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, co-author of “Big Data Science in Finance” (Wiley, 2020) The NYPost reported on November 5, 2020, just two days after the still-inconclusive U.S. Presidential Election, that “Bitcoin rallies past $15,000 for the first time since January 2018”. Bitcoin is just one of now many cryptocurrencies, “crypto” for short. Other cryptocurrencies, like Ethereum, XRP, Chainlink, and many others are surging as well, offering investors an opportunity for unparalleled returns. The surge in may seem random to some, but it also may have very strong fundamentals rooted in the current political landscape. This article makes a case for Crypto becoming a stronger performer in