#75 – Federal Open Market Committee Meeting Effect on Stocks

Authors: Nilsson

Title: The Pre-FOMC Drift Explored

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2640477

Abstract:

The pre-FOMC drift was first published in 2011 and is a strong driver of equity market performance over the last 30 years. The effect is able to explain approximately half of all the equity market returns over the measured period. We verify the results of prior studies. Furthermore, the report dives into conditional factors; equity market trend and monetary policy action to see if there is any difference in terms of macro variables. We find that FOMC is rather stable throughout time, macro conditions and has not been dependent on a particular Fed Chair.
 

It seems as if the markets are expecting that the FOCM will infuse optimism into equity markets as the majority of the gains occurs before the actual announcement. The effect can be due to behavioral issues and herding among market participants but can also be due to information leakage. The effect remains unexplained.

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#12 – Pairs Trading with Stocks

Authors: Cartea, Jaimungal

Title: Algorithmic Trading of Co-Integrated Assets

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2637883

Abstract:

We assume that the drift in the returns of asset prices consists of an idiosyncratic component and a common component given by a co-integration factor. We analyze the optimal investment strategy for an agent who maximizes expected utility of wealth by dynamically trading in these assets. The optimal solution is constructed explicitly in closed-form and is shown to be affine in the co-integration factor. We calibrate the model to three assets traded on the Nasdaq exchange (Google, Facebook, and Amazon) and employ simulations to showcase the strategy's performance.

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Authors: Engelberg, McLean, Pontiff

Title: Anomalies and News

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2631228

Abstract:

Using a sample of 97 stock return anomalies documented in published studies, we find that anomaly returns are 7 times higher on earnings announcement days and 2 times higher on corporate news days. The effects are similar on both the long and short sides, and they survive adjustments for risk exposure and data mining. We also find that anomaly signals predict analyst forecast errors of earnings announcements. Taken together, our results support the view that anomaly returns are the result of mispricing, which is at least partially corrected upon news arrival.

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#5 – FX Carry Trade

Authors: Clare, Seaton, Smith, Thomas

Title: Carry and Trend Following Returns in the Foreign Exchange Market

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2633752

Abstract:

Recent research has confirmed the behaviour of traders that significant excess returns can be achieved from following the predictions of the carry trade which involves buying currencies with relatively high short-term interest rates, or equivalently a high forward premium, and selling those with relatively low interest rates. This paper shows that similar-sized excess returns can be achieved by following a trend-following strategy which buys long positions in currencies that have achieved positive returns and otherwise holds cash. We demonstrate that market risk is an important determinant of carry returns but that the standard unconditional CAPM is inadequate in explaining the cross-section of forward premium ordered portfolio returns. We also show that the downside risk CAPM fails to explain this cross-section, in contrast to recent literature. A conditional CAPM which makes the impact of the market return as a risk factor depend on a measure of market liquidity performs very well in explaining more than 90% of the variation in portfolio returns and more than 90% of the average returns to the carry trade. Trend following is found to provide a significant hedge against these risks. The performance of the trend following factor is more surprising given that it does not have the negative skewness or maximum drawdown characteristic which is shown by the carry trade factor.

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#14 – Momentum Effect in Stocks
#26 – Value (Book-to-Market) Anomaly

Authors: Moskowitz

Title: Asset Pricing and Sports Betting

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2635517

Abstract:

I use sports betting markets as a laboratory to test behavioral theories of cross-sectional asset pricing anomalies. Two unique features of these markets provide a distinguishing test of behavioral theories: 1) the bets are completely idiosyncratic and therefore not confounded by rational theories; 2) the contracts have a known and short termination date where uncertainty is resolved that allows any mispricing to be detected. Analyzing more than a hundred thousand contracts spanning two decades across four major professional sports (NBA, NFL, MLB, and NHL), I find momentum and value effects that move betting prices from the open to the close of betting, that are then completely reversed by the game outcome. These findings are consistent with delayed overreaction theories of asset pricing. In addition, a novel implication of overreaction uncovered in sports betting markets is shown to also predict momentum and value returns in financial markets. Finally, momentum and value effects in betting markets appear smaller than in financial markets and are not large enough to overcome trading costs, limiting the ability to arbitrage them away.

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#14 – Momentum Effect in Stocks

Authors: Berghorn, Otto

Title: Mandelbrot Market-Model and Momentum

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2620112

Abstract:

Mandelbrot has significantly contributed in many ways to the area of finance. He was one of the first who criticized the oversimplifications centered around the early stochastic process models of Bachelier utilizing normal distribution. In his view, markets were fractal and much wilder than classical theory suggests. Additionally, he was a profound critic of the efficient markets hypothesis. Particularly, his work of fractional Brownian motion showed that the independence claim made by that hypothesis is not valid; in addition, he proposed a multi-fractal asset model to reconcile for effects observed in the market. However, it is also known that his vision of fractal markets used fractal trends. Recently, we were able to show that the scaling behaviour of trends, as defined by a specific trend decomposition using wavelets, are the root cause for the momentum effect. Additionally, we were able to show that these trends have fractal characteristics. In this work, we will revisit Mandelbrot’s vision of fractal markets. We will show that the momentum effect discussed heavily in literature can be modeled by the so-called Mandelbrot Market-Model. Additionally, this model shows, from the risk side, that markets are wilder because of trend structures compared with classical models. In conclusion, we derive what Mandelbrot always knew: There are no efficient markets.

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