Title: M&A activity and the macroeconomic environment - a quantitative study on the impact of the macroeconomic environment on aggregate merger and acquisition activity in the US Background: There is a lack of established theories on what drives M&A activity. A subject that has received much attention in literature but produced few compelling results. The full explanation of the dynamics of aggregate M&A activity has yet to be captured. An explanation which could provide useful insights for central banks, corporate managers and any other parties affected by this prominent feature of the US economy which have come to shape and dominate the corporate landscape. Purpose: The purpose of this thesis is to investigate the relationship between the dynamics of aggregate M&A activity and macroeconomic variables representing the state of the economy in the US. Method: The methodology that is used in the thesis is based on a deductive research approach with a quantitative research design. In addition, the thesis has also made use of a longitudinal panel research. The thesis hypotheses have been formulated using earlier research and existing theories about the subject of mergers and acquisitions as well as macroeconomic factors. Further on, the data set that has been analyzed consisted of 73137 transactions during the time period January 1, 1980 - January 1, 2020. Conclusion: The study finds that there are signs of relationships between macroeconomic variables and aggregate M&A activity, although the precise characteristics of these relationships has not been established. The result of the study indicates that the macroeconomic environment as a whole affects aggregate M&A activity and that it can be an important part of the explanation for the dynamics of aggregate M&A activity. It cannot be established that macroeconomic variables can be used to predict M&A activity, however there are interesting indications suggesting this might be the case.

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A sound banking system is essential to a well-functioning economy. With the financial crisis beginning in 2007, a renewed interest in the safety of financial institutions has dominated both the political and financial landscape. Mounting loan losses in real estate lending led to the failing of over 460 banks from 2008 to 2012. This crisis is not unique; in fact, the Savings & Loan Crisis of the 1980's to early 1990's led to the closure of 700 savings institutions. Both instances created a panic in financial markets and heavy losses to deposit insurance funds. These losses are ultimately borne by taxpayers and prudently managed banks, especially if the insurance fund requires re-capitalization. The focus of this paper is on explaining the contributing factors to different categories of loan losses. Namely, total loan losses, residential real estate loan losses, commercial real estate loan losses, and commercial and industrial loan losses are examined. A multivariate regression approach is taken in this paper to explain the four rates of loan losses for the period of 2001 to 2012. Aggregate macroeconomic data from 2001 to 2012 is used to explain loan losses across categories. It was found that the delinquency rate of loans, the consumer financial obligations ratio, and the financial crisis were all significant factors in explaining loan losses.

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[pt] Nesse artigo aplicamos a técnica de estimação dos nowcasts apresentada por Giannone, Reichlin e Small (2008), para o PIB e inflação brasileiros. Extraímos informações de um elevado número de variáveis e produzimos modelos capazes de informar contemporaneamente uma medida para as variáveis em questão. Em posse dessa leitura cotidiana, produzida por esses modelos, estimamos uma regra de Taylor diária para o Banco Central do Brasil (BCB), o que permitiu melhor identificar choques monetários e alterações na função de reação do BCB ao longo do tempo. Concluímos, primeiramente, que os modelos nowcasts apresentam acurácia comparável às previsões do relatório Focus do BCB. Segundo, 2 (duas) comparações históricas realizadas mostraram indícios que nossa proxy para choques monetários diários está relacionada às decisões explícitas de política monetária. Por fim, encontramos evidências que os modelos nowcasts puderam capturar grande parte da informação relevante para a determinação da taxa de juros de curto prazo, o que deveria estimular a aplicação de tais modelos nos processos decisórios públicos e privados. / [en] In this article we apply the two-steps nowcasting method, described in Giannone, Reichlin, and Small (2008), to build nowcast models for Brazilian GDP and inflation. Throught the application of this method, we could extract information from a large data-set and build models which could be used to produce a daily measurement of GDP and inflation. Using this measurement was possible to build a daily Taylor rule for the Brazilian Central Bank (BCB). This new application of nowcast models allowed us to extract a daily measurement of monetary shocks. Our study produced three main findings. First, the nowcast model showed an accuracy close to projections presented in the Focus survey. Second, we identified by historical comparison that the monetary shocks proxy, measured by the differences between the daily Taylor rule and the movements in the short-term interest rate, are related with unanticipated monetary policies decisions. Finally, nowcasts were able to capture a great part of relevant information to determine the short-term interest rate, which should stimulate the policymakers and financial markets members to apply those models.

A wide variety of machine learning algorithms havebeen used to predict stock prices. The aim of this project hasbeen to implement a machine learning algorithm using supportvector regression to predict the stock price of two well knowncompanies—Apple and Microsoft—one day into the future usingthe current day’s stock price, macroeconomic data and microeconomicdata and to compare the prediction error with the differentdata inputs. The results show that the addition of macroeconomicand microeconomic data did not improve the prediction error.This suggests that the macroeconomic and microeconomic dataused in this project does not contain additional information aboutfuture stock prices. The results also show that support vectorregression performs worse than linear regression, however inthis case no definite conclusion can be drawn since only onekernel and a handful of parameter values were considered whentraining and testing the algorithm. However, these results mightalso suggest that using the current day’s data is not sufficient tobe able to predict the non-linear relationships. / Ett flertal maskininlärnings-algoritmer har använts för att förutspå aktiepriser. Målet med det här projektet har varit att implementera en maskininlärnings-algoritm som använder sig av support vector regression för att förutspå aktiepriset av två välkända företag—Apple och Microsoft—en dag in i framtiden genom att använda dagens aktiepris, makroekonomisk data och mikroekonomisk data samt att jämföra prediktionsfelet med dem olika indata. Resultaten indikerar att additionen av makroekonomisk och mikroekonomisk data inte förbättrade prediktionsfelet. Detta antyder att den makroekonomiska och mikroekonomiska data som användes i projektet inte innehåller någon ytterliggare information om framtida aktiepriser. Resultaten indikerade också att linjär regression presterar bättre än support vector regression, men i detta fallet kan ingen definitiv slutsats dras eftersom endast en kernel och ett par parameter-värden användes för att träna och testa algoritmen. Däremot kan dessa resultat också antyda att a inte är tillräcklig för att kunna förutspå dem icke-linjära förhållandena. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

[pt] Black e Litterman propuseram um modelo de seleção de portfólio que combina a visão dos investidores acerca de ativos com conceitos de equilíbrio de mercado para construir portfólios ótimos. Entretanto, a eficiência do modelo depende da qualidade da visão futura acerca do retorno dos ativos, o que é desafiador na prática. Com o objetivo de melhorar a aplicação prática do modelo Black-Litterman, o foco desse trabalho é viabilizar novas alocações com base em visões de fatores macroeconômicos que estão fora do universo de alocação. A principal vantagem é que a previsão desses fatores é amplamente fornecida por agentes de mercado. Um estudo de caso baseado nas informações disponibilizadas pelo Banco Central do Brasil é apresentado para validar a estrutura proposta. Os retornos obtidos fora da amostra e ajustados ao risco incorporando a visão de fatores macroeconômicos com a estrutura proposta superaram o modelo de média-variância tradicional e o benchmark local. / [en] Black and Litterman proposed a portfolio selection model that blends investor s views on asset returns with market equilibrium concepts to construct optimal portfolios. However, the model efficiency relies on the performance of investors views regarding tradable assets, which is challenging in practice. Focusing on improving Black-Litterman practical application, this work consists in providing new allocations based upon views on macroeconomic factors, which are largely available but not directly tradable. The main advantage is that predictions on these factors are usually provided by market players. A case study based on the information disclosed by the Brazilian Central Bank is presented to test the proposed framework. The out-of-sample risk-adjusted returns obtained incorporating the players macroeconomic expectations through the use of the proposed framework outperformed the traditional mean-variance model as well as the local benchmark.

The Swedish real estate market has, and arguably still continues to, endure a crisis in terms of increased interest rate followed by uncertainties on a global scale. Both the residential and commercial real estate market has been affected, seeing prices and transaction volumes decrease as a consequence. The commercial real estate market is largely dependent on financing, which is further strengthened by the large amount of the Swedish banks’ total lending that is directed towards the commercial real estate sector. These aspects combined proves the need of accurately forecasting the real estate market, partly in the aspect of investment decision making but also in relation to the development of the overall economy.  To connect the real estate market with the economy as a whole, this study will analyze five different macroeconomic variables’ effect on the transaction price on commercial real estate in Sweden, as well as making forecasts on the future outlook of real estate prices in relation to the development of the variables. This is conducted with the time series regression model ARIMAX, which utilizes lagged versions of previous commercial real estate prices along with macroeconomic variables in terms of GDP, KIX (the krona index), real interest rate, the Euro/SEK exchange rate as well as the unemployment rate. The model is conducted in relation to the commercial real estate market in Sweden, with a dataset of commercial transactions ranging from 1996 until 2023. Additionally, an analysis of a subset of solely the industrial segment is investigated.  Lastly, the forecasting of real estate prices was conducted in relation to a scenario analysis. The analysis was built on multiple market outlooks by utilizing a predictive movement of the independent variables in relation to three scenarios: pessimistic, base and optimistic. The results of the scenario analysis depicts a fairly modest difference in predicted outcomes on the transaction price in December 2024 in relation to the different scenarios. / Den svenska fastighetsmarknaden har genomgått, och enligt vissa prognoser genomgår, en kris i form av höjda räntor följt av osäkerheter på global nivå. Både bostadsfastigheter och kommersiella fastigheter har påverkats och priserna och transaktionsvolymerna har sjunkit som en följd av detta. Den kommersiella fastighetsmarknaden är till stor del beroende av finansiering, vilket ytterligare förstärks av att en stor del av de svenska bankernas totala utlåning är riktad mot den kommersiella fastighetssektorn. Dessa aspekter sammantaget visar på behovet av att kunna göra korrekta prognoser för fastighetsmarknaden, dels för att kunna fatta investeringsbeslut men också för att kunna bedöma utvecklingen av ekonomin överlag.  För att koppla samman fastighetsmarknaden med ekonomin i stort kommer denna studie att analysera fem olika makroekonomiska variablers effekt på transaktionspriset på kommersiella fastigheter i Sverige, samt göra prognoser om fastighetsprisernas framtidsutsikter i förhållande till variablernas utveckling. Detta görs med tidsserieregressionsmodellen ARIMAX, som utnyttjar laggade versioner av tidigare kommersiella fastighetspriser tillsammans med makroekonomiska variabler i form av BNP, KIX (kronindex), realränta, växelkursen Euro/SEK samt arbetslöshet. Modellen genomförs i relation till den kommersiella fastighetsmarknaden i Sverige, med ett dataset av kommersiella transaktioner från 1996 till 2023. Dessutom genomförs en analys av enbart industrisegmentet. Slutligen genomfördes en prognostisering av fastighetspriserna med hjälp av en scenarioanalys. Analysen byggde på flera marknadsutsikter genom att använda den förutspådda förändringen av de oberoende variablerna i förhållande till tre scenarier: pessimistisk, bas och optimistisk. Resultatet av scenarioanalysen visar på en svag men noterbar skillnad i förväntat utfall för transaktionspriset i december 2024 i förhållande till de olika scenarierna.

This study discusses the case of modernising the Southern African Development Community (SADC) regional payments system facilitated by the SADC Payment System Project. The long-term objective is to have harmonised cross-border and inter-bank settlement systems to facilitate the economic activity such as supporting the flow of trade within the SADC region. The SADC Payment System Project purports to have adopted a strategic management process to achieve its mandate. The modernisation process is in line with the Regional Indicative Strategic Development Plan (RISDP). The aim of the RISDP is to provide strategic direction with respect to various SADC programmes and activities and to align the strategic objectives and priorities of SADC with the policies and strategies for achieving its long-term goals. The concept of payment, clearing and settlement system is explained to provide the context within which the national payment system fits in the economic system and its role towards economic development. The first objective of the study is to discuss the strategic management process. The objective of the discussion is to reflect how the strategic management theoretical constructs were translated into practice. The second objective of the study is to explore the environmental and country internal factors that are likely to impact on and delay the fully harmonised regional cross-border and inter-bank settlement systems. Although not exhaustive, the identified factors include; - The structural arrangements of country- specific teams that support the modernisation initiatives, - The availability of skills and capacity to harness the implemented systems within each member country in the SADC region. iii - The influence of foreign fund donors, as a result of a possible duplication of efforts, - The repair state of power supply and communication networks, - The supporting legal and regulatory regimes, - The forms of economic systems, - The influence and the extent of trade flows with the SADC region, and - The resilience banking networks in the facilitation of financial information flows within each member country and externally (internationally). The target population of central bank officials who also take an active role in the modernisation of SADC regional payments systems were requested to provide feedback on the prepared questionnaire to address the above factors. The responses provided are summarised in Chapter 5. It was clear from the responses that the identified factors appeared to pose little challenge for respective member countries. However, additional comments by respondents indicated that there is still a lot of groundwork to be covered. There was an evidence of the need for on-going training in payment systems and to improve communication networks and power supply within each member country, especially on the remote country areas/rural areas. Some members also hinted a warning on developing systems, which would have a potential to become white elephants if other sectors are not developed in parallel to the regional payment systems. / Graduate School of Business Leadership / M.B.L.

The dissertation contains essays concerning the linkages between macroeconomy and financial market or the conduct of monetary policy via DSGE modelling. The dissertation contributes to the questions of fitting macroeconomic models to the data, and so contributes to our understanding of the driving forces of fluctuations in macroeconomic and financial variables. Chapter one offers an introduction to my thesis and outlines in detail the main results and methodologies. In Chapter two I introduce a statistical measure for model evaluation and selection based on the full information of sample second moments in data. A model is said to outperform its counterpart if it produces closer similarity in simulated data variance-covariance matrix when compared with the actual data. The "distance method" is generally feasible and simple to conduct. A flexible price two-sector open economy model is studied to match the observed puzzles of international finance data. The statistical distance approach favours a model with dominant role played by the expectational errors in foreign exchange market which breaks the international interest rate parity. Chapter three applies the distance approach to a New Keynesian model augmented with habit formation and backward-looking component of pricing behaviour. A macro-finance model of yield curve is developed to showcase the dynamics of implied forward yields. This exercise, with the distance approach, reiterate the inability of macro model in explaining yield curve dynamics. The method also reveals remarkable interconnection between real quantity and bond yield slope. In Chapter four I study a general equilibrium business cycle model with sticky prices and labour market rigidities. With costly matching on labour market, output responds in a hump-shaped and persistent manner to monetary shocks and the resulting Phillips curve seems to radically change the scope for monetary policy because (i) there are speed limit effects for policy and (ii) there is a cost channel for monetary policy. Labour reforms such as in mid-1980s UK can trigger more effective monetary policy. Research on monetary policy shall pay greater attention to output when labour market adjustments are persistent. Chapter five analyzes the link between money and financial spread, which is oft missed in specification of monetary policy making analysis. When liquidity provision by banks dominates the demand for money from the real economy, money may contain information of future output and inflation due to its impact on financial spreads. I use a sign-restriction Bayesian VAR estimation to separate the liquidity provision impact from money market equilibrium. The decomposition exercise shows supply shocks dominate the money-price nexus in the short to medium term. It also uncovers distinctive policy stance of two central banks. Finally Chapter six concludes, providing a brief summary of the research work as well as a discussion of potential limitations and possible directions for future research.