Фантаццини Деан

Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death

2022 · ARTICLE · en

This paper examined a set of over two thousand crypto-coins observed between 2015 and 2020 to estimate their credit risk by computing their probability of death. We employed different definitions of dead coins, ranging from academic literature to professional practice; alternative forecasting models, ranging from credit scoring models to machine learning and time-series-based models; and different forecasting horizons. We found that the choice of the coin-death definition affected the set of the best forecasting models to compute the probability of death. However, this choice was not critical, and the best models turned out to be the same in most cases. In general, we found that the cauchit and the zero-price-probability (ZPP) based on the random walk or the Markov Switching-GARCH(1,1) were the best models for newly established coins, whereas credit-scoring models and machine-learning methods using lagged trading volumes and online searches were better choices for older coins. These results also held after a set of robustness checks that considered different time samples and the coins’ market capitalization.

Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg

2021 · ARTICLE · en

This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models to study the migration data of the two Russian cities with the largest migration inflows: Moscow and Saint Petersburg. The empirical analysis does not provide evidence that the more people search online, the more likely they are to relocate to other regions. However, the inclusion of Google Trends data in a model improves the forecasting of the migration flows, because the forecasting errors are lower for models with internet search data than for models without them. These results also hold after a set of robustness checks that consider multivariate models able to deal with potential parameter instability and with a large number of regressors.

Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure

2021 · ARTICLE · en

While there is increasing interest in crypto assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we considered a unique dataset of 144 exchanges, active from the first quarter of 2018 to the first quarter of 2021. We analyzed the determinants surrounding the decision to close an exchange using credit scoring and machine learning techniques. Cybersecurity grades, having a public developer team, the age of the exchange, and the number of available traded cryptocurrencies are the main significant covariates across different model specifications. Both in-sample and out-of-sample analyzes confirm these findings. These results are robust in regard to the inclusion of additional variables, considering the country of registration of these exchanges and whether they are centralized or decentralized.

Asymmetry and hysteresis in the Russian gasoline market: The rationale for green energy exports

2021 · ARTICLE · en

Using monthly data of 79 Russian regions from 2003 to 2017, we study the long-run relationship of the retail gasoline prices with the crude oil price and the nominal exchange rate. We find that models that were successfully applied to deal with asymmetries in other countries are not suitable for Russia without taking structural breaks into account. Once breaks are allowed, we find that there is no asymmetry in the long-run elasticities between the gasoline prices and the crude oil price, and no significant hysteresis. However, there is an asymmetric relation between the gasoline price and the exchange rate that has decreased over time. These results also hold after several robustness checks. The evidence reported in this work shows that the effects of the exchange rate on gasoline prices are much more difficult to control than the oil price, and they require a larger set of policy measures: the recent development of a plan to decrease the importance of hydrocarbons exports by producing clean hydrogen using electrolysis and pyrolysis and the potential future export of electricity generated using nuclear power and onshore wind farms may help to diversify the local economy and to shield it from new sanctions.

Forecasting German car sales using Google data and multivariate models

2015 · ARTICLE · en

Long-term forecasts are of key importance for the car industry due to the lengthy period of time required for the development and production processes. With this in mind, this paper proposes new multivariate models to forecast monthly car sales data using economic variables and Google online search data. An out-of-sample forecasting comparison with forecast horizons up to 2 years ahead was implemented using the monthly sales of ten car brands in Germany for the period from 2001M1 to 2014M6. Models including Google search data statistically outperformed the competing models for most of the car brands and forecast horizons. These results also hold after several robustness checks which consider nonlinear models, different out-of-sample forecasts, directional accuracy, the variability of Google data and additional car brands.

Кредитные свопы и базис между кредитными свопами и облигациями для российских компаний: обзор и анализ влияния запрета на короткие продажи

2012 · ARTICLE · ru

В данной работе приведен обзор теоретических основ кредитных свопов (CDS), ос- новные характеристики рынка CDS, описан метод оценки компоненты спрэда, не свя- занной с дефолтом, как базиса между фактической CDS премией и теоретической премией, получаемой на основе доходностей облигаций. Проанализированы наиболее ликвидные CDS на российские компании и рассчитан базис между CDS и облигациями с 2005 по 2010 гг. При этом особое внимание уделяется периоду запрета на короткие продажи на российских финансовых рынках (с 18 сентября 2008 г. по 15 июня 2009 г.). Показано, что базис был в основном отрицательным до запрета и стал положитель- ным в период запрета. После снятия запрета базис начал снижаться, но по‑преж- нему остается положительным для всех рассмотренных компаний. Это наблюдение подтверждает гипотезу о том, что положительный базис может быть объяснен сложностями арбитража из‑за затрат на короткие продажи.

Моделирование Многомерных Распределений С Использованием Копула-Функций. Часть 1

2011 · ARTICLE · ru

Моделирование Многомерных Распределений С Использованием Копула-Функций. Часть 2

2011 · ARTICLE · ru

Small Sample Properties of Copula - GARCH Modelling: a Monte Carlo Study

2011 · ARTICLE · en

Everything You Always Wanted to Know about Log Periodic Power Laws for Bubble Modelling but Were Afraid to Ask

2011 в печати · ARTICLE · en

Статья поясвящена анализу моделей, используемых для раннего распознания финансовых кризиов.