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This article pioneers an asset-by-asset point index, which represents a simple methodology that uses inputs rather than outputs of well-being to recognise the 'poor' on a point basis, household by household. It focuses on assets, which are a significant aspect of well-being in whose absence households may fall into deprivation. The index is well-suited for the production of localised indicators, as it allows disaggregation of data by a rural/urban divide and even at the village/household level, which facilitates area-based interventions. It is an asset-based measure, which will help to identify the poor and the type of help they need; it can thus be used as a monitoring tool at the household and community level. It represents an alternative approach to measuring household poverty.

This paper proposes a theory of endogenous differences in liquidity of assets based on the interaction between differences in the risk of assets and differences in liquidity needs of investors. An equilibrium of the model, which always exists and is unique, displays a class structure, where investors' types sort themselves across different types of assets. I also provide a detailed analysis of the possible types of sorting and of the consequences for the cross-sectional properties of asset prices and their velocity. The framework can also be useful to think about what constitute a ""light-to-liquidity" and a "safe asset".

Chapter 1. The Emergence of a New Asset Class: Digital Assets -- Chapter 2. An Asset Pricer's Toolkit -- Chapter 3. Investment Styles in General -- Chapter 4. Related Literature -- Chapter 5. Digital Assets -- Chapter 6. Digital Assets in a Multi-asset Context -- Chapter 7. On the Effectiveness of Technical Indicators in Digital Assets -- Chapter 8. Investment Styles in Digital Assets -- Chapter 9. Risk Factors in Digital Assets -- Chapter 10. How to Incorporate Characteristics into the Portfolio Construction Process -- Chapter 11. Are the Results Robust and Still Valid? -- Chapter 12. Conclusion.

Chapter 1. The Emergence of a New Asset Class: Digital Assets -- Chapter 2. An Asset Pricer's Toolkit -- Chapter 3. Investment Styles in General -- Chapter 4. Related Literature -- Chapter 5. Digital Assets -- Chapter 6. Digital Assets in a Multi-asset Context -- Chapter 7. On the Effectiveness of Technical Indicators in Digital Assets -- Chapter 8. Investment Styles in Digital Assets -- Chapter 9. Risk Factors in Digital Assets -- Chapter 10. How to Incorporate Characteristics into the Portfolio Construction Process -- Chapter 11. Are the Results Robust and Still Valid? -- Chapter 12. Conclusion.

A letter report issued by the General Accounting Office with an abstract that begins "GAO reviewed the U.S. Marshals Service's (USMS) asset forfeiture programs, focusing on: (1) controls over selected categories of seized assets--namely vehicles, vessels, real property, financial instruments, and general property--at four large USMS districts: the Central District of California, the Southern District of Florida, and the Southern and Eastern Districts of New York; and (2) whether selected seized assets at the test locations under USMS control were accurately accounted for and safeguarded against theft, loss, and deterioration."