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High Frequency Trading Demands Higher Frequency Sampling




When fortunes can be made or lost in a microsecond, network testing demands unprecedented levels of precision. ”It can be done”,
says Daryl Cornelius, Spirent Communications

Innovation disperses ever faster – and the breakthrough business strategy or technology that yesterday gave you the competitive edge, today lands you square in midfield. For the financial trader that means relying on similar trading strategies used by all the competition. So one lucky trader gets the optimum price and, a fraction of a second later, you’re the loser.

High Frequency Trading (HFT) generates massive trading volumes – an attractive proposition for financial exchanges – but puts enormous pressure on the exchange to force down latency, while maintaining reliability and market integrity. At such speeds and volumes a new challenge has emerged, called the ”microburst”. A microburst is a very short duration spike in traffic volume, that can pass undetected – both because it gets lost in the per second average traffic statistics (see Fig 1, showing max, min and average traffic plots), and also because it can be faster than the circuit design rate. Even at that speed it can result in lost packets and, for high speed traders, that’s a nightmare – especially because microbursts are most likely to occur in times of peak volume and volatility, when trading is most critical.


Fig 1 – Microbursts lost among average traffic

The industry is already addressing these pressures via technological upgrades, such as bigger buffers, extra processing capacity and the use of faster chips to meet not only normal market conditions but also freak events like the May 6th 2010 “flash crash”.

This is a very necessary process, but it will miss the mark unless network test procedures can move ahead of the actual operating conditions. It is comforting to know that your system has exceptionally low latency, but that is nothing compared to the value of metrics that not only quantify latency but also provide a detailed analysis of variations under a whole range of normal and exceptional operating conditions. To achieve this, you need a comb with finer teeth than the shortest microburst hazard: sophisticated monitoring capabilities that sample, inspect and time stamp traffic so precisely that nothing capable of damaging a trade can pass undetected. To really drill down to bottlenecks in the system, it is not even enough to measure round trip latency to this accuracy, you need to measure one-way latency with levels of precision previously unattainable by the finest round trip measurements.

The good news is that all this is now possible thanks to a new partnership between Spirent Communications – a world leader in subjecting systems to exhaustive ”real world” testing and cPacket, whose technology can inspect and classify data packets according to payload and header, at multi-Gbps speeds.

The resulting partnership established market leadership by launching a family of Traffic Access devices delivering functionality previously thought to be impossible, but now needed by the finance industry and increasingly by a wider number of organisations needing to analyse fast-moving data, such as real-time risk or performance management.

The chip that rewrites the rules

Software solutions already existed for ”deep packet inspection” – examining a packet’s content bit by bit – a vital function in network monitoring and secuity applications. Software performance, however, is inadequate because it adds latency and cannot keep up with today’s 10 Gbps or even 1Gbps line rates. cPacket’s purpose-built hardware solution, however, does the job on the fly and in real time. The time each packet takes to pass through the system is deterministic and independent of the content. Effectively, it performs like a streamlined ”bump in the wire” with no slow software processing in the data path or external memory bottlenecks. Unlike other deep packet inspection co-processors, this unique chip performs not only pattern matching but also packet header parsing in a single pass on the fly – hence the term Complete Packet Inspection (CPI) used by cPacket.

Consuming a mere five watts, the chip delivers about ten times the performance at one tenth of the cost of slower, more complex and expensive alternatives. Whatever the packet protocol The chip’s pattern-matching algorithms inspect traffic profiles defined by a simple user interface. The chip examines the stream bit-by-bit and can count, tag, redirect, replicate, or drop traffic according to user-specified criteria. Users can specify complex traffic profiles without worrying about such low-level protocol details as chained virtual local-area networks, or case-insensitive pattern searches. The unique algorithm enables linear scaling of chip performance to support 40 Gbps.

cPacket’s CPI opens up new possibilities for the integration of traffic monitoring, network security, test, and lawful intercept for a new generation of intelligent switches and network devices. Spirent have grasped this opportunity with their family of Traffic Access devices.

Spirent Traffic Access devices are designed to inspect network traffic on the fly. This replaces the time consuming process of recording the entire data stream to disk and then post-processing the recorded data for critical data inspection and pattern matching. The devices incorporate cPacket’s hardware and software architecture and come in a range of sizes – currently 12, 24 or 32 ports – handling any combination of 10G or 1G Ethernet. CPI allows the data stream to be searched for any user-specified combination of header fields and payload content and, based on the analysis, the packet can be switched to one or several ports. Packets can also be precisely time-stamped with GPS clock synchronisation. Detailed performance metrics are provided in a graphical web dashboard as well as being stored in standard CSV files that can be imported into SQL databases, spreadsheets, and monitoring frameworks.

Fig 2 above shows one example of a user-defined filter, combining both header and payload inspection. Shown below, Fig 3, is a sample graphical report of bandwidth in or out of the device as well as network behavior information such as TCP events, frame size distribution, and protocol breakdown. New filters are easily added to the reports from a simple and easy to use user interface.The data is also available as tables showing the instantaneous traffic rates , statistics such as minimum, maximum, mean and standard deviation over the 60 seconds running window, as well as cumulative values.

The potential range of benefits and uses is enormous, so we start with a few examples. Take the transition to higher speed Ethernet – few companies can afford a forklift upgrade, invariably there is considerable investment in legacy 1G equipment that does not support 10G. So a 10G data stream can be split into 10x1G streams with a single Traffic Access device and multiplexed back to 10G as needed.

Service providers can also use the device for multiplexing and de-multiplexing, or they can use it as a powerful laboratory tool for testing networks, applications and services. As such it can be used for streaming data to multiple devices simultaneously to take full advantage of the diagnostics against the selected data set, or one can apply specific traffic filtering & forwarding capability to send different data sets to each tool for selective analysis. Considerable time is saved because of the ability to isolate the relevant data, filter it, and perform multiple operations at the same time.

In addition, service providers can compare data sets being modeled in the lab with real live traffic traversing their network. This is an application close to Spirent’s heart because customers all across the globe use Spirent equipment and services to emulate real world traffic conditions to create stringent capacity tests on their networks and systems. Spirent Avalanche allows one to create traffic patterns to specification, or simply to record actual traffic and use that as the template for a test deluge. So, how much traffic must one record to get a usable ”average”? An hour? a day? a week? It could amount to a massive storage burden. Instead one can simply run the traffic through the Traffic Access device to profile the network behavior and feed the relevant metrics in to Spirent Avalanche traffic generation templates.

In the live network, network managers now have the ability to replicate traffic to multiple network tools, to aggregate traffic to a single tool, and to selectively filter traffic for enhanced security or application performance monitoring. Being able to profile and isolate traffic patterns can help to identify weaknesses or bottlenecks that hamper optimal network performance.

Keeping tabs on financial services
That above example, where a rolling average provides all the data needed without the need for massive data storage, points the way to a very important potential benefit in areas such as financial services where accountability demands an archive of transactions going back over a long period.

The first question is: do all transactions need to be recorded, or is that simply a fall-back position? The Traffic Access device would allow one to define precisely what traffic needs to be archived and what can be discarded. In many cases, this reduces the total storage burden by a factor of ten or more.

Even more useful is the opportunity to filter and sort traffic on the fly. So that, for example, all traffic involving one client – or a specific type of transaction – could be routed to a distinct archive. It is all being archived as before but, instead of one massive multi-terabit archive, it is neatly filed into chosen subsets of data, making subsequent inspection or data mining hugely faster and more efficient.

If packets get lost during a microburst you can lose revenue and also key applications such as algorithmic trading engines can receive stale data and need to be re-synced, adding further delay. If you cannot measure these spikes, you cannot fix them, but detecting microbursts requires sampling traffic in extremely fine time increments – see Fig 1. In that respect, the speed of cPacket’s chip is way ahead of the current requirements.

The precision time stamping function is another vital asset for the financial community, where timing to the sub-microsecond can make or break a deal. If two clients claim the same purchase at the same instant, how can one determine which was first without an accurate time stamp? A sale cannot be made unless the goods have already been purchased and cleared – these truths are so obvious, but with online trading they can be annulled on a minute delay. Application protocols record times to the microsecond, but cPacket’s precision time stamps are accurate to 30 nanoseconds.

In Fig 4 we see precision time stamps recorded before and after the firewall: the difference between the transaction time and the time of arrival at the firewall provides a measure of the public network latency, while the difference between the time of entering the internal network and of arriving at the transaction server, is a measure of internal network latency. This can also record the latency of the firewall, and the total internal processing time (the difference between confirmation arrival time and order arrival time).

Fig 4 – Multiple time stamps for complete and segmented latency measurements

The accountability demands of banking and financial services makes the finance industry an obvious example, but the same principle would apply to many large corporations that require transactions to be archived for review or later audit. In terms of efficiency, such pre-storage filtering makes the difference between searching through a ceiling-high mountain of unsorted paperwork, and searching a well-maintained filing system.

Compared with on-line financial trading, ordering the week’s shopping from a supermarket website might seem a very leisurely process – until the instant when the purchase button is clicked. If two customers are in contention for the last item in stock, then the precise moment of the transaction becomes a critical issue, just as it would be for the financial trader.

Security and data surveillance
Complete packet inspection at 10G Ethernet speeds, on the fly and in real-time facilitates advanced filtering and intrusion detection and prevention. Denial of service attacks can be instantly detected, code strings associated with malicious software can be detected and quarantined without impacting legitimate traffic performance. The payload searches accommodate both anchored and unanchored strings of data with wildcards included, amounting for a powerful and sophisticated search criteria.

More generally, the ability to identify and report detailed traffic patterns over a short and longer timescales can be used for behavioural detection of suspicious annomalies.

It is not often that such a powerful and broadly applicable new technology as the cPacket hardware-software and chip becomes available, and it can take time to wake up to the full potential it offers.

Traffic Access has a clear role to play as part of our test and measurement offering with a focus on increasing the speed and sophistication of Ethernet deployments. Flexible traffic access devices provide greater efficiencies in use of equipment and storage. However, as we have seen, the applications of traffic access devices goes way beyond pure testing.

When it comes to hair-trigger data processing, the finance industry is ahead of the game. But innovation spreads fast, and an increasing range of organisations will be needing our test solution in order to gain and maintain the confidence that only high precision test and measurement can ensure.




How has the online trading landscape changed in 2020?



How has the online trading landscape changed in 2020? 1

By Dáire Ferguson, CEO, AvaTrade 

This year has been all about change following the outbreak of coronavirus and the subsequent global economic downturn which has impacted nearly every aspect of personal and business life. The online trading world has been no exception to this change as volatility in the financial markets has soared.

Although the global markets have been on a rollercoaster for some time with various geopolitical tensions, the market swings that we have witnessed since March have undoubtedly been unlike anything seen before. While these are indeed challenging times, for the online trading community, the increased volatility has proven tempting for those looking to profit handsomely.

However, with the opportunity to make greater profits also comes the possibility to make a loss, so how has 2020 changed the online trading landscape and how can retail investors stay safe?

Lockdown boost

Interest rates offered by banks and other traditional forms of consumer investments have been uninspiring for some time, but with the current economic frailty, the Bank of England cut interest rates to an all-time low. This has left many people in search of more exciting and rewarding ways to grow their savings which is indeed something online trading can provide.

When the pandemic hit earlier this year, it was widely reported that user numbers for online trading rocketed due to disappointing savings rates but also because the enforced lockdown gave more people the time to learn a new skill and educate themselves on online trading.

Dáire Ferguson

Dáire Ferguson

A volatile market certainly offers great scope for profit and new sources of revenue for those that are savvy enough to put their convictions to the test. However, where people stand the chance to profit greatly from market volatility, there is also the possibility to make a loss, particularly for those that are new to online trading or who are still developing their understanding of the market.

The sharp rise in online trading over lockdown paired with this year’s unpredictable global economy has led to some financial losses, but with a number of risk management tools now available this does not necessarily have to be the case.

Protect your assets

Although not yet widely available across the retail market, risk management tools are slowly becoming more prevalent and being offered by online traders as an extra layer of security for those seeking to trade in riskier climates.

There are a range of options available for traders, but amongst the common tools are “take profit” orders in conjunction with “stop loss” orders. A take profit order is a type of limit order that specifies the exact price for traders to close out an open position for a profit, and if the price of the security does not reach the limit price, the take profit order will not be fulfilled. A stop loss order can limit the trader’s loss on a security position by buying or selling a stock when it reaches a certain price.

Take profit and stop loss orders are good for mitigating risk, but for those that are new to the game or who would prefer extra support, there are even some risk management tools, such as AvaProtect, that provide total protection against loss for a defined period. This means that if the market moves in the wrong direction than originally anticipated, traders can recoup their losses, minus the cost of taking out the protection.

Not a day has gone by this year without the news prompting a change in the financial markets. Until a cure for the coronavirus is discovered, we are unlikely to return to ‘normal’ and the global markets will continue to remain highly volatile. In addition, later this year we will witness one of the most critical US presidential elections in history and the UK’s transition period for Brexit will come to an end. The outcome of these events may well trigger further volatility.

Of course, this may also encourage more people to dip their toes into online trading for a chance to profit. As more people take an interest and sign up to online trading platforms, providers will certainly look to increase or improve the risk management tools on offer to try and keep new users on board, and this could spell a new era for the online trading world.

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Trading Strategies



Trading Strategies 2

By Paddy Osborn, Academic Dean, London Academy of Trading

Whether you’re negotiating a business deal, playing a sport or trading financial markets, it’s vital that you have a plan. Top golfers will have a strategy to get around the course in the fewest number of shots possible, and without this plan, their score will undoubtedly be worse. It’s the same with trading. You can’t just open a trading account and trade off hunches and hopes. You need to create a structured and robust plan of attack. This will not only improve your profitability, but will also significantly reduce your stress levels during the decision-making process.

In my opinion, there are four stages to any trading strategy.

S – Set-up

T – Trigger

E – Execution

M – Management

Good trading performance STEMs from a structured trading process, so you should have one or more specific rules for each stage of this process.

Before executing any trades, you need to decide on your criteria for making your trading decisions. Should you base your trades off fundamental analysis, or maybe political news or macroeconomic data? If so, then you need to understand these subjects and how markets react to specific news events.

Alternatively, of course, there’s technical analysis, whereby you base your decisions off charts and previous price action, but again, you need a set of specific rules to enable you to trade with a consistent strategy. Many traders combine both fundamental and technical analysis to initiate their positions, which, I believe, has merit.


What needs to happen for you to say “Ah, this looks interesting! Here’s a potential trade.”? It may be a news event, a major macro data announcement (such as interest rates, employment data or inflation), or a chart level breakout. The key ingredient throughout is to fix specific and measurable rules (not rough guidelines that can be over-ridden on a whim with an emotional decision). For me, I may take a view on the potential direction of an asset (i.e. whether to be long or short) through fundamental analysis, but the actual execution of the trade is always technical, based off a very specific set of rules.

To take a simple example, let’s assume an asset has been trending higher, but has stopped at a certain price, let’s say 150. The chart is telling us that, although buyers are in long-term control, sellers are dominant at 150, willing to sell each time the price touches this level. However, the uptrend may still be in place, since each time the price pulls back from the 150 level, the selling is weaker and the price makes a higher short-term low. This clearly suggests that upward pressure remains, and there’s potential to profit from the uptrend if the price breaks higher.


Once you’ve found a potential new trade set-up, the next step is to decide when to pull the trigger on the trade. However, there are two steps to this process… finger on trigger, then pull the trigger to execute.

Paddy Osborn

Paddy Osborn

Continuing the example above, the trigger would be to buy if the price breaks above the resistance level at 150. This would indicate that the sellers at 150 have been exhausted, and the buyers have re-established control of the uptrend.  Also, it is often the case that after pause in a trend such as this, the pent-up buying returns and the price surges higher. So the trigger for this trade is a breakout above 150.


We have a finger on the trigger, but now we need to decide when to squeeze it. What if the price touches 150.10 for 10 seconds only? Has our resistance level broken sufficiently to execute the trade? I’d say not, so you need to set rules to define exactly how far the price needs to break above 150 – or for how long it needs to stay above 150 – for you to execute the trade. You’re basically looking for sufficient evidence that the uptrend is continuing. Of course, the higher the price goes (or the longer it stays above 150), the more confident you can be that the breakout is valid, but the higher price you will need to pay. There’s no perfect solution to this decision, and it depends on many things, such as the amount of other supporting evidence that you have, your levels of aggression, and so on. The critical point here is to fix a set of specific rules and stick to those rules every time.


Good trade management can save a bad trade, while poor trade management can turn an excellent trade entry into a loser. I could talk for days about in-trade management, since there are many different methods you can use, but the essential ingredient for every trade is a stop loss. This is an order to exit your position for a loss if the market doesn’t perform as expected. By setting a stop loss, you can fix your maximum risk on a trade, which is essential to preserving your capital and managing your overall risk limits. Some traders set their stop loss and target levels and let the trade run to its conclusion, while others manage their trades more actively, trailing stop losses, taking interim profits, or even adding to winning positions. No matter how you decide to manage each trade, it must be the same every time, following a structured and robust process.


The final step in the process is to review every trade to see if you can learn anything, particularly from your losing trades. Are you sticking to your trading rules? Could you have done better? Should you have done the trade in the first place? Only by doing these reviews will you discover any patterns of errors in your trading, and hence be able to put them right. In this way, it’s possible to monitor the success of your strategy. If your trades are random and emotional, with lots of manual intervention, then there’s no fixed process for you to review. You also need to be honest with yourself, and face up to your bad decisions in order to learn from them.

In this way, using a structured and robust trading strategy, you’ll be able to develop your trading skills – and your profits – without the stress of a more random approach.

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Economic recovery likely to prove a ‘stuttering’ affair



Economic recovery likely to prove a ‘stuttering’ affair 3

By Rupert Thompson, Chief Investment Officer at Kingswood

Equity markets continued their upward trend last week, with global equities gaining 1.2% in local currency terms. Beneath the surface, however, the recovery has been a choppy affair of late. China and the technology sector, the big outperformers year-to-date, retreated last week whereas the UK and Europe, the laggards so far this year, led the gains.

As for US equities, they have re-tested, but so far failed to break above, their post-Covid high in early June and their end-2019 level. The recent choppiness of markets is not that surprising given they are being buffeted by a whole series of conflicting forces.

Developments regarding Covid-19 as ever remain absolutely critical and it is a mixture of bad and good news at the moment. There have been reports of encouraging early trial results for a new treatment and potential vaccine but infection rates continue to climb in the US. Reopening has now been halted or reversed in states accounting for 80% of the population.

We are a long way away from a complete lockdown being re-imposed and these moves are not expected to throw the economy back into reverse. But they do emphasise that the economic recovery, not only in the US but also elsewhere, is likely to prove a ‘stuttering’ affair.

Indeed, the May GDP numbers in the UK undid some of the optimism which had been building recently. Rather than bouncing 5% m/m in May as had been expected, GDP rose a more meagre 1.8% and remains a massive 24.5% below its pre-Covid level in February.

Even in China, where the recovery is now well underway, there is room for some caution. GDP rose a larger than expected 11.5% q/q in the second quarter and regained all of its decline the previous quarter. However, the bounce back is being led by manufacturing and public sector investment, and the recovery in retail sales is proving much more hesitant.

China is not just a focus of attention at the moment because its economy is leading the global upturn but because of the increasing tensions with Hong Kong, the US and UK. UK telecoms companies have now been banned from using Huawei’s 5G equipment in the future and the US is talking of imposing restrictions on Tik Tok, the Chinese social media platform. While this escalation is not as yet a major problem, it is a potential source of market volatility and another, albeit as yet relatively small, unwelcome drag on the global economy.

Government support will be critical over coming months and longer if the global recovery is to be sustained. This week will be crucial in this respect for Europe and the US. The EU, at the time of writing, is still engaged in a marathon four-day summit, trying to reach an agreement on an economic recovery fund.  As is almost always the case, a messy compromise will probably end up being hammered out.

An agreement will be positive but the difficulty in reaching it does highlight the underlying tensions in the EU which have far from gone away with the departure of the UK. Meanwhile in the US, the Democrats and Republicans will this week be engaged in their own battle over extending the government support schemes which would otherwise come to an end this month.

Most of these tensions and uncertainties are not going away any time soon. Markets face a choppy period over the summer and autumn with equities remaining at risk of a correction.

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