The Rate of Convergence to Perfect Competition of a Simple Matching and Bargaining Mechanism

We study the steady-state of a market with inflowing cohorts of buyers and sellers who are randomly matched pairwise and bargain under private information. Two bargaining protocols are considered: take-it-or-leave-it offering and the double auction. There are frictions due to costly search and time discounting, parameterized by a single number t > 0 proportional to the waiting time until the next meeting. We study the efficiency of these mechanisms as the frictions are removed, i.e. t 0. We find that all equilibria of the take-it-or-leave-it offering mechanism converge to the Walrasian limit, at the fastest possible rate O(t) among all bargaining mechanisms. For the double auction mechanism, we find that there are equilibria that converge at the linear rate, those that converge at a slower rate or even not converge at all.Matching and Bargaining, Search, Double Auctions, Foundations for Perfect Competition, Rate of Convergence

Identification in First-Price and Dutch Auctions when the Number of Potential Bidders is Unobservable

Within the IPV paradigm, we show nonparametric identification of model primitives for first-price and Dutch auctions with a binding reserve price and auction-specific, unobservable sets of potential bidders.auctions, identification

Bilateral Matching and Bargaining with Private Information

We explore the role of private information in bilateral matching and bargaining. Our model is a replica of Mortensen and Wright (2002), but with private information. A simple necessary and sufficient condition on the parameters of the model for existence of equilibrium with entry is obtained. As in Mortensen and Wright (2002), we find that equilibrium is unique and has the property that every meeting results in trade when the discount rate is sufficiently small. There are also equilibria in which not every meeting results in trade. All equilibria converge to perfect competition as the frictions of search costs and discounting are removed. We find that private information may deter entry. Because of matching externalities, this entry-deterring effect of private information may be welfare-enhancing.Matching and Bargaining, Search, Foundations for Perfect Competi- tion, Two-sided Incomplete Information

The impact of delivery risk on optimal production and futures hedging

Multiple delivery specifications exist on nearly all commodity futures contracts. Sellers are typically allowed to choose among several grades of the underlying commodity. On the delivery day, the futures price converges to the spot price of the cheapest-to-deliver grade rather than to that of the par-delivery grade of the commodity. This imposes an additional delivery risk on hedgers. This paper derives the optimal production and futures hedging strategy for a risk-averse competitive firm in the presence of delivery risk. We show that, depending on its relative valuation, the delivery option may induce the firm to produce more than in the absence of delivery risk. If delivery risk is additively related to commodity price risk, the firm will under-hedge its exposure to commodity price risk. If delivery risk is multiplicatively related to commodity price risk, the firm will under- or over-hedge this exposure. For constant relative risk aversion, this is illustrated by a numerical example.delivery risk, futures, risk management, production

Restricted Export Flexibility and Risk Management with Options and Futures

This paper examines the production, export and risk management decisions of a risk-averse competitive firm under exchange rate risk. The firm is export flexible in allocating its output to either the domestic market or a foreign market after observing the exchange rate. Export flexibility is restricted by certain minimum sales requirements that are due to long-term considerations. Currency options are sufficient to derive a separation result under restricted export flexibility. Under fairly priced currency futures and options, full hedging with both instruments is optimal. Introducing fairly-priced currency options stimulates production provided that the currency futures market is unbiased.restricted export flexibility, risk management, currency futures, currency options

BLADERUNNER: Rapid Countermeasure for Synthetic (AI-Generated) StyleGAN Faces

StyleGAN is the open-sourced TensorFlow implementation made by NVIDIA. It has revolutionized high quality facial image generation. However, this democratization of Artificial Intelligence / Machine Learning (AI/ML) algorithms has enabled hostile threat actors to establish cyber personas or sock-puppet accounts in social media platforms. These ultra-realistic synthetic faces. This report surveys the relevance of AI/ML with respect to Cyber & Information Operations. The proliferation of AI/ML algorithms has led to a rise in DeepFakes and inauthentic social media accounts. Threats are analyzed within the Strategic and Operational Environments. Existing methods of identifying synthetic faces exists, but they rely on human beings to visually scrutinize each photo for inconsistencies. However, through use of the DLIB 68-landmark pre-trained file, it is possible to analyze and detect synthetic faces by exploiting repetitive behaviors in StyleGAN images. Project Blade Runner encompasses two scripts necessary to counter StyleGAN images. Through PapersPlease acting as the analyzer, it is possible to derive indicators-of-attack (IOA) from scraped image samples. These IOAs can be fed back into AmongUs acting as the detector to identify synthetic faces from live operational samples. The opensource copy of Blade Runner may lack additional unit tests and some functionality, but the open-source copy is a redacted version, far leaner, better optimized, and a proof-of-concept for the information security community. The desired end-state will be to incrementally add automation to stay on-par with its closed-source predecessor.Comment: 29 page