The Indus Valley Script (IVS) has long resisted definitive decipherment due to its extreme brevity (averaging 4.6 glyphs per inscription), the absence of a bilingual parallel text, and lingering uncertainty regarding its underlying linguistic family. This study presents a mathematically validated, globally optimized decipherment of the Harappan corpus by deploying our Unified Discovery and Inference Architecture (UDIA)—a five-layer recursive reasoning framework that decouples model generation, contextual probability, and structural self-critique. Treating the script as a high-density administrative parameter space, our findings reveal that the script did not record narrative prose, but instead functioned as a decentralized, physical Distributed Ledger System governing an algorithmic framework of Astro-Jurisprudence. Indus inscriptions served as time-locked legal contracts—Astro-Temporal Permits—valid only when economic transactions aligned with precise celestial windows. Global optimization and spectral analysis validate this model against a high-status administrative dialect of Proto-Dravidian, demonstrating exceptional structural, phonetic, and morphosyllabic alignment with the South Dravidian branch. Statistical validation yields a Zipf’s Law correlation of $r = 0.98$ (slope of $-1.02$) and an organic token-distribution entropy of 3.41 bits/token. By resolving the "Universal Solvent Paradox" through a strict Dual-Track Shuffled Permutation Audit under zero-guidance parameters ($\gamma = 0, \beta \to \text{Static}$), this framework establishes an unassailable mathematical standard that isolates genuine historical convergence from engineered statistical alignments, fundamentally transforming our understanding of Bronze Age legal systems.
Rongorongo is an undeciphered script from Easter Island (Rapa Nui) surviving on fewer than 30 wooden artifacts. This paper proposes that the surviving corpus constitutes the kohau tau, a named class of annual record tablets documented in Rapanui oral tradition and assumed lost. Computational analysis of 146 parallel passages from the Horley (2021) corpus identifies eight independent structural findings supporting a distributed administrative ledger interpretation: a universal list format across nine passages on multiple artifacts; a lozenge-series quantity notation system with power-law frequency distribution consistent with real resource counts; a standardized subject-quantity-subject ledger entry format on three independent artifacts; a calendar section delimiter encoding the Miru clan chief, lunar official, and fishing activity as a recurring administrative header; directional binary encoding recording resource arrival and departure status; an unsupervised two-zone structural classification showing a 10x difference in list-format rate (18.4% administrative vs. 1.9% ceremonial), cross-validated at 94.5% accuracy; a directional invariance property of the subject-quantity-subject notation confirming it was designed for multiple readers regardless of boustrophedon orientation; and a 20/20 universality score for five compound rules confirmed across Chinese oracle bone script, Egyptian hieroglyphs, Sumerian cuneiform, and Mayan glyphs. A control test applying identical structural features to 58 Uruk-period Sumerian cuneiform tablets with known genre labels achieves 100% classification accuracy, externally validating the methodology. Thomson's (1891) tablet text explicitly listing five resource domains under chiefly control is identified as the administrative charter of the system. Ethnographic documentation from Metraux (1940) confirms the binary seasonal tapu/noa encoding predicted by the lozenge system. The most complete currently interpretable entry records one unit of turtle (honu) in Passage 123 on artifact Gr5, supported by Metoro's native speaker identification, corpus structural analysis, and quantity notation confirmation.
Purpose- The primary purpose of this study is to model Bitcoin price volatility and forecast its future price returns using advanced econometric models such as ARCH and GARCH. The study aims to enhance risk management strategies and support informed investment decisions by addressing the time-varying nature of Bitcoin’s volatility. The research explores the persistence of volatility shocks and the clustering of price movements to provide insights into market dynamics. Methodology- This research examines daily Bitcoin closing prices over the period from January 2020 to October 2024. The data was preprocessed to ensure reliability, including applying logarithmic transformations to standardize the data and eliminate trends. Stationarity tests, such as the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and KPSS tests, were conducted to confirm the series' stationarity. The ARCH-LM test was utilized to detect volatility clustering which is essential for validating the use of ARCH and GARCH models. Following this, ARIMA models were employed to define mean equations and GARCH models were used to estimate conditional variance and capture volatility dynamics. The dataset was split into training and validation subsets with data from July to October 2024 reserved for validation. Findings- The findings demonstrate that Bitcoin’s price movements exhibit significant volatility clustering and persistence of shocks which are key characteristics effectively captured by ARCH and GARCH models. These models provide valuable insights into the volatility patterns of Bitcoin, supporting their application in cryptocurrency analysis. Despite their robustness, the models face limitations in precise return forecasting during highly volatile periods, suggesting the need for further refinement or integration with advanced approaches. Conclusion- The research concludes that ARCH and GARCH models are effective tools for understanding and forecasting Bitcoin’s volatility. The study underscores the importance of acknowledging volatility persistence and clustering effects when analyzing cryptocurrency price behavior. However, it also highlights areas for improvement in econometric modelling by including the exploration of hybrid models and the integration of macroeconomic factors to enhance forecasting accuracy. Keywords: Bitcoin, ARCH models, GARCH Models, forecasting, ARIMA models JEL Codes: C58, G10, G12
As exemplified by Viking and Bronze Age societies in northern Europe, we model the political dynamics of raiding, trading, and slaving as a maritime mode of production. It includes political strategies to control trade by owning boats and financing excursions, thus permitting chiefs to channel wealth flows and establish decentralized, expansive political networks. Such political institutions often form at the edges of world systems, where chieftains support mobile warriors who were instrumental in seizing and protecting wealth. Particular properties of the maritime mode of production as relevant to Scandinavia are the fusion of agropastoral and maritime modes of production. To exemplify these two sectors, we use the Thy and Tanum cases in which we have been involved in long-term archaeological research. The historic Viking society provides specificity to model the ancestral political society of Bronze Age Scandinavia. Our model helps understand an alternative path to institutional formation in decentralized chiefdoms with low population densities, mobile warriors, and long-distance trading and raiding in valuables, weapons, and slaves.