Aug 2026· Journal of Fintech and Business Analysis· Vol 3, pp. 22-48· 0 citations
Abstract
Bitcoin has become an increasingly important asset for portfolio allocation, yet its diversification value and option-implied information remain difficult to evaluate. This paper examines Bitcoin risk from portfolio and option-implied perspectives. This study assesses whether Bitcoin improves the risk-return opportunity set with traditional assets and whether its diversification role remains stable during market stress. Option-implied measures, including the 25-delta Risk Reversal (RR25), smile curvature, and an at-the-money Implied-Volatility-minus-Realized-Volatility (IV-minus-RV) proxy, are then constructed to predict market conditions. Portfolio analysis shows that Bitcoin can improve risk-return tradeoffs but does not function as a stable minimum-variance asset or a reliable crisis hedge. Baseline regressions provide limited evidence that RR25 consistently predicts future realized volatility or returns. However, extreme negative short-dated RR25 is followed by higher future realized volatility, suggesting RR25 is more informative as a nonlinear stress-state indicator than as a continuous forecasting variable. Smile curvature captures the implied-volatility surface but provides weaker predictive information. Finally, the IV-minus-RV analysis shows that gradual RR25-based exposure scaling achieves a better risk-adjusted profile than a binary exposure rule. Overall, the findings indicate that Bitcoin's diversification benefits and option-implied information are state-dependent.
Bitcoin option prices reflect terminal variance and the cost of managing convex exposure in a market with changing depth and execution quality. This paper asks whether a liquidity state can be separated from fractional rough volatility in Bitcoin option valuation. The contribution is a modelling combination: standard s...
This study examines whether Bitcoin contains economically meaningful predictive information for gold, green bonds, and renewable-energy assets and whether such relationships vary across market conditions. Using daily data from February 2018 to February 2023, we combine multi-horizon predictive regressions, volatility-s...
Our study examines to what extent the introduction of Bitcoin spot exchange-traded funds (ETFs) affected Bitcoin’s properties, including market dynamics, volatility, returns, return distribution, and tracking errors. Using block bootstrap simulations, OLS regression, EGARCH modeling, and non-parametric tests, we find t...
Daniel Pastorek, P. Albrecht· Ekonomický casopis· 0 citations
Sentiment indicators are widely used in digital asset markets, but their economic meaning remains ambiguous. In the Bitcoin market, the Crypto Fear and Greed Index is often treated as a simple trading signal, although it may be more relevant for identifying market states and distributional risk. This study examines whe...
András Szeberényi, M. Kovács· Digital Finance· 0 citations
Traditional risk parity approaches rely largely on volatility measures, which may not fully capture asymmetric risk profiles. This study examines a dynamic allocation approach that minimizes portfolio-level Conditional Value-at-Risk (CVaR). The CVaR-Minimizing Dynamic Allocation (CVaR-DA) approach is intended to manage...
Veraphong Chutipat, Peerapat Wattanasin, Tanpat Kraiwanit· Journal of Risk and Financia...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.