Thèses sur le sujet « Structural Vector Autoregressive Analysi »

This thesis analyzed and estimated the impact of the March 1, 2018 loan to income amortization requirement on residential real estate prices in Sweden. A four variables vector autoregressive model (VAR) was used to study the relationships between residential real estate prices, GDP, real mortgage rate and consumer price index over a time period from 2005 to 2017. First, a structural vector autoregressive (SVAR) model was used to test how a structural innovation in the error term for real mortgage rate affected residential real estate prices. Secondly, an unconditional forecast from our reduced VAR was produced to estimate post 2017 price growth of the Swedish housing market. The impulse response function results stand in contradiction to economic intuition i.e. the price puzzle problem. The unconditional forecast indicates that the housing market will enter a period with slower price growth post 2017, which are in line with previous research. This thesis vector autoregressive model can give meaningful results with regard to trend forecasts but with regard to precise statements as anticipating drastic price depreciation, it falls short. We recommend the use of reduced VAR forecasting with regard to the Swedish housing market.

The focus of this paper is to evaluate if forecast produced by the Central Bank of Sweden (Riksbanken) for the 12 month change in the consumer price index is unbiased? Results shows that for shorter horizons (h < 12) the mean forecast error is unbiased but for longer horizons its negatively biased when inference is done by Maximum entropy bootstrap technique. Can the unbiasedness be improved by strict ap- pliance to econometric methodology? Forecasting with a linear univariate model (seasonal ARIMA) and a multivariate model Vector Error Correction model (VECM) shows that when controlling for the presence of structural breaks VECM outperforms both prediction produced Riksbanken and ARIMA. However Riksbanken had the best precision in their forecast, estimated as MSFE

In the last years a growing °ow of information in the ¯eld of macroeconomy has been collected in very large databases. It is well known nevertheless that, when a large number of series is available standard statistical tools do not work well. This thesis proposes new estimators for high dimensional systems, that are an optimally weighted average of two already existing estimators, a traditional unbiased one, su®ering of a large estimation error, and a target one, having a lot of bias coming from a misspeci¯ed structural assumption, but little in terms of variance. This method is generally known as shrinkage. We derive two di®erent estimators connected with large dimensional systems. First a new estimator for the coe±cient matrix in a large dimensional vector autoregressive process (VAR) is proposed. It shows a better performance in forecasting macroeconomic time series than a set of existing estimators, including factor models and bayesian shrinkage estimators. A new estimator is also built for the variance covariance matrix in high dimensional systems. This new estimator is used to test for the presence of Serial Correlation Common Features (SCCF) in a multivariate setting involving many, noisy, and collinear time series. It shows a good performance in terms of empirical size if compared to the already existing tool of Canonical Correlation Analysis (CCA).
Negli ultimi anni un °usso crescente di informazione di carattere macroeconomico ¶e stato raccolto in ampi database. Tuttavia ¶e risaputo che, quando un gran numero di serie ¶e disponibile, gli strumenti statistici standard non forniscono risultati a±dabili. Questa tesi propone nuovi stimatori in sistemi di elevate dimensioni, che sono una media ottimamente ponderata di due stimatori gi¶a esistenti, uno stimatore tradizionale non distorto, che com- mette un grande errore di stima, e uno stimatore target, distorto a causa di un'assunzione strutturale sbagliata, ma con un basso errore di stima. Questo metodo ¶e conosciuto come shrinkage. Due stimatori di®erenti legati a sistemi di grandi dimensioni sono derivati. Per primo viene proposto un nuovo stimatore per la matrice dei coe±cienti in un modello autoregressivo vettoriale (VAR) di grandi dimensioni. Questo stimatore mostra una performance migliore nel prevedere serie storiche macroeconomiche rispetto a un set di stimatori gi¶a esistenti, tra i quali gli stimatori dei modelli fattoriali e gli stimatori shrinkage bayesiani. Viene anche costruito un nuovo stimatore per la matrice di varianza e covarianza in sistemi di grandi dimensioni. Questo nuovo stimatore ¶e usato per testare la presenza della carat- teristica comune della correlazione seriale canonica (SCCF) in un contesto multivariato che comprende molte serie storiche collineari. Questo stimatore mostra una buona performance, in termini di size empirica, se confrontato con il metodo gi¶a esistente della analisi della correlazione canonica (CCA).

Questa tesi studia gli effetti macroeconomici degli shock di incertezza, shock fiscali e shock finanziari sul ciclo economico USA. La tesi si divide in quattro capitoli indipendenti, ognuno dei quali utilizza sistemi vettoriali autoregressivi, lineari e non-lineari, e local projections, al fine di estendere la ricerca empirica e valutare l’importanza dei diversi canali di trasmissione degli shock, così come proposti da modelli teorici. I risultati ottenuti dimostrano come tali shock hanno effetti non-lineari lungo il ciclo economico, e cioè la reazione delle variabili macroeconomiche è statisticamente differente se lo shock avviene durante una recessione piuttosto che durante un’espansione. Dalla prospettiva teorica, questi risultati sottolineano l’importanza di sviluppare modelli teorici non-lineari. Dalla prospettiva di politica economica, i risultati favoriscono l’implementazione di politiche asimmetriche come risposta a instabilità a livello macroeconomico.
This thesis investigates the macroeconomic effects of uncertainty, fiscal and financial shocks on the US economy. It is set out in four self-contained chapters, which use linear and nonlinear (Smooth Transition) Vector Autoregressive models, and Local Projections techniques, to extend the literature, and evaluate the importance of different transmission channels of macroeconomic shocks suggested by theoretical models. The main results show that these shocks have nonlinear effects over the business cycle, i.e., the response of macro aggregates following the shocks are statistically different depending on whether the economy is in a recession or expansion. From a theoretical perspective, this finding highlights the importance of accounting for nonlinearities when developing macroeconomic models. From a policy perspective, the results suggest the implementation of nonlinear policy rules to properly deal with macroeconomic instability.

碩士
國立嘉義大學
應用經濟學系研究所
99
This study uses structural vector autoregressive models to investigate the impact of monetary policy shocks from one country on the stock prices in another countries.We choose several large and relatively closed economies (such as the U.S. and China), and then select several small open economies (eg Taiwan and Canada), in order to set up the empirical models for comparison purposes. The empirical results show that short-term interest rates in response to domestic monetary policy shocks have different dynamic reactions; furthermore, the short-term interest rates in a small open economy quite quickly reacts, but not very sustainable, while the response in a relatively large country is long-run and persists for a period of time. In addition, we found there were differences in the macroeconomic interdependence between the two economies. The monetary policy in a relatively large economy affects the stock prices in a small economy substantially, but not sustainably. it is because the floating exchange rate regime can form a strong self-stabilizer in small open economics. Finally, this research proposes that it would be helpful on understanding the monetary policy transmission mechanism when the wealth effect is taken into account in the empirical open economies.

碩士
長庚大學
工商管理學系
101
Because it is not clear whether recent attempt for monetary integration is justified. This research aims to assess the suitability of forming a currency area in Asia. The main purpose is to examine the macroeconomic shocks among the Asian economics and its persistence properties in comparison with the European Monetary Union (EMU) countries. Estimates of structural VARs are used to ascertain if the countries under review meet the essential ingredients of an Optimum Currency Area (OCA) and thus are candidates for a monetary union. The result shows that in recent Asia area it is possible for forming a common Asian currency from a smaller currency groupings, Newly Industrialized Economies(NIEs) and ASEAN regions. The identifying candidates of economies for potential monetary union are China, South Korea, Taiwan, India and three ASEAN countries.

How do catch-up East Asian countries cultivate their exchange rate (ER) policies in a different trajectory than advanced economies often cited in current literature? What are the dynamics and results (pros and cons) of choosing a particular ER policy, and what influence does it have on the progress of developmental states? How do domestic and international politics explain the convergences and variances of ER policy decisions in East Asia? The decisions of ER policy are by all means political choices. ERs influence the prices of daily exchanged goods, and thereby determine resource allocation within and across national borders. Therefore, any internal political actor, including a government, interest group, foreign party or constituent exerts discretionary power to manipulate an ER to satisfy its own interests. Externally, the size of foreign trade and the status of international monetary accounts closely depend on the valuation and volatility of ER. Thus for the transitional polities and the trade-driving economies in East Asia, the analysis of ER politics not only helps to clarify the complex mechanisms of ER influences combined with various interests and institutional settings, but also to advance the political study of globalization. My dissertation proposes an integrated framework to contend that the domestic distributional politics and economic determinants, as well as the international monetary relations, and regional market force and adaptive policy diffusion are crucial factors that influence and interact with ER policy in East Asia. This theoretical framework explains how an ER policy decision is compromised between domestically generated preferences and apparently intense international interactions. Likewise, this dissertation provides a vigorous empirical specification toward the spatiotemporal differences of ER policy in East Asia. The application of the structural vector autoregression (SVAR) model properly specifies the theoretical dynamics across variables in the East Asian panel data compiled from 1980 to 2004. Furthermore, by using the alternative Bayesian estimation, SVAR successfully demonstrates the "spinning stories" that distinguish the variances with regard to country-specific development under the asymmetrically international and interdependently regional monetary system. The empirical findings verify that my theoretical variables interact significantly with ER policy decisions in East Asia. The statistics also demonstrate that most East Asian countries tend to strategically withstand influences from the various waves of capital liberalization and keep their currencies at low values. In a general testing, however, domestic pursuits for preferred interests gradually yield to the persistent influences of international and regional forces on ER policy making in East Asia.
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The dissertation is mainly made up of three empirical theses on the Optimum Currency Area theory, business cycle synchronization, and intra-industry trade. The second chapter conducts an empirical test into the theory of Optimum Currency Area. I investigate the feasibility of creating a currency union in East Asia by examining the dominance and symmetry of macroeconomic shocks. Relying on a series of structural Vector Autoregressive models with long-run and block exogeneity restrictions, I identify a variety of macroeconomic disturbances in eleven East Asian economies. To examine the nature of the disturbances, I look into the forecast error variance decomposition, correlation of disturbances, size of shocks, and speed of adjustments. Based on both statistical analysis and economic comparison, it is found that two groups of economies are subject to dominant and symmetrical domestic supply shocks, and that the two groups respond quickly to moderate-sized shocks. Therefore, it is economically feasible for the two groups of economies to foster common currency zones. The third chapter investigates the different effects of intra- and inter-industry trade on business cycle synchronization, controlling for financial market linkage and monetary policy making. The chapter is the first attempt to use intra- and inter-industry trade simultaneously in Instrument Variable estimations. The evidence in my paper is supportive that intra-industry trade increases business cycle synchronization, while inter-industry trade brings about divergence of cycles. The findings imply that country pairs with higher intra-industry trade intensity are more likely to experience synchronized business cycles and are more feasible to join a monetary union. My results also show that financial integration and monetary policy coordination provide no explanation for synchronization when industry-level trade are accounted for. The fourth chapter extends the third chapter and explores how the characteristics of global trade network influence intra-industry trade. Borrowing the concept of structural equivalence, the similarity of two countries’ aggregate trade relations with other countries, from the social network analysis, this study incorporates this measure of trade network to the augmented gravity model of intra-industry trade. I build up two fixed effects models to analyze intra-industry trade in the raw material and final product sectors among 182 countries from 1962 through 2000. Structural equivalence promotes intra-industry trade flows in the final product sector, but it does not influence intra-industry trade in the crude material sector. Moreover, structural equivalence has been increasingly important in boosting intra-industry trade over time.
Graduate
0508

Mestrado em Economia Monetária e Financeira.
The recent developments in the European economy, in general, and in Portugal, in particular, brought to the public debate the issue of the importance and the role of fiscal policy. The central point of this controversy is the dichotomy between discretionary fiscal policy and mies based fiscal policy, often referred as automatic fiscal stabilizers. On one hand, tliere are economists that defend the advantages of the automatic stabilizers on the economic cycle smoothing and. on the other hand; tliere are those ones that defend the implementation of discretionary fiscal measures to face adverse economic conditions. This work then arises to find answers to this discussion based on an empirical study for Portugal, from the first quarter of 1982 to the forth quarter of 2000, Using a structural VAR model, with GDP, Total Net Revenue and Total Spending, we identify, using institutional information, the automatic fiscal stabilizers. Having identified the structural shocks, the model is simulated to determine the effects of discretionary fiscal policy. These effects are then compared with the main results of others works in these area.
Os recentes desenvolvimentos na economia europeia, em geral, e em Portugal, em particular, trouxeram para o debate público a questão da importância e do papel da política orçamental. No centro desta polémica encontra-se a dicotomia entre a política orçamental discricionária e a política orçamental com base em regras ou restrições orçamentais, muitas vezes designados por estabilizadores orçamentais automáticos. Por um lado, existem aqueles que invocam as vantagens dos estabilizadores automáticos na suavização do ciclo do produto, por outro, aqueles que defendem a necessidade de fazer face a condições económicas adversas recorrendo a uma política orçamental discricionária. Este trabalho surge para tentar dar resposta a esta polémica, com base num estudo empírico para Portugal, do primeiro trimestre de 1982 ao quarto trimestre de 2000. Recorrendo a um VAR estrutural, com o PIB as Receitas Totais Líquida e as Despesas Totais do Estado, são identificadas, com base em informação institucional, os estabilizadores orçamentais automáticos. Tendo identificado os choques estruturais é simulado o modelo de forma a determinar os efeitos da política orçamental discricionária. Estes efeitos são depois comparados com os resultados de outros trabalhos desenvolvidos neste domínio.
N/A

In responding to subprime crisis with its peak with the bankruptcy of investment bank Lehman brothers in September of 2008, marking the end of the “great moderation”, several governments and central banks of developed and emerging economies change the respective fiscal and monetary policies, in order to stimulate the economy, some more than others, creating spillovers and transmit them by different channels through the stocks market worldwide. Furthermore, due to recent debate of the implementation of similar monetary stimulus program in China, like to the ones implemented in US and in currently in development in Euro Area, is relevant access the f policies consequences in China. The present work particularly focusses on the consequences of monetary and fiscal policies implemented in the United States, United Kingdom, Euro Area, Japan in China. The results show that the spillovers of the international fiscal and monetary policy are overall nonexistent or weak at best. However, there are significant spillovers of United States and Japan with China, the monetary policy of US has positive impact and the fiscal has negative impact on Shanghai stock returns, the same is true of the Japanese monetary policy.
Na resposta a crise do subprime com o seu auge com a falência do banco Lehman Brothers em setembro de 2008, marcando o fim da “grande moderação”, vários governos e bancos centrais de países desenvolvidos e em desenvolvimento mudaram as suas respetivas fiscais e monetárias, em ordem a estimular a economia, alguns com maior ímpeto que outas, criando spillovers e transmitindo os mesmos por diferentes canais para os mercados acionistas a nível mundial. Para alem do mais, devido ao recente debate de implementação de um programa de estímulos monetários semelhante na China aos que foram implementados nos EUA e atualmente em desenvolvimento na Área do Euro, é pertinente avaliar se os impactos das consequências destas politicas nos países desenvolvidos nos países emergente e viceversa. O presente trabalho foca-se nas consequências das politicas fiscais implementas nos Estados Unidos, Reino Unido, Área do Euro, Japão e China. Os resultados mostram que os spillovers das politicas monetária e fiscais seguidas por estes países são nulos ou muito residuais. Contudo, existe spillovers significativos dos Estados Unidos e do Japão com a China, a politica monetária dos Estados Unidos tem um impacto positivo e a politica fiscal tem um impacto negativo nos retornos do mercado acionista de Shanghai, o mesmo é verdade para a politica monetária japonesa.

The financial crisis of 2007/8 has triggered a profound debate about public budget finance sustainability, ever-increasing government expenditures and the efficiency of fiscal policy measures. Given this context, the following dissertation provides four contributions that analyze the long-run growth of government spending throughout economic development, discuss potential effects of fiscal policy measures on output, and provide new insights into the assessment of debt sustainability for a variety of industrialized countries. Since the breakout of the European debt crisis in 2009/2010, there has been a revival of interest in the long-term growth of government expenditures. In this context, the relationship between the size of the public sector and economic growth - often referred to as Wagner's law - has been in the focus of numerous studies, especially with regard to public policy and fiscal sustainability. Using historical data from the mid-19th century, the first chapter analyzes the validity of Wagner's law for five industrialized European countries and links the discussion to different stages of economic development. In line with Wagner's hypothesis, our findings show that the relationship between public spending and economic growth has weakened at an advanced stage of development. Furthermore, all countries under review support the notion that Wagner's law may have lost its economic relevance in recent decades. As a consequence of the 2007/8 financial crisis, there has been an increasing theoretical and empirical debate about the impact of fiscal policy measures on output. Accordingly, the Structural Vector Autoregression (SVAR) approach to estimating the fiscal multipliers developed by Blanchard and Perotti (2002) has been applied widely in the literature in recent years. In the second chapter, we point out that the fiscal multipliers derived from this approach include the predicted future path of the policy instruments as well as their dynamic interaction. We analyze a data set from the US and document that these interactions are economically and statistically significant. In a counterfactual simulation, we report fiscal multipliers that abstract from these dynamic responses. Furthermore, we use our estimates to analyze the recent fiscal stimulus of the American Recovery and Reinvestment Act (ARRA). The third chapter contributes to the existing empirical literature on fiscal multipliers by applying a five-variable SVAR approach to a uniform data set for Belgium, France, Germany, and the United Kingdom. Besides studying the effects of expenditure and tax increases on output, we additionally analyze their dynamic effects on inflation and interest rates as well as the dynamic interaction of both policy instruments. By conducting counterfactual simulations, which abstract from the dynamic response of key macroeconomic variables to the initial fiscal shocks, we study the importance of these channels for the transmission of fiscal policy on output. Overall, the results demonstrate that the effects of fiscal shocks are limited and rather different across countries. Further, it is shown that the inflation and interest rate channel are insignificant for the transmission of fiscal policy. In the field of public finances, governmental budgetary policies are among the most controversial and disputed areas of political and scientific controversy. The sustainability of public debt is often analyzed by testing stationarity conditions of government's budget deficits. The fourth chapter shows that this test can be implemented more effectively by means of an asymmetric unit root test. We argue that this approach increases the power of the test and reduces the likelihood of drawing false inferences. We illustrate this in an application to 14 countries of the European Monetary Union as well as in a Monte Carlo simulation. Distinguishing between positive and negative changes in deficits, we find consistency with the intertemporal budget constraint for more countries, i.e. lower persistence of positive changes in some countries, compared to the earlier literature.

Questa tesi presenta tre diverse applicazioni di macroeconomia e finanza delle tecniche di analisi di testi basate su algoritmi di apprendimento automatico non supervisionati. In particolare, queste tecniche di analisi di testi vengono applicate ai documenti ufficiali delle banche centrali e agli articoli di giornale scritti in inglese e spagnolo. L'implementazione di queste tecniche ha comportato un considerevole lavoro di preelaborazione per rimuovere paragrafi e articoli non rilevanti per l'analisi. Ai documenti ufficiali delle banche centrali, abbiamo assegnato etichette ad ogni paragrafo per indicare la data e altra informazione utile. Abbiamo quindi applicato vari algoritmi di apprendimento automatico non supervisionato come Latent Dirichlet Allocation (LDA), il modello Skip-Gram e K-Means per costruire misure di testo. Alcuni di questi algoritmi di apprendimento automatico non supervisionati, che erano già disponibili per la lingua inglese, sono stati adattati alla lingua spagnola. Abbiamo prodotto semplici misure del contenuto della comunicazione per identificare gli argomenti, cioè i temi o soggetti, e il tono, cioè il sentimento o il grado di incertezza del testo. Quindi, abbiamo studiato la relazione tra questi indici di incertezza e le variabili economiche chiave in macroeconomia e finanza utilizzando i modelli VAR strutturale e GARCH esponenziale. Il primo articolo indaga la relazione tra le opinioni espresse nei verbali delle riunioni del Comitato di politica monetaria (COPOM) della Banca Centrale del Brasile e l'economia reale. In primo luogo, deduciamo il contenuto dei paragrafi dei minuti con LDA e poi costruiamo un indice di incertezza per i minuti con Word Embeddings e K-Means. Dopo costruiamo due indici di incertezza per diversi contenuti, Il primo indice di incertezza del tema è costruito da paragrafi con una maggiore probabilità di argomenti relativi alle "condizioni economiche generali", mentre il secondo indice di incertezza del tema è costruito da paragrafi con una maggiore probabilità di argomenti relativi a "inflazione" e “discussione della politica monetaria”. Infine, tramite un VAR strutturale esploriamo gli effetti di questi indici di incertezza su alcune variabili macroeconomiche brasiliane Il secondo articolo studia e misura l'incertezza nei verbali delle riunioni del consiglio di amministrazione della Banca Centrale del Messico e la mette in relazione con le variabili di politica monetaria. In particolare, concepiamo due indici di incertezza per la versione spagnola dei verbali utilizzando tecniche di apprendimento automatico senza supervisione. Il primo indice di incertezza è costruito sfruttando LDA, mentre il secondo utilizza il modello Skip-Gram e K-Means. Costruiamo anche indici di incertezza per le tre sezioni principali del verbale. Troviamo che una maggiore incertezza nei verbali è correlata a un aumento dell'inflazione e della massa monetaria. Il terzo articolo indaga le reazioni dei mercati finanziari statunitensi alle notizie dei giornali dal gennaio 2019 al primo maggio 2020. A tal fine, deduciamo il contenuto e il sentimento delle notizie sviluppando indici dai titoli e dai frammenti del New York Times . In particolare, utilizziamo LDA per dedurre il contenuto degli articoli e gli algoritmi Skip-Gram e K-Means per misurare il loro sentimento (incertezza). In questo modo si arriva alla definizione di una serie di indici giornalieri di incertezza per ogni tema. Questi indici vengono quindi utilizzati per trovare spiegazioni nel comportamento dei mercati finanziari statunitensi implementando una serie di modelli EGARCH. In sostanza, troviamo che due indici di incertezza e argomento, uno relativo alle notizie COVID-19 e l'altro alle notizie sulla guerra commerciale, spiegano gran parte dei movimenti nei mercati finanziari dall'inizio del 2019 fino ai primi quattro mesi del 2020 .
This thesis presents three different applications to macroeconomics and finance of text mining techniques based on unsupervised machine learning algorithms. In particular, these text mining techniques are applied to official documents of central banks and to newspaper articles written in English and Spanish. The implementation of these techniques involved a considerable preprocessing work to remove paragraphs and articles not relevant for the analysis. To the official documents of the central banks, we also assigned tags to each paragraph to indicate the date and other useful information. We then applied various computational linguistic unsupervised machine learning algorithms such as Latent Dirichlet Allocation (LDA), Word Embedding (with the Skip-Gram model) and K-Means to construct some text measures. Some of these unsupervised machine learning algorithms, which were already available for the English language, have been adapted to the Spanish language. We produced simple measures to identify the topics, that is, the themes or subjects, and the tone, that is, the sentiment or degree of uncertainty, of the text. Finally, we investigated the relationship between these uncertainty indices and some key variables in macroeconomics and finance using Structural VAR and Exponential GARCH models. The first paper investigates the relationship between the views expressed in the minutes of the meetings of the Central Bank of Brazil’s Monetary Policy Committee (COPOM) and the real economy. Firstly, we infer the content of the paragraphs of the minutes with Latent Dirichlet Allocation and then we build an uncertainty index for the minutes with Word Embedding and K-Means. Thus, we create two topic-uncertainty indices. The first topic-uncertainty index is constructed from paragraphs with a higher probability of topics related to “general economic conditions”, whereas the second topic-uncertainty index is constructed from paragraphs with a higher probability of topics related to “inflation” and the “monetary policy discussion”. Finally, via a Structural VAR we explore the lasting effects of these uncertainty indices on some Brazilian macroeconomic variables. The second paper studies and measures uncertainty in the minutes of the meetings of the board of governors of the Central Bank of Mexico and relates it to monetary policy variables. In particular, we conceive two uncertainty indices for the Spanish version of the minutes using unsupervised machine learning techniques. The first uncertainty index is constructed exploiting Latent Dirichlet Allocation, whereas the second uses Word Embedding (with the Skip-Gram model) and K-Means. We also create uncertainty indices for the three main sections of the minutes. We find that higher uncertainty in the minutes is related to an increase in inflation and money supply. The third paper investigates the reactions of US financial markets to newspaper news from January 2019 to the first of May 2020. To this end, we deduce the content and sentiment of the news by developing apposite indices from the headlines and snippets of the New York Times. In particular, we use Latent Dirichlet Allocation to infer the content of the articles, and Word Embedding and K-Means to measure their sentiment (uncertainty). In this way, we arrive to the definition of a set of daily topic-specific uncertainty indices. These indices are then used to find explanations in the behaviour of the US financial markets by implementing a batch of EGARCH models. In substance, we find that two topic-specific uncertainty indices, one related with COVID-19 news and the other with trade war news, explain much of the movements in the financial markets from the beginning of 2019 up to the first four months of 2020.