Author: Quantifiable

Whenever you trade data, you face settlement risk. For the trade to be efficient, data asset pricing must incorporate the market value of counterparty credit risk. To calculate this premium, you take the risk-neutral expectation of discounted loss. How valuable do you find offloading this risk from your portfolio?

Fair pricing of traded data assets rests on price parities. If a parity involves derivatives, the pricing must account for the costs of hedging counterparty risks, funding initial and variation margins, and holding regulatory capital against data asset transaction. Known as xVA, these adjustments are a banking necessity.

The power of a particular fact is a difference in the validity of outcomes that depends on the fact’s availability for valuation. This difference extends into agenda setting, electioneering, and framing. If a data commons hides a voting paradox, a single fact can make this difference. Our science foundation makes it for you.

Absence of transaction costs can overcome initially allocated access to confidential information. However, presence of transaction costs can make the price of such access diverge from its value. In these conditions, minorities can profit from their exclusion from the access, as you can sell your data assets to a majority.

Proxy, voting, voting trust, and derivative agreements can contractually allocate votes. These agreements rest on fair pricing methods, including dual-class share, synthetic share, controling block, and equity-lending methods. However, since ballot is defined by voting rule, voting power ultimately rests on electoral and agenda-setting methods.

Price parities ensure fair pricing of data assets. Fair pricing is arbitrage-free. Activist, capital structure arbitrage, asset-backed credit hedging, and other strategies secure this freedom. Thereby, minorities retain a say, capital structure remains optimal, and the assets exchange hands if the debt is delinquent.

Entrepreneurs value productive relevance of data assets. Shareholders value privacy of data assets. Creditors value economic efficiency of data assets. These different approaches to data asset pricing must coincide. Whenever you are interested in specific data assets, Quantifiable manages, trades, and funds such assets on your behalf.

How do data entrepreneurs establish connection between fundraising and sales? On behalf of our clients, we identify and remove causes of vulnerability from vulnerable investments. On behalf of our investors, we provide use cases in data equity investments. Our data asset pricing capability enables us to connect the two.

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

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