This document presents a model of the over-the-counter federal funds market. It uses a search-and-bargaining framework to model how banks with reserve shortages and surpluses are matched to reallocate balances. The model shows the fed funds rate is determined by banks' discount rates and the distribution of reserve balances held by banks. It also shows under certain conditions, the market structure achieves efficient reallocation of funds among banks.
Never selling stocks is optimal for investors with a long horizon and a realistic range of preference and market parameters, if relative risk aversion, investment opportunities, proportional transaction costs, and dividend yields are constant. Such investors should buy stocks when their portfolio weight is too low, and otherwise hold them, letting dividends rebalance to cash over time rather than selling. With capital gain taxes, this policy outperforms both static buy-and-hold and dynamic rebalancing strategies that account for transaction costs. Selling stocks becomes optimal if either their target weight is low, or intermediate consumption is substantial.
Incomplete-Market Equilibrium with Unhedgeable Fundamentals and Heterogeneous...guasoni
We solve a general equilibrium model of an incomplete market with heterogeneous preferences, identifying first-order and second-order effects. Several long-lived agents with different absolute risk-aversion and discount rates make consumption and investment decisions, borrowing from and lending to each other, and trading a stock that pays a dividend whose growth rate has random fluctuations over time. For small fluctuations, the first-order equilibrium implies no trading in stocks, the existence of a representative agent, predictability of returns, multi-factor asset pricing, and that agents use a few public signals for consumption, borrowing, and lending. At the second-order, agents dynamically trade stocks and no representative agent exist. Instead, both the interest rate and asset prices depend on the dispersion of agents' preferences and their shares of wealth. Dynamic trading arises from agents' intertemporal hedging motive, even in the absence of personal labor income.
Efficient Numerical PDE Methods to Solve Calibration and Pricing Problems in ...Volatility
1) Volatility modelling
2) Local stochastic volatility models: stochastic volatility, jumps, local volatility
3) Calibration of parametric local volatility models using partial differential equation (PDE) methods
4) Calibration of non-parametric local volatility volatility models with jumps and stochastic volatility using PDE methods
5) Numerical methods for PDEs
6) Illustrations using SPX and VIX data
كان ياما كان: قصص تنمية بشرية، قصص للعبرة، قصص أطفالAli I. Al-Mosawi
كان ياما كان: قصص تنمية بشرية، قصص للعبرة، قصص أطفال
أقدم لكم في هذا الكتاب مجموعة كبيرة من قصص التنمية البشرية وتطوير الذات وقصص العبرة وقصص الأطفال والحكايات الشعبية والأمثال والتي تنوعت بين القصص التأريخية والقصص الحديثة.لقد قمت بجمع هذه القصص من مصادر كثيرة كالكتب والمدونات الإلكترونية ومن ثم رتبتها وأعدت صياغتها وقمت بتأليف وإعداد عدد منها أيضاً. آملاً أن تجدوا فيها ما ينفعكم ويدخل البهجة على نفوسكم وقلوبكم، والله الموفق.
Never selling stocks is optimal for investors with a long horizon and a realistic range of preference and market parameters, if relative risk aversion, investment opportunities, proportional transaction costs, and dividend yields are constant. Such investors should buy stocks when their portfolio weight is too low, and otherwise hold them, letting dividends rebalance to cash over time rather than selling. With capital gain taxes, this policy outperforms both static buy-and-hold and dynamic rebalancing strategies that account for transaction costs. Selling stocks becomes optimal if either their target weight is low, or intermediate consumption is substantial.
Incomplete-Market Equilibrium with Unhedgeable Fundamentals and Heterogeneous...guasoni
We solve a general equilibrium model of an incomplete market with heterogeneous preferences, identifying first-order and second-order effects. Several long-lived agents with different absolute risk-aversion and discount rates make consumption and investment decisions, borrowing from and lending to each other, and trading a stock that pays a dividend whose growth rate has random fluctuations over time. For small fluctuations, the first-order equilibrium implies no trading in stocks, the existence of a representative agent, predictability of returns, multi-factor asset pricing, and that agents use a few public signals for consumption, borrowing, and lending. At the second-order, agents dynamically trade stocks and no representative agent exist. Instead, both the interest rate and asset prices depend on the dispersion of agents' preferences and their shares of wealth. Dynamic trading arises from agents' intertemporal hedging motive, even in the absence of personal labor income.
Efficient Numerical PDE Methods to Solve Calibration and Pricing Problems in ...Volatility
1) Volatility modelling
2) Local stochastic volatility models: stochastic volatility, jumps, local volatility
3) Calibration of parametric local volatility models using partial differential equation (PDE) methods
4) Calibration of non-parametric local volatility volatility models with jumps and stochastic volatility using PDE methods
5) Numerical methods for PDEs
6) Illustrations using SPX and VIX data
كان ياما كان: قصص تنمية بشرية، قصص للعبرة، قصص أطفالAli I. Al-Mosawi
كان ياما كان: قصص تنمية بشرية، قصص للعبرة، قصص أطفال
أقدم لكم في هذا الكتاب مجموعة كبيرة من قصص التنمية البشرية وتطوير الذات وقصص العبرة وقصص الأطفال والحكايات الشعبية والأمثال والتي تنوعت بين القصص التأريخية والقصص الحديثة.لقد قمت بجمع هذه القصص من مصادر كثيرة كالكتب والمدونات الإلكترونية ومن ثم رتبتها وأعدت صياغتها وقمت بتأليف وإعداد عدد منها أيضاً. آملاً أن تجدوا فيها ما ينفعكم ويدخل البهجة على نفوسكم وقلوبكم، والله الموفق.
About Myanmar Marionettes Organization (MMOrg)Kyaw Myo Ko
Introduction, Aim and Objectives, The founding of the Myanmar Marionettes Organization (History and Background), Patrons and Executive Committee Members of the Myanmar Marionette Organization (MMOrg)
Safeguarding the Tradition of Myanmar Marionette and Performing ArtsKyaw Myo Ko
This Case Study is a reprint of the August 2016 project report concerning Safeguarding the Tradition of Myanmar marionettes and related performing arts during the period from the 1st of July 2015 through July 2nd, 2016 funded by the Swiss Agency for Development and Cooperation – SDC and implemented by Myanmar Upper Land | culture & travel (MUL)
Pakistan is now slowly realising that its friendship with China which Pakistan claims is higher than mountains and deeper than oceans, the same China has quietly duped Pakistan in the name of providing security and economic prosperity by their project CPEC. The 46 Billion dollar investment by China in China Pak Economic Corridor (CPEC) which will connect Khasgar town of mineral rich restive Xinxiang province of China with Gwador port of Pakistan located on Arabian sea, via rail and road routes passing through POK and Baluchistan province of Pakistan, a total distance of 3000 kms, is not such a big panacea which Pakistan has been tom toming about. This entire project basically benefits China with Pakistan getting some crumbs thrown at it with exorbitant costs.
Как работают редакции Медиапроектов Mail.Ru Group: все, что вы хотели знать, но боялись спросить.
«Редакционные метрики Медиапроектов Mail.Ru Group: как мы оцениваем работу редакции», Сергей Паранько, редакционный директор медиапроектов Mail.Ru Group
«5 секретов хорошего заголовка», Ольга Выходченко, главный редактор Дети Mail.Ru.
«Как писать тексты, которые дочитывают», Надежда Сокирская, главный редактор Леди Mail.Ru.
«Экспертиза: комментарии от серьезных людей, почему они нужны и как добыть», Евгений Паперный, руководитель проектов Здоровье и Дети Mail.Ru.
«Как писать интересно на узкоспециальные темы», Мария Мягкова, главный редактор Недвижимость Mail.Ru.
«Верстка вовлекающих материалов», Михаил Стецовский, руководитель направления Infotainment Медиапроектов Mail.Ru Group.
«Баланс эмоционального и объективного, простые способы привлечь внимание и работа с цифрами», Анна Феоктистова, главный редактор Hi-Tech Mail.Ru.
«Как делать интересные и полезные медицинские новости», Александра Яковлева, главный редактор Здоровье Mail.Ru.
Myanmar has tremendous potential to grow into an important tourist destination in the region, but this would need the active support of the Myanmar tourism department.
IDS Next Business Solutions is a global leader in providing Hotel ERP and technology solutions for the Hospitality and Leisure industries. We have earned the trust of over 4000 customers globally and have a strong presence in 40 plus countries across South East Asia, Oceania, Indian sub-continent, Middle East and Africa.
IDS Next designs, develops, markets and maintains a comprehensive range of information management systems for various hospitality businesses including hotels, restaurants, clubs and resorts.
IDS Next Business Solutions is a global leader in providing Hotel ERP and technology solutions for the Hospitality and Leisure industries. We have earned the trust of over 4000 customers globally and have a strong presence in 40 plus countries across South East Asia, Oceania, Indian sub-continent, Middle East and Africa.
8 июля 2016 года, Летняя школа HSE{sun}.
Доклад "Дорожная карта для hardware стартапа: где и как сделать прототип и опытную партию, а также остаться в живых", Василь Закиев (Навигатор Кампус).
Подробнее о #hsesun: http://sun.inc.hse.ru/
Multi-keyword multi-click advertisement option contracts for sponsored searchBowei Chen
In sponsored search, advertisement (abbreviated ad) slots are usually sold by a search engine to an advertiser through an auction mechanism in which advertisers bid on keywords. In theory, auction mechanisms have many desirable economic properties. However, keyword auctions have a number of limitations including: the uncertainty in payment prices for advertisers; the volatility in the search engine’s revenue; and the weak loyalty between advertiser and search engine. In this article, we propose a special ad option that alleviates these problems. In our proposal, an advertiser can purchase an option from a search engine in advance by paying an upfront fee, known as the option price. The advertiser then has the right, but no obligation, to purchase among the prespecified set of keywords at the fixed cost-per-clicks (CPCs) for a specified number of clicks in a specified period of time. The proposed option is closely related to a special exotic option in finance that contains multiple underlying assets (multi-keyword) and is also multi-exercisable (multi-click). This novel structure has many benefits: advertisers can have reduced uncertainty in advertising; the search engine can improve the advertisers’ loyalty as well as obtain a stable and increased expected revenue over time. Since the proposed ad option can be implemented in conjunction with the existing keyword auctions, the option price and corresponding fixed CPCs must be set such that there is no arbitrage between the two markets. Option pricing methods are discussed and our experimental results validate the development. Compared to keyword auctions, a search engine can have an increased expected revenue by selling an ad option.
Pricing average price advertising options when underlying spot market prices ...Bowei Chen
Advertising options have been recently studied as a special type of guaranteed contracts in online advertising, which are an alternative sales mechanism to real-time auctions. An advertising option is a contract which gives its buyer a right but not obligation to enter into transactions to purchase page views or link clicks at one or multiple pre-specified prices in a specific future period. Different from typical guaranteed contracts, the option buyer pays a lower upfront fee but can have greater flexibility and more control of advertising. Many studies on advertising options so far have been restricted to the situations where the option payoff is determined by the underlying spot market price at a specific time point and the price evolution over time is assumed to be continuous. The former leads to a biased calculation of option payoff and the latter is invalid empirically for many online advertising slots. This paper addresses these two limitations by proposing a new advertising option pricing framework. First, the option payoff is calculated based on an average price over a specific future period. Therefore, the option becomes path-dependent. The average price is measured by the power mean, which contains several existing option payoff functions as its special cases. Second, jump-diffusion stochastic models are used to describe the movement of the underlying spot market price, which incorporate several important statistical properties including jumps and spikes, non-normality, and absence of autocorrelations. A general option pricing algorithm is obtained based on Monte Carlo simulation. In addition, an explicit pricing formula is derived for the case when the option payoff is based on the geometric mean. This pricing formula is also a generalized version of several other option pricing models discussed in related studies.
Investigation of Frequent Batch Auctions using Agent Based ModelTakanobu Mizuta
Recently, the speed of order matching systems on financial exchanges increased due to competition between markets and due to large investor demands. There is an opinion that this increase is good for liquidity by increasing providing liquidity of market maker strategies (MM), on the other hand, there is also the opposite opinion that this speed causes socially wasteful arms race for speed and these costs are passed to other investors as execution costs.
A frequent batch auction (FBA) which reduces the value of speed advantages proposed, however, is also criticized that MM providing liquidity are exposed to more risks, and then they can continue to provide liquidity, then many MM retire, and finally liquidity will be reduced.
In this study we implemented a price mechanism that is changeable between a comparable continuance double auction (CDA) and FBA continuously, and analyzing profits/losses and risks of MM, we investigated whether MM can continue to provide liquidity even on FBA by using an artificial market model.
Our simulation results showed that on FBA execution rates of MM becomes smaller and this causes to reduce liquidity supply by MM. They also suggested that on FBA MM cannot avoid both an overnight risk and a price variation risk intraday, furthermore, it is very difficult that MM is rewarded for risks and continues to provide liquidity. Only on CDA MM is rewarded for risks and continue to provide liquidity.
This suggestion implies that MM that can provide liquidity on CDA cannot continue to provide liquidity on FBA and then many MM retire, finally liquidity will be reduced.
Banque de France's Workshop on Granularity: Basile Grassi's slides, June 2016 Soledad Zignago
Large Firm Dynamics and the Business Cycle, slides by Basile Grassi (University of Oxford & Nuffield College), joint work with Vasco Carvalho (University of Cambridge & CREI, University Pompeu Fabra GSE & CEPR), at the Banque de France and Sciences Po joint workshop on Granularity of Macroeconomics Fluctuations, 24 June 2016. Slides of presentations & discussions are available online: https://www.banque-france.fr/en/economics-statistics/research/seminars-and-symposiums/research-workshop-on-the-granularity-of-macroeconomic-fluctuations-where-do-we-stand.html
"Correlated Volatility Shocks" by Dr. Xiao Qiao, Researcher at SummerHaven In...Quantopian
Commonality in idiosyncratic volatility cannot be completely explained by time-varying volatility. After removing the effects of time-varying volatility, idiosyncratic volatility innovations are still positively correlated. This result suggests correlated volatility shocks contribute to the comovement in idiosyncratic volatility.
Motivated by this fact, we propose the Dynamic Factor Correlation (DFC) model, which fits the data well and captures the cross-sectional correlations in idiosyncratic volatility innovations. We decompose the common factor in idiosyncratic volatility (CIV) of Herskovic et al. (2016) into the volatility innovation factor (VIN) and time-varying volatility factor (TVV). Whereas VIN is associated with strong variation in average returns, TVV is only weakly priced in the cross section
A strategy that takes a long position in the portfolio with the lowest VIN and TVV betas, and a short position in the portfolio with the highest VIN and TVV betas earns average returns of 8.0% per year.
About Myanmar Marionettes Organization (MMOrg)Kyaw Myo Ko
Introduction, Aim and Objectives, The founding of the Myanmar Marionettes Organization (History and Background), Patrons and Executive Committee Members of the Myanmar Marionette Organization (MMOrg)
Safeguarding the Tradition of Myanmar Marionette and Performing ArtsKyaw Myo Ko
This Case Study is a reprint of the August 2016 project report concerning Safeguarding the Tradition of Myanmar marionettes and related performing arts during the period from the 1st of July 2015 through July 2nd, 2016 funded by the Swiss Agency for Development and Cooperation – SDC and implemented by Myanmar Upper Land | culture & travel (MUL)
Pakistan is now slowly realising that its friendship with China which Pakistan claims is higher than mountains and deeper than oceans, the same China has quietly duped Pakistan in the name of providing security and economic prosperity by their project CPEC. The 46 Billion dollar investment by China in China Pak Economic Corridor (CPEC) which will connect Khasgar town of mineral rich restive Xinxiang province of China with Gwador port of Pakistan located on Arabian sea, via rail and road routes passing through POK and Baluchistan province of Pakistan, a total distance of 3000 kms, is not such a big panacea which Pakistan has been tom toming about. This entire project basically benefits China with Pakistan getting some crumbs thrown at it with exorbitant costs.
Как работают редакции Медиапроектов Mail.Ru Group: все, что вы хотели знать, но боялись спросить.
«Редакционные метрики Медиапроектов Mail.Ru Group: как мы оцениваем работу редакции», Сергей Паранько, редакционный директор медиапроектов Mail.Ru Group
«5 секретов хорошего заголовка», Ольга Выходченко, главный редактор Дети Mail.Ru.
«Как писать тексты, которые дочитывают», Надежда Сокирская, главный редактор Леди Mail.Ru.
«Экспертиза: комментарии от серьезных людей, почему они нужны и как добыть», Евгений Паперный, руководитель проектов Здоровье и Дети Mail.Ru.
«Как писать интересно на узкоспециальные темы», Мария Мягкова, главный редактор Недвижимость Mail.Ru.
«Верстка вовлекающих материалов», Михаил Стецовский, руководитель направления Infotainment Медиапроектов Mail.Ru Group.
«Баланс эмоционального и объективного, простые способы привлечь внимание и работа с цифрами», Анна Феоктистова, главный редактор Hi-Tech Mail.Ru.
«Как делать интересные и полезные медицинские новости», Александра Яковлева, главный редактор Здоровье Mail.Ru.
Myanmar has tremendous potential to grow into an important tourist destination in the region, but this would need the active support of the Myanmar tourism department.
IDS Next Business Solutions is a global leader in providing Hotel ERP and technology solutions for the Hospitality and Leisure industries. We have earned the trust of over 4000 customers globally and have a strong presence in 40 plus countries across South East Asia, Oceania, Indian sub-continent, Middle East and Africa.
IDS Next designs, develops, markets and maintains a comprehensive range of information management systems for various hospitality businesses including hotels, restaurants, clubs and resorts.
IDS Next Business Solutions is a global leader in providing Hotel ERP and technology solutions for the Hospitality and Leisure industries. We have earned the trust of over 4000 customers globally and have a strong presence in 40 plus countries across South East Asia, Oceania, Indian sub-continent, Middle East and Africa.
8 июля 2016 года, Летняя школа HSE{sun}.
Доклад "Дорожная карта для hardware стартапа: где и как сделать прототип и опытную партию, а также остаться в живых", Василь Закиев (Навигатор Кампус).
Подробнее о #hsesun: http://sun.inc.hse.ru/
Multi-keyword multi-click advertisement option contracts for sponsored searchBowei Chen
In sponsored search, advertisement (abbreviated ad) slots are usually sold by a search engine to an advertiser through an auction mechanism in which advertisers bid on keywords. In theory, auction mechanisms have many desirable economic properties. However, keyword auctions have a number of limitations including: the uncertainty in payment prices for advertisers; the volatility in the search engine’s revenue; and the weak loyalty between advertiser and search engine. In this article, we propose a special ad option that alleviates these problems. In our proposal, an advertiser can purchase an option from a search engine in advance by paying an upfront fee, known as the option price. The advertiser then has the right, but no obligation, to purchase among the prespecified set of keywords at the fixed cost-per-clicks (CPCs) for a specified number of clicks in a specified period of time. The proposed option is closely related to a special exotic option in finance that contains multiple underlying assets (multi-keyword) and is also multi-exercisable (multi-click). This novel structure has many benefits: advertisers can have reduced uncertainty in advertising; the search engine can improve the advertisers’ loyalty as well as obtain a stable and increased expected revenue over time. Since the proposed ad option can be implemented in conjunction with the existing keyword auctions, the option price and corresponding fixed CPCs must be set such that there is no arbitrage between the two markets. Option pricing methods are discussed and our experimental results validate the development. Compared to keyword auctions, a search engine can have an increased expected revenue by selling an ad option.
Pricing average price advertising options when underlying spot market prices ...Bowei Chen
Advertising options have been recently studied as a special type of guaranteed contracts in online advertising, which are an alternative sales mechanism to real-time auctions. An advertising option is a contract which gives its buyer a right but not obligation to enter into transactions to purchase page views or link clicks at one or multiple pre-specified prices in a specific future period. Different from typical guaranteed contracts, the option buyer pays a lower upfront fee but can have greater flexibility and more control of advertising. Many studies on advertising options so far have been restricted to the situations where the option payoff is determined by the underlying spot market price at a specific time point and the price evolution over time is assumed to be continuous. The former leads to a biased calculation of option payoff and the latter is invalid empirically for many online advertising slots. This paper addresses these two limitations by proposing a new advertising option pricing framework. First, the option payoff is calculated based on an average price over a specific future period. Therefore, the option becomes path-dependent. The average price is measured by the power mean, which contains several existing option payoff functions as its special cases. Second, jump-diffusion stochastic models are used to describe the movement of the underlying spot market price, which incorporate several important statistical properties including jumps and spikes, non-normality, and absence of autocorrelations. A general option pricing algorithm is obtained based on Monte Carlo simulation. In addition, an explicit pricing formula is derived for the case when the option payoff is based on the geometric mean. This pricing formula is also a generalized version of several other option pricing models discussed in related studies.
Investigation of Frequent Batch Auctions using Agent Based ModelTakanobu Mizuta
Recently, the speed of order matching systems on financial exchanges increased due to competition between markets and due to large investor demands. There is an opinion that this increase is good for liquidity by increasing providing liquidity of market maker strategies (MM), on the other hand, there is also the opposite opinion that this speed causes socially wasteful arms race for speed and these costs are passed to other investors as execution costs.
A frequent batch auction (FBA) which reduces the value of speed advantages proposed, however, is also criticized that MM providing liquidity are exposed to more risks, and then they can continue to provide liquidity, then many MM retire, and finally liquidity will be reduced.
In this study we implemented a price mechanism that is changeable between a comparable continuance double auction (CDA) and FBA continuously, and analyzing profits/losses and risks of MM, we investigated whether MM can continue to provide liquidity even on FBA by using an artificial market model.
Our simulation results showed that on FBA execution rates of MM becomes smaller and this causes to reduce liquidity supply by MM. They also suggested that on FBA MM cannot avoid both an overnight risk and a price variation risk intraday, furthermore, it is very difficult that MM is rewarded for risks and continues to provide liquidity. Only on CDA MM is rewarded for risks and continue to provide liquidity.
This suggestion implies that MM that can provide liquidity on CDA cannot continue to provide liquidity on FBA and then many MM retire, finally liquidity will be reduced.
Banque de France's Workshop on Granularity: Basile Grassi's slides, June 2016 Soledad Zignago
Large Firm Dynamics and the Business Cycle, slides by Basile Grassi (University of Oxford & Nuffield College), joint work with Vasco Carvalho (University of Cambridge & CREI, University Pompeu Fabra GSE & CEPR), at the Banque de France and Sciences Po joint workshop on Granularity of Macroeconomics Fluctuations, 24 June 2016. Slides of presentations & discussions are available online: https://www.banque-france.fr/en/economics-statistics/research/seminars-and-symposiums/research-workshop-on-the-granularity-of-macroeconomic-fluctuations-where-do-we-stand.html
"Correlated Volatility Shocks" by Dr. Xiao Qiao, Researcher at SummerHaven In...Quantopian
Commonality in idiosyncratic volatility cannot be completely explained by time-varying volatility. After removing the effects of time-varying volatility, idiosyncratic volatility innovations are still positively correlated. This result suggests correlated volatility shocks contribute to the comovement in idiosyncratic volatility.
Motivated by this fact, we propose the Dynamic Factor Correlation (DFC) model, which fits the data well and captures the cross-sectional correlations in idiosyncratic volatility innovations. We decompose the common factor in idiosyncratic volatility (CIV) of Herskovic et al. (2016) into the volatility innovation factor (VIN) and time-varying volatility factor (TVV). Whereas VIN is associated with strong variation in average returns, TVV is only weakly priced in the cross section
A strategy that takes a long position in the portfolio with the lowest VIN and TVV betas, and a short position in the portfolio with the highest VIN and TVV betas earns average returns of 8.0% per year.
Nonlinear Price Impact and Portfolio Choiceguasoni
In a market with price-impact proportional to a power of the order flow, we derive optimal trading policies and their implied welfare for long-term investors with constant relative risk aversion, who trade one safe asset and one risky asset that follows geometric Brownian motion. These quantities admit asymptotic explicit formulas up to a structural constant that depends only on the price-impact exponent. Trading rates are finite as with linear impact, but they are lower near the target portfolio, and higher away from the target. The model nests the square-root impact law and, as extreme cases, linear impact and proportional transaction costs.
Affine cascade models for term structure dynamics of sovereign yield curvesLAURAMICHAELA
Rafael Serrano profesor de la Universidad del Rosario
Resumen:
In the first part of the talk, I will present an introduction to stochastic affine short rate models for term structure of yield curves In the second part, I will focus on a recursive affine cascade with persistent factors for which the number of parameters, under specifications, is invariant to the size of the state space and converges to a stochastic limit as the number of factors goes to infinity. The cascade construction thereby overcomes dimensionality difficulties associated with general affine models. We contrast two specfifications of the model using linear Kalman filter for a panel of Colombian sovereign yields.
Achieving Consistent Modeling Of VIX and Equities DerivativesVolatility
1) Discuss model complexity and calibration
2) Emphasize intuitive and robust calibration of sophisticated volatility models avoiding non-linear calibrations
3) Present local stochastic volatility models with jumps to achieve joint calibration to VIX options and (short-term) S&P500 options
4) Present two factor stochastic volatility model to fit both the short-term and long-term S&P500 option skews
We provide a comprehensive convergence analysis of the asymptotic preserving implicit-explicit particle-in-cell (IMEX-PIC) methods for the Vlasov–Poisson system with a strong magnetic field. This study is of utmost importance for understanding the behavior of plasmas in magnetic fusion devices such as tokamaks, where such a large magnetic field needs to be applied in order to keep the plasma particles on desired tracks.
Spillover Dynamics for Systemic Risk Measurement Using Spatial Financial Time...SYRTO Project
Spillover Dynamics for Systemic Risk Measurement Using Spatial Financial Time Series Models. Andre Lucas. Amsterdam - June, 25 2015. European Financial Management Association 2015 Annual Meetings.
An Approximate Distribution of Delta-Hedging Errors in a Jump-Diffusion Model...Volatility
1) Analyse the distribution of the profit&loss (P&L) of delta-hedging strategy for vanilla options in Black-Scholes-Merton (BSM) model and an extension of the Merton jump-diffusion (JDM) model assuming discrete trading and transaction costs
2) Examine the connection between the realized variance and the realized P&L
3) Find approximate solutions for the P&L volatility and the expected total transaction costs
4) Apply the mean-variance analysis to find the trade-off between the costs and P&L variance given hedger's risk tolerance
5) Consider hedging strategies to minimize the jump risk
1. Elemental Economics - Introduction to mining.pdfNeal Brewster
After this first you should: Understand the nature of mining; have an awareness of the industry’s boundaries, corporate structure and size; appreciation the complex motivations and objectives of the industries’ various participants; know how mineral reserves are defined and estimated, and how they evolve over time.
how to swap pi coins to foreign currency withdrawable.DOT TECH
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
How to get verified on Coinbase Account?_.docxBuy bitget
t's important to note that buying verified Coinbase accounts is not recommended and may violate Coinbase's terms of service. Instead of searching to "buy verified Coinbase accounts," follow the proper steps to verify your own account to ensure compliance and security.
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
Yes of course, you can easily start mining pi network coin today and sell to legit pi vendors in the United States.
Here the telegram contact of my personal vendor.
@Pi_vendor_247
#pi network #pi coins #legit #passive income
#US
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
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where can I find a legit pi merchant onlineDOT TECH
Yes. This is very easy what you need is a recommendation from someone who has successfully traded pi coins before with a merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi network coins and resell them to Investors looking forward to hold thousands of pi coins before the open mainnet.
I will leave the telegram contact of my personal pi merchant to trade with
@Pi_vendor_247
1. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
The OTC Theory of the Fed Funds Market:
A Primer
Gara Afonso Ricardo Lagos
FRB of New York New York University
2. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
The market for federal funds
A market for loans of reserve balances at the Fed.
3. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
The market for federal funds
What’s traded?
Unsecured loans (mostly overnight)
How are they traded?
Over the counter
Who trades?
Commercial banks, securities dealers, agencies and branches of
foreign banks in the U.S., thrift institutions, federal agencies
4. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
The market for federal funds
5. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Why is the fed funds market interesting?
It is an interesting example of an OTC market
(Unusually good data is available)
Reallocates reserves among banks
(Banks use it to o¤set liquidity shocks and manage reserves)
Determines the interest rate on the shortest maturity
instrument in the term structure
Is the “epicenter” of monetary policy implementation
6. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Why is the fed funds market interesting?
It is an interesting example of an OTC market
(Unusually good data is available)
Reallocates reserves among banks
(Banks use it to o¤set liquidity shocks and manage reserves)
Determines the interest rate on the shortest maturity
instrument in the term structure
Is the “epicenter” of monetary policy implementation
7. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Why is the fed funds market interesting?
It is an interesting example of an OTC market
(Unusually good data is available)
Reallocates reserves among banks
(Banks use it to o¤set liquidity shocks and manage reserves)
Determines the interest rate on the shortest maturity
instrument in the term structure
Is the “epicenter” of monetary policy implementation
8. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Why is the fed funds market interesting?
It is an interesting example of an OTC market
(Unusually good data is available)
Reallocates reserves among banks
(Banks use it to o¤set liquidity shocks and manage reserves)
Determines the interest rate on the shortest maturity
instrument in the term structure
Is the “epicenter” of monetary policy implementation
9. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
In this paper we ...
(1) Propose an OTC model of trade in the fed funds market
(2) Use the theory to address some elementary questions, e.g.,
Positive: How is the fed funds rate determined?
Normative: Is the OTC market structure able to achieve an
e¢ cient reallocation of funds?
10. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
The model
A trading session in continuous time, t 2 [0, T], τ T t
Unit measure of banks hold reserve balances k (τ) 2 f0, 1, 2g
fnk (τ)g : distribution of balances at time T τ
Linear payo¤s from balances, discount at rate r
Uk : payo¤ from holding balance k at the end of the session
Trade opportunities are bilateral and random (Poisson rate α)
Loan and repayment amounts determined by Nash bargaining
Assume all loans repaid at time T + ∆, where ∆ 2 R+
11. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining
12. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
13. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
[0, T]
14. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
[0, T] 4:00pm-6:30pm
15. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
[0, T] 4:00pm-6:30pm
fnk (T)g
16. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
[0, T] 4:00pm-6:30pm
fnk (T)g
Distribution of reserve
balances at 4:00pm
17. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
[0, T] 4:00pm-6:30pm
fnk (T)g
Distribution of reserve
balances at 4:00pm
fUk g
18. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Institutional features of the fed funds market
Model Fed funds market
Search and bargaining Over-the-counter market
[0, T] 4:00pm-6:30pm
fnk (T)g
Distribution of reserve
balances at 4:00pm
fUk g Reserve requirements,
interest on reserves...
20. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Bellman equations
rV1 (τ) + ˙V1 (τ) = 0
rV0 (τ) + ˙V0 (τ) = αn2 (τ) max fV1 (τ) V0 (τ) ¯R (τ) , 0g
rV2 (τ) + ˙V2 (τ) = αn0 (τ) max fV1 (τ) V2 (τ) + ¯R (τ) , 0g
Vk (0) = Uk
¯R (τ) = arg max
R
[V1 (τ) R V0 (τ)]θ
[V1 (τ) + R V2 (τ)]1 θ
= θ [V2 (τ) V1 (τ)] + (1 θ) [V1 (τ) V0 (τ)]
¯R (τ) e r(τ+∆)
R (τ) (PDV of repayment)
21. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Bellman equations
rV1 (τ) + ˙V1 (τ) = 0
rV0 (τ) + ˙V0 (τ) = αn2 (τ) φ (τ) θS (τ)
rV2 (τ) + ˙V2 (τ) = αn0 (τ) φ (τ) (1 θ) S (τ)
where:
S (τ) 2V1 (τ) V0 (τ) V2 (τ)
φ (τ) =
1 if 0 < S (τ)
0 if S (τ) 0
22. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Time-path for the distribution of balances
˙n0 (τ) = αφ (τ) n2 (τ) n0 (τ)
˙n1 (τ) = 2αφ (τ) n2 (τ) n0 (τ)
˙n2 (τ) = αφ (τ) n2 (τ) n0 (τ)
23. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
De…nition
An equilibrium is a value function, V, a path for the distribution of
reserve balances, n (τ), and a path for the distribution of trading
probabilities, φ (τ), such that:
(a) given the value function and the distribution of trading
probabilities, the distribution of balances evolves according to the
law of motion; and
(b) given the path for the distribution of balances, the value
function and the distribution of trading probabilities satisfy
individual optimization given the bargaining protocol.
24. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Analysis
˙S (τ) = δ (τ) S (τ)
δ (τ) fr + αφ (τ) [θn2 (τ) + (1 θ) n0 (τ)]g
)
S (τ) = e
¯δ(τ)
S (0)
¯δ (τ)
Z τ
0
δ (x) dx
S (τ) 2V1 (τ) V0 (τ) V2 (τ)
25. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Analysis
˙S (τ) = δ (τ) S (τ)
δ (τ) fr + αφ (τ) [θn2 (τ) + (1 θ) n0 (τ)]g
)
S (τ) = e
¯δ(τ)
S (0)
¯δ (τ)
Z τ
0
δ (x) dx
S (τ) 2V1 (τ) V0 (τ) V2 (τ)
26. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Assumption: S (0) 2U1 U2 U0 > 0
)
S (τ) = e
¯δ(τ)
S (0) > 0 for all τ
)
φ (τ) = 1 for all τ
27. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Assumption: S (0) 2U1 U2 U0 > 0
)
S (τ) = e
¯δ(τ)
S (0) > 0 for all τ
)
φ (τ) = 1 for all τ
28. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Assumption: S (0) 2U1 U2 U0 > 0
)
S (τ) = e
¯δ(τ)
S (0) > 0 for all τ
)
φ (τ) = 1 for all τ
33. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Proposition
Suppose 2U1 U2 U0 > 0. Then, the equilibrium supports an
e¢ cient allocation of reserve balances.
34. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
rV0 (τ) + ˙V0 (τ) = αn2 (τ) θS (τ)
rλ0 (τ) + ˙λ0 (τ) = αn2 (τ) S (τ)
rV1 (τ) + ˙V1 (τ) = 0
rλ1 (τ) + ˙λ1 (τ) = 0
rV2 (τ) + ˙V2 (τ) = αn0 (τ) (1 θ) S (τ)
rλ2 (τ) + ˙λ2 (τ) = αn0 (τ) S (τ)
S (τ) = e
¯δ(τ)
S (0)
S (τ) = e
¯δ (τ)
S (0)
35. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
rV0 (τ) + ˙V0 (τ) = αn2 (τ) θS (τ)
rλ0 (τ) + ˙λ0 (τ) = αn2 (τ) S (τ)
rV1 (τ) + ˙V1 (τ) = 0
rλ1 (τ) + ˙λ1 (τ) = 0
rV2 (τ) + ˙V2 (τ) = αn0 (τ) (1 θ) S (τ)
rλ2 (τ) + ˙λ2 (τ) = αn0 (τ) S (τ)
S (τ) = e
¯δ(τ)
S (0)
S (τ) = e
¯δ (τ)
S (0)
¯δ (τ) ¯δ (τ) = α
Z τ
0
[(1 θ) n2 (z) + θn0 (z)] dz 0
36. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
rV0 (τ) + ˙V0 (τ) = αn2 (τ) θS (τ)
rλ0 (τ) + ˙λ0 (τ) = αn2 (τ) S (τ)
rV1 (τ) + ˙V1 (τ) = 0
rλ1 (τ) + ˙λ1 (τ) = 0
rV2 (τ) + ˙V2 (τ) = αn0 (τ) (1 θ) S (τ)
rλ2 (τ) + ˙λ2 (τ) = αn0 (τ) S (τ)
S (τ) = e
¯δ(τ)
S (0)
S (τ) = e
¯δ (τ)
S (0)
¯δ (τ) ¯δ (τ) = α
Z τ
0
[(1 θ) n2 (z) + θn0 (z)] dz 0
37. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
rV0 (τ) + ˙V0 (τ) = αn2 (τ) θS (τ)
rλ0 (τ) + ˙λ0 (τ) = αn2 (τ) S (τ)
rV1 (τ) + ˙V1 (τ) = 0
rλ1 (τ) + ˙λ1 (τ) = 0
rV2 (τ) + ˙V2 (τ) = αn0 (τ) (1 θ) S (τ)
rλ2 (τ) + ˙λ2 (τ) = αn0 (τ) S (τ)
S (τ) = e
¯δ(τ)
S (0)
S (τ) = e
¯δ (τ)
S (0)
¯δ (τ) ¯δ (τ) = α
Z τ
0
[(1 θ) n2 (z) + θn0 (z)] dz 0
38. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Equilibrium:
Gain from trade as perceived by borrower: θS (τ)
Gain from trade as perceived by lender: (1 θ) S (τ)
Planner:
Each of their marginal contributions equals S (τ)
δ (τ) δ (τ) for all τ 2 [0, T], with “=” only for τ = 0
) The planner “discounts”more heavily than the equilibrium
) S (τ) < S (τ) for all τ 2 (0, 1]
) Social value of loan < joint private value of loan
39. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Equilibrium:
Gain from trade as perceived by borrower: θS (τ)
Gain from trade as perceived by lender: (1 θ) S (τ)
Planner:
Each of their marginal contributions equals S (τ)
δ (τ) δ (τ) for all τ 2 [0, T], with “=” only for τ = 0
) The planner “discounts”more heavily than the equilibrium
) S (τ) < S (τ) for all τ 2 (0, 1]
) Social value of loan < joint private value of loan
40. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Equilibrium:
Gain from trade as perceived by borrower: θS (τ)
Gain from trade as perceived by lender: (1 θ) S (τ)
Planner:
Each of their marginal contributions equals S (τ)
δ (τ) δ (τ) for all τ 2 [0, T], with “=” only for τ = 0
) The planner “discounts”more heavily than the equilibrium
) S (τ) < S (τ) for all τ 2 (0, 1]
) Social value of loan < joint private value of loan
41. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Equilibrium:
Gain from trade as perceived by borrower: θS (τ)
Gain from trade as perceived by lender: (1 θ) S (τ)
Planner:
Each of their marginal contributions equals S (τ)
δ (τ) δ (τ) for all τ 2 [0, T], with “=” only for τ = 0
) The planner “discounts”more heavily than the equilibrium
) S (τ) < S (τ) for all τ 2 (0, 1]
) Social value of loan < joint private value of loan
42. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Equilibrium:
Gain from trade as perceived by borrower: θS (τ)
Gain from trade as perceived by lender: (1 θ) S (τ)
Planner:
Each of their marginal contributions equals S (τ)
δ (τ) δ (τ) for all τ 2 [0, T], with “=” only for τ = 0
) The planner “discounts”more heavily than the equilibrium
) S (τ) < S (τ) for all τ 2 (0, 1]
) Social value of loan < joint private value of loan
43. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Equilibrium:
Gain from trade as perceived by borrower: θS (τ)
Gain from trade as perceived by lender: (1 θ) S (τ)
Planner:
Each of their marginal contributions equals S (τ)
δ (τ) δ (τ) for all τ 2 [0, T], with “=” only for τ = 0
) The planner “discounts”more heavily than the equilibrium
) S (τ) < S (τ) for all τ 2 (0, 1]
) Social value of loan < joint private value of loan
44. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Planner internalizes that searching borrowers and lenders
make it easier for other lenders and borrowers to …nd partners
These “liquidity provision services” to others receive no
compensation in the equilibrium, so individual agents ignore
them when calculating their equilibrium payo¤s
The equilibrium payo¤ to lenders may be too high or too low
relative to their shadow price in the planner’s problem:
E.g., too high if (1 θ) S (τ) > S (τ)
45. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Planner internalizes that searching borrowers and lenders
make it easier for other lenders and borrowers to …nd partners
These “liquidity provision services” to others receive no
compensation in the equilibrium, so individual agents ignore
them when calculating their equilibrium payo¤s
The equilibrium payo¤ to lenders may be too high or too low
relative to their shadow price in the planner’s problem:
E.g., too high if (1 θ) S (τ) > S (τ)
46. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intuition for e¢ ciency result
Planner internalizes that searching borrowers and lenders
make it easier for other lenders and borrowers to …nd partners
These “liquidity provision services” to others receive no
compensation in the equilibrium, so individual agents ignore
them when calculating their equilibrium payo¤s
The equilibrium payo¤ to lenders may be too high or too low
relative to their shadow price in the planner’s problem:
E.g., too high if (1 θ) S (τ) > S (τ)
47. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Frictionless limit
Proposition
Let Q ∑2
k=0 knk (T) = 1 + n2 (T) n0 (T).
For τ 2 [0, T], as α ! ∞, ρ (τ) ! ρ∞, where
1 + ρ∞
=
8
<
:
er∆
(U1 U0) if Q < 1
er∆
[θ (U2 U1) + (1 θ) (U1 U0)] if Q = 1
er∆
(U2 U1) if 1 < Q.
48. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Positive implications
The theory delivers:
(1) Time-varying trade volume
(2) Time-varying fed fund rate
(3) Intraday convergence of distribution of reserve balances
49. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Trade volume
Flow volume of trade at time T τ:
υ (τ) = αn0 (τ) n2 (τ)
Total volume traded during the trading session:
¯υ =
Z T
0
υ (τ) dτ
50. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Fed funds rate
The gross rate on a loan at time T τ is:
1 + ρ (τ) = er∆
fβ (τ) (U2 U1) + [1 β (τ)] (U1 U0)g
with
β (τ) 2 [0, 1]
The average daily rate is:
¯ρ =
1
T
Z T
0
ρ (τ) dτ
51. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Cross-sectional distribution of reserve balances
Let µ (τ) and σ2
(τ) denote the mean and variance of the
cross-sectional distribution of reserve balances at t = T τ
µ (τ) = 1 + n2 (T) n0 (T) Q
σ2
(τ) = σ2
(T) 2 [2 + n2 (T) n0 (T)] [n0 (T) n0 (τ)]
52. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
U1 = e r∆
(1 + ir
f )
U2 = e r∆
(2 + ir
f + ie
f )
U0 = e r∆
(iw
f ir
f + Pw
)
53. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
U1 = e r∆
(1 + ir
f )
U2 = e r∆
(2 + ir
f + ie
f )
U0 = e r∆
(iw
f ir
f + Pw
)
Proposition
ρ (τ) = β (τ) ie
f + [1 β (τ)] (iw
f + Pw
) where
1 If n2 (T) = n0 (T), β (τ) = θ
2 If n2 (T) < n0 (T), β (τ) 2 [0, θ], β (0) = θ and β0
(τ) < 0
3 If n0 (T) < n2 (T), β (τ) 2 [θ, 1], β (0) = θ and β0
(τ) > 0.
54. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intraday interest rate in a balanced market
55. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intraday interest rate in a market with shortage of reserves
56. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Intraday interest rate in a market with excess reserves
57. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Interest rate and the quantity of reserves
61. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Discount-Window lending rate
16:00 16:30 17:00 17:30 18:00 18:30
0
0.5
1
1.5
2
2.5
x 10
- 5
Surplus
Eastern Time
i
f
w
=0.5%
i
f
w
=0.75%
i
f
w
=1%
16:00 16:30 17:00 17:30 18:00 18:30
1.000006
1.000008
1.00001
1.000012
1.000014
1.000016
1.000018
1.00002
V
2
-V
1
Eastern Time
i
f
w
=0.5%
i
f
w
=0.75%
i
f
w
=1%
16:00 16:30 17:00 17:30 18:00 18:30
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
ρ(%)
Eastern Time
i
f
w
=0.5%
i
f
w
=0.75%
i
f
w
=1%
16:00 16:30 17:00 17:30 18:00 18:30
0
0.5
1
1.5
2
2.5
x 10
- 5
Surplus
Eastern Time
i
f
w
=0.5%
i
f
w
=0.75%
i
f
w
=1%
16:00 16:30 17:00 17:30 18:00 18:30
1.000007
1.0000075
1.000008
1.0000085
1.000009
1.0000095
1.00001
1.0000105
V
2
-V
1
Eastern Time
i
f
w
=0.5%
i
f
w
=0.75%
i
f
w
=1%
16:00 16:30 17:00 17:30 18:00 18:30
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
ρ(%)
Eastern Time
i
f
w
=0.5%
i
f
w
=0.75%
i
f
w
=1%
62. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
More to be done...
Fed funds brokers
Banks’portfolio decisions
Random “payment shocks”
Sequence of trading sessions
Ex-ante heterogeneity (αi , θi
, Ui
k )
Generalized inventories
Quantitative work
63. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
The views expressed here are not necessarily re‡ective of
views at the Federal Reserve Bank of New York
or the Federal Reserve System.
64. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Evidence of OTC frictions in the fed funds market
Price dispersion
Intermediation
Intraday evolution of the distribution of reserve balances
There are banks that are “very long” and buy
There are banks that are “very short” and sell
65. Intro Model Equilibrium E¢ ciency Frictionless Implications Policy Examples Conclusion Appx.
Price dispersion
-.15
-.1
-.05
0
.05
.1
Percent
16:00 16:30 17:00 17:30 18:00 18:30
10th/90th Percentiles 25th/75th Percentiles
Median Mean
Intraday Distribution of Fed Funds Spreads, 2005