Big Data and the Art of Teasing Intelligible Answers from the Data Glut

This article first appeared on Markets Media Experts page on February 02, 2012.

The salient fact is that Big Data is messy. Financial practitioner’s worst fears are spending more time processing and cleaning data than analyzing it. The vast hordes of data demand a devotion to the collection and management of a multiplicity and diversity of markets across assets and continents.

Chris Pickles, BT’s Head of Industry Initiatives -Global Banking & Financial Markets recently commented at an industry round table on Big Data, “… market data is probably the biggest dump of data going into a bank’s dealing rooms.”

Yet Big Data extends well beyond infrastructure.  A more competitive trading environment, tighter spreads, thinner margins and a lower risk appetite results in quantitative traders exploring more cross asset trading models and cross asset hedging. The side effect of this is increasing demands for deep data over longer time periods across a multiplicity of markets; Equities, Futures, Options and of course cross-border currencies.

The challenge of this data dump is dealing with the vagaries of multiple data sources, mapping ticker symbols across a global universe, tying indices to their constituents, tick-level granularity, ingesting cancelations and corrections, inserting corporation action price and symbol changes and detecting (missing) gaps in history. Any and all of these factors are vital to the science of quantitative trade modeling.  Big Data is about linking disparate data sets under some common thread to tease out an intelligible answer, a diamond from a mountain of coal. It’s about finding the cross asset correlations or understanding how to best hedge a position to offset risk, these are the underpinnings for trade models and portfolio management.

It is vital to recognize that data volumes can quickly overwhelm the capacity to consume and the resulting problems are manifold.  On one hand is the technology, poorly designed or legacy systems can easily translate to spending inordinate amounts of time and resources processing data, outfitting new storage and scrambling to deploy new systems to meet the rising velocity. On the other is the demand placed on the human intellect. The ‘search and (alpha) discovery’ of Big Data is to artfully leverage the mathematical and statistical sciences in a timely manner.

Big data IT is about managing scale. With 4.55B contracts traded in 2011 the Options markets, volume and velocity place enormous demands on IT infrastructure. The need for Big Data technology capable to swallow in big gulps is evident to cope with the information flood as more and more firms engage in cross asset trading. Not just for consumption of Options strikes but with the underlying Equities and the Futures and Foreign Exchange markets as well, which at last count was the world’s largest and most liquid market with average daily turnover exceeding 4 trillion dollars. But data cannot be seen as just a tech issue.

Big Data is a daunting task placed on human capital. Finding useful information in oceans of data is an increasingly complex problem. Big data is about big analytics. There is a clear and present danger of the inherent wisdom being lost in the darkness and noise as data accumulates in floods. A clear thread has to be teased from the veritable sea of information, to focus, direct and ultimately give meaning to what has been amassed. Whether its research for discovery of new models or backtesting to prove profitability, the skill to recognize the influencers of market impact, its inherent volatility need to be factored in. The quest to devise smarter models is what analysis is for. Yet ultimately to make sense of the analysis, deciding what to prune and knowing what to embrace is crucial for enabling you to make timely business decisions. It’s a matter of survival in the fiercely competitive trading landscape.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

Big Data in Finance, the Explosive Growth of the Options Market

This article first appeared at the launch of the Big DataforFinance site from the A-Team Group.

Trading volume for U.S. listed options totaled about 4.55 billion contracts in 2011 while OPRA’s message volume has been steadily increasing at an annual rate around 40%. To say that the options market is all about Big Data is like noting that Mount Everest is all about snow. It states the obvious but also the ominous. On a human scale, you cannot consume or make sense of what’s inside that avalanche of data without the right technology and analysis any more than you can climb to Everest’s peak without the right gear.  Big Data is the core, Big Data is the catalyst.

US equity options volume is expected to double over the next 12 months.  Increased demand is a big driver of growth but the expected acceleration is due to a number of factors. Two such drivers are the advent of new products and new venues such as the CBOE’s all-electronic C2 Options Exchange which saw a steady 18% year over year growth.

Another booming area is the CBOE’s short-expiration Weekly options products on more than 30 different classes of the most active stocks, indexes and ETFs. These products with rapidly changing deltas can move in the money with short notice causing their trade volume to spike dramatically. Volume on those Weekly’s accounted for up to 11% of their underlying index volume in the second half of 2011.

VIX-based options have also been a big hit, with a total of 8.5 million VIX options contracts traded in June. The CBOE SKEW Index measuring the S&P 500 out-of-the-money options spiked in early spring 2011 highlighting a greater demand for these outliers. And of course the increased growth is due to more and more strikes in all underlying assets.

The use and proliferation of options has seen explosive growth as a strategic investment tool for more sophisticated hedging, portfolio management and for additional leverage on the performance of the underlier.

The incredible growth of the options market is undeniable.  Today’s options market represents the quintessential example of Big Data in Finance. Big Data is a trendy new catch phrase in business today, but nailing down an exact definition proves to be rather elusive. This is likely because the term has largely been associated with loosely structured content, originating from web search companies and social media. For the financial industry, the need for reliability and accuracy is what distinguishes social Big Data from financial Big Data.

Gleaning meaningful value from unstructured and social content is to judge sentiment, the mood of the human psyche portraying an emotion from the voices of millions. Any one or group of data points in the analysis cannot necessarily be valued as accurate or inaccurate only the determinants in behaviors.  Any loss is of minor importance because analysis is looking for mood shifts on the order of a turning ocean liner. In fact, the science of social data involves not what to keep, but what to throw away.

In finance, data accuracy is vital to determining outcomes.  Asset prices cannot be inaccurate or missing and they must be adjusted for any corporate actions such as stock splits. The reliability of resulting analytics such as implied volatility, delta and gamma calculations for option strategies and portfolio re-balancing depend on them.

The infrastructure technology for the options market has also become specialized to cope with the fire hose volumes and very large capacity storage of Big Data.  As we see more volume and market data flow across the OPRA feeds, we can expect that additional flow will lead to greater message traffic entering the market place as orders and executions. The increased throughput will burden older technology in an attempt to handle the load. Firms will realize it is not simply a matter of buying new versions of old technology to keep up with the problems of throughput.

I’ve occasionally heard the comment that the open source platform Hadoop defines Big Data. To say that any technology defines Big Data is an obvious case of the tail wagging the dog.  It’s the demands around industry use cases that create and foster technological innovation. That’s what drove the creation of Hadoop. Hadoop is a nascent technology that resulted from the desire to obtain analytical value from the vast amount of social data. It is not optimal for the volumes and speeds of high frequency financial data.

For the algorithmic world, direct exchange feeds for Options are becoming more desirable for their depth of book and lower latency along with greater use of real-time analytics. Option premiums are manufactured from two main ingredients: intrinsic and time value and the measure of how much money we should make factoring in the implied volatility. The Weekly’s short-expiration implies option strategies can respond to news announcements such as an earnings report in a make or break fashion. The underliers reaction to the news can signal an immediate move to take a profit or stop a loss. Big Data analytics is a defining characteristic of options market data and the wealth of analysis far exceeds all other asset classes.

Big Data will become de facto terminology in the coming year. Understanding its definition for finance is vitally important since the explosive growth of the options market is likely to continue unabated.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

Regulatory Actions and Defining HFT

“Groups of people are generally not nearly as moved by rational argument as by rhetoric which stirs the emotions.”

When a definition is elusive, more subjective in nature than objective should that not dictate more discretion and a rational approach to achieve a goal?  When the CFTC’s Scott O’Malia set out to define high frequency trading through a seven-part test, definition was not his objective but simply a means to an end.  That end was a lever to enable further regulatory action in the coming New Year.

Speaking of regulation, SIFMA recently published a year-end study, The Impact of HFT where they mention the difficulty in creating a clear-cut definition. HFT does not neatly fit into any one well-defined bucket, but like so much of trading belongs to an overall categorization. A style trading that… a) leverages computer technology, b) makes use of algorithmic market making, arbitrage and directional strategies, c) limits human intervention.   Numerous buy-side, sell-side and quant firms fit into this categorization.

SIFMA’s Impact study does a nice job of summarizing the year’s regulatory actions. All those actions were designed to reduce uncertainty and the resulting risk premium in the market. A rippling backlash we’re still feeling 18 months later from the flash crash.  Here are my ‘most important’ from last year and for the next year.

Most important regulatory action of the year:

The Market Access Rule.  A euphemism for the Naked Access ban, this rule broke the unfairness certain participants were able to achieve in bypassing Broker pre-trade risk validation.  Those extra few milliseconds (or even microseconds) meant an edge for quoting or capturing a trade. Besides the fairness implied by the ban, instituting this rule has had a number of positive side-effects; a) it minimizes the possibility of a rogue algo wreaking havoc.  Here’s a prediction for the New Year. There will be no billion dollar rogue algo, and any such rhetoric is journalistic sensationalism solely for the back pages of the New York Post. The Market Access Rule for Brokers, Exchange monitored risk checks and the multitude of watchful counterparties will prevent anything but minor Infinium Capital style skirmishes from occurring. The embarrassing public hand slap they received will ensure firms will beef up their own testing before deployment. Any additional proposed regulations for algos (i.e. controls and/or source code inspection) are unnecessary. b)  Increased adoption of hardware acceleration in trading infrastructure.  On one hand, the Market Access Rule has leveled the playing field so-to-speak. The requirement that all orders run through the same (regulatory-defined) series of risk checks eliminates the advantage of Naked Access. That was a benefit to both trading firms that could afford the privilege and for Brokers marketing an attractive option in an effort to garner additional client order flow.  Poof, that disappeared overnight.  Well aware of the consequences, Brokers have rushed to hardware acceleration for pre-trade risk checks engendering a new (regulation-ascribed) low-latency battleground. Witness the announcements from  Morgan Stanley,  Bank of America and Deutsche Bank earlier in the year.  We’re not done yet, more to come in 2012.

Biggest regulatory concerns moving into next year:

1) Increased transitory volatility. There is no denying the turbulent markets are whipping up a frenzy of finger pointing. Who or what is at fault? The tumult of the market volatility has been blamed on numerous scapegoats including HFT and the human emotional response to bad news from European sovereign debt to Washington political divisiveness.  One of the side effects of present day communication technology is our ability to react to news from around the global moments after events happen. Smart phones, social media and news-based algo strategies have only extended and exacerbated this phenomena.  Volatility is not likely to ebb in the coming year; whipsawing markets are to be the new norm. Managing them is the solution so they do not run out of control. The SEC proposed Limit Up/Limit down price collars will offer protection against extreme volatility through a 5 minute pause in trading contingent upon the market’s reaction to the up/down rule’s ability to stabilize contra-side liquidity.  This is a more complex definition of the existing single-stock circuit breakers, but likely an improvement that will mitigate larger volatility swings and will have a wider calming effect.

2) Defining Market Maker obligations. I suspect there are few things that create fear and loathing for regulators as much as the difficulty in solving obligations for liquidity provisioning.  Regulators have to eventually face this difficult issue. Avoidance which has been the order of the day for the past year is not a permanent choice. HF Traders and other liquidity provisioning firms have no market obligation other than to their own bottom line. A liquidity drought is the fuel that can ignite another flash crash. Incentive mechanisms similar to the exchange rebates or amicable regulations to keep these participants in market during stressed market conditions are long in coming. However, this is not an easy problem to solve with a good chance of backfiring. Firms could simply move to more regulation friendly markets in other parts of the globe. Resulting in thinner liquidity and creating the very drought-like conditions regulators want to avoid.

The FIA Principal Traders Group (PTG) recently posted a response to Mr. O’Malia’s HFT definition.  They took issue with nebulous terms; such as “high” and “numerous” as in the statement: “The submission of numerous orders …”. Similar to SIFMA’s argument, trying to objectively define a subjective category is arbitrary. Doing so will simply result in numerous exceptions to the rule once you apply test cases to determine the validity of the definition.  The PTG present a rational argument to take advantage of existing regulatory controls, put in practice proposed rules and leverage audit trail surveillance systems.

Both SIFMA and the PTG appeal to reason with an argument devoid of emotional rhetoric, presenting a rational approach to the task of conquering market uncertainty.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

The Technology Imperative Behind What Drives Alpha

Wisdom is knowing what to do next, skill is knowing how to do it, and virtue is doing it.

-David Starr Jordan, Past-president of both Indiana University and Stanford University

This past week I attended the Quant Invest conference, a show targeting quantitative trading, risk management and regulation. I moderated a technology-focused panel with a distinguished cast from numerous quant trading firms.  In our conversation we explored the challenging choices those founders and managing partners faced on their road to success.

When it comes to a firm’s technology decisions there is always the overarching question… What do we buy vs. what do we build? How do we determine the cost benefit model of that decision?  In lightning fast markets with razor thin margins how do you prioritize a business strategy? Is it time to market, tooling for fast strategy development, a need for low-latency, global market connectivity, highly available and disaster recovery?  Looking at the entirety of the trade lifecycle from the tools to research new trading ideas all the way to post trade clearing there are so many moving parts that firms have to be extremely careful to keep their eye on the ball. You’re in the money business, not the software business. But this is not so easily recognized.

Reports from the Hedge Fund industry show an odd mix of statistics. On one hand the industry is booming, in the first quarter of 2011 and even back into 2010 there has been a sharp increase in the number of new fund start-up’s. Over 300 new funds opened their doors.  With so many layoffs from the big investment banks figuring out what many of those money managers decided to do next is not too difficult. Yet those same Hedge Fund stats reveal another trend, that in January thru March almost 200 funds closed down business.  As quick as a new fund opens another one dies on the vine. They are likely failing to achieve returns above the broader market, but is there also a hidden corollary?

The dynamics and scope of running a successful fund extend far beyond the prop trading desk at any bank.  There is a dual challenge to grapple with, managing the investment capital and the deployment of a wide range of automation technology to enable that success. Within a fund or prop shop there is no army of IT staff managing the pipes and trading infrastructure as found at those banks many left behind.

The increasing prevalence of automation and rapid-fire trading technologies has increased competition. Sophisticated algorithmic strategies have become the hunter and all else the hunted. Unfortunately the statistics bear-out that many firms are ill equipped to rise to the challenge.

Automation and the technology behind it play a critical role in the trade lifecycle. Its evolution goes hand-in-hand with innovations in trading. Knowing the right blend of build vs. buy is as big a key to success as the profitability of the deployed strategies.  Misguided development choices can often lead to costly overrun projects, leading you astray from the things that matter most, what drives alpha.

For those firms on my panel the dilemma of build vs. buy was put to the test. Most sought to achieve a fast time to market, leverage what they knew - that internal intellectual property (IP) and farm-out the rest goal. Strategy design and development in traditional languages such as C++ was the convention with vendors and brokers supplied the remaining functions; a) Tools for alpha discovery and quantitative research. b) EMS/OMS functionality c) Connectivity for market data/trade execution d) Services for post trade clearing and TCA.  One brave and daring quant fund however chose to build their entire trade platform in-house including their own custom TCP/IP stack.

Nonetheless, having a sound technology strategy is of critical importance. Knowing your priorities and defining a technology decision matrix will depend on what you aim to achieve, your trading style and internal core competencies.   In any case being smart about your technology decisions is a means to be smarter about your trading. Investing your intellectual property of human capital towards the primary goal of finding alpha can mean the difference between success and being a part of those failure statistics.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

Regulatory Ambivalence

Such were the stakes in the battles of the Persians over Greece. The development of freedom and self-government hung in the balance. So it is that, as another essayist has said, “A little of Leonidas lies in the fact that I can go where I like and write what I like.”

- Chris Stewart and Ted Stewart, The Miracle of Freedom: Seven Tipping Points That Saved the World

Over the last 3,000 years there have been numerous inflection points that have set humankind on the steady march towards the liberties and freedom most of us take for granted. Chris and Ted Stewart, authors of The Miracle of Freedom wrote of seven historic tipping points, in each they saw the portent of a new age redefining and elevating individual liberties and justice. Those decisive events were plights that span victories in battle to the preservation of the collective intelligence from barbarous hordes, each one a stepping stone in the struggle against tyranny. One could debate that there certainly have been more than seven that shaped our present day sense of self-determination. Yet the author’s goal was not to describe all such cases, but to show how the conflicts precariously hung in the balance and succeeded only by a slim margin or a stroke of luck. And all too often the norm was tyranny and injustice and despots the ruling hand across most of the last three millennia.

Global regulators are once again under pressure to provide an explanation of the whipsaw volatility in the equity markets. There is growing vexation among traders and investors. The lack of confidence in the equity markets throughout much of 2011 can be seen in lower traded volumes. Regulators are looking to better understand the role played by high-frequency traders in the volatility. The U.S Congress and European parliaments have stepped in under political pressure and are looking to legislate through taxation. The proponents argue that it would slow down or eliminate high-frequency trading by wiping out their profit margins. The analyst firm Rosenblatt Securities estimates that HFT firms make about 1/20 of a penny per transaction. A 0.03% tax would destroy any chance of a profit, worse as Dennis Dick from Bright Trading describes it would hit quant-firms as well, those investing in technology and people and are not necessarily looking at ultra-low latency arb. Such legislation is a fool’s errand driven by the desire to find a convenient scapegoat.

Attempts to legislate presumed fairness will ultimately result in a loss of freedom for all. Scapegoating high-frequency trading will undoubtedly lead to more controls to the detriment of all market participants, exacerbating the vexations and market uncertainty regulators ultimately aim to end. Since the industrial revolution, segments of society have had an irrational fear of technology (i.e. luddites). Technological advancements have always been a double edged sword providing undeniable benefits for many and the end of a way of life for others.  Yet advances in trading styles have shown to have a positive impact. This is not to say, there are not a few bad actors. There have always been those focused on market manipulation long before the advent of high performance computer technology. But Black Monday didn’t lead to computers being banned and HFTs aren’t likely to go anywhere either despite political pressure to the contrary.

Regulators have to improve their understanding of market microstructures, the impact of algorithmic and high frequency trading in particular to introduce reasonable regulations. It’s been a year and a half since the well-publicized flash crash revealed the fragility of market structures. Since that time we have had restrictions (no more stub quotes) and price collars put in place to contain the outbreak of another one. There are countless academic papers on the subject as well. Yet one key contribution that could instill investor confidence is the deployment of the consolidated audit trail (CAT). Yet there appears to be little if any advancement towards that goal. Regulators seem to be ambivalent, or are they just proceeding cautiously?  Are they now distracted by the budgetary season as Congress looks for places to reduce deficits? Are the SEC and CFTC looking to safeguard
their base just when they should be ramping up on implementing reforms? The investment community wants definitive action. John Plender, mentions in a Financial Times article the need for a ‘regulatory verdict’ to once and for all determine if algo traders are manipulating prices creating toxic liquidity in the Lit Pools. Toxicity is not only in liquidity but in attitudes towards trading styles. The CAT could provide the needed granularity for surveilling and identifying market integrity issues. The scale and magnitude of the project is obvious, yet there is always that small first step.

Volatility is an irrational behavior; explanations for the whipsawing moves are levied on leveraged ETFs to fears over the European debt. The markets won’t accept irrational outcomes, such uncertainty creates a risk premium keeping the investment community sitting on the sidelines, as can be seen in the decrease in equity volumes and consequently contributing to a stalled economy. But the anxiety that manifests itself in the markets is really structural deficiencies in the overall economy and government divisiveness. The inaction and lack of leadership in Washington has resulted in a vilification of Wall Street. And that is not likely to end until the economy comes back. But we won’t see an economic turnaround until the courageous step forward to bridge the divide in Washington. As Thomas Friedman once said, leadership is hostage to its own ineptitude. A bread and circuses style of appeasement through legislative controls under the guise of fairness will continue to be proposed further tightening the reins.

In the book, The Miracle of Freedom, the authors conclude with a conversation about ‘this thing‘. Not something tangible, but a thought, a belief in something so precious to many but often overlooked by those born into it:

“… the Russian gestured again to the wonder all around him: the pleasant home; the constant flow of clean water; the dependable source of energy; the cars; the free press; the ability of the citizens to trust though they may not agree with the outcome., their elections were free and fair; the fact that one did not need to be a member of a certain party , or not be a member of certain religion, in order to avoid persecution; the fact that Americans did not fear a knock on the door at midnight; the fact that most Americans had great hopes for their children and their future – these are what the Russian officer meant by this thing.”

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

OneTick is awarded Best Buy-Side CEP Product

The cornerstone of any product is recognizing the right mix of technology that provides the capabilities and features that resonant with the market and fit the needs of customer’s requirements like a hand in a glove. Over the course of the past year OneMarketData’s resonating validation of this has been the public announcement of numerous client wins including large firms like the hedge fund Tudor Investments and global investment banks the likes of Société Générale. But also smaller firms like the startup fund Galium Capital and the new Options exchange Miami International. Additionally numerous universities are using the OneTick product in their financial engineering curriculum for their faculty and graduate research studies. Yet this is just the tip of the iceberg in what is shaping up to be a banner year culminated by the Buy-Side Technology award for Best Complex Event Processing (CEP) product.

The judging criterion for this award is to outline the essential characteristics, achievements and innovation that place the product ahead of the competition. OneTick is technology designed solely to serve the financial industry as an integrated solution, a single source for tick data management and analytics that spans the past, the present and future for historical and real-time marketdata. One that  stretches out across the well-known assets classes of equities, futures & options, commodities and currencies but also a platform that can dig deep into the esoteric; treasures, mortgaged backed securities and sovereign bonds just to name a few.

Financial data is the quintessential definition of Big Data. But without a doubt the most important aspect is accuracy. Mid-year, 2011 we launched the big data product OneQuantData. Leveraging the OneTick high performance database, OneQuantData is designed for trade modeling, beta indicators, mark-to-market calculations and numerous other use cases where the value of clean and accurate closing prices and reference data is imperative for quantitative research and portfolio management. Pushing the limits of creative innovation for real-time analytics, high performance capture & query and accurate reference data yields an award winning combination.

Recent predictions from industry groups are expecting U.S. equity options volume to double over the next 12 months.  The Options Market Reporting Authority otherwise known as OPRA has seen data volumes on a steady annual increase of nearly 40%, peaking at 1.5 million messages per second at year end 2010.  The advent of new Options products and new Exchanges such as Miami International Securities Exchange (MIAX) will push the boundaries of technology. It’s imperative for exchanges and trading firms, even retail venues such as Scottrade to partner with the right vendors like OneTick who have developed effective high-performing technology to handle the fire-hose of market data that is the Options market.

Focused on providing buy-side and sell-side customers with the best solutions to meet their high frequency & quantitative trading and risk management needs, OneTick provides a single solution that:

a) crosses all asset classes
b) is an encompassing technology platform for trade decision modeling and costing analysis blending historic and real-time prices and execution data
c) provides a fully integrated Big Data repository of accurate closing prices and reference data

OneMarketData provides customers with the tools, technology and data to leverage their own creative innovation and human capital.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

Scottrade Goes Full Thottle with OneTick

Some firms just understand the notion of Full Throttle. When your view is global across the Equities and Options markets you’re talking about hundreds of thousands of instrument names and millions of messages. Options trading is on a record pace to reach 4.2 billion contracts in 2011. This massive volume of Big Data pushes the boundaries of ordinary technology and it has become increasingly vital for firms to recognize vendor solutions that can race to the front in this full throttle world.

Scottrade Inc. a premiere on-line investment firm, retail brokerage and a household name in online trading has chosen OneTick the leading tick data management solution to power their award-winning trading platform. Scottrade offers online investing in stocks, options, mutual funds, IRAs, fixed income and a whole lot more.  Onetick’s high performance tick database and integrated Complex Event Processing (CEP) engine blend historical and real-time market data for maximum speed and functionality. Combined with a large library of high-precision time series analytics proving time and again why firms such as Scottrade chose OneTick.  The trading lifecyle begins and ends with data, that includes historical data, live market data and corporate action reference data.  With OneTick’s ability to capture, store, reference and analyze markets, firms can devote valuable time and resources to research and trading tasks and not processing and programming.   OneTick is a solution rooted in the blending of high-performance historical database and real-time Complex Event Processing. These two paradigms fused together provide the basis for next-generation quantative research and trade decision modeling.

Tis the season for racing and its Full Throttle with OneTick.  To learn more why Scottrade and other major firms like Tudor Investments, Société Générale, and countless brokers, investment banks, hedge funds, prop shops and market places have chosen OneTick. Download one of our many webinars, whitepapers or watch a short video introduction.

OneTick is an enterprise solution capable of capturing, storing and analysing market data across any asset class even the massive OPRA feed for conducting research, strategy backtesting, building trading solutions and conducting transaction costing and slippage analysis whether against individual instruments, indices or whole portfolios.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Market you can follow me on  twitter, here.