Aggressive HFT has long been associated with volatility. Several academic studies hypothesized that higher aggressive HFT participation leads to higher volatility levels, and for good reasons, as explained below. The empirical evidence, however, has been hard to come by, until now. This note explains the empirical relationships between implied volatility of options on stocks comprising the S&P 500 and participation of aggressive HFT, as measured by the AbleMarkets Aggressive HFT Index. As the note shows, two prominent conclusions can be made about the aggressive HFTs in relation to volatility in which the aggressive HFTs are present: 1. Higher aggressive HFT leads to higher implied volatility
By Irene Aldridge Twenty years ago, television told women to buy extraordinary quantities of shoes. There was the holy grail of happiness, according to the absolute hit “Sex in the City”. For today’s generation of women “Sex and the City” is out, and a new trend is in, marching in protest. The marching is against the dominant male stereotype, but also explicitly asking for the government (another patriarchal authority?) to provide certain services, higher wages, better working conditions, and the like. How about taking charge of our own future in a constructive meaningful way? An interesting study is the Big Data Finance conference at New
Adapted from “Real-Time Risk: What Investors Should Know About Fintech, High-Frequency Trading and Flash Crashes” (with Steve Krawciw, Wiley, 2017) Big data is all the rage, but not without pitfalls. In fact, data analysis is subject to risks that may lead to poor inferences and bad decisions that follow. The process of analyzing data, regardless of complexity, can go off the rails on several fronts: A small data sample may pick up a pattern that does not recur on a sufficiently long timeline, misleading the researchers of the pattern’s power and predictability. Oversampling of data may occur when researchers torture the same sample of data
An Analysis of Institutional Activity in October 2016 Adapted from Real-Time Risk: What Investors Should Know About FinTech, High-Frequency Trading and Flash Crashes (forthcoming, Wiley, NJ). Pre-order on Amazon.com. “Money talks, bull*%$# walks”, says a classic Wall Street proverb. The expression has a lot of merit: nothing reflects one’s beliefs more than a financial bet on the markets. The larger is the bet, the stronger is the belief. AbleMarkets research indicates that institutional money sold off when negative news affected Donald Trump in October 2016, but when Hillary Clinton’s negative news emerged later in the same month, there was very little reaction from institutional money.
When large institutions like hedge funds and pension funds trade, their decisions make a difference to the direction of prices and volatility according to AbleMarkets.com. First, the prices rise on days when the institutions buy throughout the day. Prices fall on the same day when the institutions sell during the day. Second, following institutional buying of a particular financial instrument, volatility decreases for several days with 99% probability, according to the latest research from AbleMarkets. The latest analysis uses institutional buying and selling activity, as a percentage of total buyer- and seller-initiated trades as measured by the AbleMarkets Institutional Participation Index. The index, developed using
By Irene Aldridge Present economic conditions leave much to be desired: Europe is trying to resolve its debt problems, and the U.S. has seen much better times in terms of employment rates and consumer confidence. Against this backdrop of economic calamities, the financial markets are experiencing high volatility, seesawing up and down, gaining and losing in excess of 3% on a given day. Whether the current volatility is without a precedent, however, is up for a debate and depends on how volatility is measured. The most common way to assess volatility is via standard deviation, a square root of the average of squared deviations of