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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