Alternative Investments

Does Foreign Direct Investment Accelerate Economic Growth? ArXiv ID: ssrn-314924 “View on arXiv” Authors: Unknown Abstract This paper uses new statistical techniques and two new databases to reassess the relationship between economic growth and FDI. After resolving biases plaguing Keywords: Foreign Direct Investment (FDI), Economic Growth, Panel Data, Causality, Alternative Investments Complexity vs Empirical Score Math Complexity: 4.5/10 Empirical Rigor: 6.0/10 Quadrant: Street Traders Why: The paper employs advanced econometric techniques like GMM panel estimators (Arellano-Bover/Blundell-Bond) but is limited to theoretical and econometric analysis without code, backtests, or proprietary datasets. It relies on publicly available macroeconomic data and focuses on causal inference methodology, making it empirically rigorous for academic policy research but not directly backtest-ready for trading. flowchart TD A["Research Goal<br>Does FDI accelerate economic growth?"] --> B{"Data & Methodology"} B --> C["Panel Data<br>1970-2010"] B --> D["Method:<br>Alternative Investments &<br>Endogenous Growth Models"] C --> E{"Computational Process"} D --> E E --> F["Statistical Analysis<br>Causality Testing &<br>Bias Resolution"] F --> G["Findings"] G --> H["FDI Impact:<br>Mixed Results"] G --> I["Key Outcome:<br>Context-dependent relationship"]

Financing Ventures with Fungible Tokens ArXiv ID: ssrn-3137213 “View on arXiv” Authors: Unknown Abstract This paper explores how entrepreneurs can use fungible tokens—whereby they issue digital assets and commit to only accept those tokens as payment for future pro Keywords: Fungible Tokens, Initial Coin Offerings (ICOs), Venture Capital, Blockchain, Alternative Investments Complexity vs Empirical Score Math Complexity: 7.5/10 Empirical Rigor: 2.0/10 Quadrant: Lab Rats Why: The paper presents a formal economic model with proofs and an impossibility result, indicating significant theoretical math density, but it lacks any implementation-heavy backtesting, datasets, or statistical metrics, relying instead on theoretical analysis. flowchart TD A["Research Question:<br>How do entrepreneurs use fungible tokens for venture financing?"] --> B["Methodology: Conceptual Model & Case Studies"] B --> C{"Data & Inputs"} C --> C1["Token Economics"] C --> C2["ICO Whitepapers"] C --> C3["Blockchain Ledgers"] C --> C4["Regulatory Frameworks"] D["Computational Processes<br>Simulation of Funding Rounds"] --> E["Key Findings & Outcomes"] E --> E1["Tokens as Equity Alternatives"] E --> E2["Reduced Barriers to Entry"] E --> E3["Regulatory Uncertainties"] C1 & C2 & C3 & C4 --> D

Initial Coin Offerings and the Value of Crypto Tokens ArXiv ID: ssrn-3143343 “View on arXiv” Authors: Unknown Abstract This paper explores how entrepreneurs can use initial coin offerings — whereby they issue crypto tokens and commit to only accept those tokens as payment for th Keywords: Initial Coin Offerings (ICOs), Crypto Tokens, Crowdfunding, Blockchain, Alternative Investments Complexity vs Empirical Score Math Complexity: 6.5/10 Empirical Rigor: 3.0/10 Quadrant: Lab Rats Why: The paper employs a formal economic model with equilibrium analysis and derives theoretical results about token value and fundraising, indicating moderate-to-high mathematical complexity. However, the work is primarily theoretical with no backtests, datasets, or empirical implementation details, placing it in the ‘Lab Rats’ quadrant. flowchart TD A["Research Question<br/>Value of crypto tokens in ICOs"] --> B["Methodology<br/>Theoretical model & entrepreneurial decisions"] B --> C["Data/Input<br/>Token demand, network size, funding goals"] C --> D["Computational Process<br/>Mathematical derivation of token value"] D --> E["Key Findings<br/>Tokens enable crowdfunding<br/>Value tied to platform usage<br/>Commitment to token acceptance is key"]

Simulating Liquidity: Agent-Based Modeling of Illiquid Markets for Fractional Ownership ArXiv ID: 2411.13381 “View on arXiv” Authors: Unknown Abstract This research investigates liquidity dynamics in fractional ownership markets, focusing on illiquid alternative investments traded on a FinTech platform. By leveraging empirical data and employing agent-based modeling (ABM), the study simulates trading behaviors in sell offer-driven systems, providing a foundation for generating insights into how different market structures influence liquidity. The ABM-based simulation model provides a data augmentation environment which allows for the exploration of diverse trading architectures and rules, offering an alternative to direct experimentation. This approach bridges academic theory and practical application, supported by collaboration with industry and Swiss federal funding. The paper lays the foundation for planned extensions, including the identification of a liquidity-maximizing trading environment and the design of a market maker, by simulating the current functioning of the investment platform using an ABM specified with empirical data. ...