Archives for September, 2010

The Russians Are Coming

September 30th, 2010

A major Russian prime brokerage is expanding its UK client base at a rapid rate, giving impetus to the view that emerging markets like Russia will continue to see unabated growth.  The brokerage, Otkritie Securities, owned by one of Russia’s largest banking companies, announced plans this week to double the number of hedge fund clients before the year ends.

Roman Lohov, chief of global markets and investment banking at Otkritie Bank and CEO of Otkritie Securities, acknowledged his firm has a queue of potential customers that will see the bank’s UK clientele increase from around 40 to 100 by 2011. Hedge fund assets in the company’s custody operation are also anticipated to double to $2bn within the same time period.

“We are building serious traction in Europe and expect to make rapid progress in the coming months,” Lokhov declared. “Our aim is to be the leading prime broker for emerging market hedge funds in the world.”

Otkritie is based in Moscow and London, and began its prime brokerage business only 12 months ago. It now has a complete prime brokerage operation in the UK, US, Russia and Scandinavia, and also provides execution services in several of the world’s emerging territories, including Turkey, Brazil, and the CIS. An execution service in India is slated to go live this October.

The firm has seized on recent opportunities, such as acquiring three of Russia’s crisis-plagued banks in a merger scheduled for October. It is continuing its ongoing aggressive hiring campaign and recently added a team of researchers from Credit Suisse Russia.

The emerging market’s growth has been boosted by excellent performance in Russia and Latin America.  Fund managers have taken note and are planning to capitalize on the industry growth. Only last week, Brevan Howard, one of Europe’s largest hedge funds, made public plans to initiate a new office in São Paulo, Brazil.

Source

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Traders at JPMorgan Doing the Sideways Shuffle

September 29th, 2010

JPMorgan Chase has created a new unit for alternative investments that will be a part of its asset management division. Proprietary traders for the investment bank are being transferred to the new unit.

This move is part of the continued fallout from this year’s financial reform legislation. Investments banks are expediting the demise of their proprietary trading operations, which will soon be forbidden under the newly-enacted bank regulations in the U.S. In contrast to prime broker Goldman Sachs’ decision to shut down its proprietary desks, JPMorgan will relocate its traders for equity, emerging markets and structured credit to the new alternatives unit. The traders will no longer manage money for the bank itself – they will focus exclusively on outside clients.

Dealbraker .com reports the following quote from an internal memo from Mary Erdoes, CEO of JPMorgan Asset Management: “Colleagues who will transition have delivered strong risk-adjusted returns for the firm, and we are confident that clients will benefit from their investment experience and insight,”

Erdoes will supervise the proprietary traders moving to the new unit. The transition, headed by co-head of global emerging markets Mike Stewart, will take a number of years, Erdoes and Jes Staley, CEO of JPMorgan’s investment banking unit, said.

Stewart, who will lead the new unit, is also working with Larry Unrein, who heads JPMorgan Asset Management’s hedge fund and private equity operations, to establish it. Stewart will remain in his current post through the end of the year.

Source

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TradeStation’s NYSE Floor Operation Implements Buy-Side Institutional Program

September 28th, 2010

Service Focuses on Floor Broker Parity and Transaction Pricing

New York, NY, September 28, 2010 – TradeStation Securities, Inc. (Member NYSE, FINRA, NFA and SIPC), through its TradeStation Prime Services division, recently launched its NYSE Floor operation, including its outsourced trading desk, to help meet the growing demand of hedge funds and other institutional clients who seek to enhance their transaction pricing while providing additional liquidity. The NYSE trading floor features a parity based model when allocating executions allowing market participants to operate a diverse strategy mix including both classic institutional order flow and higher frequency models.

As described by NYSE Euronext on its website, “The NYSE is the only market to offer both high-tech automation for low latency and complete anonymity along with high-touch participation by market professionals to provide orderly opens and closes, lower volatility, deeper liquidity and price improvement opportunities throughout the trading day. This unique combination provides customers with the highest levels of market quality and competitiveness… Brokers on the NYSE Trading Floor leverage their physical point-of sale-presence with information technologies and order management tools to offer customers the benefits of flexibility, judgment, automation and anonymity with minimal market impact.”

As a self-clearing, agency-only broker-dealer now with NYSE Floor capabilities, TradeStation can leverage this technology and its membership by offering, through their Floor Brokers, access to the NYSE Floor along with over 40 pools of liquidity away from NYSE. Active traders, including spread traders and derivatives traders can also integrate their trading strategies into algorithms that Floor Brokers access from their Hand Held Devices that are engineered specifically for the NYSE parity based model.

For additional information about TradeStation Prime Services, please visit: http://www.tradestationprime.com/.

About TradeStation Prime Services, a division of TradeStation Securities, Inc.

TradeStation Prime Services, a division of TradeStation Securities, Inc., was founded to serve the needs of start-up to mid-sized hedge funds, registered investment advisers, professional traders and asset managers who need quality prime brokerage services, including execution and clearance, securities lending, capital introduction, and “incubation” services. Clients are offered electronic trading and decision-support platforms, including TradeStation, to analyze their trading strategies and automate or manually place their orders, and may avail themselves of the firm’s NYSE floor membership, which allows it to execute trades on behalf of clients on the NYSE floor as well as in other market centers from its NYSE floor booth/outsourced trading desk. TradeStation Prime Services is located at 400 Madison Avenue, New York, New York.

TradeStation Securities, Inc. (Member NYSE, FINRA, NFA and SIPC) is a licensed, self-clearing securities broker-dealer and a registered omnibus-clearing futures commission merchant, and has memberships or similar approved status (as well as direct connectivity for both market data and order execution) with BATS Z-Exchange, Boston Options Exchange, Chicago Board Options Exchange, Chicago Stock Exchange, EDGA Exchange, EDGX Exchange, International Securities Exchange, NASDAQ OMX BX, NASDAQ OMX PHLX, The NASDAQ Stock Market, NYSE Arca and NYSE Amex. For futures accounts, TradeStation connects directly (for both market data and order execution) with the CME Group, Eurex Group and ICE Group (U.S. and Europe) exchanges. TradeStation is a clearance member with DTCC and OCC for equities and options, serves its futures accounts on an omnibus clearance basis, and also introduces institutional equities accounts to J. P. Morgan Clearing Corp., as clearance agent. TradeStation Securities has offices in South Florida, New York, Chicago and Dallas, and an affiliated introducing broker (TradeStation Europe Limited) in London.

About TradeStation Group, Inc.

TradeStation Group, Inc. (NASDAQ GS: TRAD), through its principal operating subsidiary, TradeStation Securities, Inc., offers the TradeStation platform to the active trader and certain institutional trader markets. TradeStation is an electronic trading platform that offers state-of-the-art electronic order execution and enables clients to design, test, optimize, monitor and automate their own custom Equities, Options, Futures and Forex trading strategies. TradeStation Group’s other operating subsidiaries are TradeStation Technologies, Inc. and TradeStation Europe Limited.

Nature of this Announcement

This announcement is made on a limited basis through hedge fund and other institutional trader websites and similar media for promotional/marketing purposes, to educate potential customers of TradeStation Prime Services about its product and service offerings, and is not intended to be an investor relations or public disclosure document for TradeStation’s publicly-traded holding company (TradeStation Group, Inc.).

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Financial Statistics (6) – The Coefficient of Determination

September 27th, 2010

- Eric Bank

Determination

As we pointed out in our discussion of the standard error of estimate, it would be nice to know how well the independent variable X explains variation in the dependent variable Y. To calculate the fraction of the total variation in the dependent variable that is explained by the independent variable, one uses the coefficient of determination (R2).

There are two ways to calculate R2. The easier method involves squaring the correlation coefficient for a linear regression with a single independent variable. Recall from a previous blog that the correlation coefficient, r, is equal to the covariance of the two variables divided by the product of their standard deviations (sxsy).  (We pointed out that covariance measures the extent to which two variables (X, Y) change together).   The formula for the correlation coefficient is:

r  = Cov(X, Y) / sxsy.

We square it, giving us R2 as the coefficient of determination. However, this doesn’t work when we are dealing with more than one independent variable (X).

The alternate calculation of R2 for multiple independent variables is to use the following definition:

Total variation = Unexplained variation + Explained variation

Since R2 stands for the fraction of the total variation that is explained by a linear regression, we get this solution:

R2 = Explained Variation/Total Variation = 1 – (Unexplained Variation / Total Variation)

There is one more alternative for calculating R2 . Linear regression packages typically report a statistic called multiple R, which is the correlation between actual Y values and predicted Y values.  R2 is the square of multiple R.

As an example, let’s take the results from a hypothetical multiple regression which regresses inflation rate on money supply growth rate for several different countries over a particular period of time. We calculate the following results:

Given that

  • total variation is the sum of the squared deviations (Yi – Yavg)2 = 0.001598
  • the unexplained variation is 0.000386

the value for R2 is (0.001598 – 0.000386) / 0.001598 = 0.7586.

Now when you inspect the generated results from a linear regression, you’ll have an understanding of the reported R2 statistic, and can judge the meaningfulness of the predicted Y values.

We are making great progress with our review of elementary financial statistics. Next time, we’ll look at analysis of variance (ANOVA) and the F-test.

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Mortgage-Backed Securities Calculations

September 24th, 2010

There are several calculations specific to amortizing fixed-income securities such as MBS. We assume a fixed mortgage rate in the following examples.

Mortgage Interest Income Component

The interest component of a mortgage payment is P&L income. A monthly mortgage payment’s interest component can be calculated as follows:

Calculation:

For most mortgage-related securities, interest accrues according to the following standard calculation:

Accrued Interest = Original Face * Accrued Interest Factor * (Coupon/100) * (N/360)

Where:

Coupon = Annual coupon rate of the security, in percent

Accrued Interest Factor = Days in accrual cycle / Total days in coupon interval

N = number of days from the first day of the accrual period (the “as-of” date for accrued interest factor) to the settlement date itself.  The day count is computed according to the 30/360 calendar.

Example:

Assume a 6% $200,000 mortgage with monthly payments of $1,198, with an accrued interest factor of .98, and N = 30.

Accrued Interest = 200,000 * .98 * (6/100) * (30/360) = $980

Mortgage Principal Component

A monthly mortgage payment’s principal component is the remainder of the payment after subtracting the interest component.

Calculation:

Principal = X – B(n) * y/12 where X is the monthly mortgage payment and the second term is the interest component.

Example:

From the previous example, principal = $1,198 – $980 = $218

This payment reduces the mortgage principal to $200,000 – $218 = $199,782.

Unamortized Principal

The outstanding (unamortized) principal can be computed with the following formula.

Calculation:

X ∑ 1/(1 + y/12)n where X is the monthly mortgage payment, y is the annual mortgage rate, and n is the remaining number of payments.

The limits of the summation are from 1 to n, yielding a working calculation of X * (1 – 1/(1 + y/12)n ) / y/12.

Example:

With a monthly payment of $1198, and interest rate of 6%, and 300 remaining payments,

Outstanding principal = $1198 * (1 – 1/1+ .06/12)300) / .06/12 = $185,937.80

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FSA Levies Fines Against U.K. Law Firm Over Lehman-Backed Products

September 23rd, 2010

A U.K. lawyer

The United Kingdom’s Financial Services Authority has issued a fine against law firm Thorntons Law LLP for misleading clients during the marketing of structured products that had the backing of now-defunct prime broker Lehman Brothers Holdings Inc.  The fines against the Scotland- based firm and two individuals were levied because they did not warn customers about the riskiness of the products.

Thorntons received a fine of 35,000 pounds ($55,000) and Michael Royden, a partner at the firm, 10,500 pounds, the regulator said in a statement today on its website. The FSA also fined Robert Peter Yarr, a financial adviser at McClelland Yarr Financial Services Ltd. in Belfast, 28,000 pounds.

The FSA said in October that three firms were facing fines after it probed sales literature in the 107 million-pound structured-products market. Lehman’s September 2008 collapse and bankruptcy prompted lawsuits by former clients whose assets were frozen in insolvency proceedings around the world.

“Firms and individuals giving investment advice must properly assess their clients’ needs and make suitable recommendations,” FSA head of enforcement Margaret Cole said in the statement. “They must also have the necessary systems and controls in place to ensure that this happens.”

Royden was in charge of compliance at Thorntons’ Investment Services at the time the firm was offering the products from November 2007 and August 2008. Structured products were typically marketed as guaranteeing the principal amount of money invested, even if no returns were possible. After Lehman’s collapse, the investors’ original contributions weren’t repaid.

Thorntons “commissioned an independent review of systems, following which, a number of improvements have been implemented,” the firm said in an e-mailed statement. “We are in the process of reviewing each case to ensure that our obligations regarding redress are met and a number of clients affected by the FSA findings have already received payment.”

Royden and Yarr didn’t immediately respond to requests for comment. All three received the FSA’s standard 30 percent discount for cooperating with the probe.

In February, the regulator fined a unit of RSM Tenon Group Plc, a London-based financial-advice company, 700,000 pounds for failing to explain to customers the risks of products backed by Lehman.

Source

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Financial Statistics (5) – Standard Error of Estimate

September 22nd, 2010

Plot A has a smaller standard error of estimate than does Plot B

- Eric Bank

We left off last time having concluded a discussion of the t-test for evaluating correlations. Next, using the standard error of estimate, we’ll examine how to assess the strength of a relationship between an independent and a dependent variable as determined by a linear regression.

Recall that the equation for a linear regression is:

Yi = b0 + b1Xi + εi for i = 1, …, n

where the residual error term, ε, gives an indication of how certain we are about a particular predicted Y value via a linear regression.   The standard error of estimate tells us how spread out actual values of Y are with respect to their predicted values. The bigger the standard deviation of the error term, the less precise is the relationship between the two variables.

The standard error of estimate (SEE) measures the variability of the error term:

Don’t panic: the equation just adds up the squares of the error terms, divides the sum by number of degrees of freedom, and takes the square root of the whole thing. Another way of saying this is that the SEE is the difference between the dependent variable’s actual value for each observation and its predicted value for each observation.

SEE and standard deviation are almost identical, except that SEE has n-2 degrees of freedom (to account for the two parameters and and standard deviation has n-1 degrees of freedom.  This little difference in the denominator ensures that SEE is unbiased. Whereas the standard deviation is the square root of the average squared deviation from the mean, the standard error of the estimate is the square root of the average squared deviation from the regression line.

To get a general feel of the meaning of a particular SEE value, know that if the error residuals (ε = Yactual – Ypredicted) are normally distributed around the prediction line, about 68% of actual scores will fall between ±1 SEE of their predicted values.

While we can say that smaller SEE values result in better predictions, it would be nice to know how well the independent variable X explains variation in the dependent variable Y. To calculate the fraction of the total variation in the dependent variable that is explained by the independent variable, one uses the coefficient of determination, which will be our next topic.

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TradeStation to Add Securities Lending to Its Prime Services Offering

September 21st, 2010

Taps Industry Veteran to Head Sec. Lending Department and Co-Head Division

New York, NY, September 21, 2010 – TradeStation Securities, Inc. (Member NYSE, FINRA, SIPC and NFA) today announced the hiring of Robert Sackett to start up and lead the securities lending department of, and co-head, its TradeStation Prime Services division.

“Securities lending services are a critical component of our plan to build a first-class prime brokerage offering to small and mid-sized hedge funds and other buy-side traders who can no longer receive important prime brokerage services directly from the large firms,” said Salomon Sredni, CEO of TradeStation Group, the parent company of TradeStation Securities. “We believe TradeStation’s position as a self-clearing broker-dealer serving this market allows it to offer a more compelling value proposition compared to other firms that cannot directly provide custody, clearing, settlement and securities lending and must instead rely on the large firms to which they introduce all of their accounts.”

“We believe Rob’s 15 years of experience and relationships in securities lending will allow TradeStation to compete effectively in a market that continues to see industry fragmentation and where small to mid-sized buy-side institutional traders continue to seek prime brokers capable of directly delivering to them basic, critical prime services,” added Lance Baraker, Senior Managing Director and co-head of TradeStation Prime Services.

Mr. Sackett is leaving his position of Managing Director at Citigroup Global Markets Inc. to join TradeStation Prime Services as Senior Managing Director and co-head of the division. He has over 15 years of securities lending experience at Citigroup and its predecessors, and has been a NYSE-approved Securities Lending Representative since 1995 and a NYSE-approved Securities Lending Supervisor since 2002. He is scheduled to begin his employment with TradeStation after the Thanksgiving holiday, following the expiration of his 75-day garden leave period with Citigroup. TradeStation Prime Services expects to begin offering securities lending services in the 2011 first quarter. For additional information about TradeStation Prime Services, please visit: http://www.tradestationprime.com/.

TradeStation Prime Services, a division of TradeStation Securities, Inc., was founded to serve the needs of start-up to mid-sized hedge funds, registered investment advisers, professional traders and asset managers who need quality prime brokerage services, including execution and clearance, securities lending, capital introduction, and “incubation” services. Clients are offered electronic trading and decision-support platforms, including TradeStation, to analyze their trading strategies and automate or manually place their orders, and may avail themselves of the firm’s NYSE floor membership, which allows it to execute trades on behalf of clients on the NYSE floor as well as in other market centers from its NYSE floor booth/outsourced trading desk. TradeStation Prime Services is located at 400 Madison Avenue, New York, New York.
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About TradeStation Prime Services, a division of TradeStation Securities, Inc.
TradeStation Securities, Inc. (Member NYSE, FINRA, SIPC & NFA) is a licensed, self-clearing securities broker-dealer and a registered omnibus-clearing futures commission merchant, and has memberships or similar approved status (as well as direct connectivity for both market data and order execution) with BATS Z-Exchange, Boston Options Exchange, Chicago Board Options Exchange, Chicago Stock Exchange, EDGA Exchange, EDGX Exchange, International Securities Exchange, NASDAQ OMX BX, NASDAQ OMX PHLX, The NASDAQ Stock Market, NYSE Arca and NYSE Amex. For futures accounts, TradeStation connects directly (for both market data and order execution) with the CME Group, Eurex Group and ICE Group (U.S. and Europe) exchanges. TradeStation is a clearance member with DTCC and OCC for equities and options, serves its futures accounts on an omnibus clearance basis, and also introduces institutional equities accounts to J. P. Morgan Clearing Corp., as clearance agent. TradeStation Securities has offices in South Florida, New York, Chicago and Dallas, and an affiliated introducing broker (TradeStation Europe Limited) in London.

About TradeStation Group, Inc.
TradeStation Group, Inc. (NASDAQ GS: TRAD), through its principal operating subsidiary, TradeStation Securities, Inc., offers the TradeStation platform to the active trader and certain institutional trader markets. TradeStation is an electronic trading platform that offers state-of-the-art electronic order execution and enables clients to design, test, optimize, monitor and automate their own custom Equities, Options, Futures and Forex trading strategies. TradeStation Group’s other operating subsidiaries are TradeStation Technologies, Inc. and TradeStation Europe Limited.
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Forward-Looking Statements – Issues, Uncertainties and Risk Factors
This press release contains statements that are forward-looking and are made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. When used in this press release, the word “believe,” “expects,” “plan” and similar expressions, if and to the extent used, are intended to identify forward-looking statements. All forward-looking statements are based largely on current expectations and beliefs concerning future events that are subject to substantial risks and uncertainties. Actual results may differ materially from the results herein suggested. Factors that may cause or contribute to the various potential differences include, but are not limited to, the company’s new “TradeStation Prime Services” division, generally, including the planned new securities lending department, turning out to be less profitable, less successful, and/or more costly than expected, or resulting in unanticipated claims or liabilities against the company, as a result of (1) Mr. Sackett’s employment, and/or the securities lending department he is expected to head, not beginning or working out as planned and expected, (2) unanticipated start-up or development costs and expenses that are not offset or exceeded by expected revenues as and when planned (or at all), (3) the TradeStation prime services offering generally, and securities lending services particularly, not growing in appeal to prime services clients to the extent the company believes they will, (4) the failure of the company to make timely and quality enhancements to its trading platform, or to offer alternative platforms, which are believed necessary to attract prime services clients to use TradeStation to execute and clear trades, (5) TradeStation’s size and balance sheet being unacceptably small to mid-size and larger prime services clients (which are part of the market segment the company intends to serve) and third-party providers of credit, funding and inventory required for a successful securities lending department, and (6) the general unpredictability of operating results for a start-up business division, particularly given TradeStation’s lack of experience in offering prime brokerage services generally and securities lending in particular.

Contact –

William P. Cahill

President & Chief Operating Officer
TradeStation Securities, Inc.
954-652-7852

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Financial Statistics (4) – Testing Correlations for Significance: the t-Test

September 20th, 2010

Tea test

- Eric Bank

Now that we have examined correlation and linear regression, we now need to understand whether a correlation describes a real relationship or is just the result of chance.  Only real relationships are predictive.  Another way of saying this is that we want to test the null hypothesis (H0) that a correlation coefficient ϱ in the population is equal to zero (ϱ = 0), versus the alternative hypothesis (H1) that it is significantly different from zero (ϱ ≠ 0).

Since we are testing whether the correlation is not zero (i.e. significantly bigger or smaller than zero), we need to perform a two-tailed test. We assume that the variables (X and Y) are normally distributed – this permits us to perform a t-test:

where the sample correlation r is an estimate of the population correlation ϱ, and n is the sample size. We use (n -2) degrees of freedom to see if the test statistic has a t-distribution; if it does, then H0 is true. By using n – 2 instead of n for the degrees of freedom, we avoid introducing a bias into the calculation.  If the calculated t-value exceeds the critical t-value for the degrees of freedom, then H0 can be rejected. By the way, you can look up the critical t-value in a table at the back of any statistics book. Note that as n increases, the absolute value of the critical t-value decreases: it’s easier to reject the null hypothesis with a larger sample size. Also note that the numerator of the t-test increases with increasing n, meaning you get larger values of t for larger samples. The bottom line is that the likelihood of failing to reject a false H0 decreases with sample size.

When we perform a t-test, we need to specify a level of statistical significance.  For example, if we choose the 0.05 level of significance, we are confident in the results of test 95 times out of 100. All things being equal, a lower level of significance produces a higher critical t-value: it becomes harder to reject H0, but you have more confidence in the predictive value of the correlation.

Let’s work a numerical example[1].  We determine that the sample correlation r between monthly returns on long-term U. S. government bonds and 30-day T-bills was 0.1119 over 924 months of observations. Is this value of r high enough to reject the hypothesis that returns on the bonds were uncorrelated to returns on the T-bills?  For the 0.05 level of significance, the critical t-value is 1.96, and we can plug in the values into the t-test:

tactual > tcritical =  0.1119 (924 – 2).5 / (1 – 0.11192).5 = 3.4193 > 1.96

Thus, in this example we are able to reject the null hypothesis, and say that there is correlation between government bonds and T-bills.

We want next to assess the strength of a relationship between an independent and a dependent variable as determined by a linear regression. We will examine this test in our next blog using a statistic called the standard error of estimate.

[1] Quantitative Methods for Investment Analysis, Second Edition, by Richard A. DeFusco, CFA, Dennis W. McLeavey, CFA, Jerald E. Pinto, CFA, and David E. Runkle, 294-295.

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SEC Case Against Trader of PIPEs Bombs

September 17th, 2010

It wasn’t a total smack-down of the SEC, but close enough.

Robert Berlacher, A Pennsylvanian manager of hedge funds, claimed a triumph in his war with the Securities and Exchange Commission after U.S. District Judge Mitchell Goldberg threw out most of the charges against him and declined to levy civil penalties or pre-judgment interest.

Berlacher was found to have misrepresented his positions before participating in a pair of private investments in public entities and ordered to pay $352,364 in illegal profits. But Judge Goldberg, who heard the three-day bench trial in March, said that Berlacher was not guilty of insider-trading in one case because the PIPE-issuing company’s stock price failed to move much in the wake of the announcement. Goldberg also ruled in Berlacher’s favor on securities fraud charges in two other PIPE deals.

A PIPE, or private investment in public equity, is a deal in which publicly traded equity securities (common stock, preferred stock, warrants, etc) are sold to private investors. U.S. investors get to choose whether to register the PIPE offering with the SEC or privately place the securities on an exempted basis.

“The SEC has not sustained its burden of proof on the insider-trading count and two of the fraud claims,” Goldberg wrote. “The SEC has met its burden on two separate fraud claims.”

“We are gratified that today’s decision by the court rejects the lion’s share of the SEC’s claims and its overreaching attempt to mischaracterize certain conduct as a violation of federal law,” Berlacher’s lawyer, Nicolas Morgan, said in a statement.

The SEC had accused Berlacher of participating in four PIPE deals in which shorting the companies’ shares after learning in advance about the placements and without telling the companies issuing the shares.

Source

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