Martijn Groot, VP of Product Strategy from Asset Control
The Fundamental Review of the Trading Book (FRTB) is designed to provide institutions and regulators with an accurate risk measure of the potential impact of the worst case scenarios. But as financial institutions begin to wrestle with this upcoming regulatory demand, the challenges associated with collecting and validating ten years of history across every single instrument in order to identify the worst 2.5% of performance cannot be underestimated.
FRTB is just one component of a reinvigorated focus on historical data – but it is one that, should an organisation fail to achieve, will have significant implications on capital holdings requirements. Furthermore, this is not just a minor tweak on existing requirements: FRTB is both deep and wide-ranging and demands a substantial data infrastructure overhaul.
From identifying gaps in history, to flagging history that doesn’t qualify for use due to inaccuracy and adding external data sources and proxies, Martijn Groot, VP of Product Strategy at Asset Control insists that this renewed regulatory focus on historical time series data demands a strong information management architecture.
Value at Risk
One of the many outcomes of the 2007-2008 banking crisis was a devaluing of the Value at Risk (VaR) measure in use since the mid-1990s to evaluate an institution’s day to day risk. As the unprecedented and unpredicted events occurred, a risk probability created on a ‘business-as-usual’ basis simply did not stand up.
While the most recent regulatory focus has been on stress testing, the complete market risk evaluation is now being revisited – and with far more stringent information demands. These demands are designed to overcome the deficiencies of the VaR metric and, critically, estimate the size of potential losses in the event of unusual events, rather than putting an upper bound on losses in a business-as-usual day.
The Fundamental Review of the Trading Book (FRTB) should provide both institutions and regulators with a more accurate and trusted risk measure. However, achieving this objective will require far more than simply extending the original VaR calculations. Indeed, FRTB has thrown the VaR metric out completely – rather than looking to determine the maximum possible loss on a normal day, institutions must now calculate the Expected Shortfall (ES) on an abnormal day. Essentially, the demand now is to create a daily metric that estimates potential losses on the worst 2.5% of days for any given institution.
With regulators becoming more prescriptive and demanding less unwarranted variation between firms, FRTB is, of course, not the only legislative change refocusing activities towards historical data. However, the challenges associated with such wide-ranging data requirements may take some organisations by surprise. This shift in emphasis may sound straightforward, but drill down through the detail and the information management requirements associated with FRTB are significant and multi-layered. One of the intrinsic differences between ES and VAR calculations is that the former will be based on ten years of history, as opposed to the much shorter history required previously. It is paramount that this data is of sufficient quality and frequency to ensure there are no gaps and no inconsistencies – and it needs to be validated and audited.
In addition, FRTB distinguishes between modellable and non-modellable risk factors. Something can be modellable based on the availability of sufficient observable traded prices or non-modellable. The point here is that an organisation needs different sets of market data for the identification and calibration of these risk factors. For the determination of modellable vs non-modellable risk factors, only transaction prices can be used, whereas for the calibration thereof a wider permitted set of market data applies.
So what happens if an institution doesn’t have ten years of history for each and every aspect of the trade portfolio? If it does not have real prices? Or continuous, gap free observations? Obviously estimates can be used – but such calculations need to be audited and they must meet very specific validation requirements.
The right information management infrastructure to collect and retain this data is clearly important – but institutions will also need a way to identify gaps in the history, flag any history that doesn’t qualify for use within the risk management calculation and support the use of third party sources where required to build the complete picture.
There is no doubt that the majority of institutions will have to turn to external third party data providers, including brokers and pricing providers, to fill the gaps in their time series data. However, poor validation is one of the biggest potential issues facing organisations creating the ES metric. Without strong screening mechanisms, there is a profound risk that erroneous data could be included in the calculations. For example, if a screen has not refreshed its quotes the result will be a flat graph showing the same price for some time – something that would clearly disqualify the history from the calculations.
Another challenge will be the use of proxies. If an institution opts to use another instrument to approximate or plug a gap in the history, it will be important to record on what basis the proxy has been used, and why, in order to prove to regulators the proxy’s validity as a comparable security.
Clearly to achieve a reliable picture of the market, it will be important to combine multiple data sources – adding quotes from market makers and taking the average. The ability to combine multiple inputs, identify outliers and validate data sources is required to build up and verify this ten year history.
It is only once the complete history of returns for each instrument is in place that organisations can begin to create the ES metric. At this point, the institution must then rank returns, sorting them from low to high, and then zoom in on the tail – the 2.5% of worst cases – and determine the average associated expected loss. In addition to the challenge of scanning these histories for the most stressful period for potentially thousands of risk factors, institutions will need to take into account different periods, ranging from ten to sixty days, depending on the liquidity horizon of the instrument.
Speed is essential. The ability to focus quickly on the worst 2.5% of returns for each risk factor is key – and demands an institution can scan and identify these thousands of risks on a daily basis. The immediate challenge, however, is to get that data infrastructure in place. Collecting, identifying gaps, introducing new sources, validating ten years of history across every single risk factor and quickly identifying the most turbulent periods for each time series will be a major project.
While FRTB will soon become a regulatory requirement, there are benefits to organisations over and above compliance. Firstly, this in-depth, accurate and validated data source can become the base upon which market shock/stress tests are applied – delivering another aspect of the regulatory demands in the US and Europe.
However, over and above any regulatory compliance, there are significant financial implications associated with FRTB. Any bank that fails to achieve the ES calculation with a validated risk and information infrastructure will lose the right to use its own internal models to run risk and will be forced to use the far coarser standard models from the regulators. The result will be a demand for far higher capital holdings – as much as five times higher according to some estimates. Essentially, get FRTB right and banks will be in a position to make more efficient use of their capital, which is a clear commercial benefit beyond regulatory compliance.
This is a major shift in both mind-set and technology – and the sooner organisations embrace a new, robust data management architecture, the better.
How has the online trading landscape changed in 2020?
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?
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.
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.
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.
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.
Economic recovery likely to prove a ‘stuttering’ affair
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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