By Irene Aldridge Once you add Neural Networks to your existing analytical toolset, you can benefit from detecting patterns in data that cannot be captured otherwise. This article shows, with IBM as an example, how using Neural Networks unlocks statistical insight, you could not have achieved without it. Technical analysis is a discipline that has managed to survive it all over more than 100 years. Starting from the 1920s, and possibly even earlier, technical analysts persevered at distilling meaning from patterns in the data. Numerous generations of quants declared technical analysis to be dead, only to resurrect it in various Auto-Regressive Moving Average (ARMA) specifications.
Irene Aldridge, a co-author of the forthcoming book “Big Data Science in Finance” has launched her very own YouTube channel where she discusses her latest research in the areas of Big Data, Artificial Intelligence and Finance. Please subscribe here to receive updates: https://studio.youtube.com/channel/UCMYuhgyMhzkw5tBIyEa2p3g Aldridge has a seasoned portfolio of TV appearances, including CNBC, CNN, and even Comedy Central. Aldridge is looking to make her research more accessible through video clips and offerings. Please share with your colleagues and friends!
By Irene Aldridge S&P Global just announced acquisition of IHS Markit for a whopping US $44 billion, the largest acquisition in the financial data industry to date. The amount reflects the current reality on Wall Street: premium data brings on premium revenues and valuations follow. IHS Markit’s flagship offerings, like the ISM Manufacturing Index, has long been a beacon to selected hedge funds, who paid a fair share of their investors’ earnings for the opportunity to squeeze an extra edge out of the data. As shown in our book, “Real-Time Risk: What Investors Should Know About Fintech, Flash Crashes and High-Frequency Trading”, in many cases