https://www.aidalab.co.uk/researcharticles daily 0.75 2025-12-30 https://www.aidalab.co.uk/researcharticles/ai-for-finance-conference monthly 0.5 2025-12-30 https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062659191-IIJXUY4F0BFXSKORGZC9/1764085354510.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062719255-3LB5LI8NSY22G805EZU6/54944394020_7a9c416702_k.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062642471-64BU31OS66G7ETIFC59D/1764085354103.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062709179-3244DQS0YQAPB7UMQAZL/1764085358469.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062687709-EAP2DE9QK0K7H1TFOI54/1764085354782.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062831328-6CLEU0FA55K5OZ55SFUO/1764085355034.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062670238-2POOI7HTI0J0C7XW710B/1764085354773.jpg Articles - AI for Finance Conference https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/1767062694965-TP7IK7ME40OQZ6GBMTFX/1764085354838.jpg Articles - AI for Finance Conference https://www.aidalab.co.uk/researcharticles/artificial-intelligence-for-finance-workshop-at-imperial-college-london monthly 0.5 2025-11-06 https://www.aidalab.co.uk/researcharticles/keeping-transit-networks-moving-how-ai-powered-predictive-maintenance-transforms-public-transport monthly 0.5 2025-11-04 https://www.aidalab.co.uk/researcharticles/cracking-the-code-on-short-ticketing-using-ai-to-tackle-a-hidden-fare-evasion-challenge monthly 0.5 2025-10-24 https://www.aidalab.co.uk/researcharticles/congratulations-to-our-final-year-project-students monthly 0.5 2025-10-14 https://www.aidalab.co.uk/researcharticles/prof-mandic-speaks-at-gpai-summit-on-ais-future monthly 0.5 2025-02-03 https://www.aidalab.co.uk/researcharticles/ja-lodge-award monthly 0.5 2025-01-26 https://www.aidalab.co.uk/researcharticles/finllama monthly 0.5 2024-08-13 https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/835dd2c0-615d-4b66-b015-1d79c56db5a5/Screenshot+2024-08-02+at+01.47.04.png Articles - FinLlama: LLM-Based Financial Sentiment Analysis for Algorithmic Trading Figure 2: Comparison of the performance of the 35% long-short portfolios which were constructed using the five considered sentiment analysis methods, for the time period of February 2015 to June 2021. The MA(30) and MSTD(30) represent, respectively, the moving average and the moving standard deviation of the returns calculated over a 30-day rolling window. https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/7c9ca83c-e8fb-4bb0-9c35-59641587bb88/Screenshot+2024-08-02+at+01.51.58.png Articles - FinLlama: LLM-Based Financial Sentiment Analysis for Algorithmic Trading - Make it stand out Table 1: Statistical comparison between the performances of the five considered sentiment analysis methods using a 35% long-short portfolio. For Cumulative Returns, Annualized Return and Sharpe Ratio, higher is better. For Annualized Volatility, lower is better. https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/d013e8e5-f4fd-4e87-805a-f40d3e9cfaf0/Screenshot+2024-08-02+at+01.37.39.png Articles - FinLlama: LLM-Based Financial Sentiment Analysis for Algorithmic Trading Figure 1: Framework for sentiment analysis https://www.aidalab.co.uk/researcharticles/portfolio-cuts-a-graph-theoretic-framework-to-diversification monthly 0.5 2024-08-13 https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/2890644b-3184-4001-aef3-82a074bf60bf/Screenshot+2024-08-11+at+20.29.35.png Articles - Portfolio Cuts: A Graph-theoretic Framework To Diversification - Make it stand out A cut for a graph with the disjoint subsets V1 = {1, 2, 3, 4} and V2 = {5, 6, 7, 8}. The edges between the sets V1 and V2 are designated by thin red lines. The cut is equal to the sum of the weights that connect the sets V1 and V2, that is, Cut(V1, V2) = 0.32 + 0.24 + 0.23 = 0.79. https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/c1bb0f5e-e2c1-4ee3-bbc3-cbe9d3cc1ddc/Screenshot+2024-08-11+at+20.32.48.png Articles - Portfolio Cuts: A Graph-theoretic Framework To Diversification - Make it stand out Graph asset allocation strategies. Graph structure resulting from K = 4 portfolio cuts. https://images.squarespace-cdn.com/content/v1/66aa152f0eeb2f6164eeb25d/41dec40f-3b4c-4f0a-9d08-cc80ea55362e/Screenshot+2024-08-11+at+20.34.21.png Articles - Portfolio Cuts: A Graph-theoretic Framework To Diversification - Make it stand out Out-sample performance of the asset allocation strategies. Notice that the Sharpe ratio typically improves with each subsequent portfolio cut. 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