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1

CARTEA, ÁLVARO, SEBASTIAN JAIMUNGAL, and JASON RICCI. "TRADING STRATEGIES WITHIN THE EDGES OF NO-ARBITRAGE." International Journal of Theoretical and Applied Finance 21, no. 03 (2018): 1850025. http://dx.doi.org/10.1142/s0219024918500255.

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We develop a trading strategy that employs limit and market orders in a multiasset economy where the assets are not only correlated, but can also be structurally dependent. To model the structural dependence, the mid-price processes follow a multivariate reflected Brownian motion on the closure of a no-arbitrage region which is dictated by the bid–ask spreads of the assets. We provide a mathematical framework for such an economy and solve for the value function and optimal control for an investor who takes positions in these assets. The optimal strategy exhibits two dominant features which dep
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Fanelli, Viviana. "Mean-Reverting Statistical Arbitrage Strategies in Crude Oil Markets." Risks 12, no. 7 (2024): 106. http://dx.doi.org/10.3390/risks12070106.

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In this paper, we introduce the concept of statistical arbitrage through the definition of a mean-reverting trading strategy that captures persistent anomalies in long-run relationships among assets. We model the statistical arbitrage proceeding in three steps: (1) to identify mispricings in the chosen market, (2) to test mean-reverting statistical arbitrage, and (3) to develop statistical arbitrage trading strategies. We empirically investigate the existence of statistical arbitrage opportunities in crude oil markets. In particular, we focus on long-term pricing relationships between the West
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Bayraktar, Erhan, and Hasanjan Sayit. "No arbitrage conditions for simple trading strategies." Annals of Finance 6, no. 1 (2009): 147–56. http://dx.doi.org/10.1007/s10436-009-0120-3.

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Gao, Xiangyang, and Yuchen Hou. "Trading Strategies for Cryptocurrencies Based on Machine Learning Scenarios." BCP Business & Management 38 (March 2, 2023): 3048–56. http://dx.doi.org/10.54691/bcpbm.v38i.4234.

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A Cryptocurrency is a peer-to-peer digital exchange system in which cryptography is used to generate and distribute currency units. Bitcoin as the foremost digital currency, using asymmetric cryptographic algorithms, blockchain technology, was conceptualized by Satoshi Nakamoto in 2008 and born in 2009. In 14 years, digital currency has gone from being initially controversial and worthless to rapid increase in value. The huge fluctuations in its price have attracted worldwide attention, and more people have begun to pay attention to the investment strategy of digital currency. Starting from th
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Leung, Tim, and Hung Nguyen. "Constructing cointegrated cryptocurrency portfolios for statistical arbitrage." Studies in Economics and Finance 36, no. 4 (2019): 581–99. http://dx.doi.org/10.1108/sef-08-2018-0264.

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Purpose This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios. Design/methodology/approach The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metr
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Krauss, Christopher. "STATISTICAL ARBITRAGE PAIRS TRADING STRATEGIES: REVIEW AND OUTLOOK." Journal of Economic Surveys 31, no. 2 (2016): 513–45. http://dx.doi.org/10.1111/joes.12153.

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O’Connor, Ciaran, Joseph Collins, Steven Prestwich, and Andrea Visentin. "Optimising quantile-based trading strategies in electricity arbitrage." Energy and AI 20 (May 2025): 100476. https://doi.org/10.1016/j.egyai.2025.100476.

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Hou, Xinyu. "Comparisons of Different Arbitrage Strategies in Context of Various Models." BCP Business & Management 38 (March 2, 2023): 1145–50. http://dx.doi.org/10.54691/bcpbm.v38i.3839.

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S Statistical arbitrage is one of the key topics of research today due to its significance statistical features and the ability to control the drawdown. Previous researchers have implemented statistical arbitrage based on various approaches. However, some of these approaches lack depth and coherence. This paper therefore provides an in-depth assessment of the two scenarios. Specifically, the two approaches are distance and time-series models. The former one uses non-parametric distance indicators to identify pair trading opportunities, while the latter seeks to find optimal trading rules by ex
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Guryanova, Lidiya, and Natalia Chernova. "Metals futures market: a comparative analysis of investment and arbitrage strategies." Development Management 17, no. 4 (2020): 42–54. http://dx.doi.org/10.21511/dm.17(4).2019.04.

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The article deals with the application of optimal portfolio theory and pair trading theory on the metals futures market. Advantages of the futures market over the spot market include relatively small initial price, low transaction costs, and high volatility. The main aim of the study is to explore the potential of both strategies for effective trading. The following financial instruments were chosen as the inputs of the models: futures on industrial metals (aluminum, copper, nickel, zinc, lead, tin), futures on precious metals (gold and silver). When building the optimal portfolio, it was deci
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Zhao, Wanrong. "The Impact of Different Trading Strategies on the Same Portfolio." Advances in Economics, Management and Political Sciences 16, no. 1 (2023): 318–25. http://dx.doi.org/10.54254/2754-1169/16/20231030.

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The frequent occurrence of political events, the spread of the epidemic and changes in policies of various countries have made the market more volatile. Due to the instability of the overall economic environment, investors are increasingly focusing on using strategies to improve returns, so this article selects several hedge fund trading strategies, analyzes the same trading portfolio, and compares the performance of different trading portfolios. Different effects of the same combination give spirits to investors when making transactions. The market neutral trading strategy is effective for th
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B., Aishwarya, P. Kavin K., Abhinav S., and Krithikdharan. "Binary Trading Bot with Arbitrage Algorithm." Binary Trading Bot with Arbitrage Algorithm 8, no. 11 (2023): 6. https://doi.org/10.5281/zenodo.10164418.

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The advent of algorithmic trading has revolutionized financial markets, introducing sophisticated strategies capable of capitalizing on market inefficiencies. Our project presents a novel trading bot that leverages an arbitrage algorithm to identify and exploit price discrepancies in different markets, thereby achieving risk-free profit opportunities. Our trading bot employs real-time market data collection from multiple exchanges, scrutinizing the prices of the same asset across different platforms. Upon detecting a significant price gap, the bot swiftly triggers trades to buy the asset at th
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Papantonis, Ioannis. "Cointegration-based trading: evidence on index tracking & market-neutral strategies." Managerial Finance 42, no. 5 (2016): 449–71. http://dx.doi.org/10.1108/mf-12-2014-0318.

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Purpose – The purpose of this paper is to present an alternative approach to equity trading that is based on cointegration. If there are long-run equilibria among financial assets, a cointegration-based trading strategy can exploit profitable opportunities by capturing mean-reverting short-run deviations. Design/methodology/approach – First, the author introduces an equity indexing technique to form cointegration tracking portfolios that are able to replicate an index effectively. The author later enhances this tracking methodology in order to construct more complex portfolio-trading strategie
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Soto, Paula Andrea, and Juan Carlos Ruilova Teran. "Arbitragem Estatística: Uma Abordagem por VECM." Brazilian Review of Finance 15, no. 4 (2018): 537. http://dx.doi.org/10.12660/rbfin.v15n4.2017.65761.

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This work develops a statistical arbitrage model which was tested on the Brazilian stock market. Prices were modeled using VECM (Vector Error Correction Models) to create a self-financing, market-neutral, long/short trading strategy. In this strategy, deviations in the long-term equilibrium of prices are identified in order to create buy and sell signals. Portfolios with common trends were selected by means of Principal Component Analysis. The viability of this strategy was empirically addressed using simulations on these portfolios. Its performance was also compared to other long/short tradin
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Wu, Ruibo, Tao Zhang, and Feng Xu. "Cross-Market Arbitrage Strategies Based on Deep Learning." Academic Journal of Sociology and Management 2, no. 4 (2024): 20–26. https://doi.org/10.5281/zenodo.12747401.

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Cross-market arbitrage involves exploiting price differences of the same or similar financial instruments across different markets. The advent of deep learning (DL) has introduced new avenues for developing sophisticated arbitrage strategies. This paper explores how DL can be leveraged to enhance cross-market arbitrage strategies, focusing on the potential benefits, challenges, and practical applications. Through a comprehensive review of current literature and empirical case studies, we aim to provide insights into the integration of DL in arbitrage strategies, highlighting its impact on mark
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15

Chen, Yue, Xiaojian Niu, and Yan Zhang. "Exploring Contrarian Degree in the Trading Behavior of China's Stock Market." Complexity 2019 (April 10, 2019): 1–12. http://dx.doi.org/10.1155/2019/1678086.

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We study the contrarian and trend-following trading behavior of market timers in China's stock market. Using a network model to describe interpersonal relationships, we deploy the Ising model to capture trading strategies for both contrarians and followers. With empirical data of China's stock market, we find that contrarians account for 12-14% of trading volume. We further compare the performance of contrarians and followers and demonstrate the inefficiency of China's stock market where timing arbitrage exists. We highlight the fact that while the actual return sequence is driven by followers
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16

Han, Guodong, and Hecheng Li. "An LSTM-based optimization algorithm for enhancing quantitative arbitrage trading." PeerJ Computer Science 10 (July 8, 2024): e2164. http://dx.doi.org/10.7717/peerj-cs.2164.

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Arbitrage trading is a common quantitative trading strategy that leverages the long-term cointegration relationships between multiple related assets to conduct spread trading for profit. Specifically, when the cointegration relationship between two or more related series holds, it utilizes the stability and mean-reverting characteristics of their cointegration relationship for spread trading. However, in real quantitative trading, determining the cointegration relationship based on the Engle-Granger two-step method imposes stringent conditions for the cointegration to hold, which can easily be
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Stander, Yolanda, Daniël Marais, and Ilse Botha. "Trading strategies with copulas." Journal of Economic and Financial Sciences 6, no. 1 (2013): 83–108. http://dx.doi.org/10.4102/jef.v6i1.278.

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A new approach is proposed to identify trading opportunities in the equity market by using the information contained in the bivariate dependence structure of two equities. The relationships between the equity pairs are modelled with bivariate copulas and the fitted copula structures are utilised to identify the trading opportunities. Two trading strategies are considered that take advantage of the relative mispricing between a pair of correlated stocks and involve taking a position on the stocks when they diverge from their historical relationship. The position is then reversed when the two st
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18

STOYANOV, STOYAN V., SVETLOZAR T. RACHEV, STEFAN MITTNIK, and FRANK J. FABOZZI. "PRICING DERIVATIVES IN HERMITE MARKETS." International Journal of Theoretical and Applied Finance 22, no. 06 (2019): 1950031. http://dx.doi.org/10.1142/s0219024919500316.

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We present a new framework for Hermite fractional financial markets, generalizing the fractional Brownian motion (FBM) and fractional Rosenblatt markets. Considering pure and mixed Hermite markets, we introduce a strategy-specific arbitrage tax on the rate of transaction volume acceleration of the hedging portfolio as the prices of risky assets change, allowing us to transform Hermite markets with arbitrage opportunities to markets with no arbitrage opportunities within the class of Markov trading strategies. We derive PDEs for the price of such strategies in the presence of an arbitrage tax i
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19

Mitchell, John. "Soybean Futures Crush Spread Arbitrage: Trading Strategies and Market Efficiency." Journal of Risk and Financial Management 3, no. 1 (2010): 63–96. http://dx.doi.org/10.3390/jrfm3010063.

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20

Montoya-Cruz, Estefanía, José Pedro Ramos-Requena, Juan Evangelista Trinidad-Segovia, and Miguel Ángel Sánchez-Granero. "Exploring Arbitrage Strategies in Corporate Social Responsibility Companies." Sustainability 12, no. 16 (2020): 6293. http://dx.doi.org/10.3390/su12166293.

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Today, Socially Responsible financial investment has taken on particular importance. Investors normally select their most profitable investments, but over the years they have appreciated that companies develop Socially Responsible policies. Financial indices have also created Socially Responsible versions. In this paper, we run a statistical arbitrage technique known as Pairs Trading using stocks of the FTSE4GOOD Socially Responsible Index. Different strategies will be tested to demonstrate that there are no significant differences between the performance of the portfolio composed by Corporate
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Yang, Chen, and Shaotian Liu. "Research on Cross-Variety Arbitrage Strategy of Metal Futures in China." International Business & Economics Studies 5, no. 1 (2023): p81. http://dx.doi.org/10.22158/ibes.v5n1p81.

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With the vigorous development of China’s futures market, the number of varieties is gradually increasing, the number of investors is increasing, and the liquidity of futures is getting better and better. The “T+0” trading mechanism of the futures market makes arbitrage traders prefer to carry out arbitrage in the futures market. Cross-variety arbitrage is one of the main ways of arbitrage in China’s futures market, and its key is to find the appropriate variety combination and arbitrage strategy. The purpose of this paper is to conduct scientific and detailed research and analysis on futures c
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CORDERO, FERNANDO, and LAVINIA PEREZ-OSTAFE. "CRITICAL TRANSACTION COSTS AND 1-STEP ASYMPTOTIC ARBITRAGE IN FRACTIONAL BINARY MARKETS." International Journal of Theoretical and Applied Finance 18, no. 05 (2015): 1550029. http://dx.doi.org/10.1142/s0219024915500296.

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We study the arbitrage opportunities in the presence of transaction costs in a sequence of binary markets approximating the fractional Black–Scholes model. This approximating sequence was constructed by Sottinen and named fractional binary markets. Since, in the frictionless case, these markets admit arbitrage, we aim to determine the size of the transaction costs needed to eliminate the arbitrage from these models. To gain more insight, we first consider only 1-step trading strategies and we prove that arbitrage opportunities appear when the transaction costs are of order [Formula: see text].
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Korkishko, Grigory. "Estimation of Aggregate Expectations of Economic Agents by Using Derivatives." Administrative Consulting 97, no. 1 (2017): 218–25. https://doi.org/10.5281/zenodo.14959092.

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Macroeconomic theories based on expectations of economic agents appeared at the end of the last century. There are various ways of defining these expectations, and in this paper we propose to estimate the economic expectations on the basis of official data about transactions in derivative financial instruments.Using data of trades on the Moscow stock exchange were analyzed arbitrage strategy spot-futures and futures-futures for the purpose of estimating inflation expectations of investors. To assess suggestions about the stability of the economy were considered options
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Mukerji, Purba, Christine Chung, Timothy Walsh, and Bo Xiong. "The Impact of Algorithmic Trading in a Simulated Asset Market." Journal of Risk and Financial Management 12, no. 2 (2019): 68. http://dx.doi.org/10.3390/jrfm12020068.

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In this work we simulate algorithmic trading (AT) in asset markets to clarify its impact. Our markets consist of human and algorithmic counterparts of traders that trade based on technical and fundamental analysis, and statistical arbitrage strategies. Our specific contributions are: (1) directly analyze AT behavior to connect AT trading strategies to specific outcomes in the market; (2) measure the impact of AT on market quality; and (3) test the sensitivity of our findings to variations in market conditions and possible future events of interest. Examples of such variations and future events
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ALLAJ, ERINDI. "IMPLICIT TRANSACTION COSTS AND THE FUNDAMENTAL THEOREMS OF ASSET PRICING." International Journal of Theoretical and Applied Finance 20, no. 04 (2017): 1750024. http://dx.doi.org/10.1142/s0219024917500248.

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This paper studies arbitrage pricing theory in financial markets with implicit transaction costs. We extend the existing theory to include the more realistic possibility that the price at which the investors trade is dependent on the traded volume. The investors in the market always buy at the ask and sell at the bid price. Implicit transaction costs are composed of two terms, one is able to capture the bid-ask spread, and the second the price impact. Moreover, a new definition of a self-financing portfolio is obtained. The self-financing condition suggests that continuous trading is possible,
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Mavrakis, Emmanouil, and Christos Alexakis. "Statistical Arbitrage Strategies under Different Market Conditions: The Case of the Greek Banking Sector." Journal of Emerging Market Finance 17, no. 2 (2018): 159–85. http://dx.doi.org/10.1177/0972652718776858.

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In this article, we examine the behaviour of cointegration-based pairs trading (PT) strategies, under different market conditions. Reported results indicate that changes in market conditions affect the stability of long-run relations between pairs of stocks, therefore suggesting that arbitrageurs should perform rebalancing between the examined stocks when a change in market trend is evident. The applicability of our results may be of importance to market participants; although cointegration applications have received considerable attention from hedge funds adopting statistical arbitrage (SA) s
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Stadnik, Bohumil. "INTEREST RATES SENSITIVITY ARBITRAGE – THEORY AND PRACTICAL ASSESMENT FOR FINANCIAL MARKET TRADING." Journal Business, Management and Economics Engineering 19, no. 01 (2021): 12–23. http://dx.doi.org/10.3846/bmee.2021.12658.

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Purpose – Nowadays popular algorithmic trading uses many strategies which are algoritmizable and promise profitability. This research assess if it is possible successfully use interest rates sensitivity arbitrage in bond portfolio (also known as convexity arbitrage) in financial praxis. This arbitrage is sparsely described in literature and an assessment about its practical success is missing. Research methodology – Methodology steps: mathematical definition of given arbitrage; construction of sufficient portfolio; backtesting on USD zero-coupon curves. Portfolio of two bonds is constructed (t
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Danso, Charles Armah, and James Refalo. "An Examination of G10 Carry Trade and Covered Interest Arbitrage Before, During, and After Financial Crises." Journal of Risk and Financial Management 18, no. 4 (2025): 190. https://doi.org/10.3390/jrfm18040190.

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This paper examines and compares the trading strategies of carry and covered interest arbitrage. This study constructs portfolios for G10 countries based on interest rates’ spot and forward exchange rates. We extend the prior literature by focusing on the profitability of the strategies during and around the two crisis periods, comparing both carry trade (CT), i.e., unhedged, and covered interest arbitrage (CIAT), i.e., hedged. We find that both CT and CIAT have variable profits during the period examined, with both strategies’ profits generally concentrated in the pre-crisis period and most l
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CHEN, JIANGUO, and LLOYD P. BLENMAN. "EQUILIBRIUM CONDITIONS OF FORWARD EXCHANGE MARKET EXPRESSED IN A SIMPLE GEOMETRIC STRUCTURE." International Journal of Theoretical and Applied Finance 08, no. 07 (2005): 915–32. http://dx.doi.org/10.1142/s021902490500330x.

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The paper focuses on the market equilibrium conditions in forward exchange quotes. By careful analysis of the market arbitrage conditions, market supply and demand, we construct the equilibrium ranges for bid and ask forward quotes separately. We present our analysis in a bid-ask cost structure setting, and directly tie the equilibrium and arbitrage conditions to specific trading strategies. We conclude that in equilibrium there will be no chance for one-way-arbitrage in foreign exchange and securities markets, provided that non-reversed traders are active and set the arbitrage boundaries. The
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Dong, Jun. "Research on High-Frequency Stock Pair Trading Strategy Based on MS-GARCH Model." Financial Economics Insights 1, no. 1 (2024): 99–110. https://doi.org/10.70088/9v1tf276.

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With the rapid development of high-frequency trading, pair trading, a classic statistical arbitrage strategy, has gradually become a widely applied trading method in the market. This paper focuses on the construction and application of high-frequency stock pair trading strategies based on the MS-GARCH (Markov Switching Generalized Autoregressive Conditional Heteroskedasticity) model. First, we select suitable stock pairs for pair trading by performing cointegration tests on high-frequency stock data. Then, the MS-GARCH model is used to model the price volatility of these stock pairs, and a hig
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Bayram, Mehmet, and Muzaffer Akat. "Market-neutral trading with fuzzy inference, a new method for the pairs trading strategy." Engineering Economics 30, no. 4 (2019): 411–21. http://dx.doi.org/10.5755/j01.ee.30.4.14350.

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Financial pricing and prediction of stock markets is a specific and relatively narrow field, which have been mainly explored by mathematicians, economists and financial engineers. Prediction with the purpose of making profits in a martingale domain is a hard task. Pairs trading, a market neutral arbitrage strategy, attempts to resolve the drawback of unpredictability and yield market independent returns using relative pricing idea. If two securities have similar characteristics, so should their prices. Deviation from the acceptable similarity range in prices is considered an anomaly, and whene
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Baron, Matthew, Jonathan Brogaard, Björn Hagströmer, and Andrei Kirilenko. "Risk and Return in High-Frequency Trading." Journal of Financial and Quantitative Analysis 54, no. 3 (2018): 993–1024. http://dx.doi.org/10.1017/s0022109018001096.

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We study performance and competition among firms engaging in high-frequency trading (HFT). We construct measures of latency and find that differences in relative latency account for large differences in HFT firms’ trading performance. HFT firms that improve their latency rank due to colocation upgrades see improved trading performance. The stronger performance associated with speed comes through both the short-lived information channel and the risk management channel, and speed is useful for various strategies, including market making and cross-market arbitrage. We find empirical support for m
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SAYYED, ZAID. "Real Time-Cutting Algorithmic Trading." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35766.

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a. Brief overview of algorithmic trading. Algorithmic trading, also known as algo trading or automated trading, refers to the use of computer algorithms and mathematical models to execute trading orders in financial markets. The primary goal of algorithmic trading is to achieve efficient and optimized execution of trading strategies, leveraging the speed and precision of computer systems. Here is a brief overview of algorithmic trading: 1. **Automation:** Algorithmic trading involves automating the process of buying or selling financial instruments, such as stocks, bonds, currencies, or commod
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Caldeira, João Frois, and Gulherme Valle Moura. "Seleção de uma Carteira de Pares de Ações Usando Cointegração: Uma Estratégia de Arbitragem Estatística." Brazilian Review of Finance 11, no. 1 (2013): 49. http://dx.doi.org/10.12660/rbfin.v11n1.2013.4785.

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Statistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean- reverting spreads with a certain degree of predictability. This paper applies cointegration tests to identify stocks to be used in pairs trading strategies. In addition to estimating long-term equilibrium and to model the resulting residuals, we select stock pairs to compose a pairs trading portfolio based on an indicator of profitability evaluated in-sample. The profitability of the strategy is assessed with data from the São Paulo stock exchange ranging from January 2005 to Octo
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ALVAREZ, ALEXANDER, and SEBASTIAN E. FERRANDO. "TRAJECTORY-BASED MODELS, ARBITRAGE AND CONTINUITY." International Journal of Theoretical and Applied Finance 19, no. 03 (2016): 1650015. http://dx.doi.org/10.1142/s0219024916500151.

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In a nonprobabilistic setting, we prove general trajectory-based models to have no free lunch with vanishing risk. The main ingredient is a local continuity requirement on the final portfolio value considered as a functional on the trajectory space. This is shown to be a natural assumption by establishing that a large class of practical trading strategies, defined by means of trajectory-based stopping times, give rise to locally continuous functionals. The theory is applied to two specific trajectory models of practical interest. The established results are then used to derive no free lunch re
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Charoenwong, Charlie, David K. Ding, and Nuttawat Visaltanachoti. "Warrants and their underlying stocks: Microstructure evidence from an emerging market." Risk Governance and Control: Financial Markets and Institutions 8, no. 3 (2018): 43–60. http://dx.doi.org/10.22495/rgcv8i3p3.

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The Stock Exchange of Thailand provides an ideal platform for comparing the trading characteristics of warrants and their underlying stocks since both of them trade in the same market under identical trading rules. If their patterns diverge significantly, it may be possible for an astute trader to devise profitable arbitrage strategies during the life of the warrants. We find that both their patterns are downward-sloping for spreads, U-shaped for flow toxicity, volatility, depth concentration, and trading volume; and upward-sloping for depth and market order flow ratio. This implies that tradi
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Yan, Honglei, Suigen Yang, and shengmin zhao. "Research on convertible bond pricing efficiency based on nonparametric fixed effect panel data model." China Finance Review International 6, no. 1 (2016): 32–55. http://dx.doi.org/10.1108/cfri-04-2015-0030.

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Purpose – The purpose of this paper is to study the pricing efficiency of convertible bonds and arbitrage opportunities between the convertible bonds and the underlying stocks thus improve market efficiency. Design/methodology/approach – Using nonparametric fixed effect panel data model, the authors build pricing model of convertible bonds and obtain fitted value for them. Then the authors constructs simultaneous confidence band for the smooth function to identify mispricing and study the pricing efficiency and arbitrage opportunities of convertible bonds. Findings – Result shows, convertible
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Kim, Taewook, and Ha Young Kim. "Optimizing the Pairs-Trading Strategy Using Deep Reinforcement Learning with Trading and Stop-Loss Boundaries." Complexity 2019 (November 12, 2019): 1–20. http://dx.doi.org/10.1155/2019/3582516.

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Many researchers have tried to optimize pairs trading as the numbers of opportunities for arbitrage profit have gradually decreased. Pairs trading is a market-neutral strategy; it profits if the given condition is satisfied within a given trading window, and if not, there is a risk of loss. In this study, we propose an optimized pairs-trading strategy using deep reinforcement learning—particularly with the deep Q-network—utilizing various trading and stop-loss boundaries. More specifically, if spreads hit trading thresholds and reverse to the mean, the agent receives a positive reward. However
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Wang, Yongfeng, and Guofeng Yan. "Survey on the application of deep learning in algorithmic trading." Data Science in Finance and Economics 1, no. 4 (2021): 345–61. http://dx.doi.org/10.3934/dsfe.2021019.

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<abstract> <p>Algorithmic trading is one of the most concerned directions in financial applications. Compared with traditional trading strategies, algorithmic trading applications perform forecasting and arbitrage with higher efficiency and more stable performance. Numerous studies on algorithmic trading models using deep learning have been conducted to perform trading forecasting and analysis. In this article, we firstly summarize several deep learning methods that have shown good performance in algorithmic trading applications, and briefly introduce some applications of deep lear
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Bayraktar, Erhan, and Zhou Zhou. "Arbitrage, hedging and utility maximization using semi-static trading strategies with American options." Annals of Applied Probability 26, no. 6 (2016): 3531–58. http://dx.doi.org/10.1214/16-aap1184.

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Rothschild, David, and Rajiv Sethi. "Trading Strategies and Market Microstructure: Evidence from a Prediction Market." Journal of Prediction Markets 10, no. 1 (2016): 1–29. http://dx.doi.org/10.5750/jpm.v10i1.1179.

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We examine transaction-level data from Intrade's 2012 presidential winner market for the entire two-year period for which trading occurred. The data allow us to compute key statistics, including volume, transactions, aggression, directional exposure, holding duration, margin, and profit for each of 6,300 unique trader accounts. We identify a diverse set of trading strategies that constitute a rich market ecology. These range from arbitrage-based strategies with low and fleeting directional exposure to strategies involving large accumulated positions in one of the two major party candidates. Mo
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CHEN, SON-NAN, AN-PIN CHEN, and CAMUS CHANG. "HEDGING AND ARBITRAGE WARRANTS UNDER SMILE EFFECTS: ANALYSIS AND EVIDENCE." International Journal of Theoretical and Applied Finance 04, no. 05 (2001): 733–58. http://dx.doi.org/10.1142/s0219024901001255.

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While the Black–Scholes (BS) model and binomial trees assume that the stock price evolves lognormally with constant volatility, volatility smiles are pronounced in almost all the worlds equity markets. To study the effects of volatility smiles on hedging and arbitrage, the method based on the BS model and implemented with observed market volatility smiles is proposed. The empirical results indicate that the proposed model can reduce risk exposure and increase profits on hedging as compared with the BS model, and hence leading to considerable returns on arbitrage-trading in the Taiwan warrant m
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Peng, Zhen, and Changsheng Hu. "Leveraged Trading, Irrational Sentiment and Sustainability in the Stock Market: Evidence from China." Sustainability 12, no. 4 (2020): 1310. http://dx.doi.org/10.3390/su12041310.

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Leveraged trading exhibits the characteristics of “strong margin trading and weak short selling” in the Chinese stock market. On the basis of monthly data on leveraged trading in the Chinese stock market from January 2014 to December 2016, we aim to empirically examine the relationship between leveraged trading and investor sentiment, and analyze the characteristics of investor sentiment contained in the leverage ratio. The results show that (1) as the leverage ratio increases, the pattern of investor trading changes from the positive feedback trading of “chasing up and down” to the negative f
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Wilhelmina Afua Addy, Adeola Olusola Ajayi-Nifise, Binaebi Gloria Bello, Sunday Tubokirifuruar Tula, Olubusola Odeyemi, and Titilola Falaiye. "Algorithmic Trading and AI: A Review of Strategies and Market Impact." World Journal of Advanced Engineering Technology and Sciences 11, no. 1 (2024): 258–67. http://dx.doi.org/10.30574/wjaets.2024.11.1.0054.

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This review explores the dynamic intersection of algorithmic trading and artificial intelligence (AI) within financial markets. It delves into the evolution, strategies, and broader market impact of algorithmic trading fueled by AI technologies. Examining the symbiotic relationship between advanced algorithms and AI, the review navigates through the various strategies employed, shedding light on their implications for market efficiency, liquidity, and overall stability. From high-frequency trading to machine learning-driven predictive analytics, this review unveils the multifaceted landscape o
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Thazhungal Govindan Nair, Saji. "Pairs trading in cryptocurrency market: A long-short story." Investment Management and Financial Innovations 18, no. 3 (2021): 127–41. http://dx.doi.org/10.21511/imfi.18(3).2021.12.

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Pairs trading that is built on ’Relative-Value Arbitrage Rule’ is a popular short-term speculation strategy enabling traders to make profits from temporary mispricing of close substitutes. This paper aims at investigating the profit potentials of pairs trading in a new finance area – on cryptocurrencies market. The empirical design builds upon four well-known approaches to implement pairs trading, namely: correlation analysis, distance approach, stochastic return differential approach, and cointegration analysis, that use monthly closing prices of leading cryptocoins over the period January 1,
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Broumandi, Shadie, and Tobias Reuber. "Statistical arbitrage and FX exposure with South American ADRs listed on the NYSE." Financial Assets and Investing 3, no. 2 (2012): 5–18. http://dx.doi.org/10.5817/fai2012-2-1.

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An American Depositary Receipt (ADR) represents ownership in the shares of a foreign company trading in US financial markets. We test a pair trading rule based on the mean reversion assumption for six South American stocks and their ADR counterparts on the NYSE. In our opinion, such a strategy should separate the spread risk from the currency risk. This paper aims to challenge the positive results found in similar settings. The main achievement is to show that isolating FX exposure turns such strategies that were presented as profitable to unprofitable and abnormal returns are just due to an a
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Vlastakis, Nikolaos, George Dotsis, and Raphael N. Markellos. "How efficient is the European football betting market? Evidence from arbitrage and trading strategies." Journal of Forecasting 28, no. 5 (2009): 426–44. http://dx.doi.org/10.1002/for.1085.

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Morelli, Michael. "Implementing High Frequency Trading Regulation: A Critical Analysis of Current Reforms." Michigan Business & Entrepreneurial Law Review, no. 6.2 (2017): 201. http://dx.doi.org/10.36639/mbelr.6.2.implementing.

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Technological developments in securities markets, most notably high frequency trading, have fundamentally changed the structure and nature of trading over the past fifty years. Policymakers, both domestically and abroad, now face many new challenges influencing the secondary market’s effectiveness as a generator of economic growth and stability. Faced with these rapid structural changes, many are quick to denounce high frequency trading as opportunistic and parasitic. This article, however, instead argues that while high frequency trading presents certain general risks to secondary market effi
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Morelli, Michael. "Regulating Secondary Markets in the High Frequency Age: A Principled and Coordinated Approach." Michigan Business & Entrepreneurial Law Review, no. 6.1 (2016): 79. http://dx.doi.org/10.36639/mbelr.6.1.regulating.

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Technological developments in securities markets, most notably high frequency trading, have fundamentally changed the structure and nature of trading over the past 50 years. Policymakers both domestically and abroad now face many new challenges impacting the secondary market’s effectiveness as a generator of economic growth and stability. Faced with these rapid structural changes, many are quick to denounce high frequency trading as opportunistic and parasitic. This article, however, instead argues that while high frequency trading presents certain general risks to secondary market efficiency,
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Ma, Ranbo. "Hedge Fund Strategies Performance in Bad Market Condition Analysis." Highlights in Business, Economics and Management 2 (November 6, 2022): 188–95. http://dx.doi.org/10.54097/hbem.v2i.2360.

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In this article, the performance of hedge fund strategies is measured and analyzed by the following aspects: potential risk of the strategies excepted return of selected hedge fund and the sample performance in pressured stock market conditions. The study will provide theoretical explanations of the efficacy of Merger Arbitrage, Mutual Fund strategies, and PE ratio-related hedge fund strategies and their profitability as well as risk tolerance. Throughout equity data collection, asset markets including the S&P and NASDAQ have experienced downward pressure on systemic risk caused by inflati
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