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Implementing machine learning in the stock picking process of Nova students portfolio
Publication . Afonso, Miguel Pardal; Ribeiro, Gonçalo Sommer
In a time when algorithmic trading accounts for over 50% of US equities’ traded volume, this work project proposes a holistic approach to the implementation of Machine Learning in the Stock Picking process of the Nova Students Portfolio. The presented algorithms can help investors in the identification of the features that drive stock returns and results show that our predictive algorithm provides an edge in the selection of outperforming stocks. An investor using our method from 2006 to 2019 would have achieved an annualized return of 4.8% in excess of the S&P 500 and an Info Sharpe gain of 0.2.
General equilibrium essays on securities financing transactions
Publication . Hunter, Guillermo; Páscoa, Mário
This dissertation studies different aspects of Securities Financing Transactions (SFT). The
first chapter addresses the impact of repo margins on security prices. It is shown that when
the agents leveraging their positions are short sellers, prices rise as margins go up. The second
chapter studies how repo margins are determined in a model allowing for bankruptcy. The
third chapter discusses shareholders' unanimity under market incompleteness when shares can
be short sold. For a firm that is perfectly competitive both in the securities market and in the
SFT market (a securities lending market), shareholders unanimously agree on maximizing firm's
present value.
Weather derivatives pricing and risk management applications
Publication . Anzilotti, Luca; Pereira, João Pedro
The main objective of this paper is to discuss suitable methods for the modelling of weather
variables and to bring together much of the current thinking in terms of the pricing of their
respective derivative contracts (CDD, HDD) with payoffs depending on temperature. In
addition to the theoretical overview provided, an empirical investigation is undertaken using
historical data from the De Bilt meteorological station: we use the aforementioned data to first
suggest a stochastic process that describes the evolution of the temperature. Further, such
temperature modelling phase is accompanied by the numerical technique of Monte Carlo
simulation for derivatives pricing. Finally, we will analyse some weather-sensitive industries
and discuss possible weather hedging strategies they could apply.
Fiscal consolidation programs and income inequality
Publication . Brinca, Pedro; Ferreira, Miguel H.; Franco, Francesco; Holter, Hans A.; Malafry, Laurence
Following the Great Recession, many European countries implemented fiscal con-
solidation policies aimed at reducing government debt. Using three independent data
sources and three different empirical approaches, we document a strong positive re-
lationship between higher income inequality and stronger recessive impacts of fiscal
consolidation programs across time and place. To explain this finding, we develop
a life-cycle, overlapping generations economy with uninsurable labor market risk. We
calibrate our model to match key characteristics of a number of European economies, in-
cluding the distribution of wages and wealth, social security, taxes and debt, and study
the effects of fiscal consolidation programs. We find that higher income risk induces
precautionary savings behavior, which decreases the proportion of credit-constrained
agents in the economy. Credit-constrained agents have less elastic labor supply re-
sponses to fiscal consolidation achieved through either tax hikes or public spending
cuts, and this explains the relationship between income inequality and the impact of
fiscal consolidation programs. Our model produces a cross-country correlation between
inequality and the fiscal consolidation multipliers, which is quite similar to that in the
data.
The Impact of Airbnb on Residential Property Values and Rents: Evidence from Portugal
Publication . Fernandes Franco, Sofia; Santos, Carlos Daniel; Longo, Rafael
Short-term rentals have facilitated the upraise trend in tourism growth in several cities around the world. However, concerns for the negative effects that such home-sharing platforms may have on the housing market and traditional markets have driven community groups and housing advocates to intensely react against them. Whether or not shortterm rentals increase housing prices and rentsfor local residents is an empirical question. We quantify the causal effects of Airbnb´s short-term rentals on urban housing affordability in Portugal by estimating quarterly housing rents and prices as a function of Airbnb concentration. We take advantage of the 2014 regulatory reform and employ a differencein-differences (DiD) empirical strategy. We estimate an overall increase in property values of 34% and 10.9% for rents due to the short-term lease regulatory reform. We also find that these effects are particularly localized to the historical centers and areas attractive to tourists in the cities of Lisbon and Porto. A better understanding of the effects of shortterm home rentals on housing markets and of the magnitude of its impact on residential property prices and rents are crucial information to determine whether it needs to be regulated and how proper regulation should be designed.
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Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
5876
Número da atribuição
UID/ECO/00124/2013