U.S. regulators have recently questioned the role that high-frequency trading (HFT) plays in the bond market. The latest research from AbleMarkets studies a subclass of HFTs known as aggressive HFT. The research shows that: 1) Aggressive HFTs initiate, on average, 20% of trades in the U.S. Treasuries market. 2) Aggressive HFTs often trade U.S. Treasuries when no one else does: aggressive HFTs accounted for nearly all of the trades on the post-Thanksgiving Monday in 2014 and the post-Memorial Day Tuesday in 2015. 3) Participation of aggressive HFTs in the U.S. Treasury market has declined slightly in 2015 from 30% in much of December 2014 and
Market microstructure is traditionally thought to aid execution traders and market makers, the two types of intraday financial practitioners continuously interfacing within the markets. For longer-term investors, such as pension funds and long-only hedge funds’ portfolio managers, market microstructure is usually not considered to be a variable in portfolio optimization. However, the latest research from AbleMarkets.com shows that long-only managers ignore the effects of market microstructure at the expense of their clients’ portfolios. This note summarizes the latest findings. First of all, what is market microstructure? In broad terms, the science of market microstructure that examines the evolution of orders and order matching that occur
Markets are bursting at their seams with financial data. Much of the data that researchers are now mining is called Level I, II, and III data; this data comprises information on orders, executions and cancellations across different price levels. Until recently, such data was scarce. Today, it is more accessible, but still little understood. The not-for-profit Big Data Finance 2015 conference taking place at NYU Courant on March 6, 2015, will present selected techniques and results of big data analytics applied to Finance. This article briefly explores a data phenomenon. The relationship between returns and order placement and cancellations is examined and the following findings
Traditional variables taken into consideration by investors have included growth prospects, competition, recent earnings, dividends, long-term volatility and the like. Fairly recently, investor relations began taking into account and explaining shorter-term market moves, such as the stock’s responses to market-wide events. Lately, however, this information is no longer sufficient. Today’s institutional investors increasingly care about the comparative intraday price dynamics of stocks, including participation of aggressive high-frequency traders and the stock’s propensity for flash crashes. Aggressive high-frequency traders are the ultra-fast mostly automated trading systems that are capable of swooping in and out of a stock at lightning speed. Aggressive high-frequency traders have been shown
You feel it, you know it: some stocks tend to have more intraday volatility than other stocks. Some stocks are specifically more prone to Flash Crashes than others. Some stocks have higher aggressive high-frequency trading (HFT) participation than other stocks. At this point in financial innovation, no savvy portfolio manager can afford to ignore intraday risk, and, instead, needs to make it an integral part of his portfolio selection model. Why do intraday dynamics need to enter portfolio selection models? Can’t portfolio managers simply ride out the intraday ups and downs in their pursuit of longer-term goals? The answer, yes, but at a considerable cost.
By Irene Aldridge With the advent of high-frequency trading, measuring microstructure risk has not only become easier due to the availability of data, it has also become mandatory. Over the past several years, so-called flash crashes have triggered stop losses and caused numerous investors to liquidate positions early or forced investors out on the sidelines of the market altogether. Aggressive high-frequency traders have been shown to worsen market conditions and instilled dread, anger and a feeling of hopelessness in many market participants. Runaway algorithms sank ships like Knight Capital Group, dealing multi-million dollar losses in a matter of minutes. While the academics have worked on
By Irene Aldridge Many investors are rightfully concerned about market manipulation — after all, who wants to be taken for a ride? High-frequency market manipulation proved to be particularly disconcerting to many investors as it is evolutionary, difficult to detect without appropriate tools, and is still not universally understood. Adding even more complexity to investor decision-making is the explosion of various types of exchanges and other alternative trading venues, some known as dark pools. As my latest research shows, however, certain types of trading venues can be more suited to specific classes of investors. Investors may further select to trade on venues that minimize undesired
By Irene Aldridge Big Data is the new Big Bang. It is a buzzword that has exploded into every discipline that process expansive data sets. Computing, medical sciences, biology, and advertising are adjusting their methodologies to harness the ever expanding processing power that is available. In finance, the data is omnipresent: exchanges generate tick data, news services deliver real-time machine readable newsfeeds, and Internet traffic analysts produce sentiment feeds. Even the United States Federal Reserve has seemingly jumped on the big data wagon and is producing more data points than ever before. All of this is a great thing. Big data generates transparency, it