This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...

In this paper we consider the question of how to improve the efficacy of strategies designed to capture factor premiums in equity markets and, in particular, from the value, quality, low risk and momentum factors. We consider a number of portfolio construction approaches designed to capture...

The US Treasury effectively ”owns” about 24% of the stocks held by high income US taxable investors. Through the capital gains tax, Uncle Sam has an effective exposure of more than $1 trillion of equities. And this huge-but-silent investor might be about to get a lot bigger if capital gains...

In this short note, we show investors one way to calculate ideal investment sizing by using two rules of thumb based on a simple outline of individual risk aversion. We illustrate these two heuristics, which are not widely appreciated, with thought experiments involving coin flips and ketchup &...

Most existing studies conclude that the accuracy of analysts' target prices is questionable. In forecasting target prices, analysts estimate a future stock price under the constraint of a time frame of usually 12 months. We exclude this source of uncertainty by focusing on valuations in takeover...

We investigate the price dynamics of large market-capitalization U.S. equity exchange-traded funds (ETFs) in order to uncover trader motivations and strategy. We show that prices of highly liquid ETFs can deviate significantly from their daily net asset values. By adjusting for changes in...

The bedrock of financial economics is that there should be a tradeoff between risk and reward: an investment with low risk should have a low expected return, while one that could make you rich should also be one which could lose you a lot of money. A lot of research in finance is focused on...

In this paper information theoretical approach is applied to the description of financial markets A model which is expected to describe the markets dynamics is presented. It is shown the possibility to describe market trend and cycle dynamics from a unified viewpoint. The model predictions...

The methodology presented provides a quantitative way to characterize investor behavior and price dynamics within a particular asset class and time period. The methodology is applied to a data set consisting of over 250,000 data points of the S&P 100 stocks during 2004-2018. Using a two-way...