AC Investment Research is an A.I. research company. Our mission is to conduct fundamental research and develop a totally new, scientific technology that uses machine learning and the fundamentals of game theory.
Our Mission
There are many widely used traditional techniques of stock forecasting each with its own limits and biases. Human-oriented approaches focus more on back-dated data while not being able to well define or relate how those back-dated financials or people actions will reflect on future performance or pricing. At its best the number of facts or signals that can be considered and correlated simultaneously in human-oriented approaches is quite limited and is subject to personal biases.
Our goal is to conduct fundamental research and develop a totally new, scientific technology that uses machine learning and the fundamentals of game theory to create objective forecasting frameworks. We are currently developing this technology and are excited to share it with the world because we believe it has the potential to revolutionize the way we make predictions.
Our Research
Game theory can be applied to the stock market in several ways. One way is to analyze the strategic decision-making of market participants, such as traders, investors, and companies. For example, game theory can be used to understand how traders might make decisions about when to buy or sell a particular stock, or how companies might make decisions about when to issue new stock or buy back existing stock.
Another way that game theory can be applied to the stock market is to analyze the overall market dynamics and how they might affect stock prices. For example, game theory can be used to understand how the actions of individual market participants might influence the overall market and how different market conditions, such as supply and demand, might affect stock prices.
Game theory and neural networks can be used together in a variety of ways. One way to use game theory with neural networks is to apply game-theoretic concepts and techniques to the design and analysis of neural networks.
We conduct machine learning based financial market analysis. We’re committed to meeting the highest methodological standards — and to exploring the newest frontiers of research.
Our People
We are led by Adem Çetinkaya and have a staff of more than 20 people and 4 research teams. Our experts combine the support-vector networks and financial skills with the analytical rigor of scientists.
Project Advisors
Martin L. Weitzman (2016-2018)
Martin Lawrence Weitzman (April 1, 1942 – August 27, 2019) was an American economist and professor of economics at Harvard University. He was among the most influential economists in the world according to Research Papers in Economics (RePEc).
Weitzman was born in New York City in 1942. He received a B.A. in mathematics and physics from Swarthmore College in 1963 and an M.S. in statistics and operations research from Stanford University in 1964. He received his Ph.D. in economics from the Massachusetts Institute of Technology (MIT) in 1967.
Weitzman's work helped AC Investment Research to develop an algorithm that could predict how investors would react to different market conditions. This allowed the company to make more accurate predictions about future stock prices.
Weitzman's insights helped AC Investment Research to develop a more sophisticated algorithm that could better predict future stock prices. This allowed the company to make more informed investment decisions.
Dale W. Jorgenson (2018-2019)
Dale Weldeau Jorgenson (May 7, 1933 – June 8, 2022) was an American economist who specialized in economic growth, productivity, and the economics of information technology. He was the Samuel W. Morris University Professor at Harvard University, where he taught from 1969 until his death.
Jorgenson was born in Bozeman, Montana. He received his B.A. in economics from Reed College in 1955 and his Ph.D. in economics from Harvard in 1959. After graduating from Harvard, he taught at the University of California, Berkeley, from 1959 to 1969.
Jorgenson's work focused on how technological change affects economic growth and productivity. He developed a new method for measuring the contribution of technology to economic growth, which is now widely used by economists. Jorgenson also showed how technological change can lead to changes in the structure of the economy, as new industries emerge and old industries decline.
Jorgenson's insights into technological change were essential to AC Investment Research's game theory algorithm. The algorithm is designed to predict how investors will react to changes in technology. By understanding how technology affects economic growth and productivity, Jorgenson was able to help AC Investment Research develop an algorithm that could accurately predict how investors would react to changes in technology.
Jorgenson's work with AC Investment Research was a testament to his commitment to using his expertise to help solve real-world problems. He was a true visionary who saw the potential of technology to revolutionize the way we live and work.
Our History
Launched as AC Investment Research in 2017, AC Investment Research is the investment research arm of AC Advisory. AC Investment Research is headquartered in (Saint Helier) Jersey, with offices in San Francisco, Boston, New York, Cambridge and London.
Careers
We believe we can solve problems faster and better together.
That's why we work together to produce solutions suitable for the new needs of the changing world with an inclusive perspective. At AC Investment Research, we are a global community where everyone feels like they belong, develop unique skills, and work on exciting topics, powered by the cutting edge of technology. We invite you to be a part of this community where everyone is seen, heard and cared about.
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