Query: i have an introduction of my paper i want u to help me add some citations to it 'Introduction
Triangular arbitrage is a trading strategy that exploits price discrepancies among three currencies to generate profit. It works by sequentially converting an initial currency into a second, then a third, and finally back into the original currency, all at different exchange rates. If the exchange rates between these three currencies are out of sync, traders can profit from the temporary mispricing. This process hinges on the principle of market inefficiency, where exchange rates do not accurately reflect the true value relationships between currencies [1]. By strategically executing a sequence of currency exchanges, traders can capitalize on these inefficiencies and generate risk-free profits.

In financial markets, inefficiencies such as these often exist only for brief periods before being corrected by the market itself. As a result, speed and accuracy are critical factors when identifying and acting on arbitrage opportunities [2]. The importance of triangular arbitrage lies in its ability to exploit these fleeting moments of price discrepancy in currency markets, allowing traders to gain profits with minimal risk. For investors, the ability to identify these opportunities is crucial, as modern financial markets are highly competitive, and mispricing windows are typically narrow [3].

Traditional approaches to identifying triangular arbitrage opportunities have relied on complex mathematical models, such as non-linear optimization techniques and heuristics. However, these methods often suffer from limitations in both speed and precision. Given the dynamic nature of financial markets, these older techniques may not be sufficient for real-time arbitrage detection. As financial markets evolve, there is a growing need for innovative, faster, and more accurate methods that can adapt to rapidly changing market conditions and provide actionable insights in real time [4].

This study applies the Bellman-Ford algorithm to identify triangular arbitrage opportunities by modeling currency exchange rates as a graph. The algorithm's ability to detect negative-weight cycles aligns well with the speed requirements of high-frequency trading environments, such as cryptocurrency markets.
The graph-based approach proposed in this study has several key advantages over traditional models. First, it allows for the systematic exploration of multiple currencies and their relationships, capturing the intricate interdependencies that drive arbitrage opportunities. Second, by leveraging the computational efficiency of the Bellman-Ford algorithm, we can significantly reduce the time required to identify arbitrage opportunities, making the method suitable for real-time trading in fast-moving markets [5]. Furthermore, the algorithm’s ability to handle both positive and negative weight cycles ensures that it can detect profitable opportunities even in complex, highly interconnected currency markets [6].

The objectives of this study are twofold. First, we aim to demonstrate the effectiveness of our proposed method in identifying triangular arbitrage opportunities. Second, we seek to compare its performance against existing methods, focusing on key metrics such as accuracy, speed, and computational efficiency. To validate our approach, we will apply it to real-world currency exchange data, providing a robust evaluation of its performance relative to traditional techniques.
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Subject: finance
Intent: Literature Understanding