Author: Quantifiable

Fair pricing of traded data assets depends on pricing relationships. When derivatives are involved, pricing must account for the costs of hedging counterparty risk, covering margin requirements, and holding regulatory capital. These essential adjustments, known as xVA, are at the core of banking operations.

Intrinsic valuation discounts projected cash flows for smart contracts and dApps. Relative valuation compares dApps using metrics like price-to-sales and market cap-to-assets. The total addressable market approach values crypto-monetary assets based on factors like market size, adoption, and supply.

The absence of transaction costs can overcome initially allocated access to confidential information. However, when transaction costs are present, the price of such access may diverge from its true value. In these conditions, minorities can profit from their exclusion by selling their data assets to a majority.

Proxy, voting, voting trust, and derivative agreements can contractually allocate votes. These agreements rely on fair pricing methods, such as dual-class shares, synthetic shares, controlling blocks, and equity-lending methods. However, since the ballot is defined by the voting rule, ultimate voting power depends on electoral and agenda-setting methods.

Price parities ensure the fair pricing of data assets, making it arbitrage-free. Strategies like activist capital structure arbitrage, asset-backed credit hedging, and others secure this balance. As a result, minorities retain a say, capital structure remains optimal, and assets change hands if debt becomes delinquent.

Entrepreneurs value the productive relevance of data assets, shareholders value privacy, and creditors value economic efficiency. These perspectives must align. Whenever you’re interested in specific data assets, Quantifiable manages, trades, and funds them on your behalf.

Data entrepreneurs establish the connection between fundraising and sales by aligning investment with actionable value. On behalf of our clients, we identify and remove causes of vulnerability from their investments. On behalf of our investors, we provide use cases in data equity investments. Our expertise in data asset pricing enables us to seamlessly connect these two crucial aspects, driving growth and mitigating risk.

Price movements can leak proprietary information. If these leaks, related to a client, can be organized, a security issued by that client becomes vulnerable. When we identify such vulnerabilities, we offer remedies. The fair value of data is the price our client pays to eliminate the causes of vulnerability from their investments.

A good company responds to key challenges. We solve yours by applying due diligence, asset pricing, and privacy preservation to common data resources. If your company requires stable investor relations, we enhance your AGMs, EGMs, and class meetings with effective fundraising, agenda-setting, and voting strategies.

We trade and restructure data assets, leveraging formalisms to extract and curate sensitive open-source information. Our focus is on diagnosing its security-related characteristics. Our current applications draw on the Arrow information paradox, Grossman-Stiglitz, and Newcomb’s paradoxes to guide and refine our approach.