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The infusion of algorithms into organizational fields—accelerated by advances in artificial intelligence—can have disruptive effects that trigger defensive responses. One important response involves establishing a boundary around an algorithm to delimit its interactions with its environment—in engineering terms, constructing an "envelope." Yet, we know little about the process through which such envelopes are constructed. We address this issue by exploring how institutional custodians construct envelopes around disruptive algorithms. We empirically examine custodians' responses to the high-frequency trading algorithms that disrupted the field of U.S. securities trading, focusing on the years 2009–2016. Our inductive analysis shows that custodians created an envelope with interconnected normative, governance, and practice "layers" that jointly constrained high-frequency trading. Each layer emerged as custodians "coupled" one element of the field (e.g., its values) to one aspect of the disruptive algorithms (e.g., their impacts). Our study contributes to research on the social dynamics of algorithms by generating novel theory of how envelopes around algorithms are constructed, and to research on institutional custodianship by highlighting the constructing of envelopes as a custodial response to a wide range of threats—including, but not restricted to, disruptive algorithms. [ABSTRACT FROM AUTHOR]

We argue that institutional brokerage networks facilitate liquidity provision and mitigate the price impact of large non-information-motivated trades. Using commissions, we map trading networks of mutual funds (institutions) and their brokers. Central funds (institutions) tend to outperform their peripheral counterparts in terms of return gap (execution shortfall). This outperformance is more pronounced when funds experience large outflows and for large trades in less liquid stocks. Central brokers can deliver superior trade execution compared to peripheral brokers, but mainly for central institutions. We use the collapse of Lehman Brothers as a quasi-natural experiment to establish the likely causality of our findings. [ABSTRACT FROM AUTHOR]

Combining experimental data sets from seven individual studies, including 255 asset markets with 2,031 participants, and 36,326 short-term price forecasts, we analyze the role of heterogeneity of beliefs in the organization of trading behavior by reproducing and reconsidering earlier experimental findings. Our results confirm prior evidence that price expectations affect trading behavior. However, heterogeneity in beliefs does not seem to drive overpricing and asset market bubbles, as suggested by earlier studies, and we find no indication of short-term beliefs being better determinants of trading behavior than longer-term beliefs. [ABSTRACT FROM AUTHOR]

We identify Industry-Neutral Self-Financed Informed Trading (INSFIT) as stock trades financed by offsetting, equivalent dollar-denominated stock trades in the same industry. Approximately 37% of short-term mutual fund trading profits can be attributed to these trade pairs. Consistent with informed trading, INSFIT precedes unusually high media coverage for the underlying stocks. The trades underlying INSFIT are also larger as the release of stock-level news becomes more imminent. Both relative valuation and the hedging of industry exposure motivate INSFIT's industry neutrality. While INSFIT positively impacts fund performance, active fund managers who execute INSFIT more aggressively obtain smaller trading profits per execution. [ABSTRACT FROM AUTHOR]

Momentum profits depend mainly on the short leg and therefore on barriers to short sales. Our research indicates that the decline in momentum profitability in the past 2 decades is driven partly by a contemporaneous growth in stock options trading. Stock options offer an alternative to short selling, augmenting the stock lending market, and thereby contributing to improved pricing efficiency. The resulting reduction in barriers to short sales contributes to lower returns to momentum trading from the short leg. Our results persist after matching stocks with and without options based on different firm-level characteristics. [ABSTRACT FROM AUTHOR]

A short squeeze occurs if borrowed shares are recalled and the short seller is unable to find another source of shares. This forces the short seller to terminate a position early. For most stocks, the probability of a short squeeze is very low. Short squeezes, however, are not unusual for the hardest to borrow stocks. For these stocks, trading costs from squeezes are high and have a significant impact on the returns to short selling. For hard-to-borrow stocks, short sellers also miss out on significant abnormal returns because squeezes force them to close positions. [ABSTRACT FROM AUTHOR]

U.S. equity exchanges have experienced a dramatic increase in competition from new entrants, resulting in the fragmentation of trading across venues. While market quality has generally improved over this period, we show most of the improvements have accrued to the largest stocks. We then show this bifurcation in market quality is related to the fragmentation of trading. Theoretically, more exchange competition should reduce trading costs, yet it may also increase adverse selection for liquidity providers, leading to higher spreads. We document evidence of both effects (fragmentation improves market quality for large stocks while small stocks experience relatively worse quality). [ABSTRACT FROM AUTHOR]

Programmatic advertising has come to dominate the landscape of digital media planning. To prepare ad majors for their future careers in the industry, it is essential to teach students programmatic buying and provide them with hands-on experience. In this article, the authors present their approach of integrating teaching programmatic buying into a media planning course. A key feature of their educational package is a custom digital media buying tool developed by the authors. They hope this article will benefit other college educators in this field and spark further discussions on best teaching practices of programmatic buying and digital media planning. [ABSTRACT FROM AUTHOR]

This article examines the impact of ideational elements on state efforts to achieve regional integration, with a specific focus on Morocco's pursuit of membership in the Economic Community of West African States (ECOWAS). This study investigates how shared cultural heritage, historical narratives, and common views on principles such as free trade and security partnerships foster a sense of collective identity among states, thereby promoting deeper cooperation and integration within regions. However, conflicting ideologies can create obstacles to meaningful integration by breeding distrust and friction among participating states. This study argues that constructivism provides valuable insights into regional integration processes by emphasizing the importance of shared norms, identities, and social interactions among states. The analysis reveals thatMorocco's aspiration to align with the interests of other African states in ECOWAS and promote economic integration serves as the ideological basis for its pursuit of ECOWAS membership, viewing it as a symbol of African resurgence and a means to strengthen its regional position. Although Morocco's history, laws, society, and politics align with ECOWAS norms, the absence of provisions for new members in the ECOWAS Treaty presents a hurdle for Moroccan accession. Nevertheless, this article suggests that the ECOWAS Authority of the Heads of State and Government could potentially address this issue by establishing a supplementary protocol to admit Morocco, underscoring the significance of ideological factors in shaping regional integration processes and institutions. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are promising tools in mobile communication due to their flexibility. However, the rapid development of mobile communications further intensifies the challenge of spectrum scarcity, necessitating spectrum sharing with other systems. We suggest a Spectrum Sharing Algorithm for a UAV-Assisted Relay System. The utility function of secondary users (SUs) is defined by their communication rate, rewards from relay primary users (PUs), and spectrum leasing expenses. The utility function of PUs consists of their communication rate and revenue from spectrum leasing. We propose a joint optimization algorithm for the positioning and power allocation of UAVs, maximizing the frequency spectrum utilization rate of users. Spectrum trading between PUs and SUs is modeled as a Stackelberg game, and the problem is solved by using Lagrange multipliers and KKT conditions. To enhance the security of spectrum trading, a reputation-based spectrum sharing blockchain consensus algorithm is designed. We utilize Shamir's secret sharing method to reduce computational complexity. Additionally, we design a smart contract to optimize the functionality of transaction transfers. The findings demonstrate that the proposed algorithm enhances the benefits for both participants in spectrum sharing, while safeguarding the security of spectrum transactions. [ABSTRACT FROM AUTHOR]

This article deals with the security sliding mode control (SMC) issue for T‐S fuzzy systems under random injection attacks. As a way to increase the communication efficiency of network control systems, the weighted try‐once‐discard (WTOD) protocol is utilized to decide whether the sensor nodes transmit or not. A compensating strategy is introduced in this controller side, based on which a fuzzy sliding mode controller depending on the scheduling signal is constructed. Then, the reachability of the given sliding surface together with the stochastic stability of the closed‐loop system are analyzed by incorporating the membership function, and the relaxed stability conditions are derived. Moreover, a GA‐based solving algorithm is proposed to search an optimized sliding matrix and improve the SMC performance. Finally, numerical simulation results are provided to verify the proposed SMC strategy. [ABSTRACT FROM AUTHOR]

Financial securities fraud is one of the serious problems facing the global financial market at present, which not only destroys the fairness of the market, but also has a serious negative impact on investors and the economic system. The aim of this research is to develop and implement a deep learning-based approach to the identification and prevention of financial securities fraud. Firstly, the definition, types and characteristics of financial securities fraud are deeply discussed, and a financial securities fraud detection model is constructed with the help of deep learning technology. The model is trained, tested and optimized by collecting and preprocessing large amounts of securities trading data and corporate financial reporting data. The empirical results show that our model has high accuracy and precision in the task of financial securities fraud detection. However, this study also reveals some challenges and limitations, such as problems with the model's interpretability and adaptability to novel fraud strategies. Nevertheless, we believe that as deep learning technology is further developed and improved, its application in financial securities fraud identification and prevention will become more widespread and effective. [ABSTRACT FROM AUTHOR]

In this article, we examine for the first time a set of securities traded in the Baltic stock exchanges for indication of price clustering. This study adds to the literature about the efficiency of the Baltic stock markets, as well as to knowledge about the clustering of financial prices. Our main conclusion is that clustering is pervasive at the firm level, with traders having a striking preference for closing prices ending in zero. Price clustering tends to increase with price level, turnover, and relative spread and to decrease with tick size. Overall, our results are consistent with the idea that the lower the cost of rounding prices and the greater the uncertainty about the proper value of the securities, the higher the propensity of prices to cluster at round numbers. Therefore, the evidence provides some support for the negotiation/resolution hypotheses. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, computer intelligent grouping, as a research hotspot of political ideology examination paper proposition, can greatly shorten the time of generating examination papers, reduce the human cost, reduce the human factor, and improve the quality of political ideology teaching evaluation. Aiming at the problem that the current political ideology examination paper-grouping strategy method easily falls into the local optimum, a kind of intelligent paper-grouping method for political ideology examination based on the improved stock market trading optimisation algorithm is proposed. Firstly, by analyzing the traditional steps of political test paper generation, according to the index genus of the grouping problem and the condition constraints, we construct the grouping model of political thought test questions; then, combining the segmented real number coding method and the fitness function, we use the securities market trading optimization algorithm based on the Circle chaotic mapping initialization strategy and adaptive tdistribution variability strategy to solve the grouping problem of the political thought test. The experimental results show that the method can effectively find the optimal strategy of political thought exam grouping, and the test questions have higher knowledge point coverage, moderate difficulty, and more stable performance. [ABSTRACT FROM AUTHOR]

We document that a significant number of insiders violate the Securities and Exchange Commission (SEC) reporting requirements by filing open market transactions after the legally required deadline. Prior to the Sarbanes–Oxley Act (SOX), 29% of transactions fell outside the required reporting window. Following SOX, 8% are delinquent. Violations cluster in periods of high information asymmetry, incentivizing insiders to keep trades private and earn abnormal returns. Collectively, these findings suggest that a subgroup of insiders personally benefit from violating SEC disclosure requirements. Evidence also suggests that blockholders provide governance for violations. Guilty insiders experience a reduction in board seats and an increased likelihood of turnover. [ABSTRACT FROM AUTHOR]

Practitioners allocate substantial resources to technical analysis whereas academic theories of market efficiency rule out technical trading profitability. We study this long-standing puzzle by applying a diverse set of machine learning algorithms. The results show that an investor can find profitable technical trading rules using past prices, and that this out-of-sample profitability decreases through time, showing that markets have become more efficient over time. In addition, we find that the evolutionary genetic algorithm's attitude in not shying away from erroneous predictions gives it an edge in building profitable strategies compared to the strict loss-minimization-focused machine learning algorithms. [ABSTRACT FROM AUTHOR]

We link equity and treasury bond markets via an informational channel. When macroeconomic state shifts are more probable, informed traders are more likely to have valid signals about fundamentals, so that uninformed traders are less willing to trade against informed ones. This implies low volume and high volatility, that is, a high volatility–volume ratio (VVR). Central banks react to state shifts, but their actions are uncertain. Therefore, a higher state shift likelihood implies larger bond risk premia. These arguments together imply that VVR should positively predict bond excess returns. We empirically test and confirm this prediction, both in- and out-of-sample. [ABSTRACT FROM AUTHOR]

The coqu llanero seems like an unlikely mascot for bold investing. Pale yellow and no wider than a dime, the tiny Puerto Rican frog bears little resemblance to the bulls, [...]

Current data trading systems only support plaintext or unaudited private transactions. To overcome these, we present a confidential batch payment scheme with integrated auditing for enhanced data trading security. We use Castagnos–Laguillaumie (CL) homomorphic encryption and batch zero-knowledge proofs to construct the scheme. The scheme reduces decryption complexity and ciphertext length while enabling malicious model operations. In addition, it supports efficient batch payments to multiple recipients and includes features for payment statistic analysis and auditing. Experimental results indicate that the system efficiently handles encryption, decryption, and auditing tasks, completing each operation in an average of 0.89, 1.55, and 1.55 milliseconds, respectively. [ABSTRACT FROM AUTHOR]

Quantum secret sharing is a basic quantum cryptographic primitive, which has a lot of applications in information security and privacy preservation. An efficient multiparty quantum secret sharing protocol (Kuo et al. in EPJ Quantum Technol 10(1):29, 2023) based on a novel structure and single qubits was reported recently. In this paper, we give a cryptanalysis of this protocol and show that it cannot satisfy the security requirement for secret sharing because an unauthorized set of agents can gain access to some information on the dealer's secret by a special collusion attack. Furthermore, we put forward a way to deal with the security problem. [ABSTRACT FROM AUTHOR]

The widespread practice of Bring your own device (BYOD) to work significantly raises cyberse- curity risks. All organization’s employees and employers will greatly benefit from this trend. The growth of spyware, malware and other dubious downloads on individual devices has compelled the government to review its data security guidelines. Without user knowledge, hazardous apps are downloaded to personal devices. Both people and governments could suffer tragic conse- quences as a result of this. In this situation, BYODs are problematic since they can alter policies without permission and release private information. The main goal of the research was to detect fraudulent communications coming from BYOD environments. A network monitoring and man- aging information configuration settings of mobile devices in the network is established by providing policies and authenticating endpoint devices in the BYOD network using a mix of NAC and MDM. This framework deals with Security Manager (SaaS) as the second module is briefly described. The study’s early results were positive and suggested that the framework would lessen access control-related issues. [ABSTRACT FROM AUTHOR]

Wireless network attacks are some of the most common network security threats dealt with daily. Their ease of execution and effectiveness make them commonplace within most public networks. The goal of this paper is to develop a tool which provides defenses against these attacks, one which can also generate the attacks to test its own effectiveness in defending against them. The research involved the design, testing, and implementation of attacks/defenses tool, which benefits from a user-friendly user interface that simplifies the testing process. The attacks were generated using existing tools, linked to one central interface. The defense methodology was scriptbased and created entirely from scratch. It was also linked to a single interface which continuously monitors logs to detect and prevent attacks in an efficient timely manner. The results showed that the proposed defenses to the studied wireless attacks were effective at mitigation, or outright prevention. They were also more lightweight than existing solutions, making them more appealing for less powerful hardware. [ABSTRACT FROM AUTHOR]

Washington policy research analysts (WAs) monitor political developments and produce research to interpret the impact of these events. We find institutional clients channel more commissions to brokerages providing policy research and commission-allocating institutional clients generate superior returns on their politically sensitive trades. We find that WA policy research reports are associated with significant price and volume reactions. Finally, we find sell-side analysts with access to WA issue superior stock recommendations on politically sensitive stocks. These effects are particularly acute during periods of high political uncertainty. Overall, we uncover a unique and an important conduit through which political information filters into asset prices. This paper was accepted by David Sraer, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4919. [ABSTRACT FROM AUTHOR]

AbstractThe island of Syros in the Cyclades almost spontaneously emerged in 1830 as a prominent transit and trade hub for Greece and the Ottoman Empire. The present work is an attempt to conduct a deductive reading on the impressive number of documents produced by the Ottoman Consulate General of Syros (şehbenderlik) records to answer two interrelated questions: (I) how the Ottoman Empire engaged with its former territory and (II) what kind of diplomatic tools the Sublime Porte used to deal with the security challenges it perceived emerging in the Eastern Mediterranean after the establishment of the Hellenic Kingdom in 1830. Delimiting a definition of illegality during the Age of Mobility in the Middle East, the states depended on one another to control and define the movements of illegality but paradoxically refused to cooperate. Frustrated, the Ottoman Empire, appropriated from European international legal thought, acted in typical nineteenth-century imperial coerciveness and considered using force to occupy Syros to compel the Greek state. The current article asserts that the Ottomans not only appropriated the French model of diplomacy but also European justifications of imperialism as it pertained to diplomatic coercion. [ABSTRACT FROM AUTHOR]

The discussion regarding the responsibility of municipalities in dealing with public security has always led to divergent opinions. However, with the publication of Law No. 13,675/2018, which created the Unified Public Security System and included municipalities in the process of creating security policies, brought new responsibilities to the municipal executive branch. Given this context, this research aimed to analyze the potential of the Municipal Public Administration of Estância/SE in complying with the National Public Security and Social Defense Policy, established by Law No. 13,675/18. The methodology adopted an descriptive research, based on a case study in the Municipality of Estância/SE, outlined by bibliographic and documentary research, based on a qualitative approach. The results showed that the Municipality of Estância/SE has sought to comply with the national public security policy, in addition to having other means of obtaining financial resources to exercise security in the municipality. However, there was a need to accelerate the process of constructing the policy and creating some instruments, such as the observatory and public security council, considering that they are essential attributes for the application for resources from the National Public Security Fund. [ABSTRACT FROM AUTHOR]

Strong commercial ties promote peace as states shun the opportunity costs of economic disruption. However, trade also enriches and empowers states, rendering them more capable of enforcing long-term settlements. Given economic disruption does not last forever, countries can be incentivized to trade short-term economic losses for long-term political or territorial gains. This trade-off can restrict or even reverse the pacifying effect of commerce as it renders states incapable of committing to existing peaceful deals. I argue the scope condition hinges on the existing power imbalance and the security externalities of trade, defined as states' abilities to translate trade gains into (potential) military power. For countries where the existing power gap is not extreme, the impact of bilateral strategic trade is contingent upon a country's trade externality relative to its opponent's. Although increased bilateral trade can be peace-promoting when the relative externality is small, the pacifying effects can dissipate as a relatively weaker state becomes more capable of exploiting trade gains. Building on recent work in network analysis, I propose a new measurement of trade externalities to test the above theory and find supporting results. [ABSTRACT FROM AUTHOR]

From an economic perspective, rice is not only a principal staple food for nearly half of the world's population but also a significant commodity in many countries. Consequently, the accuracy of demand uncertainty concerning rice imports, which can be useful information to support critical decision-making on trading and food security management, is very challenging. The proposed model of simple exponential smoothing, support vector regression, and generalized simulated annealing is proposed and developed to predict annual rice imports based on twenty datasets across importer countries. The proposed model takes advantage of both suitable parameter selection and noise reduction in systematic error reduction with smoothing series to achieve more accuracy and precision. The empirical results revealed that the proposed model can improve accuracy based on five accuracy measures and is significantly different from other models at 0.05 significance levels. Moreover, the proposed model can provide consistency and reliability for forecasting rice imports in advance. Consequently, the proposed model can be a promising tool to support decision-making for policymakers. [ABSTRACT FROM AUTHOR]

The intersection of trade openness and national security in the realm of international trade law constitutes a nuanced and intricate landscape. This paper endeavors to unravel the complexities inherent in this delicate equilibrium, examining legal frameworks within the General Agreement on Tariffs and Trade (GATT)/World Trade Organization (WTO), Regional Trade Agreements (RTAs), and emerging global trends. The foundational principles outlined in GATT, particularly Article XXI, acknowledge the sovereign right of nations to take actions necessary for their essential security interests. However, the broad and permissive nature of this provision introduces challenges related to potential misuse and a lack of robust scrutiny mechanisms. The proliferation of RTAs, each housing unique national security clauses, adds layers of complexity to the overarching legal framework. Divergent standards, conflicting obligations, and the risk of fragmentation highlight the intricate balancing act that nations must perform to reconcile regional commitments with the principles of the global trade governance structure. The paper delves into practical applications and case studies, dissecting the challenges nations face as they navigate the fine line between economic integration and strategic safeguarding. [ABSTRACT FROM AUTHOR]

Trading actors like the European Union (EU) are increasingly seen as geopoliticising trade policy, but such assertions may not capture the extent to which the Directorate General for Trade (DG Trade) uses this policy to achieve security objectives. This article investigates changes over time in justifications for trade policy by differentiating between how the EU and DG Trade use frames – articulated in four EU trade strategies with two DG Trade strategic plans and 10 annual management plans – to propose solutions in response to the geoeconomic turn. This article finds that, whilst DG Trade's discourse continues to reflect the dominant market liberal frame, geopoliticising pressures are encouraging the emergence of an EU counter‐frame linking trade to non‐trade issues and a reframing of the counter‐frame that increasingly links trade and security policy. As a result, the EU's framing of trade policy resembles deep geopoliticisation, whilst DG Trade's framing resembles reluctant geopoliticisation. [ABSTRACT FROM AUTHOR]

Leveraging the availability of a large panel of signed trade data in the corporate bond market, we explore how machine learning methods can be used to improve upon standard trade direction classification methods in markets in general, both with and without pre-trade transparency. Using the signed data set allows us to show how both the trading and information environment at the time of the trade critically affect the accuracy of existing trade classification rules in general and also illustrate the importance of optimizing the feature set in correctly classifying trade direction. These insights extend to the equity market. [ABSTRACT FROM AUTHOR]

The Southern District of New York's July 2023 decision in SEC v. Ripple Labs, Inc. has been touted as a monumental win for cryptocurrency purchasers and related businesses. The Ripple court held that, except institutional investor transactions, all sales of Ripple's XRP token were not investment contracts, a class of security subject to federal securities law. The court's ruling meant that Ripple could not be held liable for the unregistered trading of XRP beyond its sales to institutional investors. Ripple adds new insights to a pervasive policymaking dilemma addressed in this Note: is the Securities and Exchange Commission's (SEC) regulatory approach effectively serving purchasers? This Note answers this question in the negative and explores the disconnect between the SEC's approach and the actual protection of purchasers. First, it briefly surveys the value of cryptocurrency like XRP to outline the many forms digital assets take beyond a passive, speculative investment. Second, it outlines the framework for SEC enforcement under the Supreme Court's Howey test for "investment contracts" and securities registration requirements in Section 5 of the Securities Act. Third, it examines the Ripple court's holding regarding reasonable expectation of profit to distinguish XRP trading activity from investment contracts under Howey. Fourth, it contends that the Ripple court's focus on enforcing securities law to protect reasonable investor expectations of profit is a proper step toward addressing a larger regulatory disconnect between the SEC and the investing public it is entrusted to serve. [ABSTRACT FROM AUTHOR]

As Internet of Things (IoT) is a realism that variations in numerous aspects of our everyday life, from smart monitoring to the management of life-threatening infrastructure. In the modern world, secure communication is vital, and it is accomplished by routing protocol. The routing protocol for low power and lossy networks (RPL) is the only defector-consistent routing protocol in IoT systems and is thus deployed for many IoT applications. In the literature, we can bargain several attacks pointing to affect and interrupt RPL-based networks. Therefore, it is essential to develop security apparatuses that detect and mitigate any probable attack in RPL-based networks. Current state-of-the-art security solutions deal with very few attacks while proposing heavy mechanisms at the expense of IoT systems and overall network performance. In this paper, we proposed secure hybrid and collaborative intrusion detection in RPL based on blockchain (Block-RPL) to overcome these issues. The propounded work has wrapped out with four phases as symbolized as follows: network fabrication and node authentication, ideal parent node election, and Deep Learningassisted collaborative and hybrid intrusion detection. Initially, we perform network fabrication in order to ideally place the Mr. Fixits and to cope with the network dynamics using the Bettered Remora Algorithm (Be-Remo). Then, the RPL topology is urged to register at the Dutiful Advisor (DA) by charitable parameters, and the DA offers the secret key to the nodes using the Boosted CHACHA algorithm (B-CHACHA). Subsequently, the root node in the RPL disseminates the DODAG Information Object (DIO) messages and each node selects its parent by considering several optimal features using the Be-Remo algorithm. Finally, collaborative and hybrid (i.e., specification and anomaly) intrusion detection is performed based on network behaviors using the Light residual attention mechanism aided by the VGG16 algorithm (LightVGG16). In our work, we have employed blockchain for data privacy and enhancing security during message dissemination. The proposed work was conducted using the Cooja simulator available in Contiki OS, and the performance of the proposed Block-RPL model is itemized based on various performance metrics in terms of number of the DIOs received, downward latency, energy consumption and attack detection accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Realidad Economica is the property of Realidad Economica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study explains how the gap between theory and empirical research hinders scientific progress in the area of international political economy. To demonstrate this point, I use Chen's Extended Dependence Theory, which challenges liberal peace theory but fails to provide supporting empirical evidence. Chen contends that it is not trade dependence between two states that fosters peace but a challenger's trade relations with the defense-pact partners of the target. Although Chen criticizes liberal peace proponents whose primary concern is how to deter war, his empirical analysis is confined to how to decrease (fatal) militarized disputes short of war. I argue that for his theory to succeed, it must be validated against the most severe and intense form of conflict. Using statistical tests and substantive significance, I uncover no peace-building effect, with regards to war, attributable to Extended Dependence. It appears that the Extended Dependence variable exhibits a ceiling effect. Future research should explain why economic ties and security institutions fail to work together to lower the risk of the most destructive form of conflict. [ABSTRACT FROM AUTHOR]

Enormous information is an accumulation of vast measures of information that contains copied things gathered from different sources. Distinguishing copied information from enormous information is a difficult issue. In this paper secure deduplication scheme has been presented for huge information stockpiling. Customers may store and transmit data effectively and efficiently due to cloud service providers. Providers of cloud services are drawn to the application of data de-duplication tools to lower storage costs and conserve bandwidth. To secure the data they share on the cloud, users of the cloud are interested in having a secure and private connection. As a result, the priory is transferred to the cloud, and the data is encrypted. Because the encryption objective conflicts with the purpose of data deduplication, this feature presents a difficult problem. The author then suggested brand-new hybrid chunking methods to boost deduplication performance in cloud storage. Content-based hybrid chunking algorithm of Two Threshold Two Divisor (TTTD) with a Dynamic Prime Coding (DPC) algorithm is suggested for reducing the deduplication data. To increase throughput, which means reducing execution time and CPU resource utilisation, an index method must be incorporated into the deduplication matching process. For chunks with higher security levels, it offers greater security protection, while for chunks with lower security levels, it trades off security for greater deduplication effectiveness. When moving data to open, semi-trusted systems like public clouds, identity management, secure data exchange, and privacy preservation become more challenging than they are in closed, trusted systems where security and privacy can be controlled more simply. Accordingly, the article proposed a cross-domain authentication technique for the verification process. Evaluations of the real-world datasets show the efficiency of the design. With other methods, the proposed hybrid Content-based TTTD-DPC analyses many performance parameters, including chunk distribution, processing time, chunking time, throughput, average chunk size, and deduplication ratio. The deduplication system's total throughput and processing speed are both enhanced by the proposed approach. In addition, the recommended methodology reduces computational cost (772 ms) in terms of hash function compared to other existing methods. [ABSTRACT FROM AUTHOR]

We point out the primary riddle of risk management, which is that the life of a risk manager is very similar to someone doing a slow walk on a tight rope. We provide a set of directives, the five pillars risk mitigation guidelines, aimed at brevity so that it is readily apparent what actions to perform, and implement. The guidelines are based on our experience on trading desks across many different asset classes, and they are particularly applicable for the burgeoning field of crypto risk management. It is generally a troubling scenario wherein someone tries to manage something they do not fully understand. Risk, as we know it, requires a lot more in-depth studies to be performed before we are in a position to more fully appreciate its etiology. Once that starts to happen, we will be in a better place to try to manage risk more thoroughly. Our present attempts are better referred to as risk mitigation. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Finance & Financial Law / Finanse i Prawo Finansowe is the property of Wydawnictwo Uniwersytetu Lodzkiego and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The authors develop an options trading strategy that takes advantage of the fact that options' implied volatilities tend to be higher than their realized volatilities. Therefore, they dynamically adjust the strike prices of the options included in the strategy to accurate Value-at-Risk forecasts. The authors implement a comprehensive set of Value-at-Risk forecasting models and show, in a real world backtest, the profitability of their strategy, even after accounting for various trading frictions. [ABSTRACT FROM AUTHOR]

In this study, we investigate the tail dependency between bank stocks in China and 35 common risk factors. We measure univariate and multivariate conditional tail risk probabilities. The evidence indicates that tail events from risk factors in the banking, security trading, real estate, and energy industries have the largest effects on the realization of extreme returns from Chinese bank stocks. The univariate conditional tail risk is considerably higher than the unconditional tail risk. The impact of multiple tail events from several risk factors occurring simultaneously is much stronger than tail events from one single risk factor. In general, there is a stronger cross‐market tail linkage between emerging market risk factors and bank stocks in China when compared with developed market risk factors. However, the cross‐market tail linkage between developed market risk factors and bank stocks in China rose sharply during the 2008 financial crisis. [ABSTRACT FROM AUTHOR]

Postcrisis bank regulations raised market-making costs for bank-affiliated dealers. We show that this can, somewhat surprisingly, improve overall investor welfare and reduce average transaction costs despite the increased cost of immediacy. Bank dealers in OTC markets optimize between two parallel trading mechanisms: market making and matchmaking. Bank regulations that increase market-making costs change the market structure by intensifying competitive pressure from nonbank dealers and incentivizing bank dealers to shift their business activities toward matchmaking. Thus, postcrisis bank regulations have the (unintended) benefit of replacing costly bank balance sheets with a more efficient form of financial intermediation. [ABSTRACT FROM AUTHOR]

We study the effect of dealer exit on prices and quantities in a model of an over-the-counter market featuring a core-periphery network with bilateral trading costs. The model is calibrated using regulatory data on the entire U.S. credit default swap (CDS) market between 2010 and 2013. Prices depend crucially on the risk-bearing capacity of core dealers, yet unlike standard models featuring a dealer sector, we allow for heterogeneity in dealer risk-bearing capacity. This heterogeneity is quantitatively important. Depending on how well dealers share risk, the exit of a single dealer can cause credit spreads to rise by 8 |$\%$| to 24 |$\%$|⁠. [ABSTRACT FROM AUTHOR]

This article investigates the short-side anomaly trading behavior of alternative mutual funds (AMFs) based on their short positions in U.S. domestic equities. In aggregate, AMFs demonstrate the ability to exploit well-documented stock market anomalies on the short side, and the overpriced stocks sold short by AMFs generate significant negative alpha. Further, AMFs' short-side trades exhibit significant return predictability, which can at least partially derive from their ability to process public information on firm and anomaly characteristics. Finally, AMFs' short-side anomaly-based trading activity and profitability appear to be more pronounced among the stocks with higher credit risk or dynamic short-selling risk. [ABSTRACT FROM AUTHOR]