Stay Ahead Of The Curve: AI Weekly

Algorithmic Trading Strategy Video: Understanding I Know First's Signal Strength We have created this tutorial to explain how to trade using Dr. Rotiman's cutting-edge signal strategy and I Know First's "Top 10 Stock Picks" chart. Read on for key advice, and click this link for the full tutorial. A signal is not an entry point. Only trade according to the strongest signals. Buy when: the last close of the specific asset is above the 5 day average AND the average of the forecast signals over the last 5 days is "up."

Watch here! Quantitative Trading: The Predictability of Stock Markets From August 2011 to June 2012, we recorded the predictability of over a hundred equities by our machine learning system, a tool used to forecast the future movement curve of the market based on past history. Our algorithms constantly look for patterns in the markets, make and test conjectures, and provide a daily stock forecast for six different time horizons (3 days, 7 days, 14 days, 1 month, 3 months, and 1 year). This self-learning algorithm is evolving constantly, adding more data and creating a better machine model.

To see how predictable the markets are, we make observations from the records for the time period mentioned above. We see the following: Through the time period, the predictability of the top 100 most predictable markets in our system was a remarkable 0.53. Some markets were on average more predictable than others. For examples, our graphs show that the DAX index was more predictable than the Disney stock. Each market had a unique predictability curve, not necessarily synchronized with other markets. There were long periods of predictability interspersed with a few short unpredictability spikes. The long term forecast was more reliable than the short term forecast. We can see some different waves in predictability. Read more. Wisdom of the Crowd vs. Algorithmic Trading When it comes to financial markets, the “wisdom of the crowd” doesn't function as a viable stock trading strategy. Investors will gravitate towards a set of similar assets, to which they are attracted solely by the fact that others are doing the same. In fact, the Corporate Finance Institute itemizes four unmistakable human errors that characterize finance: self-deception (or human limits to learning), heuristic simplification (errors in human information processing), emotion (such as fear of exclusion and greed), as well as social sways (such as the aforementioned herd instinct). The failures of crowd wisdom in finance are best exemplified by a historical series of outrageous bubbles—from the Tulip bubble of 1637, the Great Depression of the 1930s, the dot-com bubble of the 1990s, the housing bubble of 2008, all the way to the recent cryptocurrency bubble, still dragging at the heels of major semiconductor companies. Investors seem to have found the answer to avoiding these problems in algorithmic trading. Algorithmic trading harnesses the computing power of complex mathematical models fueled by massive historical datasets to generate predictions regarding the outlook of a commodity. This method is mounting as an irreplaceable alternative for investors looking to optimize prediction speed, costs, and most importantly—accuracy. Read more. Deep Learning Finance: Revolutionizing the Market Today There is a new type of self-learning AI based algorithms that are able to build trends that are often unknown even to the most intelligent analyst. The reason is because they are able to eliminate “noise” in the market. This refers to short-term (daily or intra-day) fears, worries, and negative fueled perception regarding the price of a security or general market atmosphere. By ignoring it once is able to identify trends in the market. The AI based algorithms, are able to adapt as a result of neural networks built to allow for deep learning, which then allows the algorithm to adapt accordingly. I Know First, Ltd. is a FinTech company that brings science and math to the financial world by providing daily investment forecasts based on an advanced self-learning algorithm. Developed by CTO Lipa Roitman (PhD from Weizmann Institute – 35 years of experience), the algorithm utilizes artificial intelligence and machine learning techniques through which I Know First is able to analyze, model and predict the stock market, exemplifying these new models.

Read more. AI-Driven Algorithmic Trading: Disrupting the Disruptors Enter the age of AI, and with it, new opportunities for smarter trading. The investment world has not been blind to this, and predicting the stock market is a major challenge in contemporary machine learning. One of the leaders in this sphere is I Know First has, as Israel-based company that has developed a deep learning AI delivering daily forecasts for over 10,500 financial instruments, including stocks, ETFs and currencies. Trained on a historic dataset covering 15 years of trading, it approaches markets from a holistic perspective, looking for signals in the fresh trading data and using those to model the trends and seasonal patterns. In doing so, it looks at the direction which assets across various investment universes are most likely to follow and measures the expected intensity of these price swings. Read more.



Want to learn more? Israel 21c Press Release: 18 Israeli Firms Rocking Financial Technology

In the News: Yaron Golgher Talks on the Future of Investments and Trading at FinTech Junction 2019

MarketWatch Report: I Know First's Algorithm Outperforms S&P by 5 Times