There has been and continues to be huge amounts of market research done to find profitable ways to invest and beat the stock market. However much of it doesn’t work in the real world. With that in mind, we’ve compiled the best research papers and investment software algorithms with the aim of creating a strong foundation for anyone wishing to create an investing system based on solid research and strategies that work in the real world.
The information will be continually updated as new research is found and will concentrate on the following key areas:
- Stock Selection.
- Diversification and Allocation.
- Portfolio Management including Rebalancing and Trading Strategies.
- Software Algorithms including Automated Reasoning, Machine Learning and Behavioural Economics.
Stock Market Research Papers
- Black-Litterman model: The Black-Litterman model enables investors to combine their unique views regarding the performance of various assets with the market equilibrium in a manner that results in intuitive, diversified portfolios. This paper consolidates insights from the relatively few works on the model and provides step-by-step instructions that enable the reader to implement this complex model. A new method for controlling the tilts and the final portfolio weights caused by views is introduced. The new method asserts that the magnitude of the tilts should be controlled by the user-specified confidence level based on an intuitive 0% to 100% confidence level. This is an intuitive technique for specifying one of most abstract mathematical parameters of the Black-Litterman model.
- Portfolio Selection with Transaction Costs: In this paper, optimal consumption and investment decisions are studied for an investor who has available a bank account paying a fixed rate of interest and a stock whose price is a log-normal diffusion. This problem was solved by Merton and others when transactions between bank and stock are costless. Here we suppose that there are charges on all transactions equal to a fixed percentage of the amount transacted. It is shown that the optimal buying and selling policies are the local times of the two-dimensional process of bank and stock holdings at the boundaries of a wedge-shaped region which is determined by the solution of a nonlinear free boundary problem. An algorithm for solving the free boundary problem is given.
- A Shrinkage Approach to Model Uncertainty and Asset Allocation: This paper takes a shrinkage approach to examine the empirical implications of aversion to model uncertainty.
- Portfolio Optimization, Heuristics, and the “Butterfly Effect”: The “Butterfly Effect” has been an interesting concept in the development of chaos theory. Given a complex system like the global weather system, the butterfly effect is rather intriguing. It says that the flapping of a butterfly’s wings in Beijing will work its way through the system and result in a tornado in Oklahoma. The same effect is at work with portfolio optimizers that perform asset allocation and portfolio allocation chores. A small change to an input works its way through the system of equations and results in a large change in allocations. As a result, it is very easy to arrive at a set of “non-intuitive” allocations; i.e. they don’t exhibit common sense. Once a set of portfolio allocations is put into place, a small change in the market will result in large changes (sometimes negative) in the portfolio returns. Practitioners, understandingly, have been losing confidence in the results of portfolio optimizers. The purpose of this paper is to explore the reasons why and to offer one reasonable alternative, a portfolio heuristic.
