I gave this talk about Quantum Computing and Quantum Cryptography some years ago. But after reading a lot of papers about quantum decoherence, I decided to left the field as the prospects were not very enticing.

Notwithstanding, this month has emerged with very interesting research (and it’s not the first sale of quantum computation device):

 

“κλοιῷ τέτριπται σάρκα τῷ σιδηρείῳ,
ὃν ὁ τροφεύς μοι περιτέθεικε χαλκεύσας.”
λύκος δ’ ἐπ’ αὐτῷ καγχάσας “ἐγὼ τοίνυν
χαίρειν κελεύω” φησί “τῇ τρυφῇ ταύτῃ,
δι’ ἣν σίδηρος τὸν ἐμὸν αὐχένα τρίψει.”

THE WOLF, THE DOG AND THE COLLAR

Aesop’s Fables (Valerius Babrius, 100)

The Internet and modern computer technology promised to reduce the effects from consumer myopia arising from mental calculation costs. However, it is to note that the current cost of mobile permanence agreements in Spain, calculated as the foregone value of forsaking the right to change to the best mobile provider for 18 to 24 months, ranges from 216€ to 296€.

And given that smartphone Average Selling Prices (ASPs) are around 250€, the implicit interest rate of these permanence agreements may even surpass 100% in some cases. A really astonishing figure.

Therefore, and in accordance with other studies in the empirical literature about transaction costs on the e-commerce industry (Do Lower Search Costs Reduce Prices and Price Dispersion?), very high search costs and the analysis paralysis resulting from them also exists in the mobile telecommunications industry, and are just as relevant today as they always have been.

 

Entrepreneurs are already well versed on the intricacies of startup financing and the pernicious effects it may have on their companies: down-rounds, dilution, preferred stock and stock with different voting rights, among others. For that reason, they plan ahead and try their best not to find themselves caught in stalemates and catch-22 situations with no possible resolution.

But what I find fascinating is the lack of thought exhibited by VCs on their term sheets, driven more by custom and just plain imitation than by economically rational designs. The case is most notorious in the disregard of debt instruments (convertible debt and notes), of which their advantageous properties to the entrepreneurial side of the investment are widely known, but not their equally valuable properties to the other side of equation.

The detailed study of the financing structures of tech startups is a puzzling experience of negation of the received wisdom from the classic Corporate Finance results, especially the Myers-Majluf theorem: given a project within a startup, with positive or negative NPV, and the founders knowing the project’s NPV with very high certainty but startup outsiders do not, ceteris paribus, the founders may not invest in the project with positive NPV if outside equity must be issued to finance it, because the value of the project may go to the new shareholders at the expense of earlier shareholders . That is, the asymmetric information is causing an agency cost to the current shareholders if the startup issues equity, but not if it issues debt. This straightforward result is key to explain the low start-up survival rates through the different rounds of financing since, in the light of the full lifecycle of the entrepreneur, it’s perfectly rational to prefer that the current startup goes bankrupt to start a new one with the project with positive NPV if the cost of issuing new equity is so high, avoiding any pivot in the process.

And then, by Green Theorem (from Corporate Finance, not from Calculus) convertible debt, not straight, would be the ideal instrument: if the startup can choose investment levels between different projects with different risks, and outsiders don’t know the relative scale of the investments then, ceteris paribus, current shareholders bear an agency cost if the startup gets financed only by straight debt, a cost that can be avoided by issuing convertible debt.

These pecking order results hold even with stock options and without asymmetric information or managerial firm-specific human capital (see Stock Options and Capital Structure), so I wonder how many decades it will take for practice to meet theory… if they dare!

 

The latest IPOs of tech companies like LinkedIn, Yandex and RenRen have reactivated the never-ending debate of valuations and the fear of another tech bubble, even if most tech stocks are cheaper than before the dot-com bust. But this time, we have the masterful studies of Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages and Tech Stock Valuation: Investor Psychology and Economic Analysis, providing us with tons of empirical data from previous bubbles. Or even better, real-time theories of asset bubble formation, like the Jarrow-Kchia-Protter-Shimbo theory put to test in the following paper:

Download (PDF, 470KB)

This time is different.

 
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