Mixed Mechanisms for Auctioning Ranked Items

This paper deals with the problem of designing and choosing auctioning mechanisms for multiple commonly ranked objects as, for instance, keyword auctions in search engines on Internet. We shall adopt the point of view of the auctioneer who has to select the auction mechanism to be implemented not only considering its expected revenue, but also its associated risk. In order to do this, we consider a wide parametric family of auction mechanisms which contains the generalizations of discriminatory-price auction, uniform-price auction and Vickrey auction. For completeness, we also analyze the Generalized Second Price (GSP) auction which is not in the family. The main results are: (1) all members of the family satisfy the four basic properties of fairness, no over-payment, optimality and efficiency, (2) the Bayesian Nash equilibrium and the corresponding value at risk for the auctioneer are obtained for the considered auctions, (3) the GSP and all auctions in the family provide the same expected revenue, (4) there are new interesting auction mechanisms in the family which have a lower value at risk than the GSP and the classical auctions. Therefore, a window opens to apply new auction mechanisms that can reduce the risk to be assumed by auctioneers.

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Stochastic approximation schemes for economic capital and risk margin computations

ESAIM Proceedings and Surveys ◽

10.1051/proc/201965182 ◽

2019 ◽

Vol 65 ◽

pp. 182-218 ◽

Cited By ~ 3

Author(s):

David Barrera ◽

Stéphane Crépey ◽

Babacar Diallo ◽

Gersende Fort ◽

Emmanuel Gobet ◽

...

Keyword(s):

At Risk ◽

Monte Carlo ◽

Stochastic Approximation ◽

Value At Risk ◽

Expected Shortfall ◽

Point Of View ◽

Economic Capital ◽

Approximation Schemes ◽

Risk Margin ◽

A Value

We consider the problem of the numerical computation of its economic capital by an insurance or a bank, in the form of a value-at-risk or expected shortfall of its loss over a given time horizon. This loss includes the appreciation of the mark-to-model of the liabilities of the firm, which we account for by nested Monte Carlo à la Gordy and Juneja [17] or by regression à la Broadie, Du, and Moallemi [10]. Using a stochastic approximation point of view on value-at-risk and expected shortfall, we establish the convergence of the resulting economic capital simulation schemes, under mild assumptions that only bear on the theoretical limiting problem at hand, as opposed to assumptions on the approximating problems in [17] and [10]. Our economic capital estimates can then be made conditional in a Markov framework and integrated in an outer Monte Carlo simulation to yield the risk margin of the firm, corresponding to a market value margin (MVM) in insurance or to a capital valuation adjustment (KVA) in banking parlance. This is illustrated numerically by a KVA case study implemented on GPUs.

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Market Risk Model agricolture portfolio value-at-risk

10.21203/rs.3.rs-46262/v1 ◽

2020 ◽

Author(s):

Giulio Carlone

Keyword(s):

At Risk ◽

Value At Risk ◽

Risk Model ◽

Stock Exchange ◽

Market Risk ◽

Point Of View ◽

Market Model ◽

Basel Accords ◽

Price Distortions ◽

Portfolio Investments

Abstract Thinking about this current extreme scenario of stock exchange observed in a world scenario perspective and the related choices for worldbank portfolio investments in Agricolture commodity, this study its based in an advanced economic observation and analisys of the Agricolture commodity in a scenario of portfolio diversification without have the market risk default. This study its based in an advanced financial strategy to define the market model composed of London stock exchange agricolture commodity observed first in a London scenario and second in a Europe scenario and finally in a world scenario. The authorities regulation and the requirements used to define , the mathematical point of view and to describe , the market value at risk point of view , have been standardized in this empirical market model. The commodity scenario observed and the empirical market model defined to observe the max price distortions of the agricolture commodity defined and defined to observe the porfolio value at risk , are in this market model well described and standardized. Authorities are interested in the empirical market model to observe the VaR data because they are interested in a bank’s ability to withstand extreme events. VaR is monitored and is sanctioned by regulators defined in the Basel accords. The observed price are used in a variable choice of number of data price observation of five price for week a data price observation of one prices for week and a data price observation of two price for week and further similar strategies .

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Selected GARCH‑type Models in the Metals Market – Backtesting of Value‑at‑Risk

Acta Universitatis Lodziensis Folia oeconomica ◽

10.18778/0208-6018.331.12 ◽

2018 ◽

Vol 5 (331) ◽

pp. 185-203

Author(s):

Dominik Krężołek

Keyword(s):

At Risk ◽

Financial Market ◽

Value At Risk ◽

Risk Measure ◽

Asset Returns ◽

Point Of View ◽

Quality Of Information ◽

Correct Evaluation ◽

Political Situation

Risk analysis in the financial market requires the correct evaluation of volatility in terms of both prices and asset returns. Disturbances in quality of information, the economic and political situation and investment speculations cause incredible difficulties in accurate forecasting. From the investor’s point of view, the key issue is to minimise the risk of huge losses. This article presents the results of using some selected GARCH‑type models, ARMA‑GARCH and ARMA‑APARCH, in evaluating volatility of asset returns in the metals market. To assess the level of risk, the Value‑at‑Risk measure is used. The comparison between real and estimated losses (in terms of VaR) is made using the backtesting procedure.

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MARKET MECHANISMS TO ALLOCATE HERITAGE CONSERVATION FUND: AN EXPERIMENTAL STUDY

The Singapore Economic Review ◽

10.1142/s0217590815500241 ◽

2015 ◽

Vol 60 (05) ◽

pp. 1550024

Author(s):

KEAN SIANG CH’NG ◽

SUET LENG KHOO

Keyword(s):

Market Failure ◽

Point Of View ◽

Heritage Conservation ◽

Experimental Auctions ◽

Uniform Price Auction ◽

Market Mechanisms ◽

Conservation Effort ◽

Price Auction ◽

Cost Efficient ◽

Built Heritage Conservation

The under-provision of efforts in built heritage conservation was due to market failure to allocate cost and benefit efficiently. Conservation agency could facilitate conservation effort, which was considered not beneficial from the point of view of the private owners of the heritage houses, by providing conservation subsidy. In this paper, we conducted three different experimental auctions, namely, (i) discriminative price auction, (ii) uniform price auction, and (iii) random nth price auction to investigate bidding behaviors and efficiency levels in allocating conservation subsidies. Both uniform and random nth price auctions were able to encourage cost revealing bids. Random nth price auction was able to engage the off-margin bidders. However, discriminative price auction was more cost efficient compared to the other two auctions.

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Optimal expected utility risk measures

Statistics & Risk Modeling ◽

10.1515/strm-2017-0027 ◽

2018 ◽

Vol 35 (1-2) ◽

pp. 73-87 ◽

Cited By ~ 3

Author(s):

Sebastian Geissel ◽

Jörn Sass ◽

Frank Thomas Seifried

Keyword(s):

At Risk ◽

Expected Utility ◽

Value At Risk ◽

Risk Measures ◽

Risk Measure ◽

Point Of View ◽

Financial Loss ◽

Certainty Equivalents ◽

Average Value ◽

Average Value At Risk

AbstractThis paper introduces optimal expected utility (OEU) risk measures, investigates their main properties and puts them in perspective to alternative risk measures and notions of certainty equivalents. By taking the investor’s point of view, OEU maximizes the sum of capital available today and the certainty equivalent of capital in the future. To the best of our knowledge, OEU is the only existing utility-based risk measure that is (non-trivial and) coherent if the utility functionuhas constant relative risk aversion. We present several different risk measures that can be derived with special choices ofuand illustrate that OEU is more sensitive than value at risk and average value at risk with respect to changes of the probability of a financial loss.

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