probability interpretation, provides introduction and systematization of risk indicators, and the necessity of improving theoretical and probabilistic disciplines of economic orientation. Analysis of recent research and publications has shown that despite significant investigations, financial modeling is not theoretically complete scientific direction in terms of economic risk indicators and derivative characteristics, important scientific and practical problems remain unresolved in the analysis of socio-economic phenomena in unce­rtainty and implementation of modern achievements of scientists to the process. The aim of the article is to study theoretical and probabilistic concepts of socio-economic processes in conditions of uncertainty and uniqueness based on the financial modeling methods. Materials and methods. Analytical and statistical methods, methods of mathematical statistics and probability theory are used in the research process. Information database is data from trading sessions of world stock markets. Results. Theoretical and probabilistic concepts, including interpretations of probability and risk are considered through formalization of the analysis process by the subject of the socio-economic phenomenon in conditions of uncertainty. Models of typical stationary, dynamic, parity and dominant lotteries with introduced risk indicators are built. Risk is interpreted as the ratio of negative and favorable factors of the phenomenon information background. Relevant indicators are illustrated and calculated using various socio-economic and financial cases. Subjective-probabilistic modeling (SPM) in relation to decision-making in the financial market is studied as the development of Bayesian subjectivism. It has been shown that group consensus SPM-assessments of risk generate specific derivative financial instruments such as binary options, index derivatives, crypto-assets, etc. Conclusion. The results of the study showed the application effectiveness of financial modeling methods of risks assessment in financial markets, the prospects of relevant development in the field of financial engineering. Teaching economic disciplines, which are based on theoretical and probabilistic postulates, statistical and analytical-statistical procedures for calculating probabilistic indicators (probability, risk, prevention regulations, etc.), requires significant addition using the introduction of new methods of information analysis of social background, financial sphere to determine the optimal direction of development and investment activities. Keywords: risk ratio, probability interpretation, binary options, financial modeling, high-risk financial markets, subjective-probabilistic modeling.

An analytical approximation formula for the pricing of credit default swaps with regime switching

We derive an analytical approximation for the price of a credit default swap (CDS) contract under a regime-switching Black–Scholes model. To achieve this, we first derive a general formula for the CDS price, and establish the relationship between the unknown no-default probability and the price of a down-and-out binary option written on the same reference asset. Then we present a two-step procedure: the first step assumes that all the future information of the Markov chain is known at the current time and presents an approximation for the conditional price under a time-dependent Black–Scholes model, based on which the second step derives the target option pricing formula written in a Fourier cosine series. The efficiency and accuracy of the newly derived formula are demonstrated through numerical experiments. doi:10.1017/S1446181121000274

Analoging the digital: Designing better binary option contracts

AbstractBinary option pays a fixed dollar amount if it matures in the money and nothing otherwise. While this cash‐or‐nothing payoff structure is very attractive to speculators, it also creates incentives to manipulate the underlying asset price in order to gain extra payoff. In this paper, we propose better designs for binary options that disincentivize market manipulation and highlight two key features of such designs. We demonstrate the effectiveness of the new contract designs using numerical examples.

Simulating self-selection in public management research: implications from caseworker discretion in the child welfare system

PurposeThe purpose of this study was to measure the bias on a binary option's effect estimate that appeared in the types of questions asked and in the placement changes of public service users.Design/methodology/approachThe author designed Monte Carlo simulations with the analytical strategy of latent trait theory leveraging a probability of care-placement change. The author used difference-in-difference (DID) method to estimate the effects of care settings.FindingsThe author explained the extent of discrepancy between the estimates and the true values of care service effects in changes across time. The time trend of in-home care for the combined effect of in-home care, general maturity, and other environmental factors was estimated in a biased manner, while the bias for the estimate of the incremental effect for foster care could be negligible.Research limitations/implicationsThis study was designed based on individual child-unit only. Therefore, higher-level units, such as care setting or cluster, county, and state, should be considered for the simulation model.Social implicationsThis study contributed to illuminating an overlooked facet in causal inferences that embrace disproportionate selection biases that appear in categorical data scales in public management research.Originality/valueTo model the nuance of a disproportionate self-selection problem, the author constructed a scenario surrounding a caseworker's judgment of care placement in the child welfare system and investigated potential bias of the caseworker's discretion. The unfolding model has not been widely used in public management research, but it can be usefully leveraged for the estimation of a decision probability.

ESMA as a Residual Lawmaker: The Political Economy and Constitutionality of ESMA\u2019s Product Intervention Measures on Complex Financial Products

This article proposes that product intervention constitutes a form of residual lawmaking by ESMA that allows it to tackle aspects of investor protection not addressed by EU incomplete financial laws. Whilst product intervention may bring about certain advantages and may contribute to mitigating regulatory arbitrage problems, it constitutes a highly intrusive regulatory mechanism that raises important questions concerning: (a) ESMA’s rationale and motivations for its use; (b) its compliance with the EU constitutional framework; and (c) its adequacy for the regulation of complex financial products. This article addresses these questions through an analysis of the rationale and consequences of ESMA’s product intervention measures on binary options and contracts for differences of May 2018–July 2019, and of recent reforms of ESMA’s powers. It offers three main contributions to the existing literature. First, it contributes to the literature on administrative discretion and agencies’ rulemaking through an analysis of the political economy of ESMA’s deployment of product intervention powers and, also, of what this reveals about the relationships between ESMA and the EU Institutions, on the one side, and ESMA and National Competent Authorities, on the other. Second, it contributes to the literature on the constitutionality of EU agencies through an examination of the compliance of ESMA’s product intervention measures with EU constitutional law and requirements. Third, it examines whether product intervention constitutes an adequate mechanism to address problems pertaining to investor protection in complex financial products markets and, in doing so, it contributes to the scholarly discussion on complex financial products’ regulation.

Optimizing the Preventive Maintenance Scheduling Based on Dynamic Deterministic Demand in The Cement Manufacturing

Preventive maintenance is a planned and scheduled maintenance method that is carried out before a machine failure occurs. The maintenance schedule can be determined based on experience, historical data, or recommendations. Selecting the maintenance schedule greatly affects the production system. The Clin machine in cement manufacturing has an important role in the cement production process. During treatment, the client machine cannot produce clinker, so it is necessary to plan a production system to meet the demand. This paper aims to design an optimization model for determining the preventive maintenance schedule for cement manufacturing by considering the production process and inventory control. Mathematical models with binary options are used to model that system. The model supports showing the optimal preventive maintenance schedule for the ciln machines with a binary decision each period. This mathematical model describes the interaction of production planning, inventory control, and scheduling of total maintenance on a kiln machine. The goal of this system is to determine the optimal preventive maintenance schedule with minimum costs. In addition, the system's output is the optimal production and inventory decision rule for each period. Based on the analysis and simulation of the model with the deterministic and dynamic demand, the optimal preventive maintenance schedule is in the 9th and 21st periods. The kiln machines are maintained every July with minimal costs. The model scenario shows the interaction of the variables and the sensitivity of the production capacity and demand to the decision rule of the variable.

Guaranteed Deterministic Approach to Superhedging: Case of Binary European Option

For the superreplication problem with discrete time, a guaranteed deterministic formulation is considered: the problem is to guarantee coverage of the contingent liability on sold option under all admissible scenarios. These scenarios are defined by means of a priori defined compacts dependent on price prehistory: the price increments at each point in time must lie in the corresponding compacts. In a general case, we consider a market with trading constraints and assume the absence of transaction costs. The formulation of the problem is game theoretic and leads to the Bellman–Isaacs equations. This paper analyses the solution to these equations for a specific pricing problem, i.e., for a binary option of the European type, within a multiplicative market model, with no trading constraints. A number of solution properties and an algorithm for the numerical solution of the Bellman equations are derived. The interest in this problem, from a mathematical prospective, is related to the discontinuity of the option payoff function.

The use of Contracts for difference (‘CFD’) Spread Bets and Binary Options (‘forbin’) to Trade Foreign Exchange (‘forex’) Commodities and Stocks and Shares in Volatile Financial Markets

This paper examines the popularity of forex and derivatives - contracts for difference (‘CFD’) spread bets and binary options - at a time when the markets are turbulent and speculating by trading is popular. The paper provides theoretical calculations of the probability of success of trading in this way together with empirical evidence.

Do Personal Stories Make Patient Decision Aids More Effective? An Update from the International Patient Decision Aids Standards.

This article evaluates the evidence for the inclusion of patient narratives in patient decision aids (PtDAs). We define patient narratives as stories, testimonials, or anecdotes that provide illustrative examples of the experiences of others that are relevant to the decision at hand. To evaluate the evidence for the effectiveness of narratives in PtDAs, we conducted a narrative scoping review of the literature from January 2013 through June 2019 to identify relevant literature published since the last International Patient Decision Aid Standards (IPDAS) update in 2013. We considered research articles that examined the impact of narratives on relevant outcomes or described relevant theoretical mechanisms. The majority of the empirical work on narratives did not measure concepts that are typically found in the PtDA literature (e.g., decisional conflict). Yet, a few themes emerged from our review that can be applied to the PtDA context, including the impact of narratives on relevant outcomes (knowledge, behavior change, and psychological constructs), as well as several theoretical mechanisms about how and why narratives work that can be applied to the PtDA context. Based on this evidence update, we suggest that there may be situations when narratives could enhance the effectiveness of PtDAs. The recent theoretical work on narratives has underscored the fact that narratives are a multifaceted construct and should no longer be considered a binary option (include narratives or not). However, the bottom line is that the evidence does not support a recommendation for narratives to be a necessary component of PtDAs.

Should we stay or should we go: EU input legitimacy under threat? Social media and Brexit

PurposeThe purpose of the paper is to reflect on the conditions of referenda as an EU input legitimacy, on the era of social media microtargeting campaigns. Taking the case of Brexit as an example, it takes conclusions for the democracy as an inherent value of the EU multilevel polity and opens prospects for possible solutions.Design/methodology/approachThe paper is interdisciplinary based, complementing political science approaches on EU democratic legitimacy and communication studies on social media and political communication. These are the theoretical frameworks for analysing the case of Brexit referendum campaign, which is based on an empirical tracing of strategies and contents used. This empirical assessment is supported by official reports of the House of Commons and of the UK Information Commissioner’s Office and media news on the case. Analysis and discussion of it allows to come to conclusions.FindingsPrimary finding is that manipulation and disinformation occurred in Brexit campaign, creating a biased, fake and unbalanced information. Second main finding is that microtargeting and suppression of public debate enhances the typical polarisation of binary options on a referendum, and in the case of Brexit deepened the social cleavage that already shaped voter’s preferences, once information consumed by citizens functioned as “eco-chambers”, strengthening preconceptions. The ultimate conclusion in this case is a sign that social media can deepen the historical gap between elites and voters in the EU, with negative consequences for democracy and social legitimacy of the EU political system.Research limitations/implicationsThe almost impossible access to the digital microtargeted adverts used in campaigns, to allow a more detailed analysis of the EU content issued.Practical implicationsConclusions of this research are useful for politicians and advisers of policy-making to reflect on the future of the political system of the EU in terms of democracy, and the Europe as a whole and think about measures to be taken either on the level of improving legitimacy processes or regulation of digital media.Social implicationsIf practical implications are taken from conclusions of this study, enhancing democratic processes, avoiding privacy data manipulation and providing accurate, impartial and trustworthy information to citizens public can be a social benefit achieved mainly through regulation.Originality/valueDespite some studies have been released on Brexit referendum, they have mainly been single-disciplinary. This study innovates because it conciliates political science theoretical views with communications studies’ ones, to produce strengthened reasoning ground on the purposed of this research: to search evidence that new political communication strategies within the social media landscape can be of special negative influence in EU referenda and for the future of the multilevel polity.

AN ANALYTICAL APPROXIMATION FORMULA FOR THE PRICING OF CREDIT DEFAULT SWAPS WITH REGIME SWITCHING

AbstractWe derive an analytical approximation for the price of a credit default swap (CDS) contract under a regime-switching Black–Scholes model. To achieve this, we first derive a general formula for the CDS price, and establish the relationship between the unknown no-default probability and the price of a down-and-out binary option written on the same reference asset. Then we present a two-step procedure: the first step assumes that all the future information of the Markov chain is known at the current time and presents an approximation for the conditional price under a time-dependent Black–Scholes model, based on which the second step derives the target option pricing formula written in a Fourier cosine series. The efficiency and accuracy of the newly derived formula are demonstrated through numerical experiments.

Quantum unary approach to option pricing

We present a quantum algorithm for European option pricing in finance, where the key idea is to work in the unary representation of the asset value. The algorithm needs novel circuitry and is divided in three parts: first, the amplitude distribution corresponding to the asset value at maturity is generated using a low depth circuit; second, the computation of the expected return is computed with simple controlled gates; and third, standard Amplitude Estimation is used to gain quantum advantage. On the positive side, unary representation remarkably simplifies the structure and depth of the quantum circuit. Amplitude distributions uses quantum superposition to bypass the role of classical Monte Carlo simulation. The unary representation also provides a post-selection consistency check that allows for a substantial mitigation in the error of the computation. On the negative side, unary representation requires linearly many qubits to represent a target probability distribution, as compared to the logarithmic scaling of binary algorithms. We compare the performance of both unary vs. binary option pricing algorithms using error maps, and find that unary representation may bring a relevant advantage in practice for near-term devices.

An IoT-Based Hedge System for Solar Power Generation

Environmental protection is an important issue in recent decades, and renewable energy is an ideal solution for eco-friendly power generation. Solar-power generation is a popular renewable energy with low cost and small environmental footprint, which leads to exponential growth and high industrial investment. A mature solar business model has been established, but some uncertainties hinder the development, especially when focusing on the lack of solar-radiation. To address these issues, in this article we propose a hedging system to hedge the low-radiation risk for solar-investors through the designed IoT-based data, edge-based models for predicting solar-radiation as well as hedging options. Our experimental results show that the edge-based predictive models can obtain an R-squared value of 0.841 and a correlation coefficient of 0.917. For binary options designed in the hedging system, the broker can obtain stable payoffs with the highest Sharpe ratio of 3.354, and the investors can obtain large payoffs during low-radiation. Our simulation results show the effectiveness of the proposed hedging system for investors (buyer-side), simultaneously, present the motivation of the broker (seller-side) to join the designed hedging system utilized in solar-power generation.

The Development of Consensus-Based Descriptors for Low-Acuity Emergency Medical Services Cases for the South African Setting

Emergency Medical Services (EMS) are designed to respond to and manage patients experiencing life-threatening emergencies; however, not all emergency calls are necessarily emergent and of high acuity. Emergency responses to low-acuity patients affect not only EMS, but other areas of the health care system. However, definitions of low-acuity calls are vague and subjective; therefore, it was necessary to provide a clear description of the low-acuity patient in EMS. The goal of this study was to develop descriptors for "low-acuity EMS patients" through expert consensus within the EMS environment. A Modified Delphi survey was used to develop call-out categories and descriptors of low acuity through expert opinion of practitioners within EMS. Purposive, snowball sampling was used to recruit 60 participants, of which 29 completed all three rounds. An online survey tool was used and offered both binary and free-text options to participants. Consensus of 75% was accepted on the binary options while free text offered further proposals for consideration during the survey. On completion of round two, consensus was obtained on 45% (70/155) of the descriptors, and a further 30% (46/155) consensus was obtained in round three. Experts felt that respiratory distress, unconsciousness, chest pain, and severe hemorrhage cannot be considered low acuity. For other emergency response categories, specific descriptors were offered to denote a case as low acuity. Descriptors of low acuity in EMS are provided in both medical and trauma cases. These descriptors may not only assist in the reduction of unnecessary response and transport of patients, but also assist in identifying the most appropriate response of EMS resources to call-outs. Further development and validation are required of these descriptors in order to improve accuracy and effectiveness within the EMS dispatch environment.

Binary options trading: candlestick prediction using Support Vector Machine (SVM) on M5 time period

Many people choose to trade binary options because it is not difficult to understand. They need to predict whether the price will be higher or lower than their open position in a specific timeframe. The most popular timeframe for binary options traders is the M5 (5-minutes). Many traders prefer to use a candlestick chart model to predict. We use SVM (Support Vector Machine) to indicate the next-candlestick based on the previous-candlestick features in this research. This paper uses six features such as Open Value, Close Value, High Value, Low Value, Volume Value, and previous Candlestick Color on each candlestick. The result of the prediction accuracy using SVM is only 56%.

Translating Taboo: Blasphemy in an Afrikaans Translation of Chaucer’s Canterbury Tales

Summary The purpose of this study is to examine the role of the translator of Chaucer’s Canterbury Tales into Afrikaans in the dual contexts of the ideological milieu that dominated the Afrikaans literary scene and of the literary theory that prevailed at the time. The bulk of the translation fell in the period 1960 to 1980, the heyday of Afrikaner nationalism. The prevalent translation theory in the 1970s and 1980s was Descriptive Translation Studies, with Gideon Toury as its leading exponent. This theory emphasised the need for compliance with the cultural norms of the receiving community, which, in this case, would have included observing a blasphemy taboo. The problem examined here arises from the fact that compliance with this taboo was in conflict with the cultural context of the source text. The translator’s alternation between compliance with and resistance to the taboo is indicative of a translator’s central role in the translation, which became the focus of attention in the 1990s with the rise of the “cultural turn”, espoused by Susan Bassnett and André Lefevere. For these theorists the emphasis fell on the translation process, as opposed to the translation product, the central concern of the Descriptive Translation Studies of the 1970s and 1980s. Rather than viewing norms as determinative, binary options, it is their diachronic variability that merits priority, all the more so in contemporary South Africa.

Probing Covert Progressions

Probing Covert Progressions

A Replicating Portfolio Approach to Valuing American Options in Closed-Form

I derive closed-form expressions for the value of American call and put options (on an asset with continuous yield) using the Feynman-Kac formula, modelling the size of early exercise premium as a function of the strike, dividend yield and time to maturity. Strategies involving European options and binary options on forwards on the asset replicate an American option exactly. Violations of Put-Call parity for American options is also explored in this framework.

Portfolio Optimization for Binary Options Based on Relative Entropy.

The portfolio optimization problem generally refers to creating an investment portfolio or asset allocation that achieves an optimal balance of expected risk and return. These portfolio returns are traditionally assumed to be continuous random variables. In An Entropy-Based Approach to Portfolio Optimization, we introduced a novel non-parametric optimization method based on Shannon entropy, called return-entropy portfolio optimization (REPO), which offers a simple and fast optimization algorithm for assets with continuous returns. Here, in this paper, we would like to extend the REPO approach to the optimization problem for assets with discrete distributed returns, such as those from a Bernoulli distribution like binary options. Under a discrete probability distribution, portfolios of binary options can be viewed as repeated short-term investments with an optimal buy/sell strategy or general betting strategy. Upon the outcome of each contract, the portfolio incurs a profit (success) or loss (failure). This is similar to a series of gambling wagers. Portfolio selection under this setting can be formulated as a new optimization problem called discrete entropic portfolio optimization (DEPO). DEPO creates optimal portfolios for discrete return assets based on expected growth rate and relative entropy. We show how a portfolio of binary options provides an ideal general setting for this kind of portfolio selection. As an example we apply DEPO to a portfolio of short-term foreign exchange currency pair binary options from the NADEX exchange platform and show how it outperforms leading Kelly criterion strategies. We also provide an additional example of a gambling application using a portfolio of sports bets over the course of an NFL season and present the advantages of DEPO over competing Kelly criterion strategies.