1,832 research outputs found
Enhancing Markowitz model: inspection of correlations and tail covariances
No full textInformation contained in the correlation matrix of the nancial products plays
a crucial in order to construct portfolios as well as the tail e ects of asset returns.
Structure hidden in the correlation matrix can be revealed appealing to hierarchcal
clustering algorithms and spectral methods individually, or through a combination
of them. Furthermore, covariance as a mesure of portfolio risk does not
distinguish downside from upside risk. .
The work shows the state of the art of asset allocation models which enhances
Markowitz portfolios focusing on Minimum Spanning Tree and Random Matrix
Theory used to extract information from correlations and on di erent measures of
portfolio risk accounting for asymmetry in the risk
Network metrics for FinTech services: an application on robot-advisors and crypto assets.
Get PDFL'ultimo decennio ha visto il rapido sviluppo di un'ampia gamma di servizi della tecnologia finanziaria (FinTech). Questo lavoro mostra innovazioni in due funzioni di FinTech: piattaforme di robot-advisors e prezzi delle cryptovalute.
I robot-advisors prevedono la fornitura di servizi di investimento automatizzato online, in modo tale da ridurre i costi e migliorare la qualità del servizio, rendendo più trasparente il coinvolgimento degli utenti. Tuttavia, queste piattaforme digitali possono sottostimare i rischi di mercato, portando a una discrepanza tra il rischio atteso ed effettivo degli investitori.
Il lavoro dimostra come random matrix theory e modelli di rete possano essere combinati per costruire portafogli di investimento che offrano rischi più bassi e rendimenti più elevati rispetto ai portafogli di Markowitz.
In riferimento alle monete virtuali che consentono di inviare pagamenti online direttamente da una parte all'altra senza passare attraverso un istituto finanziario, questo lavoro analizza le dinamiche dei prezzi delle criptovalute e, in particolare, il modo in cui le informazioni sui prezzi vengono trasmesse tra i diversi mercati bitcoin e tra mercati bitcoin e mercati tradizionali.
La metodologia concerne l'algoritmo di spanning tree basato sulla correlazione con un metodo di filtraggio preliminare basato sull'approccio random matrix.
A tale scopo, i principali risultati empirici sono: i) i prezzi di scambio dei bitcoin sono positivamente correlati tra loro e, tra questi, i principali bitcoin guidano i prezzi; ii) i prezzi di scambio dei bitcoin non sono influenzati dai prezzi delle attività classiche mentre le loro volatilità lo sono, con un effetto negativo e ritardato.
Alcune delle tecniche più note possono essere combinate al fine di raggiungere obiettivi diversi, da un lato la costruzione di un modello di asset allocation e dall'altro il rilevamento di meccanismi di informazione sui prezzi tra prodotti finanziari nuovi e tradizionali.The last decade has witnessed the rapid development of a broad range of Financial Technology (FinTech) services. This work shows innovations in two functions of FinTech: robot-advisory platforms and crypto prices.
Robot-advisors involve the provision of online automated investment services without human contact. For this reason, they may reduce costs and improve the quality of the service, making user involvement more transparent. However, this digital platforms may underestimate market risks, leading to a mismatch between investors' expected and actual risk.
In particular, this work demonstrates how random matrix theory and network models can be combined to construct investment portfolios that provide lower risks and higher returns with respect to standard Markowitz portfolios.
According to digital currencies that allow online payments to be sent directly from one party to another without going through a financial institution, this work analyses the dynamics of crypto asset prices and, specifically, how price information is transmitted among different bitcoin market exchanges, and between bitcoin markets and traditional ones.
The methodology adopted groups bitcoin prices from different exchanges, as well as classic assets, by enriching the correlation based minimal spanning tree algorithm with a preliminary filtering method based on the random matrix approach.
To this aim, main empirical findings are: i) bitcoin exchange prices are positively related with each other and, among them, the largest exchanges drive the prices; ii) bitcoin exchange prices are not affected by classic asset prices while their volatilities are, with a negative and lagged effect.
Some of the most known techniques can be combined in order to reach up completely different goals, from one side the construction of asset allocation model and to the other the detection of mechanisms of price information between traditional and new financial products
Crypto price discovery through correlation networks
Get PDFWe aim to understand the dynamics of crypto asset prices and, specifically, how price information is transmitted among different bitcoin market exchanges, and between bitcoin markets and traditional ones. To this aim, we hierarchically cluster bitcoin prices from different exchanges, as well as classic assets, by enriching the correlation based minimum spanning tree method with a preliminary filtering method based on the random matrix approach. Our main empirical findings are that: (i) bitcoin exchange prices are positively related with each other and, among them, the largest exchanges, such as Bitstamp, drive the prices; (ii) bitcoin exchange prices are not affected by classic asset prices, but their volatilities are, with a negative and lagged effect
Supplemental Material - Agglomeration v<i>s</i> amenities? Unraveling the latent engine of growth in metropolitan Greece
No full textSupplemental Material for Agglomeration vs amenities? Unraveling the latent engine of growth in metropolitan Greece by Margherita Carlucci, Gloria Polinesi, and Luca Salvati in Environment and Planning B: Urban Analytics and City Science.</p
Impact of COVID-19 on elderly population well-being: evidence from European countries
Get PDFThe aim of this paper is to analyse the effect of COVID-19 on multidimensional well-being in the European population aged 50 and over by measuring changes in individual well-being before and after the pandemic outbreak. To capture the multidimensional nature of well-being, we consider different dimensions: economic well-being, health status, social connections and work status. We introduce new indices of change in individual well-being that measure non-directional, downward and upward movements. Individual indices are then aggregated by country and subgroup for comparison. The properties satisfied by the indices are also discussed. The empirical application is based on micro-data from waves 8 and 9 of the Survey of Health, Ageing and Retirement in Europe (SHARE), carried out for 24 European countries before the pandemic outbreak (regular survey) and in the first two years of the COVID-19 pandemic (June–August 2020 and June–August 2021). The findings suggest that employed and richer individuals suffered greater losses in well-being, while differences based on gender and education diverge from country to country. It also emerges that while the main driver of well-being changes in the first year of the pandemic was economics, the health dimension also strongly contributed to upward and downward well-being changes in the second year
Smart Beta Allocation and Macroeconomic Variables: The Impact of COVID-19
Get PDFSmart beta strategies across economic regimes seek to address inefficiencies created by market-based indices, thereby enhancing portfolio returns above traditional benchmarks. Our goal is to develop a strategy for re-hedging smart beta portfolios that shows the connection between multi-factor strategies and macroeconomic variables. This is done, first, by analyzing finite correlations between the portfolio weights and macroeconomic variables and, more remarkably, by defining an investment tilting variable. The latter is analyzed with a discriminant analysis approach with a twofold application. The first is the selection of the crucial re-hedging thresholds which generate a strong connection between factors and macroeconomic variables. The second is forecasting portfolio dynamics (gain and loss). The capability of forecasting is even more evident in the COVID-19 period. Analysis is carried out on the iShares US exchange traded fund (ETF) market using monthly data in the period December 2013–May 2020, thereby highlighting the impact of COVID-19
Sprawl or Segregation? Local Fertility as a Proxy of Socio-spatial Disparities Under Sequential Economic Downturns
No full textAlthough long-term demographic trends have been extensively analyzed in advanced economies, impact of economic downturns on local fertility has been poorly investigated in low fertility contexts. Earlier studies have documented suburban fertility as signifcantly higher than urban and rural fertility, thanks to a mix of macro (contextual) and micro (behavioral) factors shaping birth rates. In light of the ‘suburban fertility hypothesis’, the present study provides a refned analysis of local fertility rates between 1999 and 2019 at urban,suburban, and rural locations in Athens (Greece), a metropolitan region experiencing sequential expansion and stagnation waves. A superior fertility at suburban locations has been observed during the 2000s and the 2010s, with crude birth rates increasing in socially dynamic and wealthier neighborhoods. With economic expansion, these contexts corresponded with (rapidly growing) industrial districts West of Athens. With recession, these contexts were mostly associated with residential (and service-specialized) neighborhoods East of Athens, with local communities displaying a more efective response to crisis
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