<p>The purpose of this paper is to investigate the predictive power of the variables advanced notice of dismissal (layoffs) and vacancies for the unemployment rate. Based on the Box Jenkins Methodology, the paper makes use of Granger causality and out-of-sample tests to compare the forecast performance of a naïve reference model and the two models extended to include either lagged values of layoffs or vacancies. It is shown that layoffs make up a significant leading variable, exhibiting particularly strong predictive power at forecast horizons of 2-6 months. It is also shown that the predictive power of vacancies is more ambiguous. Vacancies constitute a valuable explanatory variable for the unemployment rate, but does not possess the same leading, predictive qualities as layoffs.</p>

The purpose of this paper is to investigate the predictive power of the variables advanced notice of dismissal (layoffs) and vacancies for the unemployment rate. Based on the Box Jenkins Methodology, the paper makes use of Granger causality and out-of-sample tests to compare the forecast performance of a naïve reference model and the two models extended to include either lagged values of layoffs or vacancies. It is shown that layoffs make up a significant leading variable, exhibiting particularly strong predictive power at forecast horizons of 2-6 months. It is also shown that the predictive power of vacancies is more ambiguous. Vacancies constitute a valuable explanatory variable for the unemployment rate, but does not possess the same leading, predictive qualities as layoffs.

This thesis examines whether the level of Swedish economic policy uncertainty (EPU) can predict excess returns on the Swedish stock market. We run out-of-sample forecasting using an EPU-based predictive model constructed with the official Swedish EPU index developed by Armelius et al. (2017). Forecasting errors for one-, two-, three-, six-, and twelve-month holding periods and four measures of central tendency are analysed and compared against a random walk benchmark. The findings suggest that EPU has limited forecasting ability for excess stock returns in Sweden, and the EPU-based model demonstrates superior forecasting accuracy only in two out of twenty instances, both for the one-month holding period. However, the forecast errors remain relatively large, casting doubt on the model's ability to outperform the market. Furthermore, the EPU-based model consistently underestimates excess returns, questioning its usefulness as a predictor. Notably, the random walk benchmark's forecast error improves with longer holding periods, raising doubts about the predictability of market movements in the long term.

Submitted by Vinicius Vale Pereira (viniciusvale@gmail.com) on 2016-03-01T18:04:06Z No. of bitstreams: 1 tese.v4.1.FINAL.pdf: 1143339 bytes, checksum: e3167f8ba5e577bce7f0c40605716c5d (MD5) / Rejected by Renata de Souza Nascimento (renata.souza@fgv.br), reason: Vinicius, boa noite Para que possamos aceitar seu trabalho deverá realizar os ajustes: O título deve estar em letras maiúsculas. A ficha catalográfica após a contra capa, na parte inferior. Não deve constar números romanos. As páginas anteriores não podem estar numeradas. Centralizar os títulos Agradecimentos, Resumo e Abstract. Após ajustes, submeter novamente o trabalho. Att on 2016-03-02T00:43:38Z (GMT) / Submitted by Vinicius Vale Pereira (viniciusvale@gmail.com) on 2016-03-02T13:49:51Z No. of bitstreams: 1 tese.v4.2.pdf: 1141368 bytes, checksum: 31f0646f0c15281795a6b96bd647ef42 (MD5) / Rejected by Renata de Souza Nascimento (renata.souza@fgv.br), reason: Vinicius, boa tarde Por gentileza, colocar o código CDU no canto do lado direito, da ficha catalográfica. Att on 2016-03-02T16:18:05Z (GMT) / Submitted by Vinicius Vale Pereira (viniciusvale@gmail.com) on 2016-03-02T16:48:39Z No. of bitstreams: 1 tese.v4.2.pdf: 1141278 bytes, checksum: 9f554d94d8c1ab631bb8127fadbbe43a (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2016-03-02T17:07:51Z (GMT) No. of bitstreams: 1 tese.v4.2.pdf: 1141278 bytes, checksum: 9f554d94d8c1ab631bb8127fadbbe43a (MD5) / Made available in DSpace on 2016-03-02T17:27:52Z (GMT). No. of bitstreams: 1 tese.v4.2.pdf: 1141278 bytes, checksum: 9f554d94d8c1ab631bb8127fadbbe43a (MD5) Previous issue date: 2016-02-03 / O presente trabalho propõe um modelo de previsão simultânea de taxas de câmbio de vários países utilizando a abordagem GVAR e analisa a qualidade destas previsões. Para isso foram utilizados dados de 10 países ou regiões de taxa de câmbio, taxas de juros e nível de preços com frequência mensal entre 2003 e 2015. As previsões foram feitas utilizando janela móvel de 60 meses e avaliadas através da comparação dos erros quadráticos médios contra o benchmark padrão, o random walk, e dos testes de Pesaran e Timmermann e de Diebold e Mariano. Foram feitas previsões out-of-sample para horizontes de 1, 3, 12 e 18 meses. Os resultados mostram que o modelo proposto não consegue superar sistematicamente o random walk, contudo apresenta algum poder de previsão em alguns casos específicos / This paper proposes a model that simultaneously forecasts foreign exchange rate for several countries using the GVAR framework and analyzes the quality of these forecasts. For this purpose, data from 10 countries or regions regarding exchange rates, interest rates and price levels on a monthly basis between 2003 and 2015 was used. The forecasting was performed using a 60 months moving window and the evaluation of these was performed comparing the root mean square errors against the standard benchmark, the random walk, and by Pesaran-Timmermann and Diebold-Mariano Tests. Out-of-sample forecasts were estimated for horizons of 1, 3, 12 and 18 months. The results show that the model cannot systematically outperform the random walk, although it has some predictive power in some specific cases.

This doctoral thesis is a collection of four papers on the analysis of the term structure of interest rates with a focus at the intersection of macroeconomics and finance. "Risk in Macroeconomic Fundamentals and Bond Return Predictability" documents that factors related to risks underlying the macroeconomy such as expectations, uncertainty and downside (upside) macroeconomic risks are able to explain variation in bond risk premia. The information provided is found to be, to a large extent, unrelated to that contained in forward rates and current macroeconomic conditions. "Out-of-sample bond excess returns predictability" provides evidence that macroeconomic variables, risks in macroeconomic outcomes as well as the combination of these different sources of information are able to generate statistical as well as economic bond excess returns predictability in an out-of-sample setting. Results suggest that this finding is not driven by revisions in macroeconomic data. The term spread (yield curve slope) is largely used as an indicator of future economic activity. "Re-examining the predictive power of the yield curve with quantile regression" provides new evidence on the predictive ability of the term spread by studying the whole conditional distribution of GDP growth. "Modeling and forecasting the yield curve by extended Nelson-Siegel class of models: a quantile regression approach" deals with yield curve prediction. More flexible Nelson-Siegel models are found to provide better fitting to the data, even when penalizing for additional model complexity. For the forecasting exercise, quantile-based models are found to overcome all competitors. / <p>Diss. Stockholm :  Stockholm School of Economics, 2014. Introduction together with 4 papers.</p>

我國自民國68年成立外匯市場以來，積極的推動經濟國際化與自由化，由於台灣對外經貿依存度相當的高，國際貿易是我國經濟發展的趨動力，而匯率扮演著經貿活動關鍵的角色，因而對匯率走勢的預測與掌握，乃成為管理外匯風險的首要工作。 　　影響匯率的因素相當的複雜，其常受到政府政策的干預，再者，匯率未來的走勢往往容易受到預期心理的影響，眾多的影響因素往往使得對匯率預測的困難程度提高。有鑑於此，本文試圖從貨幣學派結構模型著手--包括價格充分調整模型與實質利率差模型，討論貨幣學派結構模型與匯率資料是否配適良好，然而，若未考慮變數的恆定性與否，而進行迴歸分析，將會造成「假性迴歸」的錯誤。於是本文再引進Johansen共積法，擬找出變數間的長期關係，導入錯誤校正模型，以對匯率進行預測的工作。最後，藉由Hamilton所發展的馬可夫轉轍模型，將不可觀察的隨機變數融入模型中，透過機率控制狀態變數的變動，再對匯率進行統計的推估與預測。 　　基於本文採用的資料與樣本期間內，本文作成下列結論： 　　1.貨幣學派結構模型的實證表現不佳，實證的係數符號與理論設定的相差甚多，而其樣本外預測表現也遠不如隨機遊走模型。 　　2.導入共積關係的錯誤校正模型，其樣本外預測表現仍舊不及隨機遊走模型，然而相較於結構模型，其有明顯的改善。 　　3.馬可夫轉轍模型的樣本外預測表現，與隨機遊走模型接近，而對匯率變動方向的預測其表現良好。 　　4.將所有模型一併考慮，則樣本外預測表現以馬可夫轉轍模型最佳，錯誤校正模型次之，而以結構模型為最差。