Hello everyone. Good morning, good afternoon, good evening. From part of the world. You are listening to this presentation. It's a privilege to speak to you today on a subject that sits at the intersection of cutting edge physics, advanced computing, and the fast world of. As we know, today's financial markets are already driven by ultra low latency trading strategies, massive data analytics, sophisticated algorithms, but as computing approaches the physical and performance limits, we are standing on the edge of a new technological frontier with quantum computing. Quantum computing isn't just another leaking speed or storage, it's completely re-imagining of how computation works. By leveraging principles like super position entanglement, quantum computers are capable of solving certain complex problems exponentially faster than classical machines. And this capability opens up. Imagine a real time portfolio optimization across thousands of correlated assets. Imagine risk simulation that wants to co reduced to milliseconds. Imagine a trading system that doesn't just react faster, but can process and astronomically large decision space, evaluating market signals, counterparty behavior, and regulatory impact nevertheless simultaneously and in real time. While the potential is vast, the challenge are equally significant from hardware limitations to algorithm development and critically integration into today's market infrastructure. In this presentation, we'll explore how quantum computing is being harnessed in trading where the real computational advantages lie. Quantum accelerated financial future might actually look like. As you all know, these days, this isn't fiction anymore. This paradigm how markets move, I'm senior techn with investment. Specializing in delivering high performance, cost effective technology solutions. My expertise spans across fixed income trading, risk management, regulatory compliance, client reporting, and I have extensively worked with the industry leading products, trading products such as ion. Broker, broker dealer, Bloomberg and Wall Street fx, which is also product of Ion brought carrier. I built a reputation for managing, designing, and optimizing advanced technology infrastructures that support business operations in the capital markets and financial services. I have a deep understanding of the fixed income trading platforms and the businesses, commodity trading platforms capability, particularly in managing and streamlining fixed income trading processes. I have involved in design development optimization trading strategy that leveraged advanced quantitative models market might work, include implementing. Trading algorithms, market making strategies, risk adjusted grad strategies that have significantly improved execution and efficiency. With that understanding of execution venues, liquidity management, I have worked to find tune algorithmic strategies that optimize slippage, reduce trading cost, and minimize market impact. I have a diverse range of financial experience in financial products such as US Treasury, swaps, credit equities, and OT OTC database. That's a short summary about me. Now let's deep dive into the quantum accelerated trading systems, which is revolutionizing financial markets through computational. Unprecedented volume of data leading exchanges generating three 42 billion market data messages daily. That's an incredible and amount of data that we process. Additional computing, architecture, fundamental limitations, and processing this efficiently. Research how quantum computing A are transforming H infrastructure, offering significant computational stake environment. On the next slide, quantum FinTech over recognition of quantum computing transformative potential in trading systems. The significant improvements in both processing speed and resource efficiency demonstrate why leading firms are rapidly adopting these technologies. 94% on the leadership recognition, financial technology leaders identify quantum advantage critical for the next generation systems. Calculation speed reduction in complex calculation time compare to the classical approaches. 78% of calculation speed that has been reduced. So things which used to take let's say one hour, about 80% have been reduced in doing the calculation for the high frequency. 67% of the resource efficiencies decrease in the computational resource requirements while implementing quantum inspired algorithms crossing capabilities. The in parameter crossing capabilities translates directly to competitive in algorithmic trading models. Sophistication drives profitability. Quantum enhanced systems. Systems leveraging quantum technique demonstrated that they can process optimization problems with 300 half times more parameters while maintaining sub millisecond response times. This expanded parameter space enables more sophisticated rating models that can incorporate a wider range of market factors and signals. Simultaneously, traditional computing approaches manages only 1.4. Parameter capacity under the same latency conditions. Significantly limiting complexity. These systems struggle to incorporate the full range of relevant market variables leading to less optimized rating based on incomplete information. The response times, as you see in the chart, quantum enhanced the in high frequency trading. That nanoseconds can become a profit or loss. This advantage represents a revolutionary leap forward in execution capabilities. The integration of quantum algorithms with acceleration has enabled superior pattern recognition capabilities and trading systems that this technological combination allows for. Industry average of about 1 45 microsecond machine learning performance improvements. These enhanced models can identify complex market patterns, invisible to classical algorithms enabling more precise entry and accurate in volatile market conditions. Quantum machine learning techniques have demonstrated remarkable improvements. Accuracy while maintaining the stringent latency requirements. Essential for high frequency trading application. The 41% reduction in forecasting as you see in the. Requirements, SUBSECOND processing prediction accuracy, 41% reduction in error rates. This is one interesting case study implementation of a three year one trading firms. This case study followed three trading forms through their complete implementation journey, each organization followed a similar process assessment for our process of assessment, development, integration, and evaluation with performance improvements of. Initial assessment, basically identification of comput, computational bottlenecks and existing trading infrastructure, algorithm development, creation of quantum inspired optimization algorithms, tailored for portfolio management, infrastructure integration, deployment of hybrid quantum classical computing architecture. And finally, the performance evaluation measurement of about like 80% of reduction in calculation time across the complex trading operations. Classical hybrid framework. This architecture has been validated across multiple asset classes, consistently delivering 99.9% execution reliability, while enabling implementation of advanced trading strategies. Quantum classical hybrid framework leverages the strength of each computational paradigm. Classical systems handle high volume data. Quantum processors tackle complex optimization problems and the hardware. The F hardware provides a deterministic execution with minimal la, the data ion high throughput market data processing via classical systems, ultra low latency. Complex calculations offloaded to quantum processors and the hardware level implementation of optimized algorithm, competitive implementation, timeline advantage, classical computing approach. The implementation of timeline advantage represents perhaps most significant competitive edge for early. To market advantage translates directly to capturing trading opportunities before competitors. This first more advantage is particularly valuable in emerging market situation and during the periods of heightened volatility where the. Heavy duty of sell and volatility in the dealer to dealer platform or dealer to client platform market happens then. Market is huge classical computing approach. The traditional implementation pathways require extensive development cycles for new trading strategies. The complex risk models and optimization proteins can take months to develop, test, and deploy using conventional computing resources. But the quantum enhanced approach firms utilizing the Quantum Enhanced Computing frameworks can implement advanced strategies, which is three enough times faster than the. Acceler from both computational speed and superior parameter optimization. This self-explanatory if you look at it at the equities fixed income, the multi-asset performance analysis, latency improvement, equities, person percent. This is one area where the error reduction can we have a lot of opportunity to reduce to 50% latency improvement is 80%, 75%, and the parameter capacity is 3% for foreign exchange. Amazing. Return of investment for relatedly implement using quantum systems. Three. Commodity trading, 79% ency improvement, 3% sorry, three times parameter capacity and error reduction of 39% derivatives over 88%. Latency improvement, 90% of latency improvement can be achieved. 3.5% five times parameter capacity, and 47% error reduction. Equities and effect markets also showed remarkable improvements, particularly in latency reduction and error rate minimization. Our research validated the quantum classical hybrids framework across all major asset classes while performance improvements based. Most significant gains were observed in derivative ratings where the complex mathematical models benefit most from quantum optimization. Now the interesting topic challenges now that we have spoken extensively on the advantages of quantum max related ratings, what are. Second system reliability, third incorporation complexity, and fourth regulatory considerations. Let's go through one by one. The limited pool of professionals, even both quantum computing and financial markets. Remember even get somebody with a heavy duty map, knowledge heavy. Comprehend the financial markets presents a significant barrier to the implementation. Forward we identify for quantum computing has to have extensive knowledge in both finance and the technology leading firms are addressing this through specialized training programs and partnership with academic institutions. System reliability, early quantum processes have higher error rates than classical systems. Hybrid architectures mitigate this by implementing error correction protocols and verification methods that ensure 99% execution, reliability, integration complex systems with the quantum computing systems connecting quantum processing. And APIs that heal trading systems. From the complexities of quantum operation, why maintaining the performance? Finally, the regulatory and compliance considerations. Financial regulators are still developing frameworks for quantum enhanced trading systems. Forward thinking firms are proactively engaging with regulatory bodies to establish operational standards. So extensive analysis and research are being carried out on the trade surveillance and the spoofing related activities, which is very closely tried with the trading systems, future outlook and strategic recommendations. The quantum revolution in. They begin with targeted applications. So developing a hybrid architecture and preparing for a quantum advantages advantage scaling begins with a targeted application. Start by for any future outlook, right? Start by applying quantum enhanced algorithms, specific computational bottleneck. Portfolio optimization in US treasury rate rating rather than completely expanding the scope across all the rates, commodities red, but rather narrow down to one particular segment under the fixed income portfolio under US treasuries, let's say focus only on the keynotes or some level of US treasuries and pricing applications that. Built internal capabilities in quantum classical hybrid system design. The most successful implementation. We leverage both paradigms using quantum processes for optimization problems while maintaining classical systems for deterministic operation. Preparing for quantum advantage is scaling as quantum hardware matures over the next three to five years, prepare varying systems to. Now we'll be positioned to rapidly fund capabilities as the technology evolves. Quantum revolution in, like I said, the financial world is no longer a theory. It's happening. And several firms, the firms which I am working are trying to. Organizations that embrace quantum enhanced trading systems that today will establish competitive advantages that will be difficult to fall to overcome at the end of time Implementation. Speed advantage compounds over time, creating an expanding capability gap between leaders and followers. And that comes to the. This presentation science.