The importance of a currency war and its consequences is nowadays a hot topic of all economies around the world. My master thesis is designed to explain this concept, to introduce the main actors of the currency wars, the ways, in which national economies were and are trying to boost and improve their economic situation and highlight the main tools that are usually used by major powers within currency wars. The practical part is divided into three main sub-chapters that analyze the causes and consequences of currency wars, which we have previously witnessed. Analysis of the currency war I. relates to the years 1921-1936, the currency war II. relates to the period around World War II. and the formation of Bretton Woods system, and finally currency war III. relates to last years, when a superpowers like US, China and EU entered the war as a result of economic recessions of 2007.

The main focus of this thesis rests in the assessment of the quantitative easing policy impact on commodity prices and prices of commodity derivatives in the US. Several VAR models have been constructed in this paper to capture the relations between time series of monetary policy variables and commodity markets indices. The impulse-response analysis applied in the VAR models has discovered the causal connection between the QE policy and the value of commodity indices. The official announcement of initiation (extension) of the policy of the QE policy and its realization consisting of purchases of vast amount of treasury securities and federal agency debt and MBS has lead to the major commodity indices increase. Since this fact has been overlooked by Fed so far, its acceptance might enhance the realization of possible future QE policy and the valuation of the QE as a monetary policy alternative in conditions of zero-bound.

The diploma thesis is focused on the origin and development of the world financial crisis started in 2007 and its analysis. The steps taken by the European Central Bank and the Czech National Bank to respond to this crisis are then analyzed. Furthermore, the work shows the impact of the crisis and central bank measures on two selected domestic banks. At the end of the thesis are made suggestions and recommendations.

This thesis applies time-varying parameter vector autoregression (TVP-VAR) model with stochastic volatility to assess the effectiveness of quantitative easing in time for the Bank of Japan, the European Central Bank, the Bank of England and the Federal Reserve System between the global financial crisis and COVID-19 pandemic. We find pronounced and statistically significant response of GDP and level of implied stock market volatility to a QE shock whereas the response of CPI is feeble and statistically insignificant. We argue that this does not necessarily imply that there is no effect of QE on CPI but rather that our model was not able to detect it. We believe that this may be due to inflation expectations channel which our model did not account for. This can be reassessed with a TVP-FAVAR model which is more suitable for such an analysis as it can encompass a larger set of variables. Moreover, apart from the US, we report increasing effectiveness of QE in time. This is opposed by the researchers who believe that QE has rather decreasing effectiveness in time because it is more efficient during economic distress and then its efficiency tends to decrease during normal times. We explain this deviation by citing other unconventional monetary tools such as credit easing, forward guidance or negative...

Quantitative easing (QE) is an unconventional monetary policy tool used by central banks to stimulate the economy in times when conventional monetary policy is not sufficient. In the wake of covid-19, central banks around the world has announced significant increases in their QE-programs. This research paper aims to find out whether quantitative easing has any statistically significant effect on the stock prices of the Swedish real estate market. Moreover, it aims to produce an indication of the direction of the real estate stock prices over the year of 2020. To those ends, a combination of statistical analysis and economic theory is used. We estimate three Autoregressive Distributed Lag (ARDL) models. For a chosen model, an out-of-sample prediction is carried out as a way to model future stock price movements. We conclude that quantitative easing indeed has a statistically significant effect on real estate stock prices in Sweden. Furthermore, we estimate that stock prices in the real estate sector will see negative movements during the second and third quarter of 2020, followed by a return to positives during the fourth quarter. / Kvantitativa lättnader (QE) är ett redskap inom okonventionell penningpolitik som används av centralbanker för att stimulera ekonomin när konventionella metoder inte är tillräckliga. I kölvattnet av covid-19 så har centralbanker runt om i världen meddelat kraftiga ökningar i deras program för kvantitativa lättnader. Den här uppsatsen syftar till att ta reda på om kvantitativa lättnader har någon statistiskt signifikant påverkan på priserna för fastighetsaktier som handlas på öppen marknad i Sverige. Därutöver syftar den till att ge en anvisning kring i vilken riktning priserna på dessa aktier kommer röra sig under 2020. För dessa ändamål används en kombination av statistisk analys och ekonomisk teori. Vi estimerar tre Autoregressive Distributed Lag (ARDL) modeller. För en av modellerna görs en out-of-sample prediktion för att modellera framtida prisrörelser på aktiemarknaden. Utifrån våra modeller och analys kan vi konstatera att kvantitativa lättnader har en effekt på priserna för fastighetsaktier. Vidare så estimerar vi att priserna på fastighetsaktier kommer röra sig i en negativ riktning under andra och tredje kvartalet 2020, för att sedan svänga tillbaka till positiva rörelser under fjärde kvartalet.

This thesis aims to study how much of price appreciations on the Swedish real-estate market in recent times have been fundamentally warranted, as well as if the unconventional monetary policies implemented by the Swedish central bank have had any interaction with these price escalations. The methodology employed to research this is divided into two parts. Firstly, a bubble component time series has been computed using a Kalman filtering technique in a state-space model in which the bubble is inferred from a fundamental equation. The next step involves studying the dynamics between the bubble element vis-a-vis the quantitative easing policies implemented by Riksbanken. This procedure involves estimating vector autoregressive models in which several policy variables are included in the nexus and analyzed simultaneously to better grasp how QE transmits and impacts the component for the bubble. The empirical results from the first segment designate that price inflation on the Swedish housing market has become more and more principally unjustifiable throughout the sample. However, no significant inference may be made in this stage as to whether or not the market is influenced by a speculative bubble. In the dynamic system, some, yet thin evidence is found of quantitative easing policies preceding the evolvement of exuberance in house prices. Conclusively, this thesis affirms most of the growth in the non-fundamental part of prices to an expansion of credit, which in turn cannot be accredited to the policies of the Swedish Riksbank. Only a slight expectational effect is found and therefore we conclude that quantitative easing only has a trivial impact on the development of a speculative bubble in the market for real-estate.

This licentiate thesis is a collection of two essays that utilize time-series econometric methods in real estate finance. The first essay applies econometric modelling on Real Estate Investment Trust (REIT) index returns, focusing on estimating the effect of the quantitative easing (QE) and quantitative tightening (QT) programmes on U.S. equity REIT index returns, while controlling for several other important macro-financial factors. The second essay instead focuses on forecasting U.S. equity REIT index returns empirically, where the performance of a traditional econometric model (ARIMA) is compared to a modern state-of-the-art deep learning-based model (LSTM). Digitalization, which encompasses a broad range of technological advancements, is the main factor that we study for its impact on REIT investments. One perspective on the impact of digitalization on REITs is its effect on inflation. Digitalization has the potential to increase productivity and reduce costs, which could help to keep inflation low. This, in turn, has in the recent decades provided a supportive environment for REIT investments through lower interest rates, which we partly investigate in the first essay. Another perspective is that digitalization has not only led, but is also expected to lead, to significant innovations in the field of artificial intelligence (AI) and machine learning (ML), including deep learning (DL), which is a subset of ML. Many researchers and market practitioners are currently working to develop models that can use large amounts of data to make better forecasts and investment decisions. If successful, these models could significantly improve the performance of REIT investments. Can DL models be trained to make better forecasts for making investments? This is a question we ask ourselves in the second essay. The study of digitalization and its effects on inflation has been a growing area of interest in recent years, with researchers exploring the potential impact of technological advancements on macroeconomic trends, which founded the base to our studies. However, recent developments in the global economy have shifted the focus of this research, as inflation levels have unexpectedly risen from what was previously believed to be a low and stable environment. As a result, the setting and framework for our research on digitalization and inflation have been significantly altered, as we have tried to adapt to this changing landscape. / Denna licentiatuppsats är en samling av två forskningsartiklar som använder tidsserieekonometriska metoder inom finansiell ekonomi med fokus på fastighetsaktier. Den första artikeln tillämpar ekonometriska metoder på tidsseriedata för amerikanska börsnoterade fastighetsfonder, Real Estate Investment Trusts (REITs), med fokus på att uppskatta effekten av icke-konventionella penningpolitiska aktiviteter (kvantitativa lättnader och kvantitativ åtstramning) på avkastningsserierna, samtidigt som vi kontrollerar för andra viktiga makroekonomiska och finansiella variabler. Den andra artikeln fokuserar istället på att bygga modeller för prognoser av avkastningen på avkastningsserierna empiriskt, där prognosfelen för en traditionell ekonometrisk modell (ARIMA) jämförs med en modern djupinlärningsbaserad modell (LSTM). Digitalisering, som omfattar ett brett spektrum av tekniska framsteg, är den viktigaste faktorn som vi studerar för dess inverkan på REIT-investeringar. Ett perspektiv på digitaliseringens inverkan på REITs är dess effekt på inflationen. Digitalisering har potential att öka produktiviteten och minska kostnaderna, vilket kan bidra till att hålla inflationen låg. Detta har i sin tur under de senaste decennierna varit fördelaktigt för REIT-investeringar genom lägre räntor, vilket vi delvis undersöker i den första uppsatsen. Ett annat perspektiv är att digitaliseringen inte bara har lett, utan också förväntas leda, till betydande innovationer inom området artificiell intelligens (AI) och maskininlärning (ML), inklusive djupinlärning (DL), som är en delmängd av ML. Många forskare och professionella aktörer arbetar just nu med att utveckla modeller som kan använda stora mängder data för att göra bättre prognoser och investeringsbeslut. Om de lyckas kan dessa modeller förbättra resultatet för REITinvesteringar avsevärt. Kan DL-modeller tränas för att förbättra möjligheterna till att göra mer tillförlitliga prognoser och därmed öka chanserna till att göra mer lönsamma investeringar? Det är en fråga vi ställer oss i den andra artikeln. Digitalisering och dess effekter på inflationen har varit ett starkt växande fält inom såväl forskning som praktisk tillämpning de senaste åren, med forskare som undersöker den potentiella inverkan av tekniska framsteg på makroekonomiska trender, vilket har legat till grund för våra studier. Den senaste tidens utveckling i den globala ekonomin har dock flyttat fokus för denna forskning, eftersom inflationsnivåerna oväntat har stigit från vad som tidigare ansågs vara en låg och stabil miljö. Som ett resultat har miljön och ramarna för vår forskning om digitalisering och inflation ändrats avsevärt, eftersom vi har försökt anpassa oss till detta föränderliga landskap. / <p>QC 20231201</p>

The aim of this thesis is monetary policy of the Federal Reserve during the global financial crisis and its impact on the U.S. economy. Intensively carried out the financial crisis in 2007 - 2009. At that time, the Fed has created several tools to support liquidity of depository institutions and primary dealers, which are represented mainly by investment banks and other businesses, such as money market funds. The balance sheet of the central bank has fundamentally transformed. Securities accepted in open market operations have expanded and amount of the balance sheet has increased several times. Operations that change size of liabilities and composition of assets are called quantitative easing. After the interventions of the U.S. central bank the financial markets stabilized and Fed set aside some of the new tools. From December 2007 to June 2009 was the U.S. economy officially in recession. Since then has economic activity been growing but only very slowly.

Cette thèse contribue à la littérature sur le défaut souverain en offrant une nouvelle approche d'analyse, réconciliant les approches statistiques et structurelles. Avec comme fil rouge le lien entre crises financières, accumulation de dette et défaut souverain, ce travail répond à trois questions principales.En premier lieu, quand les pays font-ils défaut ? En posant un simple regard sur les principales variables macroéconomiques et les composantes cycliques des défauts souverains, je montre que le défaut se produit quand le pays subit un retournement brutal de croissance, ajouté à un large choc discontinu sur son ratio de dette sur PIB, apporté en majorité par une crise de change ou une crise bancaire.En second lieu, en quoi le risque souverain au sein d'une zone monétaire (par exemple la zone euro) diffère de celui d'une petite économie ouverte en change flexible, majoritairement décrit dans la littérature ? Je construis un modèle DSGE néo-keynésien dans lequel j'introduis du risque souverain ; je mets l'accent sur le rôle clé des comportements de consommation, à la fois dans la préférence pour l'union monétaire et dans la décision de défaut. Je regarde également l'efficacité de certaines politiques fiscales sur la réduction du risque souverain dans une zone monétaire.Enfin, les instruments de politique monétaire ont-ils été efficaces pendant la crise pour réduire les taux souverains ? J'évalue la transmission de la politique monétaire de la BCE, à la fois conventionnelle et non-conventionnelle, aux taux et aux volumes d'émissions de titres souverains pour les quatre plus importantes économies européennes. Je montre que seule la transmission du taux directeur vers les taux souverains a été effective ; les instruments non-conventionnels ont eu des résultats contrastés et essentiellement sur les taux d'intérêt. / This thesis offers a new approach to sovereign default analysis, by tackling both statistical and the structural approaches to sovereign default. Starting from the link between financial crises, debt accumulation and sovereign default, it answers three main questions.First, when do countries default? Taking a simple look at macroeconomic variables and business cycles around default, I show that economic defaults occur when the country experiences a switch from a boom to a bust, combined with a large discontinuous shock on its debt-to-GDP ratio, brought mainly by a currency or a banking crisis.Second, how sovereign risk in a monetary union (e.g. the Eurozone) differs from sovereign default risk in a small open economy usually described in default literature? Constructing a New-Keynesian DSGE model with sovereign default risk, I exhibit the key role of habit persistence in the preference for a monetary union and the default decision. I am also able to test the efficiency of various policy tools on sovereign risk.Third, have monetary policy tools been efficient to reduce sovereign spreads in the Eurozone? I assess the transmission of ECB monetary policies, conventional and unconventional, to both interest rates and bond issuance for the four largest economies of the Euro area. The main result is that only the pass-through from the ECB rate to interest rates has been effective. Unconventional policies have had uneven effects and primarily on interest rates.

本研究致力於探討美國聯準會(FED)實施量化寬鬆政策(QE)與否，商業銀行資產負債表對於股價的影響。本文藉由總經指標(工業生產指數、製造業採購經理人指數)、利差變數(公司債利差、10年期公司債利差)，以及資產負債表變數(存款、貸款等)，對商業銀行股價進行解釋。並透過量化寬鬆政策(QE)的虛擬變數，了解該政策對股價的影響，以及實施該政策是否能夠改善資產負債表變數的顯著程度和影響方向。方法上，本文採用迴歸分析的方式進行實證分析。首先，研究以總經指標以及利差變數對股價進行解釋，且期間限定為量化寬鬆政策期間，藉此確認這兩類變數對股價的影響。後續則以加入資產負債表變數、量化寬鬆(QE)虛擬變數等，並將期間延伸至15年，以進一步釐清實施量化寬鬆(QE)政策的影響。本文實證結果顯示，美國量化寬鬆政策對於商業銀行股的股價有負面影響，且活期存款對股價的影響亦為負向。 / The thesis focuses on the FED policy – Quantitative Easing (QE) and how the policy affect the S&P 500 commercial bank sub-index return. Based on past researches, the article includes macroeconomic variables (IP, PMI), term structure variables, bank balance sheet variables (deposits and loans), and a QE dummy variable. With these variables, the outcomes are generated by regression. It can be observed that with the implementation of QE policy, stock returns are negative on average. Moreover, large banks would benefit from provide more commercial loans; on the other hand, small banks would obtain a positive return by lending more consumer loans. Demand deposits are another significant variable which would have negative impact on stock returns.