Financial maps

Financial maps

Prof. François Longin

A new for this website: Financial maps

The financial maps provide a visual representation of key financial measures of financial markets worldwide.

The current version focuses on the following performance and risk measures:

  • Performance measured by the average return
  • Risk measured by the Value at Risk (VaR)
  • Extreme risk measured by the Stress Value (SV)

You will find below an example of financial maps for the equity markets. For each country, we chose the equity index that best represented the national market.

Performance map

Performance map

Risk map

Risk map

Extreme risk map

Extreme risk map

The financial map for extreme risk is based on the following academic research:

Longin F. (1996) The asymptotic distribution of extreme stock market returns Journal of Business, N°63, pp 383-408.

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. and B. Solnik (2001) Extreme correlation of international equity markets Journal of Finance, N°56, pp 651-678.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

This project will be regularly updated with new financial data and relevant measures.

More information about financial indexes

The basics to know about financial indexes:

   ▶ Financial indexes

   ▶ Calculation of financial indexes

   ▶ Float

Examples of countries covered by the financial maps:

   ▶ The United States The S&P 500 index

   ▶ China The CSI 300 index

   ▶ The United Kingdom The FTSE 100 index

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Is bitcoin the new digital gold?

Is bitcoin the new digital gold?

Konstantinos Gkillas Patras University Article on capital controls

Is bitcoin the new digital gold? Ten years after the seminal work of Satoshi Nakamoto in 2008, at which time he introduced the bitcoin, a heated debate has started about this matter, and a wide audience has participated, including academics, practitioners (asset managers, financial advisors and investors) and journalists in the financial press. Although bitcoin and gold are two basically different assets in several respects (free of sovereign risk and independent from regulatory authorities), their statistical behavior leads us to consider if bitcoin – similarly to gold – could provide diversification benefits during downside market conditions. Such market conditions are a primary concern for investors.

To contribute to the current debate for the role of bitcoin as a new digital gold, we examine the potential benefits of bitcoin during extremely volatile periods in financial markets, using the multivariate extreme value theory. This statistical theory is the appropriate approach to model the tail dependence structure.

For our analysis, we focused on the correlation of extreme returns and we adopted a four-step research strategy.

Step 1. We considered a position in equity markets (Europe and the United States). We found that the extreme correlation increases during stock market crashes and decreases during stock market booms.

Step 2. We combined each equity market with bitcoin. We found that the correlation of extreme returns sharply decreases during both market booms and crashes. This means that bitcoin can play an important role in portfolio risk management during extreme market movements.

Step 3. We combined each equity market with gold. We found a similar result, confirming the well-recognized status of gold as a safe haven.

Step 4. We examined the joint behavior of bitcoin and gold. We found a low level of extreme correlation. This means that bitcoin and gold can be useful together in an equity portfolio in times of turbulence in financial markets.

Is bitcoin the new digital gold?

Our findings showed that bitcoin can be considered as the new digital gold. However, gold is still important in an equity portfolio. To the question: “Is bitcoin the new digital gold?” we answer that both bitcoin and gold are the best choice.

Gkillas, K. and Longin, F. (2018). Is Bitcoin the New Digital Gold? Evidence from Extreme Price Movements in Financial Markets. http://dx.doi.org/10.2139/ssrn.3245571

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ESSEC Workshop on “Nonstandard Investment Choice” – September 20, 2019

The ESSEC Finance Department is delighted to organize a Workshop on “Nonstandard Investment Choice” that will take place on September 20, 2019 at ESSEC Campus in Cergy.
To register, please use our Eventbrite space.
Please visit our website to consult the program: http://energy-commodity-finance.essec.edu/essec-workshop-on-nonstandard-investment-choice/

Sincerely yours,
Andrea Roncoroni & Roméo Tédongap – Co-Organizers

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ESSEC Workshop on Nonstandard Investment Choice – 20/09/19

SUBMISSION DEADLINE: April 30th, 2019

Click here to submit your paper:
https://easychair.org/my/conference.cgi?conf=nsic2019h

ESSEC Business School is delighted to organize a Workshop on “Nonstandard Investment Choice” that will take place on September 20, 2019 at ESSEC Campus in Cergy.

This workshop aims at bringing together, during a full one-day event, international scholars doing research in a wide range of topics including, but not limited to, behavioral portfolio choice models, asset allocation with derivatives, portfolio insurance, hybrid portfolios, crypto-assets and blockchain, energy and commodity assets, alternative investments, and frictional asset allocation.

The submission deadline is on April 30th, 2019.

Please consult our website for more information: http://nsic.essec.edu/

Sincerely yours,
Andrea Roncoroni & Roméo Tédongap – Co-Organizers

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Is bitcoin the new digital gold?

Is bitcoin the new digital gold?

Konstantinos Gkillas Patras University Article on capital controls

Is bitcoin the new digital gold? Ten years after the seminal work of Satoshi Nakamoto in 2008, at which time he introduced the bitcoin, a heated debate has started about this matter, and a wide audience has participated, including academics, practitioners (asset managers, financial advisors and investors) and journalists in the financial press. Although bitcoin and gold are two basically different assets in several respects (free of sovereign risk and independent from regulatory authorities), their statistical behavior leads us to consider if bitcoin – similarly to gold – could provide diversification benefits during downside market conditions. Such market conditions are a primary concern for investors.

To contribute to the current debate for the role of bitcoin as a new digital gold, we examine the potential benefits of bitcoin during extremely volatile periods in financial markets, using the multivariate extreme value theory. This statistical theory is the appropriate approach to model the tail dependence structure.

For our analysis, we focused on the correlation of extreme returns and we adopted a four-step research strategy.

Step 1. We considered a position in equity markets (Europe and the United States). We found that the extreme correlation increases during stock market crashes and decreases during stock market booms.

Step 2. We combined each equity market with bitcoin. We found that the correlation of extreme returns sharply decreases during both market booms and crashes. This means that bitcoin can play an important role in portfolio risk management during extreme market movements.

Step 3. We combined each equity market with gold. We found a similar result, confirming the well-recognized status of gold as a safe haven.

Step 4. We examined the joint behavior of bitcoin and gold. We found a low level of extreme correlation. This means that bitcoin and gold can be useful together in an equity portfolio in times of turbulence in financial markets.

Is bitcoin the new digital gold?

Our findings showed that bitcoin can be considered as the new digital gold. However, gold is still important in an equity portfolio. To the question: “Is bitcoin the new digital gold?” we answer that both bitcoin and gold are the best choice.

Gkillas, K. and Longin, F. (2018). Is Bitcoin the New Digital Gold? Evidence from Extreme Price Movements in Financial Markets. http://dx.doi.org/10.2139/ssrn.3245571

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Financial market activity under capital controls: Lessons from extreme events

Financial market activity under capital controls: Lessons from extreme events

Konstantinos Gkillas Patras University Article on capital controls

This post presents a recent article by Gkillas and Longin published in Economics Letters (2018). In this article we investigate the relation between extreme return and transaction volume under the restrictions on transactions. We use bivariate extreme value theory to model the tail dependence structure. We show that restrictions on transactions have an impact on the activity of market participants.

The market activity and, therefore, the behavior of market participants is measured by the transaction volume. The stylized fact assumes a positive correlation between returns and volumes. However, contradictory results are obtained considering extremely volatile periods.

Such periods in combination with a financial crisis of a domestic origin, like the Greek crisis, can lead to strict intervention policies such as capital controls. The sovereign debt crisis in Greece led to the use of a financial support rescue mechanism by the European Monetary Union and the International Monetary Fund early in 2010. The domestic authorities imposed several restrictions on transactions. The Athens Stock Exchange stopped trading for more than two months and then opened to a dramatic decline. Greece became one of the few cases of a Eurozone country implementing such austerity policies.

In our work, we show that these long-term restrictions can be avoided. To this end, we apply bivariate extreme value theory. We show that capital controls have a significant negative impact on the activity of market participants. Therefore, we propose an automatic intra-day circuit-breaker mechanism when the market moves downwards and exceeds a specific threshold, in order to avoid not only the panic selling but long-term distortions for closing of the market.

Gkillas K. and F. Longin (2018) “Financial market activity under capital controls: lessons from extreme events” Economics Letters, 171C, 10-13.

You can download this paper via the following link: https://authors.elsevier.com/c/1XLFobZedijjr

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Mathematics for Industry: Blockchain & Cryptocurrencies Conference

Mathematics for Industry: Blockchain & Cryptocurrencies Conference

A one-day conference Mathematics for Industry: Blockchain and Cryptocurrencies is due to be held in the School of Mathematics at the University of Manchester, UK, on 8th September 2018.

The aim of the workshop is to strengthen the ties and bridge the gap between academics and industry, and also enthusiasts. This will provide an opportunity to promote and share recent research and developments in the relatively new area of blockchain and cryptocurrencies. The workshop will feature invited talks from academics and those in industry, in addition to contributed talks and a poster session.

This conference will allow us to learn about how these two key tools are being used by both sides, and how academic research can support work in industry. The meeting will also strengthen and promote mathematics for industry regionally, in the UK, across the EU, and also in the Middle East.

Conference Blockchain Cryptocurrencies

Prof. François Longin
ESSEC Business School

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Congratulations to Shashwat Gangwal for his best award paper

Congratulations to Shashwat Gangwal for his best award paper

Prof. François Longin

It seems that Bitcoin is a hot topic these days. In fact, many of my students at ESSEC Business School have invested (real) money in cryptocurrencies. When I started to do research on the behavior of Bitcoin prices, especially extreme price movements, the topic was not so trendy…

Research paper

Since the introduction of Bitcoin in 2010, Bitcoin prices have shown dramatic volatility. It is associated with impressive booms and crashes. I’ve written a research paper on the subject with Shashwat Gangwal. Shashwat is an extremely bright undergraduate student at Indian Institute of Technology Kharagpur. In our paper, we use extreme value theory to investigate the statistical distribution of extreme price movements. We also compute risk measures commonly used in both risk and asset management by financial institutions. We also draw some conclusions about the status of Bitcoin as a currency or a speculative asset and how governments should deal with it.

Best award paper

I am extremely pleased to announce that Shashwat received the “Best Paper Award” at the International Conference on Finance and Economics Research in Prague 2018. It was conferred on Shashwat by Professor Jiří Strouhal, who’s been a President of Association of Czech Professional Accountants since 2011.

Congratulations to Shashwat for this astonishing performance!

Financial markets

Prof. François Longin
ESSEC Business School

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Extreme Operational Events

Extreme Operational Events

Maxime Laot ECB

This post about extreme operational events was added by Maxime Laot supervisor at European Central Bank.

Another type of extreme events

Extreme events in finance do not consist in stock market crashes only. Unfortunately, their scope is much broader than the volatility of asset prices such as stocks, bonds, commodities or currencies. Extreme events occur as well in the normal run of financial institutions, or in other words, in their daily, trading and non-trading operations. Actually, one could argue that frauds, fat fingers errors, rogue traders, AML and conduct issues have caused – and are still causing – more harm to large financial institutions than any stock crashes have done in the past!

Operational risk

This type of risk is branded “operational risk” by the financial sector, and the Wiley Handbook on Extreme Events in Finance explains how it has been first formalized by the banking regulators (i.e. the Basel Committee) in 1999, and with much push back from the industry at the time! Since then, banks are required to set aside capital to create a buffer that would shield themselves from against potential operational losses. The Handbook details the methods available to banks to compute this amount of capital, from the basic indicator approach (as a percentage of the Operating Income, 15%) to the advanced measurement approach (or AMA), where the banks have internal models to estimate the level of operational risk they are exposed to (usually Monte Carlo simulations combining frequency and severity distributions). The models are subject to the supervisor’s approval, and rely on and internal and external loss databases. The Handbook insists on the quality of the data, and how important it is to institutions to ensure robust data collection processes. Garbage in, garbage out.

A new framework for operational risk

However, since the Handbook has been published, the regulatory framework has been further strengthened with the Basel III reforms being finalized in December 2017. The AMA will be stopped and all internal models for operational risk with it. It is the results of the industry failure to produce a homogeneous and reliable method to model extreme operational events. The new framework, or standardized measurement approach (SMA), will, as its name suggests it, be a single non-model-based method, akin to the former standardized approach in its simplicity and comparability, but embodying also risk sensitivity by scaling the capital requirements to the level of realized losses. It will be applicable as of January 2022.

Is it the end of modelling extreme events?

Is it the end of modelling extreme events? Probably not. Institutions will always have forecasting needs in that respect, and if some valid and robust industry method emerges, it is not inconceivable to think that Basel might give AMA a successor one day.

Maxime Laot
Supervisor at European Central Bank

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Can we avoid financial crises?

Can we avoid financial crises?

Extreme events in finance are characterized by very large price fluctuations on the financial markets. These stock market crashes always occur on very short periods, a day or even a few minutes with flash crashes. But then why be interested in these events? Explanation in the video by François Longin, Professor of Finance at ESSEC Business School, Challenges partner.

Watch the 3 minutes video below (English version coming soon)!

Video by Prof. Longin about extreme events in finance
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The LTCM crisis: what can we learn 20 years after?

The LTCM crisis: what can we learn 20 years after?

Matthieu Benavoli Ace Finance Conseil LTCM crisis

This post about the LTCM crisis presents a recent resource about financial crises added by Matthieu Benavoli financial analyst at Ace Finance Conseil.

LTCM

LTCM, “Long Term Capital Management”, was a hedge fund created by John Meriwether in 1994. The mismanagement of the fund led to a major financial crisis in the late 90s. In the beginning, Meriwether had a simple strategy: being accompanied by the most brilliant minds of America. Hence, he gathered an all-star team of traders and academics composed of eminent professionals, professors, and the Nobel Prize recipients Robert Merton and Myron Scholes. This team convinced investors, including many large banks, to flock to the fund and to invest more than $1.3 billion in spite of the huge entry barriers Meriwether set. These experts team designed a strategy mainly based on convergence and relative-value trades, both combined with a high leverage effect.

What happened?

In the first years this strategy scored a huge success: LTCM marketed itself as providing the highest returns, superior to 40% in 1995 and 1996, for a risk that had no equivalent among competitors. But the catastrophe occurred in 1998. In August 1998, Russia devalued the rouble and declared a moratorium on $13.5 billion of its Treasury debt: these decisions undermined LTCM’s profit sources and trashed its hedging strategies. Russia’s default was the first strike of a long series: then the so-called “flight to liquidity” across fixed-income markets precipitated the debacle of LTCM. The fund lost a lot when the banks raised doubts about the fund’s ability to survive. On 21st September, the Fed of NYC, for the first time, organised a rescue package under which a consortium of banks injected $3.5-billion into the fund and took over its management and saved the situation at the expense of heavy losses.

What can we learn 20 years after?

What has to be taken away from this debacle? One should keep in mind that this debacle is due to the pride of talented, skilled intellectuals who could not imagine they were wrong. Warren Buffet underlined that “[The members of this team] had probably the highest average IQ of any 16 people working together in one business, 400 years of experience in their jobs […] and they went broke. That is absolutely fascinating. If I wrote a book, it’s going to be called “Why do smart people do dumb things?””. Never before had any financial institution benefited from such an impeccable reputation. That’s this “over-confidence” which dragged the fund down. So professionals and investors should take that “ego risk” into account when they invest.

Know more about the LTCM crisis…

Matthieu Benavoli
Financial analyst at Ace Finance Conseil

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Introducing the asymmetric time-exceedance model with optimal threshold

Introducing the asymmetric time-exceedance model with optimal threshold

Konstantinos Gkillas Patras University

This post presents a recent paper by Gkillas, Longin and Tsagkanos (2017). This paper introduces a new model with asymmetric time-exceedance of extreme shocks defined with optimal threshold derived from extreme value theory. It has implications in economics and finance.

Concept

We propose an innovative model, entitled asymmetric exceedance time model with optimal threshold, by combing the extreme value theory (distribution tails models) with regression techniques. Building on works related to the asymmetric phenomenon which has been widely documented in economic, finance and statistics, we examine the concept of asymmetry in extreme volatile periods. We use extreme value theory (peak-over-threshold method) to model extremes. We propose a procedure for the automatic computation of optimal thresholds, at the point where the fitting of the extreme value distribution is maximized. We define extreme shocks as exceedances over the optimal threshold and determine how the duration between past and present extreme shocks affects the dependent variable, introducing the temporal variability of extreme events.

Application

We present an empirical application to the exchange and equity markets. The mechanism of interactions between these markets is substantial for many outstanding issues in international economics and finance. Furthermore, both in theoretical and empirical literature, there is not consensus between the economic relation which connect these markets. We use daily data from S&P 500 and GBP/USD.

In this application we explore whether investors’ memory of past extreme events has a feedback effect at the time of an extreme shock. In other words, we separate the investors’ direct perceptions from the investors’ indirect expectations based on their memory. Our empirical findings suggest that the investors’ reaction at the time of an extreme shock is significantly affected by their memory and are consistent with the ‘portfolio balance’ models.

Usefulness

The understanding of interactions among financial variables in extreme volatile periods is crucial for several reasons. For example, theoretical economic models can be tested in extreme conditions or empirical findings can be useful in practice for asset managers (building portfolios based on diversification) and risk managers (defining hedging strategies against adverse events). However, the model is general and can be applied in any time series with heavy tails.

Reference: Gkillas K., F. Longin and A. Tsagkanos (2017) “Asymmetric Exceedance-Time Model: An Optimal Threshold Approach Based on Extreme Value Theory”. Available at SSRN: https://ssrn.com/abstract=3016145

Financial markets

Konstantinos Gkillas
University of Patras

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Crowdfunding research on cryptocurrency

Crowdfunding Research on Cryptocurrency ICOs

Stephen Chan Manchester University

Crowdfunding research on cryptocurrency : along with a few colleagues, I am testing out a relatively new crowdfunding platform (experiment.com) to raise some funding for research related to cryptocurrencies and the blockchain, see https://experiment.com/projects/quantifying-risks-associated-with-blockchain-tokens-by-how-much-will-or-will-not-equity-backing-protect-the-markets.

Quantifying risks associated with blockchain tokens. By how much will or will not equity backing protect the markets?

The cryptocurrency market has reached an overall value of $100B dollars with companies raising millions of dollars in a few minutes. Aragon raised $25m, Qtum $15.5m, Bancor at $150m, Golem at $8.6m, Status at $250m with new ICO projects coming out 4x a week. The token market carries a lot of potential in terms of reducing costs associated with security and eliminating middle men. Although it increases liquidity for a secondary markets, investors do not understand the risks involved. We want to fill in the gaps by providing quantitative analysis. Backing the tokens with fundamentals such as equity, which can create a linear compensation model for the team, and protection for investors create a less volatile environment for token holders.

We believe that it is a great project and the results will be of pivotal importance for the blockchain community. It has already been supported and endorsed by Prof KM Abadir, Professor of Financial Econometrics, Imperial College London and Prof Joerg Osterrieder,Senior Lecturer, Zurich University of Applied Sciences, Switzerland.

For more information about the project and its funding, contact Stephen Chan.

Crowdfunding Research on Cryptocurrency ICOs

Stephen Chan
Manchester University

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New book on investing

New book on investing: “Ever invested. Ever Failed. No matter. Invest again. Invest better”

Charles Pahud de Mortgange University Liege Non-parametric marketCharles Pahud de Mortgange University Liege Non-parametric market

New book on investing by Prof. Jean-Marie Choffray and Charles Pahud de Mortanges: “Ever invested. Ever Failed. No matter. Invest again. Invest better”

Ten thoughts, facts and rules :

  • 1. Watch out! Events that did not happen in the past, and facts that did not materialize, are usually the best predictors of the future.
  • 2. Most politicians are “naked” short-sellers. They sell what they don’t own and usually can’t provide.
  • 3. Investment candidates (businesses) should ideally generate a recurrent level of return on equity (greater than the cost capital), as well as a high level of earnings per share growth (greater than operational growth and return on equity).
  • 4. If you believe you understand financial statements, keep in mind that those who produce them usually don’t.
  • 5. Sad Belgian joke. Banks whose assets were greater than GDP collapsed. Hundreds of years of growth in smoke. Nobody responsible!
  • 6. Respect quarterly cycles. Invest on solid businesses (roe, Δeps, Δeps > roe, low peg, regular analysts estimates beats) at the end of their consolidation (bottoming) process. Avoid being invested when quarterly reports are released.
  • 7. In today’s low growth environment, the most strategic “products” of any business might be its shares and its bonds.
  • 8. As an investor, if you’re willing to pay managers/directors to do nothing, you will be amazed at how well they do it!
  • 9. There are two opposing crowds on the market: those who sell what they don’t own (short-sellers), and those who buy what they can’t afford (margin-buyers). Good investors follow them. Great investors lead them.
  • 10. Over time, financial markets don’t lie. Never. That’s why people – managers, directors, and leaders of all sorts – hate them!

Ever invested. Ever Failed. No matter. Invest again. Invest better

If you don’t see the link between these ten thoughts, facts and rules, you might consider having a look at Jean-Marie Choffray & Charles Pahud de Mortanges last book: Ever invested. Ever Failed. No matter. Invest again. Invest better. Their book provides a semi-ordered set of several hundred “experience-based” thoughts, facts and rules – allowing for some redundancy and randomness – whose any subset could provide a reasonable basis on which to build your own theory of investing. Painful and solitary work. But, your survival on the markets is at that price.

Protecting assets in non-parametric market conditions

In today’s chaotic economic and political environment, protecting assets, against all extreme – unpredictable, impossible, and even unthinkable – events, is the key to success. As we discussed in our contribution in the Wiley handbook Extreme Events in Finance edited by Prof. Longin, under such non-parametric market conditions, the analysis of the past is of limited help. As to the future, it might never exist! The present is all that matters, and that’s why investors usually become more concerned about the return of their money than about the return on their money. For a comprehensive discussion of this topic, refer to Extreme Events in Finance.

Investing. Ever invested. Ever failed. No matter. Invest again. Invest better

Prof. Jean-Marie Choffray
ESSEC Business School & University of Liège

Charles Pahud de Mortanges
University of Liège

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Statistical tools for extreme value analysis

Statistical tools for extreme value analysis

Stephen Chan Manchester University

Both academics and pratictioners widely apply Extreme Value Analysis (EVA) in their applied research work. Some examples of field applications: coastal engineers, structural engineers, geological engineers, investment banks, risk management, hydrologists and seismologists. More specifically the modelling of extreme events in environmental science has particularly intensified through disaster planning purposes for flood, wind, mudslides, fire, tornado, extreme temperatures and droughts.

EVA is a branch of statistics, which deals with the extreme deviations from the median of the probability distribution. Two distributions are commonly associated with the analysis of extreme value: the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD).

Many software packages, particularly in the open source environment, are available to assist academics and industrial partners to perform analysis on extreme values. The main functions in these packages allow us to perform estimation of univariate, bivariate and multivariate extreme value theory. They include the following methods: block maxima, threshold model, estimation methods and non–stationary regression). Graphical techniques to analyse extreme value data are also available.

Statistical tools for extreme value analysis: a review of software packages

I propose a compiled review of the currently available software packages for extreme value analysis. This may not be a comprehensive list but it contains the most commonly used packages.

The development of software for statistical extremes has been rapid, particularly in the open source environment of R. R contains the most utilities and tools for modelling extreme values and is freely available without proprietary licensing requirements, causing R to be extremely popular for many academic statisticians.

This review list will greatly simplify the process of finding and understanding available software for EVA.

For more information on the use of statistical tools in risk management

For more information about statistical methods and their applications in finance (especially risk management with Value at Risk), you can read our contribution Estimation methods for Value at Risk with Professor Saralees Nadarajah (Manchester University) published in the Wiley handbook Extreme Events in Finance.

Stephen Chan
Manchester University

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