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Neal Goldstein, J.P. Morgan, Timothy Furey, Goldman Sachs and Greg Wood elaborate on the forthcoming FPL Risk Subcommittee’s Risk Management Guidelines including their extension to cover DMA, symbology and futures.

While margin checks do not fit into the typical pre-trade risk check, how can traders assimilate the risk limit functionality of FIX with their margin-level risk monitoring?

 

Neal Goldstein, J.P. Morgan:

Pre-trade risk checks are a key element of the comprehensive risk management strategy applied for business lines like prime brokerage. For electronic trading relationships where a client is offered leverage based on some level of collateral, real time positions for each client are usually calculated based on start of day, and intra-day drop copies of execution reports. A typical risk control is to link the post-trade position checks with the pre-trade checks applied at the gateway. If a client’s intra-day position approaches a level that exceeds the pre-arranged leverage or margin agreements, the post-trade system can send a cut off signal to the pre-trade gateway. The client would then be allowed to liquidate the position to reduce the long/short positions, but not go any further long or short.

The basic definition of DMA trading is that brokers provide access to a venue in the most efficient and effective way possible. What can brokers do to ensure they do not miss client risk limits, internal counterparty checks, rule 15c3-5 requirements, etc while maintaining speed of access?

 

Timothy Furey, Goldman Sachs:

Whether using algorithms, smart order routing and/or DMA to access the market, it is important to make sure that the rules are optimized and that automated testing and checkout processes are in place to verify that they are working. Appropriate risk controls are a key part of execution and are baked into the process. With all the advances in technology, development teams have the ability not only to better optimize the execution path for speed and efficiency, but also to provide benefits like automated testing to check that controls are functioning properly.

How important is symbology validation to equity risk controls? Can better technology remove fat finger errors from trading?

Greg Wood:
Symbology validation is very important to any type of electronic order flow since the broker must clearly identify the instrument being traded by the client. An erroneous validation of a symbol could have serious repercussions in how the order is executed in the market, including inadvertent disruption to the market. One of the key rules of engagement when a broker certifies a FIX connection with a client or vendor is for both parties to agree what symbology is being used on the session and then not to deviate from that without a subsequent recertification.

Risk management technology is definitely evolving alongside trading technology to provide better controls for the way people are trading now. A simple fat finger check can prevent an inadvertently large order being sent direct to the market. However clients are increasingly using algos to trade large orders over a longer duration or using different types of interaction with the market. In this situation the fat finger check is deliberately large to allow the order to be submitted to the algo. The algo then needs to assess whether the parameters of the order - instrument, aggression, duration, time of day, etc - are suitable for the size of the order. If a large order has parameters that are too aggressive in comparison to the average daily volume of the instrument and the desired timeframe for execution then the algo should either reject or pause the order to avoid impact to the market. If this happens then the broker and client should discuss how to adjust the parameters of the order to avoid impact.

Banco Fator’s Rodrigo Campos chats with FIXGlobal about the current condition of high frequency trading in Brazil and the improvement to the exchange’s trad

Michael Corcoran of ITG sits down with Jason Lapping, Head of Asia Pacific Trading for Dimensional Fund Advisors (DFA), to discuss the practical impact of electronic trading and dark aggregation on his trading process.

Michael Corcoran, ITG: DFA is one of the largest users of electronic trading techniques in Asia Pacific. Why have you chosen this model and what benefits does it bring?

Jason Lapping, DFA: The primary driver for us using electronic trading is to give us full control over the trading outcomes. DFA’s unique process of generating investment returns is highly focused on the overall returns of an investment decision, and that includes the impact of trading. Portfolio managers generate orders for the trading desk but provide some flexibility over what to purchase on a specific day. This means we can be patient, exploiting the opportunities and liquidity available at any given moment. As a result, around 90% of our global trading volume is electronic. In Asia Pacific, that number is even higher, with over 95% of trading managed by our own traders using DMA and algorithms accessing both lit and dark liquidity simultaneously.

Dark and alternative sources of liquidity also form an important part of our strategy. DFA manages in excess of US $240bn, so we are often interested in trading a large percentage of a day’s volume in a stock. We utilize dark pools to try to achieve this in a way that does not signal to the market. Most of our dark pool fills are small, but cumulatively they amount to a significant extra size traded without signaling the extent of our interest to the market.

We generally trade in dark and lit simultaneously as there is an opportunity cost to placing an order only in the dark. So for us dark liquidity is particularly useful as a complementary strategy.

Firms often describe what they do as trading securities, but in fact what we are doing is trading liquidity. And anything that helps us interact with more liquidity is really important. Therefore in the developed Asia Pacific markets, about 10-15% of our total executions are done in dark pools. We believe this helps reduce implementation costs while getting more done. Both of these elements benefit our investors.

MC: Has the move to full control of the trading process been explained to your investors and do you find it’s a differentiator for DFA?

JL: Trading is very much a value-add in DFA’s overall investment process. So our engagement with clients involves explaining that we have an integrated investment process where portfolio managers work closely with the trading desks, giving them a degree of flexibility. When the market is not going our way, this flexibility allows DFA traders to be patient on a specific stock at a given point in time. When the market is going our way, it allows our traders to be opportunistic. We execute at prices where it makes sense to do so, not because we have been told to get the order done today.

What this ultimately means is that trading can start to add value, rather than being a drag on a portfolio’s returns. The cost of implementation can be significant, and our job as traders is to minimize the gap between the theoretical and actual returns of portfolios. I think that many of our clients find this is a differentiator for DFA, and it is potentially a reason to choose us over another investment manager.

Guosen Securities’ Shen Tao reveals the latest trends in algo usage by Chinese asset managers, domestic mutual funds and Qualified Foreign Institutional Investors (QFIIs).

Who are the primary customers for algorithmic products in China?
Algorithmic trading started in the Chinese A share market some time in 2007. In 2005, the first commercial FIX engine went live to accommodate the execution needs of the Chinese A share market of Qualified Foreign Institutional Investors, or QFIIs, as part of the plan by the Chinese government to allow regulated capital market investment by foreign investors. After an initial experimental phase of FIX connectivity with global trading networks, the local FIX trading platform became solid enough to interface with a real algo engine. In 2007, some leading global investment banks (predominantly, QFIIs from the sell-side) began to offer algorithmic trading facilities for their clients and their own proprietary trading desks. Most of these facilities were located offshore (e.g. Hong Kong) and connected to the Chinese brokers’ FIX gateway via a financial trading network such as Bloomberg.

The earliest providers and users of algo trading in the Chinese market were solely QFIIs and their clients. In 2008, although the global market was in turmoil and many infrastructure budgets were cut across the international financial community, there were still some firms seeking expansion opportunities for the future. Among them, some global banks with local brokerage joint venture subsidiaries began to build their onshore algo facilities. At about the same time, some leading purely local brokers also started their efforts in algo development, Guosen among them. We started in March 2008 and also targeted QFII investors for algorithmic trading, however, we understood the future of algorithmic trading in the Chinese market would rest on the domestic mutual fund industry. In late 2009, the Guosen algo platform was almost ready and the aforementioned onshore algo facilities run by the sell-side joint ventures of global banks also went live. The day of the algo had finally arrived for China.

In 2010, with support from a leading buy-side OMS vendor Hundsun; Guosen and UBS began their efforts by offering an algo solution for local mutual fund companies. In November 2010, UBS won its first success with two Beijing-based mutual fund companies, with Guosen securing a third six months later. Since that time, more than a dozen mutual fund companies have started using algorithms from UBS and Guosen. 2010 was the first year of the algo, from a local perspective. Currently, the momentum of mutual fund companies adopting algo platforms continues. We estimate that by the end of 2011, in terms of assets under management, over 40% of the local mutual fund industry could be covered by broker-provided algo services.

In retrospect, QFII investors were the founders of the market, but soon, the local mutual fund industry will become the primary user of algos. In addition, we foresee insurance companies adopting algo trading soon.

Raymond Russell, of the FIX Inter-Party Latency (FIXIPL) Working Group and Corvil lays out the use cases for the FIX Inter-Party Latency standard and the functionality of Version 1.0.

 Raymond Russell, CorvilGoals for FIXIPL

The principal goal of the Inter-Party Latency Working Group is to ensure interoperability between different latency monitoring vendors. Interoperability is essential because latency monitoring is vital to running a low-latency service, therefore the people building systems need confidence that they can start with one vendor and still migrate to another. What we have seen through the proliferation of latency monitoring systems across the trading world, whether DMA providers, market data providers or trading desks, is that often the problems in managing latency within an environment happen between the cracks. Most firms have a good handle on latency in their own environment because they have engineered it well, but when they connect into a counterparty, it gets tricky.
 
Use Cases
A trader who sees a slowdown in response time will want to understand why they have missed trades or why their fill rates are low, but there are multiple places where that latency could have occurred. One place is in the exchange matching engine, which in some respects is unavoidable. If there is considerable interest and activity in a symbol at the same time, those orders will have to queue in the matching engine, purely as a result of market activity. The latency might also have occurred in the exchange gateway. It is common practice for exchanges to load balance across multiple gateways to accommodate high volumes, and you might have hit a slow gateway. Perhaps the service provider you connect through may have oversubscribed their network and you could be caught in cross traffic unrelated to trading. We have seen all these things happen, so the ability to see where the latency is occurring requires a consistent set of time stamps across the architecture.
 
Most exchanges already employ latency monitoring in their own environment, and inter-party latency and the sharing of time stamps, while less important within the exchange, enables them to work with their members to identify areas of latency. The benefits unlocked through interparty latency are somewhat biased towards the end traders, but they also extend to brokers and market data providers, who receive better quality execution feeds and market data speeds, respectively.
 
For exchanges, the need for latency transparency is becoming a standard requirement as latency has become a competitive differentiator. To the extent that exchanges are comfortable with their own infrastructure and are ready to compete on their latency, they will want to share their latency measurements with members. In my experience, venues and brokers are no longer as reticent to share their latency figures as they were before.
 
Version 1.0 Rollout
Much of the work that we have done with Version 1.0 involved deciding how to produce a standard that on one hand is simple enough to be easily implemented, while ensuring it can still perform in all the basic use cases. Version 1.0, due out in December 2011, is clean and simple and emphasizes the core capability to publish time stamps. We have agreed on the technical scope and it is now going through the formal review procedures required to be standardized by FPL, including a public review. The other important part to be done before it is real is to get two different implementations. There are a number of things that will be ready in a few months’ time, such as distribution through multicast and the ability to automatically group several measurements together across the trade, which we will include in the next version later next year.

Michael Thom, Equities Trader, Genus Capital Management offers a look into the Canadian equities world, including perspectives on dark pools as well as algo implementation and usage. 

Inverted pricing models
We have just seen the introduction of more innovative pricing models in Canada, essentially since the launch of TMX Select. For most buy-side participants like me, we do not see our tick fees as rebates because they are bundled into the commissions we pay to our brokers. This is an exciting development for participants that thrive on different market structures, but I would not say that we particularly benefit from this market model. From an intellectual perspective, it is interesting to wonder what will happen as a result of these developments, but I would not say it has any immediate net benefit to us or our clients.
 
Trends for Dark Pools in Canada
Canadian regulators have taken the right approach. There are lessons to be learned from other jurisdictions where dark liquidity was left to develop and regulators then had to play catch up. I applaud the Canadian regulators for giving their approach to dark liquidity critical thought before it gets to the point of significantly damaging market quality. Regulators in Canada are at a point now where if they change the regulations significantly, venues and firms would be able to adjust. The debate over the trade-at rule in the US shows that whole business models are built around sub-penny pricing and trading not at the touch. I do not think that is where we want to go in Canada.
 
I am a little cautious around some of the regulators’ specific proposals on minimum size. I am more in favor of the minimum increment being set at a half penny. The minimum size is the more difficult concept because anything that functions around a single pivot size, either in value or number of shares, can disseminate information through trading around that pivot point.
 
Although to my knowledge very few participants choose to structure their orders in such a way, it should be up to market participants to build into their orders the minimum execution quantities for dark pools as they see fit. I do not think a lot of buy-side participants are currently building their orders or customizing their third party algorithms to that level of detail. From where I sit, it is not a perfect solution, but this compromise might be the best of the difficult alternatives.
 
It is important to point out that they are not putting in a minimum size right away. The architecture is built to allow the regulator to, on very short notice or if they start to see some compelling data points, put limits in place without going through the full comment and review process, which is all very prudent. They are giving themselves the tools to deal with all possible market outcomes. Flexibility does not come easily to regulators. Typically, they adopt very specific proposals and if those proposals fail, it is back to square one, whereas here they have given themselves a degree of latitude which is commendable.
 
Simplifying Algo Implementation The algo and DMA providers who are winning our business are those who can give us transparency right down to how they are interacting with each individual venue, what order types they are using and how they are implementing venue specific idiosyncrasies. If a venue has very unique order types, our providers should say how they are using those and why they made the decision to use the order types they did. Providing a transparent, empirical basis for decisions regarding algo structure, architecture, order types and routing is really important. Many decisions go into building quality algorithms and routing, and those who will share the data behind it are my providers of choice. Algo providers seem to now be more willing to tailor and be empirical about constantly improving the product to fit a firm’s or a trader’s trading styles. That is where algorithmic trading is headed, as it relates to buy-side, and we are just starting to see the leading edge of that in Canada.

Corwin Yu, Director of Trading at PhaseCapital, sits down with FIXGlobal to discuss his trading architecture, the proliferation of Complex Event Processing (CEP) and why he would rather his brokers just not call.

FIXGlobal: What instruments does your system cover?
Corwin Yu: At the moment, we trade the S&P 500, and we have expanded that to include the Russell 2000, although not as an individual instrument, but as an index. We also trade the E-Mini futures on the Russell 2000 and also for the S&P500. We have done some investigation on doing the same exact type of trading with Treasuries using the TIPS indices and the TIPS ETFs and a few of the similar futures regarding those as well. We are not looking at expanding the equity side except to consider adding ETFs, indices, or futures of indices.

FG: Anything you would not add to your list?
CY: We gravitate to liquid items with substantial historical market data because we really do not enter into a particular trading strategy unless there is market data to do sufficient
back testing. Equities was a great fit because it has history behind it and great technology for market data, likewise for futures, where market data coverage has recently expanded. Options is a possibility, but the other asset class that is liquid but not a good fit is commodities. We shy away from emerging markets that are not completely electronic and do not have good market data. While we have not made moves into the emerging markets, we know that some other systematic traders have found opportunities there.

FG: How much of your architecture is original and how often do you review it for upgrades?
CY: In terms of hardware, we maintain a two year end-of-life cycle, so whatever we have that is two years old, we retire to the back-test pool and purchase new hardware. We are just past the four year mark right now, so we have been through two hardware migrations. Usually this process is a wakeup call as to how technology has changed. When we bought our first servers, they were expensive four-core machines with a maximum memory of 64 GB. We just bought another system that can handle 256 GB through six-core processors. We are researching a one year end-of-life cycle because two years was a big leap in terms of technology and we could have leveraged some of that a year ago.

DATAROAD’s David In-hwan Lee shows how Korean traders are utilizing FIX to improve both domestic and international trading capabilities.

How has FIX adoption improved Korean trading?

David In-hwan Lee, DATAROADIt was at the end of 2002 that Korean institutions were able to process orders from foreign institutions using the FIX Protocol for the first time. During the following years the FIX Protocol in Korea developed very fast over almost a decade of use.

Before the adoption of the FIX Protocol, approximately 60 securities firms, 40 institutional investors and multiple foreign institutions had been processing orders using telephone, FAX and emails, which were very inefficient means of one-toone communication. Now, most sell-side and buy-side firms are able to place orders conveniently and promptly, and receive execution reports realtime using the FIX Protocol.

After adopting the FIX Protocol and Order Management Systems (OMSs), both institutional investors which place orders and securities firms which receive orders and execute them at the exchange were able to improve their internal trading tasks noticeably. Korean securities firms were now able to connect via networks with the trading systems of overseas institutional investors more efficiently, in contrast with the past. Moreover, since they are actively using the FIX Protocol in connection with outbound orders such as FX transactions and overseas future trading, as well as inbound orders, the adoption of FIX greatly contributed to the internationalization of the Korean securities market.

What is the opinion of Korean brokers toward algorithmic trading?

As OMSs are adopted along with the FIX Protocol, Korean securities firms perform basic algorithm trading using the automatic order system provided by their OMS. Although they currently support simple types of algorithmic trading only, I believe that more diverse algorithm trading functions will be necessary as the Korean securities industry goes through environmental changes.

The Korean securities market is expected to go through a major systemic change in the near future. Although it has not been finalized yet, securities exchanges in Korea are expected to compete with one another starting from the second half of 2012 because the establishment of an Alternative Trading System (ATS) in the Korean securities market will be allowed by then.

Also, the Korea Exchange (KRX) announced a plan for developing a next-generation trading system EXTURE+ in late July 2011. More specifically, KRX plans to develop a new system aiming for two-digit microsecond latency for its trading system. I believe that Korean securities firms should expand the functionality of their own algorithm trading for brokerage business and adopt ultra-high speed DMA systems in order to be able to perform low latency trading demanded by the algorithm trading systems commonly used by buy-side firms. As a result of the changes in the environment of the Korean securities market, High Frequency Trading (HFT) and algorithm trading are expected to develop quickly during the next several years.

What benefits have Korean buy-side firms seen since adopting FIX?

It was the buy-side that received the greatest benefit after adopting the FIX Protocol.

Before discussing the benefits of adopting FIX, it is important to know the relevant  circumstances before the adoption of the FIX Protocol. During the early 2000’s (right after the IMF crisis), Korean asset managers’ systems for managing funds had several problems. For example, the distinction of the roles between fund managers and traders was unclear, the compliance system was not established and people processed orders (placing orders and confirmation of executions) manually, often using telephone, FAX or email. Moreover, although there were back office systems for calculating NAV (Net Asset Value) and accounting, they were not prepared with OMSs for their trading systems.

Senrigan’s Head of Trading, John Tompkins, and RBS’ Andrew Freyre-Sanders discuss the way event based funds use liquidity and the effect of ID markets in Asia.

Andrew Freyre-Sanders, RBS: What would you say Senrigan is known for among Asia hedge funds?

John Tompkins, Senrigan: What we are most known for now is being an event-driven fund that is entirely based out of Asia. Nick Taylor founded Senrigan in 2009, and he is known for doing event-driven trading and has been verysuccessful at it. Nick was at Goldman Sachs and Credit Suisse, where he ran Modal Capital Partners for nine years before going to Citadel with his team. Senrigan’s capital raising and first year metrics made the first two years a success.

AFS: I know you trade in the US and Europe as well, so is the global fund entirely based out of Asia?

JT: The entire firm is based in Hong Kong, although we have some analysts who spend extended periods of time in the regions of focus. If we do any US and European trading, it always has an Asian bent to it; for example, a UK or European listed company that has a large percentage of their business located in Asia. The few examples are Renault-Nissan, all the Chinese Depository Receipts (DRs) in the US and some Canadian companies doing M&A into Australia.

AFS: Event driven funds require quick access to liquidity.  How does the type of deal or event catalyst affect the relative weighting of these items?

JT: The exchanges and companies are smarter, so they generally halt or suspend the names coming into the announcement, and then you have a short window until a given stock starts to trade up towards the terms. Any reasonably-sized fund is not going to be able to get anything done in that time period. After the event, the main concern is your targeted rate of return for the particular deal, which is impacted by the closing timeframe, surrounding risk, regulatory approval, dividend payments, etc, and you set levels where you want to be involved.

Traditionally safe deals with very tight spreads are viewed as the simplest way to risk-reduce, so people take those off and we give liquidity then because we are comfortable with what we are taking on. A lot of people think about the event as just the announcement on the day, but it is actually the time between when you see it and the range gets set. Only if it closes sporadically do you need access to greater liquidity; most of the time, you just need to be in touch with providers rather than have direct access.

AFS: From a trading perspective, once a deal is gone, it is not about that deal. The only speed liquidity advantage is in having systems that can take advantage of the spreads when they may be moving around a certain level. Is that the case for you?

JT: It definitely is. The big differences between Europe and Asia are the number of auctions and the  number of times stocks stop trading, which is quite significant. Between three and four distinct times a day, you will have dislocations in spreads for a variety of reasons, and this is an opportunity to improve. Beyond that, a majority of sell-side firms are setting up their own dark pools and there are alternative exchanges in Japan. In those venues, we deal with liquidity providers and market makers who do not care about the individual mechanics of a name; they simply care about the level of spread that they can access.

The most relevant thing is making sure you have the connectivity turned on to access all the forms of liquidity that exist. There is a big differentiation between counterparties in Asia from an executing broker’s standpoint: e.g. what is their default, what do they turn on for you right away, whatcountries do they have their crossing engines in, who do they have in their pool as liquidity providers? You have to know to ask those questions, and it has been very helpful to do that.