Geuro: a Parallel Currency as Alternative to the Grexit?

CEIBS MBA programme
CEIBS MBA programme

Greece has been in recession for past seven years and has already partially defaulted. Greece already has a sovereign debt crisis. The Markets are already in turmoil with bond yields very high, and stock markets falling. Greece already has bank runs. Multinationals are not keeping money in Greek banks.

Due to unemployment of 23% and youth unemployment of 53%, there already is a political backlash, with growth of extremism on both left and right of political spectrum. Recent opinion polls suggest that a new Greek government will be dominated by parties rejecting the Toika-led adjustment programme.

The Greek euro exit is the speculated self-abdication – or dismissal – of Greece from the Eurozone. This is known as Grexit, a slang term introduced in 2012 in world business trading. It is a portmanteau combining the words Greek Euro Area exit. The term was introduced by Citigroup’s Chief Analysts Willem Hendrik Buiter and Ebrahim Rahbari on 6 February 2012.

Deutsche Bank’s economics team sees, however, the potential for an alternative path. This alternative idea facilitates running a Greek parallel currency to the Euro, which Deutsche Bank dubs Geuro to represent government issued IoUs to meet current payment obligations . This would enable, in Deutsche Bank’s view, Greece to engineer exchange rate devaluation without formally exiting the EMU (Economic and Monetary Union of the European Union).

The Greek Euro Exit scenario („Grexit“)

Compared to the hard struggle trying to recover while remaining in the Euro zone, a faster and more sustainable recover could happen if Greece decides to leave the Euro zone. Greece would begin to recover much faster if it is decoupled from the Euro, defaulted and devalued. The two biggest sectors of the Greek economy are shipping and tourism. Both could benefit hugely from a competitive devaluation.

„Plan Z“ is the name given to a plan to enable Greece to withdraw from the Eurozone in the event of Greek bank collapse. It was drawn up by officials at the European Commission (Brussels), the European Central Bank (Frankfurt) and the IMF (Washington). Those officials were headed by Jörg Asmussen (member of the executive board of the European Central Bank), Thomas Wieser (Euro working group), Poul Thomsen (IMF) and Marco Buti (European Commission).

In order to prevent premature disclosure no single document was created, no emails were exchanged, and no Greece officials were informed. The plan was based on the 2003 introduction of new dinars into Iraq by the Americans and would have required rebuilding the Greek economy and banking system from the beginning, including isolating Greek banks by disconnecting them from the Target 2 system, closing ATMs and imposing capital and currency controls.

The implementation of Grexit would have to occur „within days or even hours of the decision being made“ due to the high volatility that would result. It would have to be timed at one of the public holidays in Greece. In the long-term, Greece would see an improvement in domestic demand. Demand for imports would fall due to higher cost. Greece would benefit from higher exports and (if political situation stabilizes) an inflow of tourism. Furthermore, Greece would no longer feel it is following dictates of EU (i.e. Germany) and would have greater economic and political independence.

The parallel currency scenario („Geuro“)

Due to political pressure Greece might be unlikely to formally leave the euro, nor are the other euro area countries likely to abandon Greece entirely. The path of least resistance could be the stop of financial assistance to the Greek government and the continuation of payments for debt service and the stabilization of the Greek banks in a European “Bad Bank”.

In this case, a Greek parallel currency to the euro, the Geuro, could emerge when the government issues IoUs to meet current payment obligations. This would also allow Greece to engineer exchange rate devaluation without formally exiting EMU (see chart below). Initially there would be a large depreciation, but at the same time Greek authorities would reclaim some semblance of control to stabilize or even strengthen over time their own Geuro against the Euro. In fact this would leave the door open to a return to the Euro at some point.

Parallel currency exchange rate
Parallel currency exchange rate

6 Characteristics of Companies in Emerging Markets

CEIBS MBA programme
CEIBS MBA programme

Emerging markets offer plenty of opportunities for investors. By opening themselves to international trade, the structure of these markets is dramatically altered. Foreign and local investments flood the economy with the aim of gaining enormous returns. A massive reallocation takes place and demand explodes.

As a result of these disruptions, the number of mergers and acquisitions grows exponentially. Under these circumstances, it becomes of crucial importance to understand the nature of companies in emerging markets. Such companies share many of the following characteristics:

1. Unreliable market measures:
When valuing publicly traded companies, we draw liberally from market-based measures of risk. To illustrate, we use betas, estimated by regressing stock returns against a market index, to estimate costs of equity and corporate bond ratings and interest rates to estimate the cost of debt. In many emerging markets, both these measures can be rendered less useful, if financial markets are not liquid and companies borrow from banks.

2. Currency volatility:
In many emerging markets, the local currency is volatile. This is the case in terms of what it buys of foreign currencies (exchange rates), as well as in its own purchasing power (inflation). In some emerging market economies, the exchange rate for foreign currencies is fixed. This is creating the illusion of stability, but there are significant shifts every time the currency is devalued or revalued. Furthermore, when computing risk free rates, the absence of long-term default free bonds in a currency denies us one of the basic inputs into valuation: the riskfree rate.

3. Country risk:
There is substantial growth in emerging market economies, but this growth is accompanied by significant macro economic risk. Hence, the prospects of an emerging market company will depend as much on how the country in which it operates does as it does on the company’s own decisions. Put another way, even the best run companies in an emerging economy will find themselves hurt badly if that economy collapses, politically or economically.

4. Corporate governance:
Many emerging market companies used to be family-owned businesses and while they might have made the transition to being publicly traded companies, the families retain control through a variety of devices – shares with different voting rights, pyramid holdings and cross holdings across companies. In addition, investors who challenge management at these companies often find themselves stymied by legal restrictions and absence of access to capital. As a consequence, changing the management at an emerging market company is far more difficult than at a developed market company.

5. Discontinuous risk:
The previously mentioned country risk referred to the greater volatility in emerging market economies and the effect that has on companies operating in these economies. In some emerging markets, there is an added layer of risk that can cause sudden and significant changes in a firm’s fortunes. Included here would be the threat of nationalization or terrorism. While the probability of these events may be small, the consequences are so dramatic that we ignore them at our own peril.

6. Information gaps and accounting differences:
It is not unusual for significant and material information about earnings, reinvestment and debt to be withheld in some emerging markets, making it more arduous to value firms in these markets. On top of the information gaps are differences in accounting standards that can make it difficult to compare numbers for emerging market companies with developed market firms.

Data Science Toolbox: How to use R with Tableau

Recently, Tableau released an exciting feature that enhances the capabilities of data analytics: R integration via RServe. By bringing together Tableau and R, data scientists and analysts can now enjoy a more comprehensive and powerful data science toolbox. Whether you’re an experienced data scientist or just starting your journey in data analytics, this tutorial will guide you through the process of integrating R with Tableau.

Step by Step: Integrating R in Tableau

1. Install and start R and RServe

You can download base R from r-project.org. Next, invoke R from the terminal to install and run the RServe package:

> install.packages("Rserve")
> library(Rserve)
> Rserve()

To ensure RServe is running, you can try Telnet to connect to it:

Telnet

Protip: If you prefer an IDE for R, I can highly recommend you to install RStudio.

2. Connecting Tableau to RServe

Now let’s open Tableau and set up the connection:

Tableau 10 Help menu
Tableau 10 External Service Connection

3. Adding R code to a Calculated Field

You can invoke R scripts in Tableau’s Calculated Fields, such as k-means clustering controlled by an interactive parameter slider:

SCRIPT_INT('
kmeans(data.frame(.arg1,.arg2,.arg3),' + STR([Cluster Amount]) + ')$cluster;
',
SUM([Sales]), SUM([Profit]), SUM([Quantity]))
Calculated Field in Tableau 10

4. Use Calculated Field in Tableau

You can now use your R calculation as an alternate Calculated Field in your Tableau worksheet:

Tableau 10 showing k-means clustering

Feel free to download the Tableau Packaged Workbook (twbx) here.

Connect and Stay Updated

Stay on top of the latest in data science and analytics by following me on Twitter and LinkedIn. I frequently share tips, tricks, and insights into the world of data analytics, machine learning, and beyond. Join the conversation, and let’s explore the possibilities together!

Blog post updates:

Gartner Positions Tableau as a Leader for the First Time in BI Magic Quadrant

Screenshot of Tableau's 2013 February Newsletter featuring: "Gartner Positions Tableau as a Leader in 2013 Magic Quadrant"
Screenshot of Tableau’s 2013 February Newsletter featuring: „Gartner Positions Tableau as a Leader in 2013 Magic Quadrant“

One of the most highly anticipated and highly regarded reviews of the business intelligence market was published a couple of days ago. Gartner released its 2013 iteration of the famous Magic Quadrant for BI and Analytics Platform (aka. Gartner BI MQ) – and Tableau was cited as a „Leader“ for the first time.

Congraulations team Tableau!

Transition from Academia to Capgemini: A New Chapter in Data and Analytics

CERN Main Auditorium: my transition from academia to Capgemini
CERN Main Auditorium: my transition from academia to Capgemini

After enjoying research for the last four years, especially during my time at CERN, I have made a significant decision. I have decided to resign from my postgraduate position and make a transition from academia to the exciting world of Capgemini. My passion for Data and Analytics remains strong and will be the core focus of my new role.

Capgemini: A New Adventure After Academia

Capgemini, one of the world’s largest consulting corporations, has caught my attention. Unlike many other consulting companies, Capgemini does not yet have a dedicated team to offer effective strategies and solutions employing Big Data, Analytics, and Machine Learning. This presents an exciting opportunity for me to contribute and innovate.

My Vision: Building a Data-Driven Future at Capgemini

I love these technologies and am confident in my ability to elaborate a business development plan to drive business growth. Through customer and market definition, my plan includes new services such as:

  • Data Science Strategy: Enabling organizations to solve problems with insights from analytics.
  • Consulting: Answering questions using data.
  • Development: Building custom tools like interactive dashboards, pipelines, customized Hadoop setup, and data prep scripts.
  • Training: Offering various skill levels of training, from basic dashboard design to deep dives in R, Python, and D3.js.

This plan also includes a go-to-market strategy, which I’ll keep under wraps for now. Stay tuned for a retrospective reveal in the future!

Reflecting on My Transition from Academia

Making this transition from academia to a corporate role has been a considered decision. As I previously shared in my reflection on my software engineering internship at SAP, the blend of technological challenges and team collaboration has always intrigued me. Joining Capgemini allows me to continue pursuing my passion for data in a dynamic business environment.

Conclusion: Exciting Times Ahead

This transition from academia to Capgemini marks a thrilling new chapter in my career. I look forward to leveraging my expertise in Data and Analytics to contribute to Capgemini’s growth and innovation.

Follow my journey as I explore the intersection of data, technology, and business. Connect with me on Twitter and LinkedIn.