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Long run returns predictability and volatility with moving averages

Chang, Chia-Lin; Ilomäki, Jukka; Laurila, Hannu; … - In: Risks : open access journal 6 (2018) 4, pp. 1-18

This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and when to shift to the risk-free rate. The...

Persistent link: https://www.econbiz.de/10011906234

Stock market volatility response to COVID-19 : evidence from Thailand

Suthasinee Suwannapak; Surachai Chancharat - In: Journal of risk and financial management : JRFM 15 (2022) 12, pp. 1-9

This study investigated how stock market volatility responded dynamically to unexpected changes during the COVID-19 … pandemic and the resulting uncertainty in Thailand. Using a multivariate GARCH-BEKK model, the conditional volatility dynamics …, the interlinkages, and the conditional correlations between stock market volatility and the increasing rate of COVID-19 …

Persistent link: https://www.econbiz.de/10014284290

Equity return volatility in Africa's stock markets : a dynamic panel approach

Aawaar, Godfred; Logogye, Louis; Domeher, Daniel - In: Cogent economics & finance 11 (2023) 2, pp. 1-22

rates, money supply, inflation rates, movements in world crude oil prices, volatility of the US and UK stock markets and …This study examines the determinants of time-varying return volatility of Africa's equity markets using monthly indices … of eight top African stock markets. The conditional variance is modelled as a proxy for Africa's volatility indices using …

Persistent link: https://www.econbiz.de/10014501248

Forecasting Cryptocurrencies Volatility Using Statistical and Machine Learning Methods : A Comparative Study

Dudek, Grzegorz; Fiszeder, Piotr; Kubus, Paweł; … - 2023

volatility of the following four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Monero. Several methods, i.e., HAR, ARFIMA … experimental results demonstrate that there is no single best method for forecasting volatility of each cryptocurrency, and …

Persistent link: https://www.econbiz.de/10014362441

CRIX or evaluating blockchain based currencies

Trimborn, Simon; Härdle, Wolfgang - 2016

The S&P500 or DAX30 are important benchmarks for the financial industry. The first mimics the performance of the major US on the NYSE, AMEX and NASDAQ, while the second does the same for the German Prime Share sector. These and other indices describe different compositions of certain segments of...

Persistent link: https://www.econbiz.de/10011481648

Brave New World? Bitcoin is not the New Gold : Understanding Cryptocurrency Price Dynamics

Choi, Sangyup - 2020

While the many commonalities shared by Bitcoin and gold raise a question of whether Bitcoin is a safe-haven like gold, relevant empirical evidence to date is mixed. Unlike existing empirical studies, we derive a simple estimable model of Bitcoin price dynamics from the quantity equation, which...

Persistent link: https://www.econbiz.de/10012839350

Cryptocurrency : Tulip Mania or Digital Promise for the Millennial Generation?

Low, Rand Kwong Yew - 2019

We provide a summarized description of cryptocurrencies and their relationship with other fiat currencies globally. We discuss whether the popularity of cryptocurrency is more akin to Tulip-mania or the digital currency for future generations

Persistent link: https://www.econbiz.de/10012898031

Trading and Arbitrage in Cryptocurrency Markets

Makarov, Igor - 2019

Cryptocurrency markets exhibit periods of large, recurrent arbitrage opportunities across exchanges. These price deviations are much larger across than within countries, and smaller between cryptocurrencies, highlighting the importance of capital controls for the movement of arbitrage capital....

Persistent link: https://www.econbiz.de/10012899430

The cross-section of cryptocurrency risk and return

Günther, Steffen; Fieberg, Christian; Poddig, Thorsten - In: Vierteljahrshefte zur Wirtschaftsforschung 89 (2020) 4, pp. 7-28

Wir untersuchen den Querschnitt von über 1200 Kryptowährungen, gesammelt von 350 Handelsplätzen, in der Zeitspanne von Januar 2014 bis Juni 2020. Im speziellen untersuchen wir, ob weit verbreitete Charakteristika, wie Beta (Fama/MacBeth (1973)), Size (Banz (1981)) oder Momentum...

Persistent link: https://www.econbiz.de/10012940081

Bitcoin, Not Crypto : A Comparative Analysis of Bitcoin's Fundamentally Unique and Irreplicable Properties

Selvam, Vijay - 2021

The crypto industry comprises thousands of cryptocurrencies offering different versions of blockchain-based decentralization – a concept that was described originally in the Bitcoin Whitepaper in 2008. What is Bitcoin’s value proposition in this confusing landscape? Bitcoin is a monetary...

Persistent link: https://www.econbiz.de/10013218946