We live in a brave new world: bombarded by news, data, and information from other sources, such as e-mail and social media. People cope with the volumes of data in different ways: some turn off e-mail after hours and on weekends, some ban selected channels like television (me!), still some take it all in. Dealing with increasing amounts of data has generated its own scientific category: Big Data. In investment and trading industries, the big data science becomes the Big Data Finance.

Big Data Finance is not ultra-new. Quantitative hedge funds have been using Big Data Finance since these large data sets became available. Sophisticated hedge fund brokers have been parsing data using Big Data Finance techniques to achieve optimal execution. Databases, data-processing tools, even high-frequency trading (HFT) are all manifestations of Big Data Finance that have now been around for a while semi-autonomously. Now, all the Big Data Finance techniques and trends are brought together and formalized in academia (see www.BigDataFinanceConference.com ).

Treating Big Data Finance as a science is important. For one, it is critical to separate legitimate methodologies for distilling valuable data signals from meaningless “spurious” noise derivations. Methodologies for advanced identification of information in reams of data—say, methodologies based on eigenvalue computations—help investors identify true signals in the drowning din of noise. Spurious signals are often a result of “data-mining” activity, otherwise known as “spaghetti principle” that is analogous to throwing a plate full of spaghetti onto a wall and seeing what sticks. Spurious derivations such as the ones obtained from thoughtless data mining can destabilize the markets.

At present, both meaningful and meaningless analyses can be practiced in large institutions and small ones alike, in part because the unifying science of Big Data Finance is still relatively new, and the quality controls of data analytics are still applied haphazardly. As the market participants increasingly transition to the quantitative data universe, if not by choice then by necessity, Big Data Finance will be de rigeur subject to know and to apply.

Irene Aldridge is an Industry Assistant Professor of Finance and Risk Engineering at New York University (Poly), as well as Managing Partner at ABLE Alpha Trading, LTD. Irene’s new book, High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems has been translated into several languages and is being published by Wiley in its second edition at the end of this month.

In the continuing series of discussing methods of trading the CBOE Volatility Index® (VIX®) futures contract traded on CBOE Futures Exchange, LLC (CFE®), this article will discuss utilizing the Commodity Channel Index (CCI).

In each article, readers are reminded that the liquidity of a trading instrument is always very important. On March 1, 2013, CFE again reported a continuing trend of increased volume in the VIX futures contract. Specifically, February 2013 was the second consecutive month that achieved record average daily volume, total volume and single-day volume for the VIX futures contract and for CFE.i

The average daily volume (ADV) for the VIX futures contract reached a record 161,176 contracts traded. This was an increase of 141% from February 2012 and an increase of 17% from January of 2013. February 25 and 26, 2013 experienced record volume days of 302,278 and 299,566 contracts traded respectively. This was also the first time that the VIX futures daily volume exceeded 300,000 contracts. The previously single-day record volume of 221,323 contracts was set on January 2, 2013. In February 2013, 3,062,344 VIX futures contracts were traded, representing an increase of 129% from February 2012. February 2013 trading represented a 6% increase from the record of 2,897,739 traded contracts set in January 2013. February 2013 was the sixth consecutive month in which trading exceeding two million VIX futures contracts and it was the first month in which trading exceeded 3 million VIX futures contracts.

The CCI was developed by Donald Lambert and introduced in the October 1980 issue of Commodities magazine (aka Futures magazine). Application of the CCI is not limited to physical commodities and may apply to financial instruments as well. The CCI is a metric of an investment’s variance from its statistical mean. The CCI reports high values when a market reaches an extended high price relative to its average price. It will report low values when a market reaches an extended low price relative to its average price. In basic terms, the CCI is an overbought/ oversold indicator.ii

The CCI is based on the premise that all markets have cycles from low to low or high to high. The CCI is calculated by calculating a typical price of the day from the high + low + close and then creating a simple moving average of the typical price. The final equation of the CCI = (typical price – moving average)/ (0.015* mean deviation). Lambert applies a constant of 0.015 to keep 70% to 80% of the CCI value between +100 and -100.iii

The CCI is considered overbought when the value exceeds +100 and is considered oversold when the value is below -100. However the CCI may extend beyond +100 and -100 and the market could remain overbought/ oversold for an extended period of time. If a market continues to remain overbought/ oversold, but the CCI is reversing (divergence appears) it may imply the market is nearing a correction. Some examples of divergence are provided in this article.

Parameters of the CCI are based on cyclical periods of the market. For this article we assumed a 60 day cycle, using a 20 day (1/3 of the cycle) CCI parameter setting. The lower the parameter setting, the greater the probability of the CCI to reach overbought/ oversold values.

Chart 1: Nearest Monthly VIX Futures Chart, 20 Month CCI

The fastest growing segment of the financial services industry was the one hardest hit by MF Global’s suspicious demise and overt fraud at Peregrine Financial Group (PFG).

The managed futures industry, which had grown from $14 billion under management in 1991 to over $329 billion to end 2012, was a shining star of the new economy. Offering the unique ability to zig when other investments zagged, the lack of correlation and performance during crisis were key points of attraction. This attraction came to a screeching halt with the MF Global and PFG criminal incidents. Not only were investors getting acquainted with the asset class shocked to learn their accounts were looted of assets, but more troubling criminal behavior appeared the cause - casting a shadow over all participants.

“There is a severe loss of trust, a loss of confidence. There is incredible anger and frustration. Things need to change,” said Diane Mix Birnberg, president of Horizon Cash Management. Her firm just released a study, The Aftermath of MF Global and Peregrine Financial Group Meltdowns: A Crisis of Trust, showing that a whopping 91% of respondents believed there was a breakdown in audit procedures.

The study themes that emerged included:

• The laws and rules that govern the industry need to have ‘teeth’ – and those involved in fraud and theft need to be punished.
• Customer segregated funds must either be kept completely out of the FCM and/or be verified in real-time by regulators.

A strong and rare female voice inside a Type A male dominated industry, Ms Birnberg’s firm, Horizon Cash Management, has become the top cash management firm for participants in the managed futures industry. Starting in the 1970s as a secretary in a stock brokerage firm in Atlanta, where “women generally didn’t think about career aspirations,” she later joined Lehman Brothers in the bond business. After moving to New York City to work on Wall Street, she was recruited in 1980 by investors to operate a cash management firm in the futures industry and in 1991 founded Horizon Cash Management, which currently has $2 billion under management.

In MF Global “there was very little institutional leadership (from exchanges, regulators and major firms),” she said. “This resulted in rumor, innuendo and ultimately a lack of trust. The void in leadership is terrifying.”

Looking back on the MF Global and PFG disasters, Ms. Birnberg has the experience of witnessing 10 FCM implosions. “In every FCM implosion it has negatively touched the CTA / CPO segment of the industry.”

“Think about a plane crash,” she said. “When it happens? Key issues and facts are addressed by the airline, the FAA and even the US president. Information is available regarding what happened, why it happened and steps being taken to address the problem.”

With MF Global a plane crashed and there was silence.

This is the first part of a two part article.

Mark Melin is author of three books and taught a managed futures course for Northwestern University’s Executive Education program. To read additional blog posts visit www.UncorrelatedInvestments.com (requires free registration).

The voluntary return of $546 million in MF Global customer assets, the subject of hard fought 2 ½ year battle, was not motivated solely by the kindness of JP Morgan.  Rather, it could be considered fruit from a likely hard investigation now gearing up if not already under way.  This investigation, declared “dead” many times over in leaks to the press from official sources, has heated up, as first discussed here.

The return of illegally transferred MF Global customer assets was always a key bone of contention.  JP Morgan had summarily dismissed regulatory and public pressure to return customer assets, so the question is: why submit to authority now?

In 2012 the National Futures Association (NFA) went so far as to send the bank a public letter, which was generally brushed aside as were numerous verbal requests and mounting public pressure from groups such as the Commodity Customer Collation and its leaders James Koutoulas and John Roe.  This significant pressure was dismissed, yet an attempt by bankruptcy trustee James Giddens was successful.  The fact this occurred at this moment in time is not a coincidence.

Speculation is JP Morgan’s normally dismissive attitude towards government regulators might have changed in the face of what is expected to be a no holds bar CFTC / DoJ criminal investigation.  In other words, the specter of government actually asserting itself and allowing career investigators to do their jobs unimpeded is enough motivation for JP Morgan to return what are documented to be illegally transferred customer assets.

But perhaps more important to the future, a real investigation could also be motivation for JP Morgan to provide critical testimony regarding the criminal activity of MF Global executives, including that of Jon Corzine.

The need for deterrence that derives from a Jon Corzine conviction is more important because the future that matters most.  Since 2008, when financial crimes that damaged the US financial system were was documented not to be investigated by DoJ’s former assistant attorney general in charge of criminal investigations Lanny Breuer, Wall Street crime has imploded in its brazen disregard.  MF Global is one example, but the case of HSBC laundering money for terrorist organizations and drug cartels – after being warned on several occasions not to do so – is a sign of complete disrespect and a breakdown of law and order on Wall Street.   When the full story is known, Mr. Corzine’s disrespect for the US financial system and its cogs of justice will likely stand as the turning point in a long battle.

Is this real?  Is the investigation a serious point where the rule of law might actually apply to once exempt Wall Street players?  We don’t know for certain at this point, but one key tell is going to be the type of charges filed against MF Global executives.  If RICO charges are used, this will send the powerful message that a cop is in fact back on the beat.

Mark Melin is author of three books and taught a course on managed futures for Northwestern University’s Executive Education program.  To read more of his blog posts, click here (requires free registration).  Contents Copyright (C) 2013 Mark Melin.

Although it hasn’t been written about nor formally discussed, understanding a managed futures investment from the standpoint of market environments and macro performance drivers first solves many problems for asset managers.

· It enables a quick description of the investment to provide the investor and understanding of how beta performance is generated

· Allows the asset manager to establish logical performance expectations in two sentences

· Sets up further structural analysis with performance measures relative to the strategy

· It enables logical strategic correlation consideration

· It explains how and why the investment operates

How Beta Performance Drivers Work

Each of the primary managed futures strategies have an environment in which they are expected to find success and relative failure.

For instance, several strategies are based on the market environment of price persistence.  These include trend following, breakout, momentum among the many similar named strategies.

Other strategies are based on the market environment of relative price divergence and then convergence back to a statistical mean.  These include relative value, arbitrage and strategies based on how pricing of one asset relates to a related asset.

Strategies based on the market environment of volatility utilize options and have a different set of considerations depending on the specific strategy type.

Describing The Investment

The first step in the analysis process is to identify this beta performance factor, which leads to an understanding of performance generation factors and can assist in setting expectations.  Using the market environment performance driver, an asset manager may describe the investment as such:

“This trend following program has a macro performance driver of price persistence.  It is expected to prosper when the price of a given asset moves in one consistent direction.”

In two sentences, the investor can set macro performance expectations when the investment should and should not work, as well as provide the core strategic logic as to why the investment is so uncorrelated to that of the stock market.

Performance Measures Relative to Strategy

Another reason to understand the performance driver concept is that the performance measures should be relative to each strategy.  For instance, trade time frame might be given a different weighting in a trend following program than certain volatility programs.  Expected margin to equity usage, win percentage and correlation to the equity markets during times of crisis are all examples of performance measures that are different relative to each strategy.

The important takeaway is with each performance driver, the relative alpha strategy considerations of the managers can vary.  Thus starting at the high level and working downward is most appropriate.

Mark Melin is author of three books, including High Performance Managed Futures, taught a course for Northwestern University’s executive education program and edits the web site www.Uncorrelated-Investements.com.  Entire contents Copyright (C) Mark Melin 2013

How does one define a previously un-definable topic such as High Frequency Trading (HFT)?

Sources close to the Commodity Futures Trading Commission (CFTC) indicate new thinking may be underway regarding the topic of High Frequency Trading (HFT). Speculation is this thinking could look at the relative market impact HFT may have in a given market move as a legal definition. Such a definition could consider the relative impact of a particular HFT player as a percentage of a market damaging move and could be used for potential CFTC action on the issue. This new thinking could be outlined sometime in March, sources said.

Current US regulation regarding HFT is considered by some market participants to be behind the curve relative to the European Union. In the EU, for instance, algorithm type is used as an identifier to determine market participant behavior during crisis conditions.

“There is significant uneasiness on the speed in markets,” noted Vassilis Vergotis, Executive Vice President, Head of Eurex, Americas.

For the full article, visit the source web site (requires free registration): http://www.uncorrelatedinvestments.com/blog/?p=59

Mark H. Melin is author of several books, including High Performance Managed Futures and taught on the topic at Northwestern University’s Executive Education program

In 2012 we discussed methods of trading the CBOE Volatility Index (VIX) futures contract at CBOE Futures Exchange, LLC (CFE). In this article, we will review the previously discussed trading methods and how to apply them to the current market environment.

Liquidity is an important factor for trading. Several times during 2012 VIX futures volume reached record levels including a record high of 2,734,248 contracts in November, Which was a 233% increase from November 2011’s 822,017 contracts and which broke the prior trading volume record set in October by 12%. In November the Average Daily Volume for VIX futures was 130,202, an increase of 233% from November 2011. To date, the November VIX futures total volume is 86% higher than it was in 2011 and year-to-date trading volume is 21,344,285 contracts versus 11,455,871 in 2011.i

In past articles we discussed the use of four VIX futures trading strategies: 1) utilizing support and resistance to seek contrarian changes at range bound extremes; 2) crossing of moving averages; 3) utilizing the Aroon Oscillator; and 4) using the True Range to trade VIX futures. In this article the parameters have been set to the same level as they were set in previous articles.

We begin discussing the support and resistance methodology. We originally discussed this in the September 2012 article “VIX Trading Strategies”. The VIX futures contract historically tends to find major price support between 10 and 15 and it finds major price resistance around 40 (with the exception of the financial crisis). As you will notice in the monthly chart below VIX futures tend to rally after forming a floor at or near a price of 15. This most recently occurred in 2010 and 2011. During the last several months, the VIX contract has once again found the price of 15 to be major price support area. Could this be the foundation of a floor for a rally in 2013?

Chart 1: Monthly Nearest VIX Futures Chart with Support and Resistance
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Copyright ©2012 Mark Shore. Contact the author for permission for republication at info@shorecapmgmt.com Mark Shore has more than 20 years of experience in the futures markets and managed futures, publishes research, consults on alternative investments and conducts educational workshops. www.shorecapmgmt.com

Mark Shore is also an Adjunct Professor at DePaul University’s Kellstadt Graduate School of Business in Chicago where he teaches a managed futures / global macro course and an Adjunct at the New York Institute of Finance.

Past performance is not necessarily indicative of future results.  There is risk of loss when investing in futures and options.  Always review a complete CTA disclosure document before investing in any Managed Futures program.  Managed futures can be a volatile and risky investment; only use appropriate risk capital; this investment is not for everyone.  The opinions expressed are solely those of the author and are only for educational purposes. Please talk to your financial advisor before making any investment decisions.

In the September 2012 newsletter, the article “VIX Trading Strategies” was the first in a series discussing various technical and quantitative trading strategies beginning with a simple moving average approach to trading the CBOE Volatility Index (VIX) VIX futures contract. This article discusses the use of the Aroon Oscillator.

The VIX futures contract tends to be mean-reverting, thus seeking overbought conditions is a logical approach to trading this market. As we noted in the previous article, VIX futures tends to trade between a major resistance near 40 and a major support of 10 to 15, and within that the market may trend.

Developing trading strategies involves the investigation of a market’s liquidity for various reasons, including the potential for slippage. On October 1, 2012, CBOE Futures Exchange, LLC (CFE) once again reported record volume in VIX futures. In September 2012 the Average Daily Volume reached a new record of 126,345 contracts versus the previous record of 102,587 contracts traded in June 2012. A new record was set in September 2012 of 2,400,552 contracts traded surpassing the previous record of 2,154,325 contracts traded in June 2012. i

For those not familiar with the Aroon Oscillator, it was developed by Tushar Chande in 1995. The oscillator first appeared in the September 1995 issue of Technical Analysis of Stocks and Commodities magazine. The word “Aroon” is Sanskrit for “dawn’s early light”, thus seeking changes in a market. The oscillator is the differential between the Aroon Up and the Aroon Down indicators which creates an oscillator indicating a market’s strength in a trading range.

It is defined as an oscillator because it ranges between READ MORE

Copyright ©2012 Mark Shore. Contact the author for permission for republication at info@shorecapmgmt.com Mark Shore has more than 20 years of experience in the futures markets and managed futures, publishes research, consults on alternative investments and conducts educational workshops. www.shorecapmgmt.com

Mark Shore is also an Adjunct Professor at DePaul University’s Kellstadt Graduate School of Business in Chicago where he teaches a managed futures / global macro course and an Adjunct at the New York Institute of Finance. Mark is a contributing writer to Reuters HedgeWorld.

Past performance is not necessarily indicative of future results.  There is risk of loss when investing in futures and options.  Always review a complete CTA disclosure document before investing in any Managed Futures program.  Managed futures can be a volatile and risky investment; only use appropriate risk capital; this investment is not for everyone.  The opinions expressed are solely those of the author and are only for educational purposes. Please talk to your financial advisor before making any investment decisions.

In the May 2012 newsletter article “Volatility Futures: Relative Strength: A Family of Futures Products”, we discussed various methods of trading volatility futures products as spreads or indicators, with some discussion of their basic characteristics.

This article will provide discussion of trading methods for individual volatility futures products. The CBOE Volatility Index® (VIX®) futures contract tends to be mean-reverting and trades within a range bound market.

Excluding the 2008 financial crisis, the VIX level tends to fluctuate between 40 and 10. For liquidity seeking traders, hedgers or managers, the chart below demonstrates the increasing volume and open interest in VIX futures, making it a viable choice for a liquid portfolio.

VIX futures trading volume recently reached a new high on three fronts:

1) In August 2012, the VIX futures average daily volume increased by 4.6% to 83,016 contracts versus August 2011 volume of 79,402 contracts.

2) The total volume year to date trading volume in VIX futures has increased by 59% to 13.7 million contracts versus January through August of 2011 volume of 8.6 million contracts.

3) On September 13, 2012 the VIX futures contract reached a new single-day volume record of 190,081 contracts traded. The previous record was 159,744 contracts traded on June 8, 2012.

In a range bound market, long term directional trading may not work as well as it would in other futures markets. Overbought and oversold indicators may have greater utility value. However in the shorter term (duration of days and weeks), directional trades may offer some value.

Read more

Copyright ©2012 Mark Shore. Contact the author for permission for republication at info@shorecapmgmt.com Mark Shore has more than 20 years of experience in the futures markets and managed futures, publishes research, consults on alternative investments and conducts educational workshops. www.shorecapmgmt.com

Mark Shore is also an Adjunct Professor at DePaul University’s Kellstadt Graduate School of Business in Chicago where he teaches a managed futures / global macro course and an Adjunct at the New York Institute of Finance. Mark is a contributing writer to CBOE’s Chicago Futures Exchange and to Reuters HedgeWorld.

Past performance is not necessarily indicative of future results.  There is risk of loss when investing in futures and options.  Always review a complete CTA disclosure document before investing in any Managed Futures program.  Managed futures can be a volatile and risky investment; only use appropriate risk capital; this investment is not for everyone.  The opinions expressed are solely those of the author and are only for educational purposes. Please talk to your financial advisor before making any investment decisions.

Opinions on high-frequency trading still run the gamut. On one end of the spectrum we find individuals such as like Mark Cuban, a successful Dallas-based businessman, who recently proclaimed that he is afraid of high-frequency traders. Mr. Cuban’s fears are based on his belief that high-frequency traders are nothing more than “hackers,” seeking to game the markets and take unfair advantage of systems and investors.

On the other extreme are employers in the financial services industry. Just open the “Jobs” page in “Money and Investment” section in The Wall Street Journal, and all you will find are job postings seeking talent with high-frequency trading experience for high-frequency trading roles. The advertising employers are the whitest shoe investment banks like Morgan Stanley. These careful firms invest resources only into something they deem worthwhile and legitimate. The extent of their hiring (the only hiring advertised in The Wall Street Journal) implies that the industry is enormously profitable and here to stay.

So, how can Mr. Cuban and Morgan Stanley have such divergent views of the high-frequency world? For one, Mr. Cuban has likely fallen prey to some unscrupulous uncompetitive financial services providers making a scapegoat out of high-frequency traders. Opponents of high-frequency traders identify a range of purported HFT strategies that are supposedly evidence
of how HFT destroys the markets. Supposedly malicious HFT strategies compiled by one of the workgroups of the CFTC’s Subcommittee on high-frequency trading included such ominous names as “spread scalping,” “market ignition,” and “sniping,” just to name a few.

As my upcoming HFT course in NYC (www.hftcourse.com) illustrates, most, if not all, of the HFT strategies thought to be malicious are simply not feasible on regulated exchanges (these same strategies may work in dark pools, however, non-regulated trading venues designed for sophisticated investors and operating under the “buyer beware” principle). Take, for example, the dangerous-sounding “spread-scalping” strategy, the mere name of which conjures images of shady characters in trench coats emerging from behind the pillars of an institution to hawk their wares.
Spread scalping is thought to be a strategy whereby the HFT trader “simply” places limit orders on both sides of the market and takes the spread, without providing any economic benefit to the markets.

Of course, as any seasoned market-maker will tell you, no strategy taking the spread is simple. In fact, associated risks are huge: 1) the trader posting limit orders may accumulate imbalanced inventory, resulting in sharp market losses due to adverse price movements; and 2) the trader
always risks ending up on the losing end of the trade, facing a trader better-informed about the market’s imminent direction.

In their normal state, markets are fraught with informational asymmetries, whereby some traders know more than the market-maker. Better-informed traders may have superior information about impending fundamentals or just superior forecasting skills. In such situations, better-informed traders are bound to leave the market-maker on the losing end of trades, erasing all other spread-scalping profits the market-maker may have accumulated.

For a specific example, consider a news announcement. Suppose a spread-scalping HFT has positions on both sides of the market, ahead of the impending announcement on the jobs figures – information on how many jobs were added or lost during the preceding month. A better-informed trader, whether of the low or high-frequency variety, may have forecasted with reasonable accuracy that the jobs number is likely to have increased. Suppose the better-informed trader next decides to bet on his forecast, sending a large market buy order to the market. The presumed spread-scalping market-maker then takes the opposite side of the
informed-trader’s order, selling large quantities in the market that is just about to rise considerably on the news announcement. In a matter of seconds, and due to activity of lower-frequency traders, our high-frequency market-maker may end up with a considerable loss in his
portfolio.

In summary, spread scalping may seem like a predatory strategy to some market participants, yet is hardly profitable in its most naïve incarnation. Spread-scalping enhanced with inventory and informational considerations is what most market participants call market-making, a legitimate activity that is the integral parts of market functionality. Without limit orders sitting on either side of the spread, traders desiring immediacy would not be capable of executing their market orders. Compensation of a spread is a tiny profit when compared to the amount of work required to be able to provide the limit orders on both sides of the market on the daily basis.

Similar analysis can be applied to a range of strategies considered to be adverse. Granted, some strategies are a direct result of market manipulation, and those, like “spoofing” outlawed under the Dodd-Frank act, should be screened for. Many other strategies thought to be malicious, however, are myths reflecting unease with technology experienced by some market participants. As HFTcourse.com shows, most high-frequency trading strategies are tried and true automated methods of traditionally human market making and short-term arbitrage functions.

Irene Aldridge is teaching courses on design and implementation of algorithms in Chicago (September 5 and 6, 2012) and New York (September 20 and 21, 2012). For more information and to register, please visit http://www.hftcourse.com today. She will also be speaking on a panel about algorithmic trading at HedgeWorld New York 2012, to be held Sept. 19 at the Metropolitan Club.