Graphs with no time line – why and how

| 7-8-2017 | Lionel Pavey |

A key role within the Treasury function is providing forecasts to the directors and management. Graphs are a frequently used tool of course.
When constructing graphs it is normal to put time on the horizontal x axis and read the prices from left to right – from old to new. Visually, this appeals to us as we normally read from left to right. However, when the price does not change much for a long period of time the graph no longer looks fluid – there is a period of activity, followed by a long period of almost standing still, followed by another period of activity. To try and eliminate this period of inactivity whilst still presenting the data requires an approach where sequential time is removed from the equation. This brings us to the last article in this series.

The following two graphs ignore time and focus purely on changes in the price that have been filtered to meet specific criteria.

Renko Charts

 

Prices are represented by blocks – hollow for upward movements and solid for price falls.

Every block has a predefined value – if we were showing interest rates a block could represent 5 basis points. If we had an upward price movement this means that the following upward block can only been drawn once prices have risen more than 5 basis points from the last block. If the price moved up 4 basis points and then dropped by 3 basis points, no additional blocks would be added to the graph.

Blocks are plotted at a 45 degree angle showing upward and downward sloping price changes.
Price reversals are shown when prices have moved more than 2 blocks in the opposite direction. Yet again if we had an upward slope and the price was 1.25 (our blocks are set to 0.05 or 5 basis points) we would require a downward movement of more than 0.15 (15 basis points) to 1.10 to draw 2 solid blocks downwards.

What remains is a very smooth representation of price movements with a uniform value for every block, whilst filtering out smaller movements that have been filtered out by the conditions set on block size.

Point and Figure Charts

Price changes are represented by vertical columns – X’s for rising prices and O’s for falling prices.
As with Renko charts, the X’s and O’s have a predetermined size and a price reversal is shown when prices change by 3 boxes as opposed to 2 on a normal Renko chart. When direction changes a new column is drawn to the right of the present column. Otherwise, the same criteria is applied to both charts except point and figure show true vertical columns as opposed to 45 degree lines.

So why would someone look at prices in this particular way? Such a chart does not necessarily show the latest price – the predefined filters ensure that only price changes that meet the criteria are shown.

The main advantages include:

  • A constant filter that reduces the noise associated with normal time charts
  • Analysis is based only on movement – not on time
  • Perceived support and resistance levels are easier to see
  • The current trend is very clear to see

All the techniques shown in this series are applicable to everyday analysis and everyone has their favourite approach. Some like to see all data, whilst others prefer to see filtered, smoother data. The eternal question when looking at charts and seeing the current trend is to ask “where will the price go?” Initially, the immediate answer is that price will follow the current trend until such time as it does not anymore. This might seem a cheap flippant answer, but it is the truth. We have firmly established that we need to know the price in the past to determine if the present price movement is in a clearly established trend. If we knew nothing about the price in the past it would be pure guesswork to say which way the price would go?

We could still be wrong however, but at least we can establish why and how we made our opinion.

No chart or charting system can clearly determine what the future price will be with 100 per cent accuracy. By following the trend we can at least say what the current market direction is, without being able to clarify, purely on price, when the market will change direction.

Charts that eliminate time make it easier to see where the top and bottom of the market prices have been established. Therefore, if we are in an upward trend and approaching a market high that has been reached twice before, we can state with a reasonable amount of confidence that we are approaching a level that the market has tested twice before but not been able to break above. This would imply, on a technical analysis, that there is perceived resistance in the market to taking the price above the previous high.

However, a word of caution when using charts.
The best analogy I have ever heard for not relying 100 per cent on charts is as follows:

Would you sit behind the steering wheel of a vehicle and drive forward whilst the windscreen was blacked out and only have the rear view mirror to show you where you have been and only have that information to decide when you had to steer?

There is no system that can guarantee telling you what the future price will be. Analysis has to be taken with a pinch of salt but, any market professional should be able to perform analysis. If you can not analyse then you can not predict.

Lionel Pavey

 

Lionel Pavey

Cash Management and Treasury Specialist


You might have missed the first two articles of this series and can find them here:

Treasury for non-treasurers: Data analysis and forecasting – seeing the future by looking at the past (Part I)

Treasury for non-treasurers: Data analysis and forecasting – Seeing the future by looking at the past (Part II)

 

Re-inventing treasury workflows: Smart Treasury

| 3-8-2017 | Nicolas Christiaen | Cashforce | Sponsored Content |

While the role of the treasurer is changing, it becomes increasingly challenging to maintain the current workflows and simultaneously take on new demanding tasks. One of these often manual and time-consuming tasks is risk management. As seen in, among others, this year’s Global Treasury Benchmark Survey of PwC, the registration and management of financial instruments stands among the top 3 challenges on the agenda of the surveyed treasurers. In this article, we take a more in-depth look at possible optimizations in some key treasury workflows.

 

 

 

 

 

 


Example FX management workflow

Hedging your FX exposure risk made easy

A common problem is the lack of visibility on the existing (global/local) FX exposure risk.
In order to calculate the FX transaction risk, transactional data from the TMS & ERP systems need to be consolidated effectively. Typically, this happens to be a (very) painful exercise. With Cashforce, however, using our off-the-shelf connectors (for ERP & TMS) and our full drill-down capabilities, you have all FX exposures at your fingertips.

 


FX Exposure Management – Current positions & exposures

 

But there is more to it. Imagine that linked to your FX exposure, an automated proposal of the most relevant FX deal would be generated to properly hedge this risk. A grin from ear to ear you say?


FX Exposure Management – Suggested hedge

 

And what about forecasting FX exposures? It’s now all within reach!

FX Exposure Management – Future positions & exposures

 

Whether you choose to take on an intercompany loan, a plain vanilla FX forward or another more exotic derivative product, chosen deals could then be automatically passed on to your deal transaction platform, to effectively execute the deal without any hassle. After execution, deals will automatically flow back into the system. Consequently, a useful summary/overview will be generated to effectively manage all your financial instruments.


Workflow integrated cash forecast

Finally, integrated cash management

New financial instruments / deals will generate a set of related cash flows. Ideally, these are directly integrated in your cash flow forecasts. In Cashforce, this data is automatically integrated within the cash flow forecast module, and will be put into a dedicated cash flow category. Learn more one how to set up an effective cash forecast in this article or this webinar.


Cash flow forecast overview

 

The analysis possibilities are now limitless, thanks to the ability to drill down to the very transactional-level details. The real number crunchers strike gold here: the analysis features open doors to unlimited in-depth analysis and comparison of various scenarios (E.g. the simulated effects of various exchange rate movements).


Drill-down to the transaction level

 

Using our big data engine, the delivery of rich and highly flexible reporting is facilitated. It’s fair to say that the typical SQL server (which currently 95% of the TMS systems use) can’t hold a candle to this. Through an advanced ‘self-service’ interface, users can drill down completely into respective amortization tables, historical transactions and effortlessly create customized reports and dashboards. We’ll talk more about why we believe Big Data engines are crucial for any Treasury software in our next blog.

Integration with ERPs & payment platforms

Next to this, Cashforce will automatically generate the accounting entries (in the format of your ERP/accounting system) related to your deals. The appropriate payment files will be generated in a similar fashion.

So…

As might be clear after reading this article, we strongly believe that integrated data flows & a Big Data engine are the foundation of a new type of Treasury Management System that runs like clockwork and can serve effective treasury departments, but also renewed finance/controlling/FP&A departments.

You are curious to hear more about effective treasury management? We’ve recently recorded a webchat on how to set up an efficient cash flow forecast process.

 

Nicolas Christiaen

Managing Partner at Cashforce

 

Bitcoins or banks, who is taking care of the business?

| 2-8-2017 | Hans de Vries |

Banks have long been target of wild spread ideas that their role as facilitator in the (inter) national money transaction industry will soon be overtaken by new Fintech initiatives like PayPal, Bitcoin and recently Ethereum. The idea behind these new technologies is that the Trusted Third Party (TTP) role of the conventional banks which is crucial for the operational day to day operations of the economic systems can be overtaken by the new block chain technology. Main advantages are clear: transactions are no longer limited by timing (no dependency on the operational boundaries of clearing houses, cut-off times of banks per currency, immediate processing etc), account opening procedures at the banks, the costs involved in maintaining accounts and transactions themselves etc.

The recent Ransomware attacks, that had an enormous impact on numerous companies and governmental institutions at a global level, showed however a less favorable aspect of this new technology. Due to its lack of control on the specifics of account ownership, Bitcoin proved to be the ideal means to collect the ransom money the victims have to pay to free their systems. This piracy trend will in my view also seriously hamper the future development of these sort of bank independent transaction mechanisms. Even more threatening for the Bitcoin development are the recent crypto robbery cases in which millions of dollars’ worth balances were stolen from the accounts. These incidents show the vital role of the banks as TTP since most banks are obliged to deliver their services according to the rules and regulations of their national and super-national banks. As indicated before, this means that for opening accounts lots of formalities have to be endured (the KYC rules are in some countries stretched to the absolute max). At the same time., due to the international regulations the control on international transactions are very extensive and therefore at the same time very costly for the banks. Every violation of the international code book on transactions to banned countries can have severe financial consequences for the banks involved. An last but not least banks have to maintain an international network of correspondent banks to make sure that the international transactions reach their beneficiaries in a reasonable timeframe and at reasonable costs.

This whole system has of course been developed to gain maximum control on transaction flows locally and worldwide. However it also provides the trust needed to be able to deal with (inter) national trade flows crucial to our economic day to day operations. As long as there are no ways to secure your transactions and balances in a bitcoin like environment as most transaction banks are providing today, Bitcoins remain a very interesting technological experience but will in no way replace the role of banks as TTP shortly.

 

 

Hans de Vries

Treasury/Cash Management Consultant

 

 

More articles of this author: 

Will the European banks strike back?

The Euro from a treasury perspective

New norms in banking: More than 30 new areas emerging. Pick your fights!

Moving Averages – how to calculate them

| 1-8-2017 | Lionel Pavey |


In the second article in this series we will be looking at different types of moving averages. Moving averages are used to determine the current trend of a price. They filter out the extremes within a range of data and present a smoother picture. They are almost exclusively calculated using the arithmetic mean. Some studies have been done using the median, though no advantages have been discovered. The following 3 methods are the most common approaches. In all following examples we shall assume an average calculated over a continuous series of 10 data points.

Simple Moving Average (SMA)

We take 10 consecutive values and calculate the simple arithmetic mean. When we calculate the next value we drop the oldest value in the series and add the newest value. We are constantly using the most current data in our calculation. Every data point receives the same weighting i.e. 10 per cent of the complete series. Whilst being very easy to calculate criticism is levelled at the fact that all data points receive the same weighting. This can distort the average when the market is volatile – more recent data is closer to the true market price.

Weighted Moving Average (WMA)

Here the 10 data points are assigned different weights, usually based on a simple mathematical progression. The 10th data point (most recent data) would be multiplied by 10; the 9th data point (second most recent data) would be multiplied by 9; etc. The product of these calculations would then be divided by 55 to produce a weighted average. This weighted average applies more importance on the most recent prices and, therefore, more closely match the current price.

Exponential Moving Average (EMA)

This is another form of a weighted average, but the weighting factors decrease exponentially. As such, whilst the older data points decrease exponentially in value, they never stop. Therefore, this average encompasses considerably more data than the previous 2 examples whilst still being an average calculated with only 10 data points.

The results

EMA is more responsive than SMA. An EMA graph will accelerate faster, turn quicker and fall faster than a SMA graph. This is due to the weighting given to the most recent data. However, these are all lagging indicators – they will always be behind the price. Furthermore, if a market is trapped in a very small trading range the averages will not be as smooth as the actual data. One of the main goals of using averages is to see if prices break out of a range and start a new trend.

Moving averages can be used simply to see what the current trend is. They can be further used by applying different 2 moving averages (one for 10 days and another for 50 days) to ascertain the change in momentum by 2 different time lines. But they all lag the market data.

Most of the time prices will tend to concentrate in a small area, with occasional larger movements up or down establishing the next area of consolidation. Is there an alternative way to design moving averages that take this into consideration?

Adaptive Moving Average (AMA)

Instead of just weighting the data, AMA also look at the price volatility. When prices are in a small range AMA will notice this lack of volatility and provide a trendline that is almost flat. As prices break out of the range AMA will move quickly up or down, depending on the change in prices. The advantages of AMA are that, visually, when prices are reasonably flat (little volatility) a clear flat line is shown so that even if the actual market price is lower than the AMA, it is clear that it is still within a range. As AMA is more sensitive to volatility, it can contain more data about the current trend. An initial breakout from a tight range will result in a very steep line for AMA. The trend can continue, but AMA will clearly show earlier than other averages when the trend is weakening. The only basic problem with AMA is the calculation – it is far more complex to calculate and is not so intuitive when you come to explain it to someone who does not know it.

As stated earlier, all moving averages suffer from lag – they are behind the actual price curve. Our last example is an average that attempts to remove this lag, whilst being more reactive to the current price.

Hull Moving Average (HMA)

Initially, a WMA is taken for 10 data points. Then a WMA is taken for half this period (5 data points) and is calculated with the 5 newest data points. The difference between these 2 is then combined with the WMA for the shorter period to arrive at a new average – the HMA.

The HMA is faster, smoother and eliminates most of the lag that is present in the other moving averages. In fact, it most closely resembles the actual market data.

All these averages are used to attempt to show what the trend is in the actual price, whilst filtering out the noise from all the prices, and presenting the data in a smooth form. Yet again, as previously mentioned, a change in the underlying fundamentals of the price will always have more impact on the price than any form of technical analysis.

However, if we concede that for a large majority of time prices are just trending, a moving average can be used to try and predict when the prices have moved out of their range and are on a new path with fresh momentum until that slows down and the following range is established.

When charting data we need to appreciate the amount of data we will be producing. Even if we just use the price at the start of the day, or the end of the day, we will accumulate at least 255 data points every year. If prices are in a small range, then more data is added to the chart series to provide a more dynamic picture. But this can make the visual data more cluttered once we include the actual data and 1 or 2 moving averages. Would it not be better if we could eliminate time and just look at price?

Read also my first article in this series where I tell you more about several types of forecasts.

In the last article in this series I will look at 2 common methods of showing price data devoid of timelines.

Lionel Pavey

 

Lionel Pavey

Cash Management and Treasury Specialist

 

Preparing the roll out of instant payment services: testing EBA’s RT1 platform

| 31-7-2017 | Jan Meulendijks | Finextra |

Instant payment services become more popular. UniCredit is testing the EBA Clearing’s RT1 real-time platform and preparing for the roll out of this service to 30 banks in Italy and Germany. Last week Finextra published an article about this development. Our expert Jan Meulendijks gives his opinion about the EBA Clearing’s RT1 real-time platform.

EBA’s RT1 is a probably a life-saving step for the banking/financial world as we know it today. SEPA was of course a major improvement in speeding up cross-border EURO-payments, but still the clearing process and therefore also the required processing time, was rather something from the 20th century and not up to today’s technical standards.

Without RT1 (and maybe similar developments yet to come) the banks are about to lose their payment processing activities and the related profits to other parties, mainly in the public domain (Blockchain) and ITC-sector. Microsoft, Google and Apple are names that will be appearing in this industry.

Remarkable: Italian banks seem to be fore-runners in joining RT1. Italy has always been infamous for the archaic infrastructure of their local and cross border payment systems. The slogan “what is backward will become forward” seems to apply here.

Jan MeulendijksJan Meulendijks – Cash management, transaction banking and trade professional

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More articles that might be interesting to read:

SEPA Instant Payments – a catalyst for new developments in the payments market (part I)

Instant payments for treasurers

Instant Payments: the SEPA Instant Payments rulebook is published, what’s next?

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The Digital Trade Chain: the blockchain train is rolling

| 28-7-2017 | Carlo de Meijer |

Trade finance is increasingly becoming the number one use case for blockchain with the greatest potential to benefit from this technology. In previously blocks I already showed the accelerated activity in this area (see: Blockchain and Supply Chain Finance: the missing link May 7, 2017 and Blockchain: accelerated activity in trade Finance, January 26, 2017).

End seven European banks, forming the so-called Digital Trade Chain consortium, announced their plans to develop in collaboration with IBM a trade finance platform based on blockchain technology. This is said to become the first real-world application of blockchain technology and might become the start of more of the blockchain train.

What is the Digital Trade Chain consortium?

In January this year seven European banks (Deutsche Bank, HSBC, KBC, Natixis, Rabobank, Société Générale and UniCredit) signed a Memorandum of Understanding (MoU) in Brussels to create the Digital Trade Chain consortium. Under this MoU the banks intend to collaborate on the development and commercialisation of a shared supply chain management and trade finance platform for small and medium-sized companies (SMEs) using blockchain technology. That platform, called the Digital Trade Chain (DTC), should make domestic and cross border commerce easier for European SME business.

The aim of the project is to simplify trade finance processes for SMEs by “addressing the challenge of managing, tracking and securing domestic and international trade transactions.

Read the full article of our expert Carlo de Meijer on LinkedIn

 

Carlo de Meijer

Economist and researcher

 

Forecasting the future by looking at the past

| 25-7-2017 | Lionel Pavey |


A key role within the Treasury function is providing forecasts to the directors and management. The most obvious would be the cash flow forecast, but others would include foreign exchange prices, interest rates, commodities and energy.

A forecasts is a tool that helps with planning for the uncertainty in the future, by analyzing data from the past and present whilst attempting to ascertain the future.

Internal – cash flow forecast

We would like our forecasts to be as accurate as possible – that the values we predict are close to the actual values in the future. This requires designing a comprehensive matrix to determine the variables needed for the data input. Data has to be provided by all departments within a company to enable us to build a forecast. This data needs to be presented in the same way by all contributors so that there is consistency throughout.

We also have to see if the forecast data is within the parameters of the agreed budget. We also need to check for variances – why is there a difference and how can it be explained.

External – FX and Interest Rates

A more common approach is to read through the research provided by banks and data suppliers to try and see what the market thinks the future price will be. Also we need to include data from the past – we need to know where the price has been, where it is now and what the expectation is for the future.

Extrapolating forward prices is notoriously difficult – if it were simple, we would all be rich in the future! But, by including past data, we can see what the price range has been, both on a long term as well as a short term basis.

When attempting to find a future value there are 2 common methods used – fundamental and technical.

Fundamental Analysis

Use is made of economic and financial factors both macroeconomic (the economy, the industrial sector) and microeconomic (the financial health of the relevant company, the performance of the management). The financial statements of a company are analysed in an attempt to arrive at a fair value. This leads to an intrinsic value, which is not always the same as the current value.

The value is normally calculated by discounting future cash flow projections within the company.

Technical Analysis

Use is made of the supply and demand within the market as a whole and attempts to determine the future value by predicting what the trend in the price should be. This is done by using charts to identify trends and patterns within the data. This assumes that the market price now is always correct, that prices move in determinable trends and that history repeats itself. Technical analysis uses the trend – this is the direction that the market is heading towards.

Whilst these 2 approaches are independent of each other, they can be used together. You could take a fundamental approach to value a company or asset, and then use technical analysis to try and determine when you should enter and exit the market.

Fundamental analysis is more of a long term path and technical analysis is more short term. The most important thing to remember is that markets only really experience large movements based on changes to the fundamentals. Predicting the long term future only via technical analysis is likely to be incorrect. All the major movements over the last 50 years in the prices of shares, bonds, foreign exchange and interest rates have occurred because of a change in the fundamentals.

In the next article, I will look at various methods of calculating averages to determine the trend.

An economist is an expert who will know tomorrow why the things he predicted yesterday didn’t happen today.

Lionel Pavey

 

Lionel Pavey

Cash Management and Treasury Specialist

 

Why does Apple issue a green bond? Spoiler alert: I do not know (yet)

24-7-2017 | Pieter de Kiewit | treasuryXL |

Recently we had an “inner circle meeting” of treasuryXL in which we talk about developments and the direction we want to go. One of the invitees suggested we pay special attention to sustainable financing and related topics. I agree that this topic is quite prominent and this reminded me about a recent article in which a so-called “green bond issue” by Apple is described. This was the second issuance by them and raised $1 billion. Then my corporate treasury laymen’s mind started working and so far it has not stopped about this topic.

At the start of this year Apple was in the news because of the huge pile of cash in their books. The amounts are staggering and most likely not accurate. Repatriating this cash to the US would be suboptimal from a fiscal perspective but that is a topic for another blog. The funds raised with the green bond will be used to start projects around renewable energy and buying of safe raw materials.

The puzzle for me is: if you have all this cash, why would you do a bond issue? It is a lot of hassle, why not leverage the money you have? If you think this is a smart investment, why not invest yourself?

One of my colleagues suggested they do this from a marketing perspective. I don’t know about you, but I will not buy an Apple instead of a Samsung because of a green bond. So this is not the reason I expect. Perhaps it is a risk mitigation strategy in a project Apple will invest in anyway. My question to the corporate treasury and banking community: Do you know why?

Thank you for your answer and I will try to focus on other blog topics around sustainability and corporate treasury. I am convinced more obvious are available.

Pieter de Kiewit

 

 

Pieter de Kiewit
Owner Treasurer Search

 

 

Another interesting article about funding:

Business case – Funding strategy: how Fastned uses Nxchange

Banken en Financiële Markten in Vogelvlucht – Boek en e-learning voor specialisten zonder financiële achtergrond

| 21-7-2017 | Michiel van den Broek |

 

Sinds de jaren ’80 heeft er een ongekende schaalvergroting plaatsgevonden in de financiële sector. Door deze schaalvergroting hebben banken zich ontwikkeld tot gigantische financiële supermarkten die een zeer uitgebreid aantal financiële diensten en producten aanbieden. Banken zijn tegenwoordig IT-bedrijven waar een grote groep specialisten werkt met beperkte financiële vakkennis.

 

 

Mijn boek ‘Banken en Financiële Markten in Vogelvlucht’ geeft een helder overzicht ter introductie in de complexe wereld van banken en financiële markten. Bij het boek is een toegankelijke e-learning training beschikbaar met multiple choice vragen en een aantal video’s.

De combinatie van boek met e-learning biedt een efficiënte opleiding met basiskennis over de kernactiviteiten van banken, de verschillende bankactiviteiten en soorten banken, de oorzaak van de financiële crisis van 2008 en de ‘Bazelse Akkoorden’ waarop het toezicht van centrale banken is gebaseerd. Tevens bevat het een overzicht van de verschillende activiteiten op financiële markten, zoals de motivatie om bepaalde soorten financiële (derivate) producten te verhandelen, de prijsvorming en organisatie van de handel van deze producten. Ook de actuele onderwerpen risicomanagement en compliance komen aan de orde aan de hand van een aantal praktijkvoorbeelden van calamiteiten, zoals de problemen met MKB-rentswaps en de onbevoegde handelsactiviteiten van zogenaamde ‘rogue traders’, waaronder Barings Bank en woningbouwcorporatie Vestia.

Het boek is verkrijgbaar voor €25, toegang tot de e-learning kost €95.

Voor het boek en de e-learning kunt u mailen naar [email protected]

Een demo van de e-learning kunt u vinden op FTH.

Over de auteur: na mijn bedrijfseconomische studie heb ik vanaf 1990 gewerkt in de financiële sector. Sinds 2005 geef ik trainingen om ‘complexe’ financiële onderwerpen toegankelijk te maken voor professionals zonder economische of financiële opleiding.

 

Michiel van den Broek

Owner of Hecht Consult

Mobile finally makes treasury easier

| 20-7-2017 | Udo Rademakers |

On the 12th of May 2017, in GTnews an article has been placed regarding “Mobile finally makes treasury easier”. The article describes how Citibank is working to replace tokens with mobile phones and testing a multitude of options for finding a more convenient solution.

I am used to work with multiple tokens with a variety of passwords and different kind of banking applications/websites. For some of the banking sites, authorisation of payments via a smart phone was quite difficult and working from the desktop was required. A way of solving the „multiple token issue”, is using a third party provider which (re)connects all payments via (cloud based) multi-bank platforms, however this is not needed for each and every Treasury department.

If banks are working on an easy authorisation method via modern, smart and above all secure technology (like digital fingerprint ), I am confident that the payment control and executions for most Treasurers (and CFO`s) will improve. Especially for the ones who are frequently travelling. If the improved –token free- payment authorisation process could be integrated with the process of obtaining information, input & approval of transactions, viewing of balances including „smart alerts“, corporate banking via mobile technology will reach the next stage in the area of cash management as well.

However, even with the greatest solutions in place, an outage of mobile network or running out of battery remains a risk – now the holiday season started perhaps anyway good to be offline for a while.

 

Udo Rademakers
Independent Treasury Consultant & Interim Manager