On May 6th, 2010, the U.S. stock markets experienced an unusual decline (and an immediate upswing) that temporarily erased $1 trillion in market value (the Dow Jones Industrial Average plunged about 1000 points) and puzzled both actors and experts following the markets. Given the ongoing controversy about “flash orders” and its portrayed usage by high-frequency traders, this incident was quickly referred as the flash crash and just as quickly blame fell on the electronic trading industry. While it is true that some high-frequency trading firms stopped running their algorithms when the decline started (human traders stopped participating in the markets in Black Monday as well), some of them stayed in the market, and helped the markets recover just as quickly as the decline happened.
Fast forward two years and we find a twit from the Associated Press with supposedly breaking news that President Obama was injured due to explosions at the White House. That report made $136 billion in market value temporarily disappear, with the Dow Jones Industrial Average quickly dropping 150 points before swinging back.
Examples of dramatic swings can go all the way back to the origins of stock markets. We only need to take a look at Black Monday, October 19th, 1987, when the Dow Jones Industrial Average dropped by 508 points, 22.61%; by the end of October, stock markets in the United States had fallen by 22.68%, not showing any improvement for many weeks. Meanwhile, on May 6th, the Dow Jones had regained most of the drop only twenty minutes later.
Like major technology innovations in the past, computer trading was blamed for Black Monday back in 1987; as observed by economist Richard Roll though, program trading strategies were used primarily in the United States, and not in markets such as Australia and Hong Kong where the crisis started. Therefore, it is unsurprising by now that high-frequency trading has been blamed for the flash crash, the now called Twitter crash, and mini-flash crashes of certain stocks, commodities and currencies.
As Manoj Narang, CEO, Tradeworx, says in my book The Speed Traders, no matter what regulators do, there will be times when herd-like behavior among long-term investors will all be stampeding for the exits at the same time, and simply there won’t be enough high-frequency trading to cover the demand for liquidity. That is exactly what happened on May 6th, as described in painstaking detail in the CFTC/SEC report of September 30th, 2010; the report made clear that a mutual fund, identified by Reuters back in May 14 as Waddell & Reed Financial Inc., initiated a program to sell a total of 75,000 E-Mini contracts (valued at approximately $4.1 billion), certainly influenced by the pessimism in the markets due to street protests in Greece, among other reasons; the computer algorithm used to trade the position in the futures markets was set to target an execution rate set to 9% of the trading volume calculated over the previous minute, but without regard to price or time. Similarly, we will always experience technology and human errors. Dave Cummings, Chairman, Tradebot, would ask about the flash crash, “Who puts in a $4.1 billion order without a limit price?” That was the catalyst that initiated the flash crash. Knight Capital Group Inc.’s $440 million trading loss in August 1st, 2012, when the firm lost approximately $10 million per minute, is another recent example that comes to mind.
On March 7th, 2013, the U.S. Securities and Exchange Commission announced Regulation SCI (Systems Compliance and Integrity). As explained by Commissioner Luis A. Aguilar, the proposed rule would move beyond the current voluntary program and require entities to establish, maintain, and enforce written policies and procedures reasonably designed to ensure that its systems have adequate levels of capacity, integrity, resiliency, availability, and security to maintain the entity’s operational capability and promote the maintenance of fair and orderly markets, mandate participation in scheduled testing of the operation of the entity’s business continuity and disaster recovery plans, including backup systems, and coordinate such testing on an industry- or sector-wide basis with other entities, and finally make, keep, and preserve records relating to the matters covered by Regulation SCI, and provide them to Commission representatives upon request.
Electronic trading, like any other area of finance, should have sensible regulations imposed to promote sound trading practices and protect the average American investor from predatory behavior. If a market participant who does not use high-frequency trading believes that he or she cannot enter into fair transactions, then that individual will not invest in that market. But regulators could restore trust in the market without eliminating high-speed trading. They simply must be armed to analyze trading activity in real time.
In an area of finance predicated on speed, regulation must be as well. Real-time information would allow regulators to see everything that is occurring in the markets, no matter how quickly the order information is being posted and transactions are occurring. This would require significant commitments to invest in both human capital and information technology, but the investment is worthwhile: it is vital for regulators to level the playing field of electronic trading in general.
Real-time policing for potential malfeasance is the most efficient way to regulate high-frequency trading. Analysis of real-time data would provide for effective regulation of these trades. This in turn would provide peace of mind for market participants big and small.
Having spoken with professionals in the world’s most important financial centers, I can attest that America’s capital markets continue being the envy of the world, thanks to the innovation people like high-frequency traders, educated in the country’s top schools, bring to the markets. Let’s allow innovations like high-frequency trading to continue and regulators to police them accordingly, and not try to ban them, as vocal activists tried once with major innovations such as automobiles and derivatives.Read Full Post | Make a Comment ( None so far )
Financial exchanges play a vital role in economic development as one of the primary tools for the allocation of capital in both developed economies and emerging ones. The indices created using the platforms provided by global exchanges are used by the financial services industry and the government as barometers of economic health and a predictor of national financial well-being.
However, the exchanges model has changed dramatically over the past decade starting with demutualization. The first wave began with the Stockholm Stock Exchange (STO) in 1993 and included the Bombay Stock Exchange (BSE) in 1995 and Borsa Italiana (BVME) in 1997. Demutualization was followed by a second stage in which a number of exchanges became publicly traded and profit-seeking companies listed on their own platform, with the Australian Securities Exchange (ASX) being the first to follow this model in 1998. Such restructurings are still taking place in exchanges all over the world.
Exchanges have come under increasing regulatory attention. In the US, for instance, the Securities and Exchange Commission is expanding an enforcement probe into a broader look at how exchanges develop new products, communicate with investors and provide incentives to trade; this was sparked partly by an SEC probe into trading order types apparently benefiting high-speed traders, whose activity comprises more than half of all stock-trading volume.
As companies exercise more flexibility in seeking to raise capital outside their national boundaries, the environment has become even more competitive for exchanges. Furthermore, they are hugely capital intensive (mostly due to the IT infrastructure required for increasingly high frequency trading), reason why some exchanges are looking to grow through acquisitions in order to enjoy greater economies of scale.
While these challenges are common to exchanges worldwide, the impact on their bottom lines has been rather diverse. For instance, the Philippines Stock Exchange (PSE) doubled its profit in the first nine months of 2012 compared to last year. While the exchange benefited tremendously from the favorable economic environment and sky-high optimism in the country, there were a number of reforms implemented by the PSE, including the rollout of a new trading system, extension of trading hours and implementation of multiple regulatory and governance enhancements.
London Stock Exchange (LSE) reported a profit for the first half of the year nearly unchanged from last year as strong performance in information services helped offset weak capital markets. The exchange highlighted the benefits of its increasingly diversified international group and the growth from its Information, Post Trade and Technology businesses; the exchange reported a 66 percent increase in Information Services revenue, while Capital Markets revenue dropped 19 percent.
On the other side of the spectrum, NYSE Euronext, the operator of the New York Stock Exchange and other stock exchanges, announced that its third-quarter profit fell 46 percent, which the company attributed to reduced average daily trading volumes, primarily related to its derivatives business. It said its results last year were helped by the extreme volatility of the markets in Europe and the United States due to debt concerns. Certainly, volatility has declined considerably since then, reaching multi-year lows in August 2012.
Exchanges are responding to this increasing competition in a number of ways. Negotiating mergers has been the first option considered by a number of companies, only to be derailed in some cases by regulators or rebuffed by targets. NYSE Euronext face resistance from European regulators on its proposed combination with Deutsche Boerse; ASX’s agreement with Singapore Exchange (SGX) fell through as well; LSE dropped its bid for Toronto Stock Exchange (TSX) after its owners spurned them in favor of the bid from a group of Canadian banks and pensions. However, that doesn’t mean that exchanges will not attempt to find combinations that don’t run afoul of regulations, just because mergers almost in all cases strive to provide an avenue to widen their business model and to exploit economies of scale, economies of network, cross selling opportunities and trading hours; for instance in Asia, Tokyo and Hong Kong shortened their midday halt to one hour last year, while Singapore scrapped its lunch break altogether, joining Australia, South Korea and India on the list of exchanges that have uninterrupted trading days.
Second, developing cutting edge-edge technology and its further commercialization is paving the way to extract additional profits from investments already paid. For instance, LSE leveraged its IT investments with the adoption of an outsourced managed services model that allowed the exchange to run other exchanges, such as the Johannesburg Stock Exchange, using its own platform. Building a major technology franchise through outsourcing was vital for the LSE if it was to continue to compete with the likes of NYSE Euronext and Nasdaq OMX, which had extended their brand and influence in several emerging markets through major technology deals.
Finally, exchanges are standing up to the challenge of diversifying their business model. Exchanges that were primarily focused on cash trading decided to integrate services such as the trading of derivative financial instruments markets. As it was the case for LSE, information services delivered in machine-readable format are providing growth opportunities for exchanges worldwide; RapiData, company acquired by Nasdaq OMX, enabled the company to deliver U.S. government and other economic news directly from the source to customers interested in receiving information in an electronic feed, giving them instant access to events that are incorporated into algorithmic trading systems. The perennial appetite of high-frequency and algorithmic trading firms for faster access to trading data is also encouraging exchanges to provide colocation services that bring all participants equal access to their matching engines. Ultimately, exchanges will be forced to explore all upstream and downstream opportunities in the production chain of the exchange industry, from the above mentioned information services upstream to the integration of clearing and settlement services downstream.
Revenues at exchanges will need to evolve from its reliance on volume-dependent fees and commissions for a range of activities (including trading, listing, clearing, settlement, depository, custody and nominee services) to uncorrelated income sources that might not have existed just a few years ago; the infrastructure they have, the data they manage and proximity to their matching engine are all key assets that need to be fully exploited if exchanges are to succeed in 2013 and beyond.Read Full Post | Make a Comment ( None so far )
For John Netto, one of the leading high-frequency traders featured in Edgar Perez’s The Speed Traders: An Insider’s Look at the New High-Frequency Trading Phenomenon That is Transforming the Investing World, high-frequency trading is going to get bigger, stronger and more prevalent. “There are potential regulatory changes that might impact the growth of high-frequency trading; that is always a possibility. They have talked about co-location and proximity legislation but who knows how it all shakes and if the desired results from this legislation are accomplished.”
Netto is the Founder and President of M3 Capital. Mr. Netto has worked with buy-side firms, sell-side firms, and technology providers on more efficiently combining structure, strategy, and personnel to increase trading profits. Mr. Netto has presented on behalf of Eurex, CME Group, The ICE, ISE, Interactive Brokers, Thomson Reuters, Profit-Loss Forex Conferences and Golden Networking as well as appearing regularly on Forex TV, Fox Business Channel, The Money Show Video Network, and many other media outlets.
Mr. Netto sees more traditional investment managers expanding into high-frequency trading; more managers are using technology as in means of investing. Similarly, he sees more institutional investors allocating part of their asset base to quantitative trading strategies. He adds: “I think at this moment the future is more than just technology, as it is already very robust; it would be more about the adoption of the technology which will determine how fast things go. Not every exchange has the same technology or robust infrastructure; I think what we will see is that more and more firms, more and more exchanges around the world get caught up and then it will be about the interchangeability of the technology. And not just from a hardware standpoint but also from a software standpoint. Issues such as ‘what exchange trade data can we give up to another exchange trade data’, and ‘how that data gets aggregated’. Considering the current environment, the future will be more about data aggregation and data processing, and getting that data in the hands of the right people than who will build the fastest server.”Read Full Post | Make a Comment ( None so far )
It took a while for Adam Afshar, one of the leading high-frequency traders featured in Edgar Perez’s The Speed Traders: An Insider’s Look at the New High-Frequency Trading Phenomenon That is Transforming the Investing World, to believe that the markets were more or less efficient under normal circumstances and to realize that the analysts at most firms provided no value and sometimes a negative value. He says, “My first attempt at using the computer was to build a system to help traders have better information faster to enable them or their portfolio managers to make better decisions, a sort of hybrid system where the computers are helping the humans. But, in less than a year, I realized that discretionary human participation in selection, portfolio management , or trading was so deleterious that no amount of computer power or intellectual algorithms could mitigate it.”
He adds: “It’s very important to stress this point because if the system allows human discretion at any level (idea generation, portfolio management, or trading) and your machine does not have the human discretionary elements modeled correctly in its learning algorithm (which we claim is not possible at this time), what you are left with is simply a quantitative trader that uses certain calculations to assist his or her trading. It becomes difficult or even impossible to assess whether the success or failure was due to the calculations, formula, or algorithms . Although we can argue on the pros and cons of humans as traders, we have to agree that this method is not and cannot be scientific. It is not scientific because it is not possible to backtest a model that allows any discretionary human intervention. For example, if you have computers that are generating trades, but the execution is done by humans, then we would argue that you cannot determine whether the success or failure of the system was due to its robust artificial intelligence or to a very good trader, and there is no way of testing and duplicating the results. Therefore, we would argue that any backtesting becomes essentially void.”
Hyde Park Global Investments, Afshar’s firm, is an investment and trading firm that has developed an artificial intelligence system built primarily on genetic algorithms and other evolutionary models to identify mispricings, arbitrage, and patterns for many electronic financial markets and the robotic platform to monetize the opportunities. The firm, which trades its own capital so far, potentially will accept investments from outside sources.Read Full Post | Make a Comment ( None so far )