京都大学 · 経済学
Kakinaka教授の研究室は、暗号資産市場の非線形性・スケーリング特性に着目し、フラクタル解析や安定分布を用いた時間系列の多スケール的・非対称的構造の解明を主な研究テーマとしています。特に、パンデミック下における市場効率性の変化や、ボラティリティの非対称性が時間スケールごとにどのように変化するかを、DFAやGARCHモデルの拡張的手法を用いて分析しています。また、投資家のスケール選好の変化がポートフォリオパフォーマンスに与える影響についても、フラクタルマーケット仮説の観点から検証しています。
Figures are computed from collected data and may differ slightly.
This study investigates asymmetric multifractality and market efficiency of the major cryptocurrencies during the COVID-19 pandemic while accounting for different investment horizons. By applying the asymmetric multifractal detrended fluctuation analysis, we show that the outbreak affected the efficiency property of price behaviors differently between short- and long-term horizons. After the outbreak, the markets exhibited stronger multifractality in the short-term but weaker multifractality in
Asymmetric relationship between price and volatility is a prominent feature of the financial market time series. This paper explores the price–volatility nexus in cryptocurrency markets and investigates the presence of asymmetric volatility effect between uptrend (bull) and downtrend (bear) regimes. The conventional GARCH-class models have shown that in cryptocurrency markets, asymmetric reactions of volatility to returns differ from those of other traditional financial assets. We address this i
This study investigates the scale-dependent structure of asymmetric volatility effect in six representative cryptocurrencies: Bitcoin, Ethereum, Ripple, Litecoin, Monero, and Dash. By developing the dynamical approach of DFA-based fractal regression analysis, we detect whether the volatility of price changes is positively or negatively related to return shocks at different time scales. We find that the asymmetric volatility phenomenon varies by scale and cryptocurrency, and the structure is time
Stable distribution is one of the attractive models that well describes fat-tail behaviors and scaling phenomena in various scientific fields. The approach based upon the method of moments yields a simple procedure for estimating stable law parameters with the requirement of using momental points for the characteristic function, but the selection of points is only poorly explained and has not been elaborated. We propose a new characteristic function-based approach by introducing a technique of s
The mean-DCCA portfolio is known to consider the assets' nonlinearity and scaling properties by embedding the fractal correlation into the mean-variance criterion, with specific strategies under the assumption that the scale preference of investors is constant.We examine whether accounting for changes in investors' scale preference in response to market conditions improves portfolio performance.A portfolio with preference on short-scales is effective under market uncertainty, while long-scale pr
The recent emergence of cryptocurrencies such as Bitcoin and Ethereum has posed possible alternatives to global payments as well as financial assets around the globe, making investors and financial regulators aware of the importance of modeling them correctly. The Levy's stable distribution is one of the attractive distributions that well describes the fat tails and scaling phenomena in economic systems. In this paper, we show that the behaviors of price fluctuations in emerging cryptocurrency m
Asymmetric relationship between price and volatility is a prominent feature of the financial market time series. This paper explores the price-volatility nexus in cryptocurrency markets and investigates the presence of asymmetric volatility effect between uptrend (bull) and downtrend (bear) regimes. The conventional GARCH-class models have shown that in cryptocurrency markets, asymmetric reactions of volatility to returns differ from those of other traditional financial assets. We address this i
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