Social signals and algorithmic trading of Bitcoin

The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behavior offer a great potential to drive trading strategies. We contribute to this by providing a consistent approach that integrates various datasources in the design of algorithmic traders. This allows us to derive insights into the principles behind the profitability of our trading strategies. We illustrate our approach through the analysis of Bitcoin, a cryptocurrency known for its large price fluctuations. In our analysis, we include economic signals of volume and price of exchange for USD, adoption of the Bitcoin technology, and transaction volume of Bitcoin. We add social signals related to information search, word of mouth volume, emotional valence, and opinion polarization as expressed in tweets related to Bitcoin for more than 3 years. Our analysis reveals that increases in opinion polarization and exchange volume precede rising Bitcoin prices, and that emotional valence precedes opinion polarization and rising exchange volumes. We apply these insights to design algorithmic trading strategies for Bitcoin, reaching very high profits in less than a year. We verify this high profitability with robust statistical methods that take into account risk and trading costs, confirming the long-standing hypothesis that trading based social media sentiment has the potential to yield positive returns on investment.Comment: http://rsos.royalsocietypublishing.org/content/2/9/15028

On the Profitability of Optimal Mean Reversion Trading Strategies

We study the profitability of optimal mean reversion trading strategies in the US equity market. Different from regular pair trading practice, we apply maximum likelihood method to construct the optimal static pairs trading portfolio that best fits the Ornstein-Uhlenbeck process, and rigorously estimate the parameters. Therefore, we ensure that our portfolios match the mean-reverting process before trading. We then generate contrarian trading signals using the model parameters. We also optimize the thresholds and the length of in-sample period by multiple tests. In nine good pair examples, we can see that our pairs exhibit high Sharpe ratio (above 1.9) over the in-sample period and out-of-sample period. In particular, Crown Castle International Corp. (CCI) and HCP, Inc. (HCP) achieve a Sharpe ratio of 2.326 during in-sample period and a Sharpe ratio of 2.425 in out-of-sample test. Crown Castle International Corp. (CCI) and Realty Income Corporation (O) achieve a Sharpe ratio of 2.405 and 2.903 respectively during in-sample period and out-of-sample period

A guide to survival of momentum in UK style portfolios

In this study we estimate the survival time of momentum in six UK style portfolio returns from October 1980 to June 2014. We utilise the Kaplan-Meier estimator, a non-parametric method that measures the probability that momentum will persist beyond the present month. This probability enables us to compute the average momentum survival time for each of the six style portfolios. Discrepancies between these empirical mean survival times and those implied by theoretical models [Random Walk and ARMA (1, 1)] show that there is scope for profiting from momentum trading. We illustrate this by forming long-only, short-only and long-short trading strategies that exploit positive and negative momentum and their average survival time. These trading strategies yield considerably higher Sharpe ratios than the comparative buy-and-hold strategies at a feasible level of transaction costs. This result is most pronounced for the long/short strategies. Our findings remain robust during the 2007/2008 financial crisis and the aftermath, suggesting that Kaplan-Meier estimator is a powerful tool for designing a profitable momentum strategy

Naked short selling: The emperor`s new clothes?

Regulatory and media concern has focused heavily on the potentially manipulative distortion of market prices associated with naked short selling. However, naked shorting can also have beneficial effects for liquidity and pricing efficiency. We empirically investigate the impact of naked short-selling on market quality, and find that naked shorting leads to significant reduction in positive pricing errors, the volatility of stock price returns, bid-ask spreads, and pricing error volatility. We study naked shorting surrounding the demise of financial institutions hardest hit by the financial crisis in 2008 and find no evidence that stock price declines were caused by naked shorting. We also find that naked short-selling intensifies after rather than before credit downgrade announcements during the 2008 financial crisis. In general, we find that naked short sellers respond to public news and intensify their activity after price declines rather than triggering these price declines. We study the impact of the SEC ban on naked short selling of financial securities during July and August 2008, and find that the ban did not slow the price decline of those securities and had a negative impact on liquidity and pricing efficiency. Finally, after examining the speeds of mean reversion of pricing errors and order imbalances, we infer that Regulation SHO was successful in curbing the impact of manipulative naked short selling, and this reduction in the impact of manipulative naked shorting has continued through the 2008 financial crisis. Overall, our empirical results are in sharp contrast with the extremely negative preconceptions that appear to exist among media commentators and market regulators in relation to naked shortselling. --Naked Short Selling,Short Selling,Pricing Efficiency

The Arbitrage Efficiency of the Nikkei 225 Options Market: A Put-Call Parity Analysis

This paper is concerned with arbitrage efficiency of the Nikkei index option contracts traded on the Osaka Securities Exchange ( OSE) within the put-call parity (PCP) framework. A thorough ex post analysis is first carried out. The results reveal a modest number of violations with 2.74 percent of the sample breaching the PCP equation and an average arbitrage profit of 22.61 index points for OSE member firms during the sample period (2003?05). Ex ante tests are then conducted whereby ex post profitable arbitrage strategies, signified by the matched put and call contracts, are executed with lags of one minute and three minutes. The ex ante results reveal that the number of profitable arbitrage opportunities and the average profit are both reduced significantly with an execution lag. In addition, regression analysis is used to provide further evidence about the PCP and arbitrage profitability. Overall, there is no strong evidence found against the efficiency of the Nikkei 225 options market, although arbitrage opportunities do exist occasionally.Put-call parity; Market efficiency; Nikkei 225 options

The Growth and Limits of Arbitrage: Evidence from Short Interest

We develop a novel methodology to infer the amount of capital allocated to quantitative equity arbitrage strategies. Using this methodology, which exploits time-variation in the cross section of short interest, we document that the amount of capital devoted to value and momentum strategies has grown significantly since the late 1980s. We provide evidence that this increase in capital has resulted in lower strategy returns. However, consistent with theories of limited arbitrage, we show that strategy-level capital flows are influenced by past strategy returns as well as strategy return volatility, and that arbitrage capital is most limited during times when strategies perform best. This suggests that the growth of arbitrage capital may not completely eliminate returns to these strategies

Commodity strategies based on momentum, term structure, and idiosyncratic volatility

This article demonstrates that momentum, term structure, and idiosyncratic volatility signals in commodity futures markets are not overlapping, which inspires a novel triple-screen strategy. We show that simultaneously buying contracts with high past performance, high roll-yields, and low idiosyncratic volatility, and shorting contracts with poor past performance, low roll-yields, and high idiosyncratic volatility yields a Sharpe ratio over the 1985 to 2011 period that is five times that of the S&P-GSCI. The triple-screen strategy dominates the double-screen and individual strategies and this outcome cannot be attributed to overreaction, liquidity risk, transaction costs, or the financialization of commodity futures markets