“From coast to coast, the FBI and Securities and Exchange Commission have ensnared people not only at hedge funds, but at technology and pharmaceutical companies, consulting and law firms, government agencies, and even a major stock exchange.” – Preet Bharara, U.S. Attorney for the Southern District of New York, 2013; while annoucing charges in a massive insider trading scandal
Banking & High Finance are enormously complicated industries yet have significant impact on the daily lives of every denizen on the planet. Furthermore, firms in the most riskiest part of Banking – Capital Markets – deal in complex financial products in a dynamic industry. Capital Markets have been undergoing a rapid transformation – at a higher rate perhaps than Retail Banking or Corporate Banking. This is being fueled by technology advances that produce ever lower latencies of trading, an array of financial products, differing (and newer) market participants, heavy quant based trading strategies and multiple venues (exchanges, dark pools etc) that compete for flow based on new products & services.
The Capital Markets value chain encompasses firms on the buy side (e.g wealth managers), the sell side (e.g broker dealers) & firms that provide custodial services as well as technology providers who provide platforms for post trade analytics support. The crucial link to all of these is the execution venues themselves as well as the clearing houses.With increased globalization driving the capital markets and an increasing number of issuers, one finds an ever increasing amount of complexity across a range of financial instruments assets (stocks, bonds, derivatives, commodities etc).
The primary exchanges for equity (stock) trading are majors like NYSE,NASDAQ and the LSE (the London Stock Exchange). Futures and Options are dominated by CME and EUREX. However, deregulation has also resulted in increased fragmentation i.e the above traditional leaders now have competition from non traditional exchange operators like Electronic Communication Networks (ECNs), Crossing Networks (e.g. investment banks developing their own internal crossing systems to match buyers & sellers etc) & Dark Liquidity Pools etc.
Given the incredible amount of complexity & continuous fragmentation in venues, the industry has, (in what some would term a natural consequence of unchecked greed of a few), been beset by undesirable behavior (ranging from the suboptimal to criminal) by market participants, Such actions have periodically threatened the entire financial system while also shaking investor confidence in the financial system as a whole.
Despite the best efforts of regulatory authorities and legislation designed to tackle the problem of market manipulation and rigging – manipulators always seem to find newer ways of profiting at the expense of regular investors and the vast majority of (honest) participants.
To recap some of the more prominent scandals over the last few years –
- the Libor scandal of 2015 (where a rogue trader was found guilty of manipulating the global benchmark interest rate used as a basis for a range of financial deals)
- the Flash Crash of 2010 (a trillion dollar market crash that started at 2:32 PM EST on May 6 and lasted for approximately 36 minutes causing the various indices to drop precipitously
- Various Insider Trading scandals from 2008 till current day (the most prominent among these being the collapse of hedge fund Galleon Investments in 2009)
- the Collapse of Knight Capital in 2012 (due to a fat finger error caused by deploying test code into production) caused a major disruption in the trading of 140 odd securities while sending the firm into a tailspin. This single incident caused by a loss of $400 million in a single trading day. The result was that the firm’s enterprise value eroded during the matter of a few minutes forcing a sale almost overnight
The undesirable (read deleterious) consequence of High Frequency Trading (HFT) –
High-frequency trading (HFT) is essentially a high speed form of algorithmic trading that uses sophisticated networking technology and computer algorithms to rapidly trade securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.
A new trend in algorithmic trading is around the use of Big Data in a range of use-cases for both high and low latency trading. This covers and often blends, hardware solutions coupled with software algorithms. One example of this uses Big Data technologies, coupled with flash memory to facilitate development of new trading strategies that can use large volumes of tick data, weather data, social data, or geo-location data to make decisions in real time. In effect, predicting where the herd will move in a given market before they actually turn.
In fact, pioneering hedge funds are pioneering new types of algorithmic trading that rely on advanced self–learning analytics coupled with large linearly scalable data stores and low latency enabling hardware technology. Added to all these advances in automation have led to increased trading volumes and sophistication in the HFT space.
On the sell side, Banks have a strong need to provide the Head of Capital Markets & Risk Managers with a 360-degree view of the customers across their entire range of trading desks, not just to optimize enterprise profits, but to manage risk & fraudulent behavior.
Market Manipulation & the need for Surveillance –
Market manipulation is an umbrella term that usually refers to a wide array of trading practices that serve to distort securities prices thus enabling market manipulators to illicitly profit at the expense of other participants, by creating information asymmetry.
Market manipulation covers practices like insider trading (where securities are sold or bought based on nonpublic information) or misleading auto trading practices like “spoofing” or “pumping and dumping” etc.
Why is surveillance emerging as a major challenge over the last five years or so ? I contend that it is a nuanced issue with five major business trends (with downstream technology ramifications) driving them –
- The rise of automation across the Capital Markets value chain and the increasing use of technology across the lifecycle contributes to an environment where speeds and feeds are contributing to a huge number of securities changing hands (in huge quantities) in milliseconds; automation adds substantially to the risk of fraud
- The presence of multiple avenues of trading (ATF – alternative trading facilities and MTF – multilateral trading facilities) creates opportunities for information and price arbitrage that were never a huge problem before in terms of multiple markets and multiple products across multiple geographies with different regulatory requirements.This has been covered in a previous post in this blog at –
http://www.vamsitalkstech.com/?p=412 - As a natural consequence of all of the above – the globalization of trading where market participants are spread across multiple geographies makes it all the more difficult to provide a consolidated audit trail (CAT) to view all activity under a single source of truth ;as well as traceability of orders across those venues; this is extremely key as fraud is becoming increasingly sophisticated e.g the rise of insider trading rings
- Existing application (e.g ticker plant, backtesting, DevOps) architectures are becoming brittle and underperforming as data and transaction volumes continue to go up & data storage requirements keep rising every year. This leads to massive gaps in compliance data. Another significant gap is found while performing a range of post trade analytics – many of which are beyond the simple business rules being leveraged right now and now increasingly need to move into the machine learning & predictive domain
- As automation increases, backtesting of data has become a challenge – as well as being able to replay data across historical intervals. This is key in mining for patterns of suspicious activity like bursty spikes in trading as well as certain patterns that could indicate illegal insider selling
Market Surveillance –
Market surveillance is can thus be defined as the activity of ingesting, curating and analyzing trade and position information on a real-time or T+1 basis with the intention of detecting irregular activity that could denote market abuse (as defined by the local regulatory authorities).
Market surveillance is generally out by Exchanges and Self Regulating Organizations (SRO) like the FINRA in the US – all of which have dedicated surveillance departments set up for this purpose. However, capital markets players on the Buy and Sell side also need to conduct extensive trade surveillance to report up internally. Pursuant to this goal, the exchanges & the SRO’s monitor transaction data including orders and executed trades & perform deep analysis to look for any kind of abuse and fraud.
To get a sense of the scale and the challenges involved in market surveillance, let us examine the leading US market regulator FINRA (Finance Industry Regulatory Authority).FINRA is a non-governmental organization that regulates member brokerages and exchange markets. Along with the Securities and Exchange Commission (SEC) , it acts as a virtual market regulator.
FINRA have also been a pioneer in their usage of technology to monitor billions of market transactions (from an average of 40 billion to a peak volume of 75 billion a day). They apply a variety of data-gathering & processing techniques, we work to uncover insider trading and any strategies firms or individuals use to gain an unfair advantage. FINRA extensively leverages technology to a). effectively oversee brokerage firms; b). accurately monitor the U.S. equities markets; c). quickly detect potential fraud.[2]
FINRA handles more data in a single day than what MasterCard processes in a year and Visa in 6 months. We use innovative technology, such as parallel computing hardware to process our ever-increasing data volume and cloud computing to automate the process and store the massive amounts of data. [2]
Illustration : Transaction Volumes Supported by FINRA vs Payment Card Networks
FINRA have been vocal about their investments in innovative technology—namely Big Data & Cloud Computing—in order to build sophisticated surveillance systems that process extraordinary amounts of data while integrating with cutting-edge applications.
Role of Technology –
As can be seen from FINRA’s approach above, Market Surveillance essentially is a business problem that needs to be solved through the combination of large scale computing, cutting edge data management, business rules and predictive analytics.
The vast majority of current surveillance techniques, including the collection & processing of data may be insufficient to capture in a timely manner all of the information necessary to monitor efficiently and effectively trading activity that occurs in such dispersed markets.
The next post will expand on the above themes from a technology standpoint. We will throw up some interesting ideas in the area of Surveillance for players in light of the substantial data & computing assets the they possess. We also will examine how all of this can be leveraged to harness massive volumes of data across a large global marketplace.
Indeed technologies like Big Data are being looked at to provide a cross asset trade, market and static data repository. A golden source of data that can be used by the front office, middle office, operations, compliance, risk, and finance to provide a common view of the Capital Markets business. Such systems do not generally exist now making it hard to spot undesirable activity, among other things.
References –
[1] Market Surveillance – Wikipedia
[2] FINRA Technology –
http://technology.finra.org/