Reducing Volatility for a Linear and Stable Growth in a Cryptocurrency
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Realising Blockchain's Surge in Mass Adoption with Unlimited Scaling, Speed and Cross-Chain Interope
THE NuGENESIS REVOLUTION: REALISING BLOCKCHAIN’S SURGE IN MASS ADOPTION WITH UNLIMITED SCALING, SPEED AND CROSS-CHAIN INTEROPERABILITY; and, BRIDGING WITH LEGAL AND MAINSTEAM ECONOMIC SUPPORT PART A INTRODUCTION AND SUMMARY INTRODUCTION NuGenesis is a fully completed native blockchain originally built for Government and transnational corporate applications. In the context of building a blockchain for Central Bank Digital Currencies (CBDC’s), and an exchange clearing house for settlement, limitations to scaling and speed, latency and reliance on human miners and validators had to be eliminated. Security had to be enhanced, its integrity underscored by Artificial Intelligence (AI) and carbon neutral in its efficiency. We have now made the NuGenesis gasless network of cross-chain blockchains available for commercial and social application for use by modifying it to maximise its efficacy for the up-coming tidal wave of mass adoption. This has meant not only the most advanced next-generation layer 1 multi-chain blockchain configuration system that is cross-chain interoperable, but which it easy and cost effective for developers to customise their own version which can run as a parallel network and accessing explosive new potential capabilities for Smart Contracts, NFTs, virtual reality innovation. The NuGenesis multi-cross chain network provides: 1. The Most Advanced Tech The NuGenesis blockchain network currently consists of a quad cross chain configuration interoperability: (a) The NuGenesis Main blockchain, built on Substrate; (b) The Ledger X (Exchange) chain based on C++ that is itself a parallel processing chain made of a tri blockchain configuration; (c) The Ethereum chain; and, (d) The Bitcoin Chain NuGenesis achieves unlimited scalability and speed through eliminating the validation bottleneck to data flow, uses consensus before packing and, currently implementing load balancers, with their own blockchain, to maximise block data, creation and speed. -
Some Mathematical Aspects of Market Impact Modeling by Alexander Schied and Alla Slynko
EMS Series of Congress Reports EMS Congress Reports publishes volumes originating from conferences or seminars focusing on any field of pure or applied mathematics. The individual volumes include an introduction into their subject and review of the contributions in this context. Articles are required to undergo a refereeing process and are accepted only if they contain a survey or significant results not published elsewhere in the literature. Previously published: Trends in Representation Theory of Algebras and Related Topics, Andrzej Skowro´nski (ed.) K-Theory and Noncommutative Geometry, Guillermo Cortiñas et al. (eds.) Classification of Algebraic Varieties, Carel Faber, Gerard van der Geer and Eduard Looijenga (eds.) Surveys in Stochastic Processes Jochen Blath Peter Imkeller Sylvie Rœlly Editors Editors: Jochen Blath Peter Imkeller Sylvie Rœlly Institut für Mathematik Institut für Mathematik Institut für Mathematik der Technische Universität Berlin Humboldt-Universität zu Berlin Universität Potsdam Straße des 17. Juni 136 Unter den Linden 6 Am Neuen Palais, 10 10623 Berlin 10099 Berlin 14469 Potsdam Germany Germany Germany [email protected] [email protected] [email protected] 2010 Mathematics Subject Classification: Primary: 60-06, Secondary 60Gxx, 60Jxx Key words: Stochastic processes, stochastic finance, stochastic analysis,statistical physics, stochastic differential equations ISBN 978-3-03719-072-2 The Swiss National Library lists this publication in The Swiss Book, the Swiss national bibliography, and the detailed bibliographic data are available on the Internet at http://www.helveticat.ch. This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in other ways, and storage in data banks. -
126 FM12 Abstracts
126 FM12 Abstracts IC1 which happens in applications to barrier option pricing or Optimal Execution in a General One-Sided Limit structural credit risk models. In this talk, I will present Order Book novel adaptive discretization schemes for the simulation of stopped Lvy processes, which are several orders of magni- We construct an optimal execution strategy for the pur- tude faster than the traditional approaches based on uni- chase of a large number of shares of a financial asset over form discretization, and provide an explicit control of the a fixed interval of time. Purchases of the asset have a non- bias. The schemes are based on sharp asymptotic estimates linear impact on price, and this is moderated over time by for the exit probability and work by recursively adding dis- resilience in the limit-order book that determines the price. cretization dates in the parts of the trajectory which are The limit-order book is permitted to have arbitrary shape. close to the boundary, until a specified error tolerance is The form of the optimal execution strategy is to make an met. initial lump purchase and then purchase continuously for some period of time during which the rate of purchase is Peter Tankov set to match the order book resiliency. At the end of this Universit´e Paris-Diderot (Paris 7) period, another lump purchase is made, and following that [email protected] there is again a period of purchasing continuously at a rate set to match the order book resiliency. At the end of this second period, there is a final lump purchase. -
5, 2018 Room 210, Run Run Shaw Bldg., HKU
July 3 - 5, 2018 Room 210, Run Run Shaw Bldg., HKU Program and Abstracts Institute of Mathematical Research Department of Mathematics Speakers: Jiro Akahori Ritsumeikan University Guangyue Han The University of Hong Kong Yaozhong Hu University of Alberta Davar Khoshnevisan University of Utah Arturo Kohatsu-Higa Ritsumeikan University Jin Ma University of Southern California Kihun Nam Monash University Lluís Quer-Sardanyons Universitat Autònoma Barcelona Xiaoming Song Drexel University Samy Tindel Purdue University Ciprian Tudor Université Paris 1 Tai-Ho Wang Barach College, City University of New York Jing Wu Sun Yat-Sen University Panqiu Xia University of Kansas George Yuan Soochow University & BBD Inc. Jianfeng Zhang University of Southern California Xicheng Zhang Wuhan University Organizing Committee: Guangyue Han, Jian Song, Jeff Yao (The University of Hong Kong), Xiaoming Song (Drexel University) Contact: Jian Song ([email protected]), Xiaoming Song ([email protected]) July 3 - 5, 2018 Room 210, Run Run Shaw Bldg., HKU Time / Date July 3 (Tue) July 4 (Wed) July 5 (Thur) Arturo Davar 9:30 – 10:30 Jin Ma Kohatsu-Higa Khoshnevisan 10:30 – 10:50 Tea Break 10:50 – 11:50 Xicheng Zhang George Yuan Samy Tindel Lunch Break 14:00 – 15:00 Yaozhong Hu Jianfeng Zhang Jiro Akahori Lluís 15:10 – 16:10 Tai-Ho Wang Jing Wu Quer-Sardanyons 16:10 – 16:30 Tea Break 16:30 – 17:30 Kihun Nam Ciprian Tudor Xiaoming Song 17:30 – 18:30 Guangyue Han Panqiu Xia Jul 3, 2018 9:30 – 10:30 Jin Ma, University of Southern California Time Consistent Conditional Expectation -
Volume 52, Number 3, 2016 ISSN 0246-0203
Volume 52, Number 3, 2016 ISSN 0246-0203 Martingale defocusing and transience of a self-interacting random walk Y. Peres, B. Schapira and P. Sousi 1009–1022 Excited random walk with periodic cookies G. Kozma, T. Orenshtein and I. Shinkar 1023–1049 Harmonic measure in the presence of a spectral gap ....I. Benjamini and A. Yadin 1050–1060 How vertex reinforced jump process arises naturally ......................X. Zeng 1061–1075 Persistence of some additive functionals of Sinai’s walk ...............A. Devulder 1076–1105 Random directed forest and the Brownian web ......R. Roy, K. Saha and A. Sarkar 1106–1143 Slowdown in branching Brownian motion with inhomogeneous variance ..............................................P. Maillard and O. Zeitouni 1144–1160 Maximal displacement of critical branching symmetric stable processes ..................................................S. P. Lalley and Y. Shao 1161–1177 On the asymptotic behavior of the density of the supremum of Lévy processes ............................................L. Chaumont and J. Małecki 1178–1195 Large deviations for non-Markovian diffusions and a path-dependent Eikonal equation ......................................J.Ma,Z.Ren,N.TouziandJ.Zhang 1196–1216 Inviscid limits for a stochastically forced shell model of turbulent flow .....................................S. Friedlander, N. Glatt-Holtz and V. Vicol 1217–1247 Estimate for Pt D for the stochastic Burgers equation G. Da Prato and A. Debussche 1248–1258 Skorokhod embeddings via stochastic flows on the space of Gaussian measures ................................................................R. Eldan 1259–1280 Liouville heat kernel: Regularity and bounds P. Maillard, R. Rhodes, V. Vargas and O. Zeitouni 1281–1320 Total length of the genealogical tree for quadratic stationary continuous-state branching processes .......................................H. Bi and J.-F. Delmas 1321–1350 Weak shape theorem in first passage percolation with infinite passage times ........................................................R. -
Blockchain Esquire Is Not Affiliated with Any Specific Provider, Service Or Offering
BLOCKCHAIN THE BASICS R&D By Simon Hawk ESQUIRE 2021 Before Cash There Was Gold After Cash There Was Paypal. Now we have BLOCKCHAIN. If Bitcoin is digital gold. Then Ethereum is the Next generation. EBAY VS PAYPAL AS AN EXAMPLE How much would you have if you invested $10,000 in PayPal's IPO? Your eBay shares would be worth nearly $42,000 and your PayPal shares would be worth over $123,000. IPO offerings are often risky investments. There is no guarantee that a company, project or tech will be successful. We can look at case studies for basic comparisons though. https://www.fool.com/ investing/2019/11/22/if- you-invested-10000-i n-paypals-ipo-this-is- how-m.aspx THE RISE OF DIGITAL PAYMENT SYSTEMS Before Cars there were horses. Before Email there was pony express. Before Credit Cards we had cash. Now we have Blockchain. Eventually every industry takes the form of a bubble. While still a reliable means of transportation, riding horses has gone out of fashion. Crypto is the next era of money. DIGITAL CURRENCIES CREATE NEW FINANCIAL IDENTITIES Digital currency (digital money, electronic money or electronic currency) is any currency, money, or money-like asset that is primarily managed, stored or exchanged on digital computer systems, especially over the internet. Types of digital currencies include cryptocurrency, virtual currency and central bank digital currency. Digital currency may be recorded on a distributed database on the internet, a centralized electronic computer database owned by a company or bank, within digital files or even on a stored-value card.[1] Digital currencies exhibit THE CURRENT SYSTEM properties similar to traditional currencies, but generally do not have a physical form, unlike currencies with printed banknotes or minted coins. -
Modely Stochastické Volatility
MASARYKOVA UNIVERZITA PŘÍRODOVĚDECKÁ FAKULTA ÚSTAV MATEMATIKY A STATISTIKY MODELY STOCHASTICKÉ VOLATILITY Diplomová práce Martin Diviš Vedoucí práce: Mgr. Ondřej Pokora, Ph.D. Brno 2015 Bibliografický záznam Autor: Bc. Martin Diviš Přírodovědecká fakulta, Masarykova univerzita Ústav matematiky a statistiky Název práce: Modely stochastické volatility Studijní program: Matematika Studijní obor: Finanční matematika Vedoucí práce: Mgr. Ondřej Pokora, Ph.D. Akademický rok: 2014/2015 Počet stran: IX + 69 Klíčová slova: Evropská opce, volatilita, Blackův-Scholesův model, Wienerův proces, CIR proces, modely stochastické volatility, kalibrace Hestonova modelu, Lévyho procesy Bibliographic Entry Author Bc. Martin Diviš Faculty of Science, Masaryk University Department of Mathematics and Statistics Title of Thesis: Stochastic volatility models Degree programme: Mathematics Field of Study: Financial Mathematics Supervisor: Mgr. Ondřej Pokora, Ph.D. Academic Year: 2014/2015 Number of Pages: IX + 69 Keywords: European option, volatility, Black-Scholes model, Wiener process, CIR process, stochastic volatility models, calibration of the Heston model, Lévy process Abstrakt V diplomové práci se zabýváme oceňováním evropských opcí a jejich závislostí na volatilitě. Blackův-Scholesův model má mnoho slabin. Největší slabinou je předpoklad konstantní volatility. V diplomové práci jsou popsány typy volatilit, které se nevyvíjí konstantně. Zabýváme se zejména stochastickou volatilitou. Ta je sice matematicky nejkomplikovanější, ale také nejpřesnější. Popisujeme modely stochastické volatility, například Hestonův model, 3/2 model či SABR model. Tyto modely si dokážou poradit s častými problémy při oceňování opcí jako je například volatily smile či silné chvosty reálných pravděpodobnostních rozdělení. Nejslavnější Hestonův model kalibrujeme v Excelu. Také se zaměřujeme na Lévyho procesy, které si poradí se skoky podkladového aktiva. Abstract Throughout this diploma thesis we deal with the valuation of European options and their dependence on volatility. -
A Complete Bibliography of Electronic Communications in Probability
A Complete Bibliography of Electronic Communications in Probability Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 20 May 2021 Version 1.13 Title word cross-reference (1 + 1) [CB10]. (d; α, β) [Zho10]. (r + ∆) [CB10]. 0 [Sch12, Wag16]. 1 [Duc19, HL15b, Jac14, Li14, Sch12, SK15, Sim00, Uch18]. 1=2 [KV15]. 1=4 [JPR19]. 2 [BDT11, GH18b, Har12, Li14, RSS18, Sab21, Swa01, VZ11, vdBN17]. 2D [DXZ11]. 2M − X [Bau02, HMO01, MY99]. 3 [AB14, PZ18, SK15]. [0;t] [MLV15]. α [DXZ11, Pat07]. α 2 [0; 1=2) [Sch12]. BES0(d) [Win20]. β [Ven13]. d [H¨ag02, Mal15, Van07, Zho20]. d = 2 [KO06]. d>1 [Sal15]. dl2 [Wan14]. ≥ ≥ 2 + @u @mu d 2 [BR07]. d 3 [ST20]. d (0; 1) [Win20]. f [DGG 13]. @t = κm @xm [OD12]. G [NY09, BCH+00, FGM11]. H [Woj12, WP14]. k [AV12, BKR06, Gao08, GRS03]. k(n) [dBJP13]. kα [Sch12]. L1 1 2 1 p [CV07, MR01]. L ([0; 1]) [FP11]. L [HN09]. l [MHC13]. L [CGR10]. L1 [EM14]. Λ [Fou13, Fou14, Lag07, Zho14]. Lu = uα [Kuz00]. m(n) [dBJP13]. Cn [Tko11]. R2 [Kri07]. Rd [MN09]. Z [Sch12]. Z2 [Gla15]. Zd d 2 3 d C1 [DP14, SBS15, BC12]. Zn [ST20]. R [HL15a]. R [Far98]. Z [BS96]. 1 2 [DCF06]. N × N × 2 [BF11]. p [Eva06, GL14, Man05]. pc <pu [NP12a]. -
Application of SABR Model to Strategy of Accumulation of Reserves Of
Journal of Business and Economics, ISSN 2155-7950, USA May 2013, Volume 4, No. 5, pp. 419-431 Academic Star Publishing Company, 2013 http://www.academicstar.us Application of SABR Model to Strategy of Accumulation of Reserves of Central Bank in México Guillermo Sierra Juárez (Universidad de Guadalajara, CUCEA, Departamento de Métodos Cuantitativos, Jalisco, Guadalajara México) Abstract: The purpose of this paper is to review and to calibrate the SABR volatility model in order to estimate the volatility of foreign currency (US dollar) in the case of Mexican market and applied the model to the valuation of the option premium (Oc) specifically for the case of international reserves accumulation of the Central Bank on Mexico. It was found that the estimation of volatility and the premium Oc when the historical and implied volatilities are used have different estimation respect the SABR volatility case, principally when forward price is not the same from strike price. Key words: SABR; volatility; international reserves; differential geometry JEL codes: C61, G10, G12 1. Introduction Since Black-Scholes original paper (1973) plain vanilla options have been valued using market parameters and financial assumptions. However later it was discovered that Black-Scholes model estimated the same volatility for different strike prices, a fact not observed in the real world, in other words at different strike prices produce different volatilities, this behavior is observed in the market and it is known as skew or volatility smile. Market volatilities smiles and skews1 are usually managed by using local volatility models. It was discovered that the dynamics of the market smile predicted by local volatility models is opposite of observed market behavior. -
The Heston Model
Outline Introduction Stochastic Volatility Monte Carlo simulation of Heston Additional Exercise The Heston Model Hui Gong, UCL http://www.homepages.ucl.ac.uk/ ucahgon/ May 6, 2014 Hui Gong, UCL http://www.homepages.ucl.ac.uk/ ucahgon/ The Heston Model Outline Introduction Stochastic Volatility Monte Carlo simulation of Heston Additional Exercise Introduction Stochastic Volatility Generalized SV models The Heston Model Vanilla Call Option via Heston Monte Carlo simulation of Heston It^o'slemma for variance process Euler-Maruyama scheme Implement in Excel&VBA Additional Exercise Hui Gong, UCL http://www.homepages.ucl.ac.uk/ ucahgon/ The Heston Model Outline Introduction Stochastic Volatility Monte Carlo simulation of Heston Additional Exercise Introduction 1. Why the Black-Scholes model is not popular in the industry? 2. What is the stochastic volatility models? Stochastic volatility models are those in which the variance of a stochastic process is itself randomly distributed. Hui Gong, UCL http://www.homepages.ucl.ac.uk/ ucahgon/ The Heston Model Outline Introduction Generalized SV models Stochastic Volatility The Heston Model Monte Carlo simulation of Heston Vanilla Call Option via Heston Additional Exercise A general expression for non-dividend stock with stochastic volatility is as below: p 1 dSt = µt St dt + vt St dWt ; (1) 2 dvt = α(St ; vt ; t)dt + β(St ; vt ; t)dWt ; (2) with 1 2 dWt dWt = ρdt ; where St denotes the stock price and vt denotes its variance. Examples: I Heston model I SABR volatility model I GARCH model I 3/2 model I Chen model Hui Gong, UCL http://www.homepages.ucl.ac.uk/ ucahgon/ The Heston Model Outline Introduction Generalized SV models Stochastic Volatility The Heston Model Monte Carlo simulation of Heston Vanilla Call Option via Heston Additional Exercise The Heston model is a typical Stochastic Volatility model which p takes α(St ; vt ; t) = κ(θ − vt ) and β(St ; vt ; t) = σ vt , i.e. -
Proceedings of the Finance and Economics Conference 2012
Proceedings of the Finance and Economics Conference 2012 Munich, Germany August 1-3, 2012 The Lupcon Center for Business Research www.lcbr-online.com ISSN 2190-7927 All rights reserved. No part of this publication may be reprinted in any form (including electronically) without the explicit permission of the publisher and/or the respective authors. The publisher (LCBR)is in no way liable for the content of the contributions. The author(s) of the abstracts and/or papers are solely responsible for the texts submitted. 1 Procedural Notes about the Conference Proceedings 1) Selecting Abstracts and Papers for the Conference The basis of the acceptance decisions for the conference is the evaluation of the abstracts submitted to us before the deadline of March 15, 2012. Upon an initial evaluation in terms of general quality and thematic fit, each abstract is sent to a reviewer who possesses competence in the field from which the abstract originates. The reviewers return their comments to the Lupcon Center for Business Research about the quality and relevance of the abstracts. The opinion of at least one peer reviewer per abstract is solicited. In some cases, the opinion of additional reviewers is necessary to make an adequate decision. If the peer reviewers disagree about an abstract, a final decision can be facilitated through an evaluation of the full paper, if it is already available at the time of the submission. If the reviewers determine that their comments are useful for the author to improve the quality of the paper, LCBR may forward the comments to the author. -
Crypto Leaderboard One-Month Performance Defi One-Month
Crypto Leaderboard Rank Name Ticker Price MC, $b 1M One Month Performance 1 Bitcoin BTC 41,626 781 19% 2 Ethereum ETH 2,536 297 12% 3 Tether USDT 1.00 62 0% 4 Binance BNB 334 56 10% 5 CardanoCoin ADA 1.32 42 -4% 6 Ripple XRP 0.75 35 6% 7 USD//Coin USDC 1.00 27 0% 8 Dogecoin DOGE 0.21 27 -18% 9 Polkadot DOT 16.85 17 3% 10 Binance BUSD 1.00 12 0% USD One-Month Performance By Token By Category By Ecosystem Tratidional Finance AXS 832% Gaming 299% xDAI 27% Gas 7.2% FLOW 158% NFTs 152% Polygon 18% Gold 2.4% OKB 80% CEXs 26% Cosmos 13% SPX 2.3% QNT 80% Defi 19% BSC 11% N100 1.3% LUNA 79% DAOs 18% Terra 9% WTI 0.7% STX 69% DEX / B&L 13% Solana 8% EUR/USD 0.1% ICP -23% Smart Cont 6% Polkadot 7% FTSE -0.1% TEL -26% IoT 3% Avalanche 6% DAX -0.4% MDX -27% Privacy 1% USD/JPY -1.3% SHIB -29% Dist Comput -2% Nikkei -3.2% SAFEMOON -35% Meme -25% HSI -7.1% Defi Total Value Locked, LTM, $b Top TVL By Protocol, $b DefiPulse Index, 1M One-Month Trading Volumes Top 100, Spot, $b Top Spot by Token, $b Top Spot Exchanges, $b Aggregate Derivs Vols, $b USDT 1,522.7 Binance 454.8 1M O/I BTC 819.1 OKEx 96.8 Spot 1,540 11,840 ETH 591.7 Huobi 92.7 Perpetuals 2,390 2,741 BUSD 119.9 Coinbase 53.8 Futures 225 2,381 ETC 71.3 Upbit 52.6 Options 15 4,819 Sources: CoinGecko, CoinMarketCap, Santiment, DefiPulse, TradingView, WorldCoinIndex.com, Investing.com, The Block Disclaimers: “This material is a product of the GSR Sales and Trading Department.