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We examine the predictability of private and public real estate returns using recursive, out-of-sample, linear and Markov switching models, employing a rich set of predictor variables. We find considerable improved predictive power compared to simple regression models, especially at the intermediate horizon. Next, we test whether such improved forecasting accuracy translates into a positive risk-adjusted out-of-sample performance by performing a recursive mean-variance portfolio allocation analysis. We observe significant improvements in realized Sharpe ratios and mean-variance utility scores, especially when employing Markov switching models and exploiting predictability at intermediate horizons. Furthermore, our results are robust to the inclusion of transaction costs.

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2021 The Author(s)

We use 1982–2014 data on the US riskless yield curve to show that regime switching dynamics in Nelson-Siegel factor models extended to encompass variables that summarize the state of monetary policy lead to superior predictive accuracy. Such spread in forecasting power turns out to be statistically significant even controlling for parameter uncertainty and sample variation. Exploiting regimes, we obtain evidence that the increase in predictive accuracy is stronger during the Great Financial Crisis, when monetary policy underwent a significant, sudden shift. Although more caution applies in comparisons to a naïve random walk benchmark over a few sub-samples and when transaction costs are accounted for, we report that the increase in predictive power owed to the combination of regimes and of variables that capture the stance of unconventional monetary policies is tradeable. We devise and test butterfly strategies that exploit the forecasts from the models and obtain evidence of risk-adjusted profits both per se and in comparisons to simpler models.

• Questa tesi include due saggi che sono dedicati allo studio delle serie temporali e del potere predittivo a livello di cross-section di un indice di spillover di volatilità di nuova concezione basato sulle volatilità implicite delle opzioni. Nel primo saggio, ci concentriamo sulla stima dell'indice e sulla valutazione se i (cambiamenti nell'indice) possono prevedere i rendimenti in eccesso delle serie temporali di (un insieme di) singoli titoli e dello S&P 500. Si confronta il potere predittivo in-sample e out-of-sample di questo indice con quello dell'indice di spillover di volatilità proposto da Diebold e Yilmaz (2008, 2012), che si basa invece su volatilità realizzate. Sebbene entrambe le misure mostrino la prova del potere predittivo all'interno del campione, solo la misura basata sulla volatilità implicita è in grado di produrre previsioni out-of-sample che battono un semplice benchmark costituito dalla media storica. Troviamo che questo potere predittivo possa essere sfruttato da un investitore utilizzando semplici strategie di trading basate sul segno dell'eccesso di rendimento previsto e da un investitore media-varianza. Mostriamo anche che, nonostante la sovra-performance predittiva dell'indice di spillover della volatilità implicita provenga principalmente da periodi di alta volatilità, il potere previsionale aggiuntivo non è sussunto dall'inclusione del VIX (come proxy della volatilità aggregata) nelle regressioni predittive. Nel secondo saggio, indaghiamo se il rischio di spillover della volatilità (oltre al rischio di volatilità aggregata) sia valutato nella cross-section dei rendimenti delle azioni statunitensi. Per il nostro scopo, conduciamo diversi test di asset pricing (parametrici e non parametrici). In primo luogo, ordiniamo l'universo azionario in cinque portafogli quintili in base alla loro esposizione all'indice di spillover di volatilità implicita che abbiamo sviluppato nel primo saggio. In secondo luogo, utilizziamo una proced, This thesis includes two essays that are devoted to study the time-series and cross-sectional predictive power of a newly developed, forward-looking volatility spillover index based on option implied volatilities. In the first essay, we focus on the estimation of the index and on the assessment of whether the (changes in) the index can predict the time-series excess returns of (a set of) individual stocks and of the S&P 500. We also compare the in-sample and out-of-sample predictive power of this index with that of the volatility spillover index proposed by Diebold and Yilmaz (2008, 2012), which is instead based on realized, backward-looking volatilities. While both measures show evidence of in-sample predictive power, only the option-implied measure is able to produce out-of-sample forecasts that outperform a simple historical mean benchmark. We find this predictive power to be exploitable by an investor using simple trading strategies based on the sign of the predicted excess return and also by a mean-variance optimizer. We also show that, despite the predictive outperformance of the implied volatility spillover index is mostly coming from high-volatility periods, the additional forecast power is not subsumed by the inclusion of the VIX (as a proxy of aggregate volatility) in the predictive regressions. In the second essay, we investigate whether volatility spillover risk (in addition to aggregate volatility risk) is priced in the cross-section of US stock returns. To our purpose, we conduct several (parametric and non-parametric) asset pricing tests. First, we sort the stock universe into five quintile portfolios based on their exposure to the implied volatility spillover index that we have developed in the first essay. Second, we use a conditional sorting procedure to control for variables that may have a confounding effect on our results. We find that stocks with a low exposure to volatility spillovers earn an average 6.45% per annum more than stocks with a hig

We examine the effects of US monetary policy announcements during and after the Great Financial Crisis on the average abnormal returns (the “alpha”) of the hedge fund industry as a whole and of a range of hedge strategy indices. We apply a variety of tests of increasing sophistication including simple event studies, formal tests for breaks, and Markov switching models. The event studies show that both the overall index and long-short equity and fixed income arbitrage hedge strategies were systematically affected by unexpected monetary policy announcements, while other strategies appear to have been less impacted. Formal break point tests show that for all strategies as well as the overall index, there is evidence of five breakpoints. For the overall index and most of the sub-indices, many of the endogenously determined breaks closely match a list of policy surprise dates that have been already singled out because they had strongly affected financial markets in general. Especially for the long-short equity, fixed income arbitrage, dedicated short-bias, and global macro hedge funds, there is a significant tendency for estimated alphas to decline over time, following policy surprises, while we find no clear-cut evidence of systematic risk beta timing skills.

In order to optimize the performance of devices based on porphyrin thin films it is of great importance to gain a physical understanding of the various factors which affect their charge transport and lightharvesting properties. In this work, we have employed a multi-technique approach to study vacuum deposited zinc octaethyl porphyrin (ZnOEP) thin films with different degrees of long-range order as model systems. An asymmetrical stretching of the skeletal carbon atoms of the porphyrin conformer has been observed and attributed to ordered molecular stacking and intermolecular interactions. For ordered films, a detailed fitting analysis of the X-ray absorption near edge structure (XANES) using the MXAN code establishes a symmetry reduction in the molecular conformer involving the skeletal carbon atoms of the porphyrin ring; this highlights the consequences of increased p–p stacking of ZnOEP molecules adopting the triclinic structure. The observed asymmetrical stretching of the p conjugation network of the porphyrin structure can have significant implications for charge transport and light harvesting, significantly influencing the performance of porphyrin based devices.

The occupied and empty densities of states of cobalt phthalocyanine (CoPc) were investigated by photoelectron and X-ray absorption spectroscopies in the gas phase and in thin films deposited on a Au(111) surface. The comparison between the gas-phase results and density functional theory single-molecule simulations confirmed that the CoPc ground state is correctly described by the (2)A(1g) electronic configuration. Moreover, photon-energy-dependent valence photoemission spectra of both the gas phase and thin film confirmed the atomic character of the highest occupied molecular orbital as being derived from the organic ligand, with dominant contributions from the carbon atoms. Multiplet ligand-field theory was employed to simulate the Co L-edge X-ray absorption spectroscopy results.