Historical Financial Analogies of the Current Crisis Julián Andrada-Félix Fernando Fernández-Rodríguez Simón Sosvilla-Rivero WP10/11

Historical financial analogies of the current crisis Julián Andrada-Félix Fernando Fernández-Rodríguez Simón Sosvilla-Rivero WP10/11

ICEI Workingpapers

1 2 Resumen

Este trabajo intenta arrojar luz sobre las analogías históricas de la crisis actual. Para ello se compara la distri- bución de los rendimientos del Índice Dow Jones Industrial Average durante un período de 769 días (del 15 de septiembre de 2008, la quiebra de Lehman Brothers, hasta septiembre de 2011), con todas las distribucio- nes históricas posibles de rendimientos calculados con una ventana móvil de 769 días desde e 2 de enero de 1900 al 12 de septiembre de 2008. Mediante el uso de un contraste no paramétrico Kolmogorov-Smirnov y de un contraste de Chi cuadrado, ambos de homogeneidad en la distribución, encontramos que la distribu- ción de rendimientos durante la crisis actual sería similar a varios períodos anteriores de grave crisis financiera que evolucionaron hacia intensas recesiones, siendo el episodio que abarca del 28 de mayo de 1935 al 17 de junio de 1938 el más análogo a la situación actual. Además, al aplicar el procedimiento propuesto por Diebold, Gunther y Tay (1998) para comparar las densidades de sub-muestras, se obtiene un apoyo adicional para nuestros hallazgos y se detecta un subperíodo entre el 10 de septiembre de 1930 y el 13 de octubre de 1933, donde la gravedad de la crisis supera la situación actual, presentando eventos más pronunciados en las colas. Finalmente, al comparar el riesgo de mercado histórico con el riesgo actual, se observa que el riesgo de mercado actual sólo ha sido superado por el experimentado al comienzo de la Gran Depresión.

Palabras clave: Crisis financiera, Gran Recesión, Gran Depresión.

Abstract

This paper tries to shed light on the historical analogies of the current crisis. To that end we compare the current sample distribution of Dow Jones Industrial Average Index returns for a 769-day period (from 15 September 2008, the Lehman Brothers bankruptcy, to 30 September 2011), with all historical sample distributions of returns computed using a moving window of 769 days in the 2 January 1900 to 12 September 2008 period. Using a Kolmogorov-Smirnov and a χ 2 homogeneity tests which have the null hypothesis of equal distribution we find that the stock market returns distribution during the current crisis would be similar to several past periods of severe financial crises that evolved into intense recessions, being the sub-sample from 28 May 1935 to 17 Jun 1938 the most analogous episode to the current situation. Furthermore, when applying the procedure proposed by Diebold, Gunther and Tay (1998) for comparing densities of sub- samples, we obtain additional support for our findings and discover a period from 10 September 1930 to 13 October 1933 where the severity of the crisis overcome the current situation having sharper tail events. Fi- nally, when comparing historical market risk with the current risk, we observe that the current market risk has only been exceeded in the beginning of the Great Depression.

Key words: Financial crisis, Great Recession, Great Depression.

The authors gratefully acknowledge financial support from the Spanish Ministry of Science and Innovation (projects ECO2008-05565 and ECO2010-21318).

Julián Andrada-Félix Affiliation: Universidad de Las Palmas de Gran Canaria, Spain. Address: Dpto. Métodos Cuantitativos en Economía y Gestión , Facultad de Ciencias Económicas y Empresariales, Uni- versidad de Las Palmas de Gran Canaria, E-35017 Las Palmas de Gran Canaria, Spain. [email protected] Fernando Fernández-Rodríguez Affiliation: Universidad de Las Palmas de Gran Canaria, Spain. Address: Dpto. Métodos Cuantitativos en Economía y Gestión , Facultad de Ciencias Económicas y Empresariales, Uni- versidad de Las Palmas de Gran Canaria, E-35017 Las Palmas de Gran Canaria, Spain. [email protected] Corresponding author Simón Sosvilla-Rivero Affiliation: Universidad Complutense de Madrid, Spain. Address: Departamento de Economía Cuantitativa, Facultad de Ciencias Económicas y Empresariales, Universidad Com- plutense de Madrid, Campus de Somosaguas, E-28223 Madrid, Spain. [email protected]

El ICEI no comparte necesariamente las opiniones expresadas en este trabajo, que son de exclusiva responsabilidad de sus autores/as.

3 4 Index

1. Introduction...... 7 2. Econometric methodology...... 7 3. Data and empirical results ...... 8

3.1 Data ...... 8 3.2 The KS and χ 2 tests ...... 9 3.3 The DGT procedure ...... 10 3.4 Market risk evolution...... 14

4. Concluding remarks ...... 15 Bibliographical references...... 16

5 6 1. Introduction

There is a burgeoning literature on determin- Let X12,XX ,..., n and YY12, ,..., Ym be independ- ing the causes of the current global crisis and ent random samples of returns having un- on finding precursors in past global crises (see, known continuous distribution functions e. g. Reinhart and Rogoff, 2009a). In contrast F()x and Gx() respectively. with the main avenue of research in this literature that, following Eichengreen et al. (1995), Kaminsky and Reinhart (1999) and several In order to establish the hypothesis test: subsequent authors, examines the behaviour of key economic variables around crisis episodes, HFxGxforx0 :()()= −∞< <∞ (1) this paper tries to shed light on the historical H1 :()()Fx≠ Gx , analogies of the current crisis making use of the nonparametric Kolmogorov-Smirnov test we consider the sample distribution functions to detect past sub-periods where the distribu- defined as tion of the Dow Jones Industrial Average Index n m *1− *1− returns are similar to the most recent sub- Fx ()xn=−∑ε () xXj and Gxx ()=− m∑ε () xYj sample covering the current crisis outbreak. j=1 j=1 where the function ε (.) is the function The reason for studying the distribution of returns for the stock market in the United ⎧10if x ≥ States is given by the fact that while the crisis ε ()x = ⎨ 00if x < initially had its origin in this country in a rela- ⎩ tively small segment of the lending market, the * * sub-prime mortgage market, it rapidly spread so, nFx () x ( mGx () x ) is the number of X j across virtually all economies, affecting stock (Y ) that are ≤ x markets worldwide, and so, many countries j have experienced even sharper stock market crashes than the United States. Moreover, Let us consider the statistic starting with Fisher (1933), a number of re- searchers emphasize the importance of finan- ** Dnm, =−supFx n ( ) Gx m ( ) cial cycles for the real economy and there are −∞≤x ≤∞ many studies indicating that stock returns are related to current and future levels of eco- if the null H0 is true, the statistic nomic activity (see, e. g., Grossman and 1/2 mn Shiller, 1981). ⎛⎞ ⎜⎟Dnm, converges in distribution to an ⎝⎠mn+ The paper is organised as follows. Section 2 expression given by the following numerical presents the econometric methodology, while series: Section 3 describes the data set and reports the 1/2 ∞ empirical results. Finally, Section 4 offers ⎛⎞mn 22 ⎛⎞ iit−−12 (2) limPDte⎜⎟nm, ≤=− 1 2 ( − 1) some concluding remarks. n→∞ ⎜⎟⎜⎟ ∑ ⎝⎠mn+ i=1 ⎝⎠

2. Econometric methodology This result can be used to provide the critical value d for accepting the null H , that is to We first detect analogies to the current crisis α 0 using a Kolmogorov–Smirnov test (KS test). find dα such that This is a nonparametric test for the equality of ⎛⎞1/2 ⎛⎞mn , and tables of continuous, one-dimensional probability dis- limPDd⎜⎟⎜⎟nm, ≤ α =− 1 α n→∞ ⎜⎟⎝⎠mn+ tributions that can be used to compare two m→∞ ⎝⎠ sub-samples (see Rohatgi, 1976). The null dα for various values of α are available in distribution of this statistic is calculated under Owen (1962). For instance, it is easy to check the null hypothesis that the samples are drawn 1/2 using (2) that ⎛⎞⎛⎞mn and from the same distribution (i. e., equal distri- Pn⎜⎟⎜⎟ Dnm, ≤=1.36 0.95 ⎜⎟mn+ butions for both sub-samples), and the alterna- ⎝⎠⎝⎠ tive corresponds to different distributions. so, we can reject the null H0 when

7 1/2 ⎛⎞mn distribution, the Z12,ZZ ,..., m must be inde- ⎜⎟Dnm, >1.36 with a significance level ⎝⎠mn+ pendent and uniformly distributed U (0,1) in of 0.05. the interval (0,1) .

As additional evidence for detecting analogies DGT (1998) propose a graphical procedure for to the current crisis, we have also used a Chi- rejecting the null based on looking at the his- Square test for homogeneity (see Rohatgi, togram of the probability integral transforma- 1976). Now we consider a partition tion. This procedure consists of comparing the AA, ,..., A 12 k of the real line, and let estimated density of the probability integral X12,XX ,..., n and YY12, ,..., Ym be independent transformation (3) to a U (0,1) by computing random samples of returns, like above. In what confidence intervals under the null hypothesis follows n=m for convenience. Let X ()i the of of i.i.d. U (0,1) . Besides, in order to evaluate observations in X12,XX ,..., n that lie in the set whether Zt in (4) is i.i.d., they propose using

Ai , and Yi() the of observations in the correlogram, supplemented with the usual Bartlett confidence intervals. In this sense, YY12, ,..., Yn that lie in the set Ai . Let serial correlation in the Z − Z series indicates Xi( ) Yi( ) tt pˆ =+,ik = 1,2,..., . that the conditional mean dynamic of the re- i 22nn turns X are different to the conditional mean t In this case, the random variable dynamic of the returnsYt . If potentially sophisticated nonlinear forms of dependence are 22 kk looked for, it is necessary examine the correlo- ()X ()inp−−ˆˆii() Yinp() + (3) 2 ∑∑ grams of powers of Ztt− Z , that is (Ztt− Z ) , ii==11npˆˆii np 3 4 (Ztt− Z ) and (Ztt− Z ) . 2 is approximately a χ with k-1 degrees of free- dom, which allows us to establish a second 3. Data and empirical results version of the hypothesis test (1).

3.1 DATA Some authors cast doubts on the practical ap- 2 plications of the KS and χ tests because they In this paper we use daily data of the Dow are not constructive and, so, when rejection of Jones Industrial Average Index (DJIA) from 2

H0 occurs, the tests generally provide no January 1900 to 30 September 2011 provided 1 guidance as to why: because the samples are by Reuters’ EcoWin Pro . We first compute not independent, because the samples have daily returns for this period and calculate the different distributions or both. In this sense histogram of all probability distributions ob- Diebold, Gunther and Tay (1998) (DGT here- tained using a moving 769-day window. We after) have provided a new test for comparing then make use of the KS test to compare all densities of sub-samples. Given the sample these histograms with the histogram computed density function p ()u of a sam- for the last 769 days in the sample, covering X the period from the bankruptcy of Lehman ple X12,XX ,..., n , the probability integral trans- Brothers Holdings Inc. on 15 September 2008 formation of another sample YY12, ,..., Yn is the to the end of the sample. We take the collapse cumulative density function corresponding to of Lehman Brothers Holdings Inc. as a break- the density p ()u evaluated at Y , ing point since it is thought to have played a X t major role in the unfolding of the current global financial crisis and in the abrupt con- Y Z = t pudu() (4) traction of economic activity registered tX∫−∞ worldwide.

Under the null hypothesis that X ,XX ,..., 12 n 1 and YY12, ,..., Ym are independent random sam- The DJIA and Standard and Poor’s 500 Composite (S&P500) ples having a common unknown continuous indexes are very highly correlated with each other, telling a similar story in levels, returns and volatility. The use of DJIA is likely to be sufficient for analysing the issues at hand.

8 2 • II: 11 April 1914 to 26 July 1922. This 3.2 THE KS AND χ TESTS sub-sample includes the short but Figure 1 plots the computed values of the KS extremely painful recession of 1920– statistic when comparing all the histograms of 1921. possible successive 769-day returns computed for the DJIA from 2 January 1900 with the • III: 26 January 1927 to 16 December histogram associated with 769-day returns 1930. This sub-sample embraces a period after the bankruptcy of Lehman Brothers. The of stock markets crashed worldwide dashed line corresponds to the critical value of leading to the Great Depression. 1.36. As stated before, computed tests greater than 1.36 reject the null hypothesis of equal • IV: 30 December 1932 to 11 August distributions of both sub-samples at a signifi- 1941. This sub-sample encompasses the cance level of 95%. The minimum value is recession of 1937, which is among the obtained when comparing with the subsample worst recessions of the 20th century. starting on 28 May 1935 and the maximum value is reached when comparing with the • V: 5 December 1973 to 25 January subsample starting on 10 September 1930. 1977 and 21 June 1974 to 21 August 1977. These sub-samples comprehend As it is shown in Figure 1, the past periods the 1974-1975 recession after the 1973 where the KS test does not reject the null hy- oil crisis and the 1973–1974 stock pothesis of equal distribution of stock returns market crash. to the last 769-day sub-sample are the follow- 2 ing : • VI: 6 February 1986 to 14 April 1989. Figure 1: Historical evolution of Kolmogorov–Smirnov test comparing the DJIA returns in the current crisis with past periods.

• I: 28 August 1905 to 25 October 1909. This sub-sample covers the 1987 stock This sub-sample covers the Panic of market crash. 1907, a financial crisis caused by a retraction of market liquidity by a • VII: 22 July 1987 to 21 November number of New York City banks that 1990. This sub-sample includes the 1990 evolved to economic recession, with oil price shock and the early 1990s numerous runs on banks and trust recession. companies. • VIII: 24 September 1996 to 17 April 2002. This sub-sample embraces the 2 For the history of financial crises, see Kindleberger and Aliber Asian financial crisis of 1997–1998, as (2005) and Reinhart and Rogoff (2009).

9 well as the 1998 LTCM bailout and the mum value when comparing the current crisis early 2000s recession associated with the with the sub-sample running from 30 Decem- 2000 Tech Bubble bust. ber 1932 to 11 August 1941, it seems that, if History repeats itself, current high uncertainty • IX: 12 January 2001 to 4 August 2005. and intensified downside risks would lead to a This sub-sample encompasses the higher probability of a double-dip recession. WorldCom bankruptcy in 2002 (the This would be in line with the conclusion of a largest in the history of the United States sizable body of empirical literature stating that at the time) and the 2003 turbulence in recessions caused by financial crises have a stock markets related to a pessimistic history of being long, deep and difficult to outlook for the global economy and fully escape (e.g., Reinhart and Rogoff, 2009b). increased uncertainty. Our results are also consistent with Baur, As additional evidence of historical analogies Quintero and Stevens (1996) who report that with the current crisis, Figure 2 plots the com- during the periods that surrounded the crash, puted values of the χ 2 statistic in (3) compar- only changes in fundamentals have a statisti- cally significant impact on the movement of ing the returns of the current crisis with past stock prices, as well as with Shachmurove 769 day episodes during the history of DJIA. (2011) who, after examining the economic The dash line corresponds to the critical value history of the United States, concludes that 2 of χk−1 = 30.14 at a significance level of 95%. financial crises and banking panics are not As can be observed, the shape of the curves in exclusive of the nineteenth-century, but that Figure 1 and Figure 2 is very similar. The main these phenomena are still reoccurring. difference is that, in the χ 2 test, the null of equal distribution is only accepted in period III and period IV of Figure 1.

Figure 2: Historical evolution of χ 2 test comparing the DJIA returns in the current crisis with past periods.

Therefore, the KS and χ 2 tests reveal analo- 3.3 THE DGT PROCEDURE gies between the current situation and past As further evaluation of the analogies detected economic recessions, suggesting that the world 2 economy would be heading towards a new and with the KS and χ tests between the histori- marked slowdown if it evolves as in similar cal and present return, we have applied the situations during the past. graphic framework developed by DGT (1998) to the periods in Figure 1 and Figure 2 where Given that the KS and χ 2 tests take the mini- the KS and χ 2 statistics take an extreme value

10 (a local minimum, or a local maximum). In all period from 7 January 1963 to 24 January 2 cases, the density function pX ()u in the ex- 1966, where KS and χ tests have rejected pression (4) was the empirical distribution of equal distribution with the current crisis. In the 769-day sub-sample starting on 15 Sep- this case the histogram has a non-uniform tember 2008 (the bankruptcy of Lehman inverted U shape, suggesting that the empirical

Brothers), and the random variable Yt in (4) density pX ()u (corresponding to the last sub- was the historical period returns which we sample running from 15 September 2008 to 30 want to compare. As it will be shown, the na- September 2011) has a different density than ture of the histograms provided by the DGT the sub-sample (taken from 7 January 1963 to test is completely different. 24 January 1966) since both empirical densities have completely different tails. So, in (4) 2 For the case of local minima of the KS and χ X12,XX ,..., n present extreme values with re- statistics in Figure 1 and Figure 2, where the spect toYY12, ,..., Yn . null hypothesis of similar return distribution with the current crisis is accepted, the shape of The pattern shown in the histogram in Panel B the histograms for the probability integral of Figure 3 is also present in all the local transformation correspond to a uniform distri- χ 2 bution, as could be expected. As an example of maxima reached by KS and statistics with this behaviour, Panel A in Figure 3 shows the one exception. This exception corresponds to histogram of the probability integral transfor- the absolute maximum of these statistics in mation corresponding to the sub-sample be- Figure 1 and Figure 2, and it relates to the ginning on 28 May 1935, where the KS and period from 10 September 1930 to 13 October 2 1933, when the financial crisis was extremely χ take the absolute minimum; the dashed severe. Panel C of Figure 3 shows the histo- lines are the binomial confidence bands for a 3 gram corresponding to the DGT test for this confidence level of 99% . So, this histogram period. The U shape of the histogram suggests corresponds to a U (0,1) variable4. It suggests that the returns in this period have a higher that the empirical density p ()u (correspond- volatility, the tail events are more frequent, X and the market risk is higher than during the ing to the last subsample running from 15 current crisis. In terms of the empirical density September 2008 to 30 September 2011) and p ()u the density associated with the period covering X (corresponding to the current crisis), it from 28 May 1935 to 17 June 1938 have simi- means that the period taken from 10 Septem- lar properties. The histogram obtained using ber 1930 to 13 October 1933, has a different the DGT procedure is also close to the uniform density, that is YY12, ,..., Yn present extreme 2 in the rest of local minima of KS and χ statis- values with respect to X12,XX ,..., n in (4). The tics in Figure 1 and Figure 2. U shape in the histograms of the probability integral transformation is also found in the Now let us consider the histogram where the sub-periods beginning around the absolute null is strongly rejected. Neither the KS nor maximum of the KS and χ 2 statistics corre- 2 the χ tests specify the reason of rejection, sponding to Figure 1 and Figure 2. however the DGT test does, and two patterns emerge in the histograms rejecting the uni- formity. On the one hand, the KS and χ 2 rejection of similarity with the current crisis could be produced because the returns in the period analysed have a lower volatility, the tail events are less frequent and the market risk is lower. For instance, this is the case repre- sented by Panel B in Figure 3 which corresponds to the histogram associated with the

3 Monte Carlo simulations show that the null can also be accepted with a confidence level of 95%. 4 Observe that our sample size is 769, whereas in DGT (1998) the graphical exercise of comparing histograms was carried out with sample size of 4000 observations.

11 Figure 3: Histograms of DG test with binomial confidence bands

100

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

100

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

100

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Notes:

2 • Panel A corresponds to the comparison of the current crisis with the KS and χ absolute minimum, where the similarity is accepted. 2 • Panel B corresponds to the comparison of the current crisis with several local maxima of KS and χ statistics. Here the current crisis has fater tails. χ 2 • Panel C corresponds to the comparison of the current crisis with the absolute maximum of KS and statistics. The current crisis is less severe.

Following the DGT methodology, it is possible In Figure 4 we show the sample autocorrela- 2 3 to evaluate whether Zt in (4) is i.i.d., looking tions of Ztt− Z , (Ztt− Z ) , (Ztt− Z ) and for a serial correlation in the Z − Z series 4 tt Z − Z and the critical values which indicates that the conditional mean ( tt) dynamic of the returns X t (corresponding to ±2/ T (where T is the sample size) of the test the 769-day period after the Lehman Brothers H0 :0ρ = . As can be observed in Figure 4, the default) are different to conditional mean dy- correlograms show no evidence of neglected namic of the returns Y (corresponding to the t dynamics of Yt returns series with respect to 769-day period from 28 May 1935 to 17 Jun X series. 2 t 1938 where the KS and χ statistics take the minimum value in Figure 1 and Figure 2). Moreover, potentially sophisticated nonlinear forms of dependence may be looked at for examining the correlograms of powers of

Ztt− Z .

12 2 3 4 Figure 4: Correlograms of Ztt− Z , (Ztt− Z ) , (Ztt− Z ) and (Ztt− Z )

0.4 0.4

0.2 0.2

0 0

0 50 100 150 200 0 50 100 150 200 (a) (b)

0.4 0.4

0.2 0.2

0 0

0 50 100 150 200 0 50 100 150 200 (c) (d)

Notes: Z − Z (a) tt 2 Z − Z (b) ( tt) 3 Z − Z (c) ( tt) 4 Z − Z (d) ( tt)

As additional evidence of the rejection for the The correlogram of Ztt− Z and their powers reveals that, although significant serial correla- null hypothesis of equal sample distribution, tion in the series doesn’t exist, nonlinear de- we have also studied the historical aceptance of similarity by the DGT test comparing the pendences exist between Z and Z . The t th− current crisis with past episodes. In this case 2 the 95% critical values in the DGT test were strong serial correlation in ()Ztt− Z and obtained by Monte Carlo simulations and a 4 in ()Ztt− Z reveal operative dependence total of 1,480 acceptances of similar distribu- through conditional variance and conditional tion, out of 27,796 769-day periods considered kurtosis. So, the sample after the Lehman in the history of DJIA, have been supplied. The Brothers default and the sample where the KS acceptances of the null in DGT are produced around the local minimum values of KS and and χ 2 statistics take a minimum value pre- χ 2 statistics, especially during the period IV sent different behaviour from the dynamical point of view of the conditional variance, even where their absolute minimum was found. The though the histogram in the DGT procedure results are displayed in Figure 5 and the verti- (Panel A Figure 2) does not reject the null cal lines show the 769-day sample periods hypothesis of equal distributions. where the null hypothesis of equal distribution was accepted.

13 Figure 5: Historical aceptance of similarity using the GDT test comparing the current crisis with past episodes.

Therefore, the DGT methodology provides additive and convex. deeper insight into our earlier conclusion from the KS and χ 2 tests. The CVaR is the expected value of the losses exceeding the VaR, that is 3.4 MARKET RISK EVOLUTION CVaR=> E L/ L VaR α [ α ] Finally, we have also compared the historical evolution of market risk with its current level Therefore, it is a weighted average of losses for during the financial crisis. A very well-known the worst 100(1−α )% of cases exceeding VaR measure of risk used in finance is the Value at Risk (VaR). For a given portfolio and time with a confidence levelα .

VaR horizon, α is defined as a threshold value In order to estimate the CVaR from our em- such that the probability that the loss on the pirical distributions of returns and following portfolio exceeds this value is the given prob- Dowd (2005), we slice the tail into a large ability level 1−α . Nevertheless, the useful- number n of slices, each of which has the same ness of VaR as a measure of risk is highly ques- probability mass, estimate the VaR associated tionable outside the confines of near-normal with each slice, and take the CVaR as the aver- distributions and one important limitation is age of these VaRs. that VaR only tells us the most we can lose if a tail event does not occur (e.g., it tells us the In Figure 6 we show the historical behaviour most we can lose 95% of the time); if a tail of one-day 95% CVaR estimated averaging 50 event does occur, we can expect to lose more VaRs with confidence level from 95.1% to than VaR, and the VaR itself gives us no indi- 99.9%. The horizontal dashed line represents cation of how much that might be. the CVaR corresponding to the 769-day period after the Lehman Brothers default. As can be An alternative risk measurement to VaR fre- seen in Figure 6, the current market risk as- quently employed in empirical applications, is sessment has only been exceeded at the begin- the conditional VaR (CVaR), also known as ning of the Great Depression, and the maxi- expected shortfall or tail-VaR (see Artzner et mum level of CVaR corresponds to the period al., 1999). This risk assessment technique is from 24 October 1929, to 20 October 1932. more sensitive to the shape of the loss distri- This period corresponds with the maximum of bution in the tail, and is performed by assess- KS and χ 2 statistics in Figure 1 and Figure 2, ing the likelihood (at a specific confidence where the DGT test produces a U shape histo- level,α ) that a specific loss will exceed the gram (Panel C in Figure 3), revealing tail value at risk, being a more consistent measure events deeper than during the current crisis. of risk compared to VaR since it is sub-

14 Figure 6. Market risk: historical one-day CVaR compared with its current level in the dash line

4. Concluding remarks sults indicate that the most similar episode to the current situation is the Great Depression of

the 1930s, suggesting that the world economy The current global financial crisis is without would be entering a new phase of economic precedent in post-war economic history. Al- weakening, with a high probability of re- though its size and extent are exceptional, the crisis may have features in common with simi- entering recession. lar financial-stress driven recession episodes in the past. To explore the robustness of these results, we have made use of the graphic method frame- In this paper we have tried to identify analo- work proposed by Diebold, Gunther and Tay (1998) for comparing densities of sub-samples, gies in past experiences with the current fi- obtaining further support for our findings. nancial crisis. To that end, we have computed Additionally, we have computed the condi- returns form the DJIA Index using a moving 769-day window from 2 January 1900 to 30 tional value to compare the historical risk with September 2011 and, applying the Kolmo- the current risk, concluding that the current 2 market risk has only been exceeded in a period gorov-Smirnov and the χ homogeneity tests, during the Great Depression. we have detected similarities between the histogram associated with the last 796 observa- We believe that our results might have both tions (from the bankruptcy of Lehman Broth- some practical meaning for investors and pol- ers to the end of the sample) with those corre- icy makers and some theoretical insights for sponding to severe financial crises that evolved academic scholars interested in business cy- into intense recessions. Furthermore, our re cles.

15 Bibliographical references

Artzner, P., J. Delbaen, M. Ebert and D. Heath, “Coherent Measures of Risk”, Mathematical Finance 9 (1999), 203-28. Baur, M. N., S. Quintero and E. Stevens, “The 1986-1988 Stock Market: Investor sentiment or fundamentals?”, Managerial and Decision Economics 17 (1998), 319-29. Diebold, F., T. Gunther and A. Tay, “Evaluating Density Forecasts with Applications to Financial Risk Man- agement”, International Economic Review 39 (1998), 863-83. Dowd, K., Measuring Market Risk. Chichester: John Wiley & Sons, 2005 Eichengreen, B., A. Rose and C. WyplosZ, C., “Exchange Market Mayhem: The Antecedents and Aftermath of Speculative Attacks”, Economic Policy 21 (1995), 249-96. Fisher, I., “The Debt-Deflation Theory of Great Depressions”, Econometrica 1 (1933), 337-57. Grossman, S. J. and R. J. SHILLER, “The Determinants of the Variability of Stock Market Prices”, American Economic Review 71 (1981), 222-27. Kaminsky, G. L. and C. M. Reinhart, “The Twin Crises: The Causes of Banking and Balance of Payments Problems”, American Economic Review 89 (1999), 473-500. Kindleberger, C. P. and R. Z. ALIBER, Maniacs, Panics, and Crashes, Hoboken, New Jersey: Wiley, 5th ed., 2005. Owen, D. B., Handbook of Statistical Tables, Reading, Massachusetts: Addison-Wesley, 1962. Reinhart, C. M and K. S Rogoff, This Time Is Different: Eight Centuries of Financial Folly, Princeton, New Jersey: Princeton University Press, 2009a. Reinhart, C. M and K. S ROGOFF, “The Aftermath of Financial Crises”, American Economic Review 99 (2009b), 466-72. Rohatgi, V. K., An Introduction to Probability Theory and Mathematical Statistics, New York: John Wiley and Sons, 1976. Shachmurove, Y., “Reoccurring Financial Crises in the United States”, Working Paper No. 11-006, Penn Institute for Economic Research, 2011.

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DT 08/07 Rojo, Guillermo: El español en la red.

DT 07/07 Carrera, Miguel; Bonete, Rafael; Muñoz de Bustillo, Rafael: El programa ERASMUS en el marco del valor económico de la Enseñanza del Español como Lengua Extranjera.

DT 06/07 Criado, María Jesús: Inmigración y población latina en los Estados Unidos: un perfil socio- demográfico.

DT 05/07 Gutiérrez, Rodolfo: Lengua, migraciones y mercado de trabajo.

DT 04/07 Quirós Romero, Cipriano; Crespo Galán, Jorge: Sociedad de la Información y presencia del español en Internet.

DT 03/06 Moreno Fernández, Francisco; Otero Roth, Jaime: Demografía de la lengua española.

DT 02/06 Alonso, José Antonio: Naturaleza económica de la lengua.

DT 01/06 Jiménez, Juan Carlos: La Economía de la lengua: una visión de conjunto.

WORKING PAPERS

WP 10/11 Andrada-Félix, Julián; Fernández-Rodríguez, Fernando; Sosvilla-Rivero, Simón: Historical financial analogies of the current crisis.

WP 09/11 Torrecillas, Celia; Fischer, Bruno B.: Technological Attraction of FDI flows in Knowledge- Intensive Services: a Regional Innovation System Perspective for Spain.

WP 08/11 Gómez-Puig, Marta; Sosvilla-Rivero, Simón: Causality and contagion in peripheral emu public debt markets: a dynamic approach.

WP 07/11 Sosvilla-Rivero, Simón; Ramos-Herrera, María del Carmen: The US Dollar-Euro exchange rate and US-EMU bond yield differentials: A Causality Analysis.

17 WP 06/11 Sosvilla-Rivero, Simón; Morales-Zumaquero, Amalia: Volatility in EMU sovereign bond yields: Permanent and transitory components

WP 05/11 Castellacci, Fulvio; Natera, José Miguel: A new panel dataset for cross-country analyses of national systems, growth and development (CANA).

WP 04/11 Álvarez, Isabel; Marín, Raquel; Santos-Arteaga, Franciso J.: FDI entry modes, development and technological spillovers.

WP 03/11 Luengo Escalonilla, Fernando: Industria de bienes de equipo: Inserción comercial y cambio estructural.

WP 02/11 Álvarez Peralta, Ignacio; Luengo Escalonilla, Fernando: Competitividad y costes laborales en la UE: más allá de las apariencias.

WP 01/11 Fischer, Bruno B; Molero, José: Towards a Taxonomy of Firms Engaged in International R&D Cooperation Programs: The Case of Spain in Eureka.

WP 09/10 Éltető, Andrea: Foreign direct investment in Central and East European Countries and Spain – a short overview.

WP 08/10 Alonso, José Antonio; Garcimartín, Carlos: El impacto de la ayuda internacional en la cali- dad de las instituciones.

WP 07/10 Vázquez, Guillermo: Convergencia real en Centroamérica: evidencia empírica para el pe- ríodo 1990-2005.

WP 06/10 P. Jože; Kostevc, Damijan, Črt; Rojec, Matija: Does a foreign subsidiary's network status affect its innovation activity? Evidence from post-socialist economies.

WP 05/10 Garcimartín, Carlos; Rivas Luis; García Martínez, Pilar: On the role of relative prices and capital flows in balance-of-payments constrained growth: the experiences of Portugal and Spain in the euro area.

WP 04/10 Álvarez, Ignacio; Luengo, Fernando: Financiarización, empleo y salario en la UE: el impac- to de las nuevas estrategias empresariales.

WP 03/10 Sass, Magdolna: Foreign direct investments and relocations in business services – what are the locational factors? The case of Hungary.

WP 02/10 Santos-Arteaga, Francisco J.: Bank Runs Without Sunspots.

WP 01/10 Donoso, Vicente; Martín, Víctor: La sostenibilidad del déficit exterior de España.

WP 14/09 Dobado, Rafael; García, Héctor: Neither so low nor so short! Wages and heights in eighteenth and early nineteenth centuries colonial Hispanic America.

WP 13/09 Alonso, José Antonio: Colonisation, formal and informal institutions, and development.

WP 12/09 Álvarez, Francisco: Opportunity cost of CO2 emission reductions: developing vs. developed economies.

WP 11/09 J. André, Francisco: Los Biocombustibles. El Estado de la cuestión.

WP 10/09 Luengo, Fernando: Las deslocalizaciones internacionales. Una visión desde la economía crítica

WP 09/09 Dobado, Rafael; Guerrero, David: The Integration of Western Hemisphere Grain Markets in the Eighteenth Century: Early Progress and Decline of Globalization.

WP 08/09 Álvarez, Isabel; Marín, Raquel; Maldonado, Georgina: Internal and external factors of competitiveness in the middle-income countries.

18 WP 07/09 Minondo, Asier: Especialización productiva y crecimiento en los países de renta media.

WP 06/09 Martín, Víctor; Donoso, Vicente: Selección de mercados prioritarios para los Países de Renta Media.

WP 05/09 Donoso, Vicente; Martín, Víctor: Exportaciones y crecimiento económico: estudios empíri- cos.

WP 04/09 Minondo, Asier; Requena, Francisco: ¿Qué explica las diferencias en el crecimiento de las exportaciones entre los países de renta media?

WP 03/09 Alonso, José Antonio; Garcimartín, Carlos: The Determinants of Institutional Quality. More on the Debate.

WP 02/09 Granda, Inés; Fonfría, Antonio: Technology and economic inequality effects on international trade.

WP 01/09 Molero, José; Portela, Javier y Álvarez Isabel: Innovative MNEs’ Subsidiaries in different domestic environments.

WP 08/08 Boege, Volker; Brown, Anne; Clements, Kevin y Nolan Anna: ¿Qué es lo “fallido”? ¿Los Estados del Sur,o la investigación y las políticas de Occidente? Un estudio sobre órdenes políticos híbridos y los Estados emergentes.

WP 07/08 Medialdea García, Bibiana; Álvarez Peralta, Nacho: Liberalización financiera internacional, inversores institucionales y gobierno corporativo de la empresa

WP 06/08 Álvarez, Isabel; Marín, Raquel: FDI and world heterogeneities: The role of absorptive ca- pacities

WP 05/08 Molero, José; García, Antonio: Factors affecting innovation revisited

WP 04/08 Tezanos Vázquez, Sergio: The Spanish pattern of aid giving

WP 03/08 Fernández, Esther; Pérez, Rafaela; Ruiz, Jesús: Double Dividend in an Endogenous Growth Model with Pollution and Abatement

WP 02/08 Álvarez, Francisco; Camiña, Ester: Moral hazard and tradeable pollution emission permits.

WP 01/08 Cerdá Tena, Emilio; Quiroga Gómez, Sonia: Cost-loss decision models with risk aversion.

WP 05/07 Palazuelos, Enrique; García, Clara: La transición energética en China.

WP 04/07 Palazuelos, Enrique: Dinámica macroeconómica de Estados Unidos: ¿Transición entre dos recesiones?

WP 03/07 Angulo, Gloria: Opinión pública, participación ciudadana y política de cooperación en España.

WP 02/07 Luengo, Fernando; Álvarez, Ignacio: Integración comercial y dinámica económica: España ante el reto de la ampliación.

WP 01/07 Álvarez, Isabel; Magaña, Gerardo: ICT and Cross-Country Comparisons: A proposal of a new composite index.

WP 05/06 Schünemann, Julia: Cooperación interregional e interregionalismo: una aproximación so- cial-constructivista.

WP 04/06 Kruijt, Dirk: América Latina. Democracia, pobreza y violencia: Viejos y nuevos actores.

WP 03/06 Donoso, Vicente; Martín, Víctor: Exportaciones y crecimiento en España (1980-2004): Cointegración y simulación de Montecarlo.

19 WP 02/06 García Sánchez, Antonio; Molero, José: Innovación en servicios en la UE: Una aproximación a la densidad de innovación y la importancia económica de los innovadores a partir de los datos agregados de la CIS3. WP 01/06 Briscoe, Ivan: Debt crises, political change and the state in the developing world.

WP 06/05 Palazuelos, Enrique: Fases del crecimiento económico de los países de la Unión Europea– 15.

WP 05/05 Leyra, Begoña: Trabajo infantil femenino: Las niñas en las calles de la Ciudad de México.

WP 04/05 Álvarez, Isabel; Fonfría, Antonio; Marín Raquel: The role of networking in the competitiveness profile of Spanish firms.

WP 03/05 Kausch, Kristina; Barreñada, Isaías: Alliance of Civilizations. International Security and Cosmopolitan Democracy.

WP 02/05 Sastre, Luis: An alternative model for the trade balance of countries with open economies: the Spanish case.

WP 01/05 Díaz de la Guardia, Carlos; Molero, José; Valadez, Patricia: International competitiveness in services in some European countries: Basic facts and a preliminary attempt of interpreta- tion.

WP 03/04 Angulo, Gloria: La opinión pública española y la ayuda al desarrollo.

WP 02/04 Freres, Christian; Mold, Andrew: European Union trade policy and the poor. Towards im- proving the poverty impact of the GSP in Latin America.

WP 01/04 Álvarez, Isabel; Molero, José: Technology and the generation of international knowledge spillovers. An application to Spanish manufacturing firms.

POLICY PAPERS

PP 0210 Alonso, José Antonio; Garcimartín, Carlos; Ruiz Huerta, Jesús; Díaz Sarralde, Santiago: Strengthening the fiscal capacity of developing countries and supporting the international fight against tax evasión.

PP 02/10 Alonso, José Antonio; Garcimartín, Carlos; Ruiz Huerta, Jesús; Díaz Sarralde, Santiago: Fortalecimiento de la capacidad fiscal de los países en desarrollo y apoyo a la lucha internacional contra la evasión fiscal.

PP 01/10 Molero, José: Factores críticos de la innovación tecnológica en la economía española.

PP 03/09 Ferguson, Lucy: Analysing the Gender Dimensions of Tourism as a Development Strategy.

PP 02/09 Carrasco Gallego ,José Antonio: La Ronda de Doha y los países de renta media.

PP 01/09 Rodríguez Blanco, Eugenia: Género, Cultura y Desarrollo: Límites y oportunidades para el cambio cultural pro-igualdad de género en Mozambique.

PP 04/08 Tezanos, Sergio: Políticas públicas de apoyo a la investigación para el desarrollo. Los casos de Canadá, Holanda y Reino Unido

PP 03/08 Mattioli, Natalia Including Disability into Development Cooperation. Analysis of Initiatives by National and International Donors

PP 02/08 Elizondo, Luis: Espacio para Respirar: El humanitarismo en Afganistán (2001-2008).

PP 01/08 Caramés Boada, Albert: Desarme como vínculo entre seguridad y desarrollo. La reintegra- ción comunitaria en los programas de Desarme, desmovilización y reintegración (DDR) de combatientes en Haití.

20 PP 03/07 Guimón, José: Government strategies to attract R&D-intensive FDI.

PP 02/07 Czaplińska, Agata: Building public support for development cooperation.

PP 01/07 Martínez, Ignacio: La cooperación de las ONGD españolas en Perú: hacia una acción más estratégica.

PP 02/06 Ruiz Sandoval, Erika: Latinoamericanos con destino a Europa: Migración, remesas y codesa- rrollo como temas emergentes en la relación UE-AL.

PP 01/06 Freres, Christian; Sanahuja, José Antonio: Hacia una nueva estrategia en las relaciones Unión Europea – América Latina.

PP 04/05 Manalo, Rosario; Reyes, Melanie: The MDGs: Boon or bane for gender equality and wo- men’s rights?

PP 03/05 Fernández, Rafael: Irlanda y Finlandia: dos modelos de especialización en tecnologías avan- zadas.

PP 02/05 Alonso, José Antonio; Garcimartín, Carlos: Apertura comercial y estrategia de desarrollo.

PP 01/05 Lorente, Maite: Diálogos entre culturas: una reflexión sobre feminismo, género, desarrollo y mujeres indígenas kichwuas.

PP 02/04 Álvarez, Isabel: La política europea de I+D: Situación actual y perspectivas.

PP 01/04 Alonso, José Antonio; Lozano, Liliana; Prialé, María Ángela: La cooperación cultural espa- ñola: Más allá de la promoción exterior.