<![CDATA[MoneyScience: Research]]>
http://www.moneyscience.com/pg/blog-directory/research?view=rss
FinancialResearchFocushttps://feedburner.google.comhttp://www.moneyscience.com/pg/blog/arXiv/read/839014/uncovering-the-drivers-behind-urban-economic-complexity-and-their-connection-to-urban-economic-performance-arxiv181202842v1-physicssocphSun, 09 Dec 2018 19:56:32 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/yFcCC6orU6U/uncovering-the-drivers-behind-urban-economic-complexity-and-their-connection-to-urban-economic-performance-arxiv181202842v1-physicssocph
<![CDATA[Uncovering the drivers behind urban economic complexity and their connection to urban economic performance. (arXiv:1812.02842v1 [physics.soc-ph])]]>The distribution of employment across industries determines the economic
profiles of cities. But what drives the distribution of employment? We study a
simple model for the probability that an individual in a city is employed in a
given urban activity. The theory posits that three quantities drive this
probability: the activity-specific complexity, individual-specific knowhow, and
the city-specific collective knowhow. We use data on employment across
industries and metropolitan statistical areas in the US, from 1990 to 2016, to
show that these drivers can be measured and have measurable consequences.
First, we analyze the functional form of the probability function proposed by
the theory, and show its superiority when compared to competing alternatives.
Second, we show that individual and collective knowhow correlate with measures
of urban economic performance, suggesting the theory can provide testable
implications for why some cities are more prosperous than others.
]]>839014http://www.moneyscience.com/pg/blog/arXiv/read/839014/uncovering-the-drivers-behind-urban-economic-complexity-and-their-connection-to-urban-economic-performance-arxiv181202842v1-physicssocphhttp://www.moneyscience.com/pg/blog/arXiv/read/839013/optimal-investment-demand-and-arbitrage-under-price-impact-arxiv180409151v2-qfinmf-updatedSun, 09 Dec 2018 19:56:32 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/16qaH9K02Wc/optimal-investment-demand-and-arbitrage-under-price-impact-arxiv180409151v2-qfinmf-updated
<![CDATA[Optimal Investment, Demand and Arbitrage under Price Impact. (arXiv:1804.09151v2 [q-fin.MF] UPDATED)]]>This paper studies the optimal investment problem with random endowment in an
inventory-based price impact model with competitive market makers. Our goal is
to analyze how price impact affects optimal policies, as well as both pricing
rules and demand schedules for contingent claims. For exponential market makers
preferences, we establish two effects due to price impact: constrained trading,
and non-linear hedging costs. To the former, wealth processes in the impact
model are identified with those in a model without impact, but with constrained
trading, where the (random) constraint set is generically neither closed nor
convex. Regarding hedging, non-linear hedging costs motivate the study of
arbitrage free prices for the claim. We provide three such notions, which
coincide in the frictionless case, but which dramatically differ in the
presence of price impact. Additionally, we show arbitrage opportunities, should
they arise from claim prices, can be exploited only for limited position sizes,
and may be ignored if outweighed by hedging considerations. We also show that
arbitrage inducing prices may arise endogenously in equilibrium, and that
equilibrium positions are inversely proportional to the market makers'
representative risk aversion. Therefore, large positions endogenously arise in
the limit of either market maker risk neutrality, or a large number of market
makers.
]]>839013http://www.moneyscience.com/pg/blog/arXiv/read/839013/optimal-investment-demand-and-arbitrage-under-price-impact-arxiv180409151v2-qfinmf-updatedhttp://www.moneyscience.com/pg/blog/arXiv/read/838923/general-compound-hawkes-processes-in-limit-order-books-arxiv181202298v1-qfintrThu, 06 Dec 2018 19:47:07 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/9C4bCAcbP3k/general-compound-hawkes-processes-in-limit-order-books-arxiv181202298v1-qfintr
<![CDATA[General Compound Hawkes Processes in Limit Order Books. (arXiv:1812.02298v1 [q-fin.TR])]]>In this paper, we study various new Hawkes processes. Specifically, we
construct general compound Hawkes processes and investigate their properties in
limit order books. With regards to these general compound Hawkes processes, we
prove a Law of Large Numbers (LLN) and a Functional Central Limit Theorems
(FCLT) for several specific variations. We apply several of these FCLTs to
limit order books to study the link between price volatility and order flow,
where the volatility in mid-price changes is expressed in terms of parameters
describing the arrival rates and mid-price process.
]]>838923http://www.moneyscience.com/pg/blog/arXiv/read/838923/general-compound-hawkes-processes-in-limit-order-books-arxiv181202298v1-qfintrhttp://www.moneyscience.com/pg/blog/arXiv/read/838922/in-stochastic-search-of-a-fairer-alife-arxiv181202311v1-qfingnThu, 06 Dec 2018 19:47:07 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/RXgjQap2q6c/in-stochastic-search-of-a-fairer-alife-arxiv181202311v1-qfingn
<![CDATA[In (Stochastic) Search of a Fairer Alife. (arXiv:1812.02311v1 [q-fin.GN])]]>Economies and societal structures in general are complex stochastic systems
which may not lend themselves well to algebraic analysis. An addition of
subjective value criteria to the mechanics of interacting agents will further
complicate analysis. The purpose of this short study is to demonstrate
capabilities of agent-based computational economics to be a platform for
fairness or equity analysis in both a broad and practical sense.
]]>838922http://www.moneyscience.com/pg/blog/arXiv/read/838922/in-stochastic-search-of-a-fairer-alife-arxiv181202311v1-qfingnhttp://www.moneyscience.com/pg/blog/arXiv/read/838921/continuous-learning-augmented-investment-decisions-arxiv181202340v1-cslgThu, 06 Dec 2018 19:47:07 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/HBiBOcVs5a0/continuous-learning-augmented-investment-decisions-arxiv181202340v1-cslg
<![CDATA[Continuous Learning Augmented Investment Decisions. (arXiv:1812.02340v1 [cs.LG])]]>Investment decisions can benefit from incorporating an accumulated knowledge
of the past to drive future decision making. We introduce Continuous Learning
Augmentation (CLA) which is based on an explicit memory structure and a feed
forward neural network (FFNN) base model and used to drive long term financial
investment decisions. We demonstrate that our approach improves accuracy in
investment decision making while memory is addressed in an explainable way. Our
approach introduces novel remember cues, consisting of empirically learned
change points in the absolute error series of the FFNN. Memory recall is also
novel, with contextual similarity assessed over time by sampling distances
using dynamic time warping (DTW). We demonstrate the benefits of our approach
by using it in an expected return forecasting task to drive investment
decisions. In an investment simulation in a broad international equity universe
between 2003-2017, our approach significantly outperforms FFNN base models. We
also illustrate how CLA's memory addressing works in practice, using a worked
example to demonstrate the explainability of our approach.
]]>838921http://www.moneyscience.com/pg/blog/arXiv/read/838921/continuous-learning-augmented-investment-decisions-arxiv181202340v1-cslghttp://www.moneyscience.com/pg/blog/arXiv/read/838920/quantification-of-market-efficiency-based-on-informationalentropy-arxiv181202371v1-qfingnThu, 06 Dec 2018 19:47:07 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/qnhlq8LO2Wc/quantification-of-market-efficiency-based-on-informationalentropy-arxiv181202371v1-qfingn
<![CDATA[Quantification of market efficiency based on informational-entropy. (arXiv:1812.02371v1 [q-fin.GN])]]>Since the 1960s, the question whether markets are efficient or not is
controversially discussed. One reason for the difficulty to overcome the
controversy is the lack of a universal, but also precise, quantitative
definition of efficiency that is able to graduate between different states of
efficiency. The main purpose of this article is to fill this gap by developing
a measure for the efficiency of markets that fulfill all the stated
requirements. It is shown that the new definition of efficiency, based on
informational-entropy, is equivalent to the two most used definitions of
efficiency from Fama and Jensen. The new measure therefore enables steps to
settle the dispute over the state of efficiency in markets. Moreover, it is
shown that inefficiency in a market can either arise from the possibility to
use information to predict an event with higher than chance level, or can
emerge from wrong pricing/ quotes that do not reflect the right probabilities
of possible events. Finally, the calculation of efficiency is demonstrated on a
simple game (of coin tossing), to show how one could exactly quantify the
efficiency in any market-like system, if all probabilities are known.
]]>838920http://www.moneyscience.com/pg/blog/arXiv/read/838920/quantification-of-market-efficiency-based-on-informationalentropy-arxiv181202371v1-qfingnhttp://www.moneyscience.com/pg/blog/arXiv/read/838919/using-published-bidask-curves-to-error-dress-spot-electricity-price-forecasts-arxiv181202433v1-qfinstThu, 06 Dec 2018 19:47:06 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/HwQS0VdMRls/using-published-bidask-curves-to-error-dress-spot-electricity-price-forecasts-arxiv181202433v1-qfinst
<![CDATA[Using published bid/ask curves to error dress spot electricity price forecasts. (arXiv:1812.02433v1 [q-fin.ST])]]>Accurate forecasts of electricity spot prices are essential to the daily
operational and planning decisions made by power producers and distributors.
Typically, point forecasts of these quantities suffice, particularly in the
Nord Pool market where the large quantity of hydro power leads to price
stability. However, when situations become irregular, deviations on the price
scale can often be extreme and difficult to pinpoint precisely, which is a
result of the highly varying marginal costs of generating facilities at the
edges of the load curve. In these situations it is useful to supplant a point
forecast of price with a distributional forecast, in particular one whose tails
are adaptive to the current production regime. This work outlines a methodology
for leveraging published bid/ask information from the Nord Pool market to
construct such adaptive predictive distributions. Our methodology is a
non-standard application of the concept of error-dressing, which couples a
feature driven error distribution in volume space with a non-linear
transformation via the published bid/ask curves to obtain highly non-symmetric,
adaptive price distributions. Using data from the Nord Pool market, we show
that our method outperforms more standard forms of distributional modeling. We
further show how such distributions can be used to render `warning systems'
that issue reliable probabilities of prices exceeding various important
thresholds.
]]>838919http://www.moneyscience.com/pg/blog/arXiv/read/838919/using-published-bidask-curves-to-error-dress-spot-electricity-price-forecasts-arxiv181202433v1-qfinsthttp://www.moneyscience.com/pg/blog/arXiv/read/838918/evaluating-the-building-blocks-of-a-dynamically-adaptive-systematic-trading-strategy-arxiv181202527v1-qfinstThu, 06 Dec 2018 19:47:06 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/YVSyZOsoZ_4/evaluating-the-building-blocks-of-a-dynamically-adaptive-systematic-trading-strategy-arxiv181202527v1-qfinst
<![CDATA[Evaluating the Building Blocks of a Dynamically Adaptive Systematic Trading Strategy. (arXiv:1812.02527v1 [q-fin.ST])]]>Financial markets change their behaviours abruptly. The mean, variance and
correlation patterns of stocks can vary dramatically, triggered by fundamental
changes in macroeconomic variables, policies or regulations. A trader needs to
adapt her trading style to make the best out of the different phases in the
stock markets. Similarly, an investor might want to invest in different asset
classes in different market regimes for a stable risk adjusted return profile.
Here, we explore the use of State Switching Markov Autoregressive models for
identifying and predicting different market regimes loosely modeled on the
Wyckoff Price Regimes of accumulation, distribution, advance and decline. We
explore the behaviour of various asset classes and market sectors in the
identified regimes. We look at the trading strategies like trend following,
range trading, retracement trading and breakout trading in the given market
regimes and tailor them for the specific regimes. We tie together the best
trading strategy and asset allocation for the identified market regimes to come
up with a robust dynamically adaptive trading system to outperform simple
traditional alphas.
]]>838918http://www.moneyscience.com/pg/blog/arXiv/read/838918/evaluating-the-building-blocks-of-a-dynamically-adaptive-systematic-trading-strategy-arxiv181202527v1-qfinsthttp://www.moneyscience.com/pg/blog/arXiv/read/838917/simulation-of-stylized-facts-in-agentbased-computational-economic-market-models-arxiv181202726v1-econgnThu, 06 Dec 2018 19:47:00 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/gTCZNYKfwrk/simulation-of-stylized-facts-in-agentbased-computational-economic-market-models-arxiv181202726v1-econgn
<![CDATA[Simulation of Stylized Facts in Agent-Based Computational Economic Market Models. (arXiv:1812.02726v1 [econ.GN])]]>We study the qualitative and quantitative appearance of stylized facts in
several agent-based computational economic market (ABCEM) models. We perform
our simulations with the SABCEMM (Simulator for Agent-Based Computational
Economic Market Models) tool recently introduced by the authors (Trimborn et
al. 2018a). The SABCEMM simulator is implemented in C++ and is well suited for
large scale computations. Thanks to its object-oriented software design, the
SABCEMM tool enables the creation of new models by plugging together novel and
existing agent and market designs as easily as plugging together pieces of a
puzzle. We present new ABCEM models created by recombining existing models and
study them with respect to stylized facts as well. The code is available on
GitHub (Trimborn et al. 2018b), such that all results can be reproduced by the
reader.
]]>838917http://www.moneyscience.com/pg/blog/arXiv/read/838917/simulation-of-stylized-facts-in-agentbased-computational-economic-market-models-arxiv181202726v1-econgnhttp://www.moneyscience.com/pg/blog/arXiv/read/838842/on-dynamics-of-wageprice-spiral-and-stagflation-in-some-model-economic-systems-arxiv181201707v1-qfingnWed, 05 Dec 2018 19:58:55 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/KrcCr5LvOq4/on-dynamics-of-wageprice-spiral-and-stagflation-in-some-model-economic-systems-arxiv181201707v1-qfingn
<![CDATA[On dynamics of wage-price spiral and stagflation in some model economic systems. (arXiv:1812.01707v1 [q-fin.GN])]]>This article aims to present an elementary analytical solution to the
question of the formation of a structure of differentiation of rates of return
in a classical gravitation model and in a model of the dynamics of price-wage
spirals.
]]>838842http://www.moneyscience.com/pg/blog/arXiv/read/838842/on-dynamics-of-wageprice-spiral-and-stagflation-in-some-model-economic-systems-arxiv181201707v1-qfingnhttp://www.moneyscience.com/pg/blog/arXiv/read/838841/the-alphaheston-stochastic-volatility-model-arxiv181201914v1-qfinmfWed, 05 Dec 2018 19:58:55 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/E8Cu5wnGhNU/the-alphaheston-stochastic-volatility-model-arxiv181201914v1-qfinmf
<![CDATA[The Alpha-Heston Stochastic Volatility Model. (arXiv:1812.01914v1 [q-fin.MF])]]>We introduce an affine extension of the Heston model where the instantaneous
variance process contains a jump part driven by $\alpha$-stable processes with
$\alpha\in(1,2]$. In this framework, we examine the implied volatility and its
asymptotic behaviors for both asset and variance options. Furthermore, we
examine the jump clustering phenomenon observed on the variance market and
provide a jump cluster decomposition which allows to analyse the cluster
processes.
]]>838841http://www.moneyscience.com/pg/blog/arXiv/read/838841/the-alphaheston-stochastic-volatility-model-arxiv181201914v1-qfinmfhttp://www.moneyscience.com/pg/blog/arXiv/read/838786/machine-learning-for-yield-curve-feature-extraction-application-to-illiquid-corporate-bonds-arxiv181201102v1-qfinstTue, 04 Dec 2018 19:48:56 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/1DTGvmNr3ac/machine-learning-for-yield-curve-feature-extraction-application-to-illiquid-corporate-bonds-arxiv181201102v1-qfinst
<![CDATA[Machine Learning for Yield Curve Feature Extraction: Application to Illiquid Corporate Bonds. (arXiv:1812.01102v1 [q-fin.ST])]]>This paper studies an application of machine learning in extracting features
from the historical market implied corporate bond yields. We consider an
example of a hypothetical illiquid fixed income market. After choosing a
surrogate liquid market, we apply the Denoising Autoencoder (DAE) algorithm to
learn the features of the missing yield parameters from the historical data of
the instruments traded in the chosen liquid market. The DAE algorithm is then
challenged by two "point-in-time" inpainting algorithms taken from the image
processing and computer vision domain. It is observed that, when tested on
unobserved rate surfaces, the DAE algorithm exhibits superior performance
thanks to the features it has learned from the historical shapes of yield
curves.
]]>838786http://www.moneyscience.com/pg/blog/arXiv/read/838786/machine-learning-for-yield-curve-feature-extraction-application-to-illiquid-corporate-bonds-arxiv181201102v1-qfinsthttp://www.moneyscience.com/pg/blog/arXiv/read/838785/predicting-future-stock-market-structure-by-combining-social-and-financial-network-information-arxiv181201103v1-qfinstTue, 04 Dec 2018 19:48:51 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/mHIR5MZDehc/predicting-future-stock-market-structure-by-combining-social-and-financial-network-information-arxiv181201103v1-qfinst
<![CDATA[Predicting future stock market structure by combining social and financial network information. (arXiv:1812.01103v1 [q-fin.ST])]]>We demonstrate that future market correlation structure can be predicted with
high out-of-sample accuracy using a multiplex network approach that combines
information from social media and financial data. Market structure is measured
by quantifying the co-movement of asset prices returns, while social structure
is measured as the co-movement of social media opinion on those same assets.
Predictions are obtained with a simple model that uses link persistence and
link formation by triadic closure across both financial and social media
layers. Results demonstrate that the proposed model can predict future market
structure with up to a 40\% out-of-sample performance improvement compared to a
benchmark model that assumes a time-invariant financial correlation structure.
Social media information leads to improved models for all settings tested,
particularly in the long-term prediction of financial market structure.
Surprisingly, financial market structure exhibited higher predictability than
social opinion structure.
]]>838785http://www.moneyscience.com/pg/blog/arXiv/read/838785/predicting-future-stock-market-structure-by-combining-social-and-financial-network-information-arxiv181201103v1-qfinsthttp://www.moneyscience.com/pg/blog/arXiv/read/838784/an-optimal-extraction-problem-with-price-impact-arxiv181201270v1-mathocTue, 04 Dec 2018 19:48:46 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/aabLAYakm8M/an-optimal-extraction-problem-with-price-impact-arxiv181201270v1-mathoc
<![CDATA[An Optimal Extraction Problem with Price Impact. (arXiv:1812.01270v1 [math.OC])]]>A price-maker company extracts an exhaustible commodity from a reservoir, and
sells it instantaneously in the spot market. In absence of any actions of the
company, the commodity's spot price evolves either as a drifted Brownian motion
or as an Ornstein-Uhlenbeck process. While extracting, the company affects the
market price of the commodity, and its actions have an impact on the dynamics
of the commodity's spot price. The company aims at maximizing the total
expected profits from selling the commodity, net of the total expected
proportional costs of extraction. We model this problem as a two-dimensional
degenerate singular stochastic control problem with finite fuel. To determine
its solution, we construct an explicit solution to the associated
Hamilton-Jacobi-Bellman equation, and then verify its actual optimality through
a verification theorem. On the one hand, when the (uncontrolled) price is a
drifted Brownian motion, it is optimal to extract whenever the current price
level is larger or equal than an endogenously determined constant threshold. On
the other hand, when the (uncontrolled) price evolves as an Ornstein-Uhlenbeck
process, we show that the optimal extraction rule is triggered by a curve
depending on the current level of the reservoir. Such a curve is a strictly
decreasing $C^{\infty}$-function for which we are able to provide an explicit
expression. Finally, our study is complemented by a theoretical and numerical
analysis of the dependency of the optimal extraction strategy and value
function on the model's parameters.
]]>838784http://www.moneyscience.com/pg/blog/arXiv/read/838784/an-optimal-extraction-problem-with-price-impact-arxiv181201270v1-mathochttp://www.moneyscience.com/pg/blog/arXiv/read/838783/modelling-chinas-credit-system-with-complex-network-theory-for-systematic-credit-risk-control-arxiv181201341v1-qfinrmTue, 04 Dec 2018 19:48:44 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/T9jxE6gAcsM/modelling-chinas-credit-system-with-complex-network-theory-for-systematic-credit-risk-control-arxiv181201341v1-qfinrm
<![CDATA[Modelling China's Credit System with Complex Network Theory for Systematic Credit Risk Control. (arXiv:1812.01341v1 [q-fin.RM])]]>The insufficient understanding of the credit network structure was recognized
as a key factor for regulators' underestimation of the destructive systematic
risk during the financial crisis that started in 2007. The existing credit
network research either took a macro perspective to clarify the topological
properties of financial systems at a descriptive level or analyzed the risk
transmission path and characteristics of individual entities with much
pre-assumptions of the network. Here, we used the theory of complex network to
model China's credit system from 2000 to 2014 based on actual financial data. A
bipartite financial institution-firm network and its projected sub-networks
were constructed for an integrated analysis from both macro and micro
perspectives, and the relationship between typological properties and
systematic credit risk control was also explored. The typological analysis of
the networks suggested that the financial institutions and firms were highly
but asymmetrically connected, and the credit network structure made local
idiosyncratic shocks possible to proliferate through the whole economy. In
addition, the Chinese credit market was still dominated by state-owned
financial institutions with firms competing fiercely for financial resources in
the past fifteen years. Furthermore, the credit risk score (CRS) was introduced
by simulation to identify the systematically important vertices in terms of
systematic risk control. The results indicated that the vertices with more
access to the credit market or less likelihood to be a bridge in the network
were the ones with higher systematically importance. The empirical results from
this study would provide specific policy suggestions to financial regulators on
supervisory approaches and optimizing the allocation of regulatory resources to
enhance the robustness of credit systems in China and in other countries.
]]>838783http://www.moneyscience.com/pg/blog/arXiv/read/838783/modelling-chinas-credit-system-with-complex-network-theory-for-systematic-credit-risk-control-arxiv181201341v1-qfinrmhttp://www.moneyscience.com/pg/blog/arXiv/read/838704/optimal-transport-on-the-probability-simplex-with-logarithmic-cost-arxiv181200032v1-mathocMon, 03 Dec 2018 20:17:10 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/g9qgCD7puMs/optimal-transport-on-the-probability-simplex-with-logarithmic-cost-arxiv181200032v1-mathoc
<![CDATA[Optimal Transport on the Probability Simplex with Logarithmic Cost. (arXiv:1812.00032v1 [math.OC])]]>Motivated by the financial problem of building financial portfolios which
outperform the market, Pal and Wong considered optimal transport on the
probability simplex $\triangle^n$ where the cost function is induced by the
free energy. We study the regularity of this problem and find that the
associated $MTW$ tensor is non-negative definite and in fact constant on
$\triangle^n \times \triangle^n$. We further find that relative $c$-convexity
corresponds to the standard notion of convexity in the probability simplex.
Hence, we are able to use standard results in optimal transport to establish
regularity for the optimal transport maps considered by Pal and Wong. We also
provide several new examples of costs satisfying the $MTW(0)$ condition.
]]>838704http://www.moneyscience.com/pg/blog/arXiv/read/838704/optimal-transport-on-the-probability-simplex-with-logarithmic-cost-arxiv181200032v1-mathochttp://www.moneyscience.com/pg/blog/arXiv/read/838703/using-column-generation-to-solve-extensions-to-the-markowitz-model-arxiv181200093v1-mathocMon, 03 Dec 2018 20:17:10 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/LCVzKd_TL3k/using-column-generation-to-solve-extensions-to-the-markowitz-model-arxiv181200093v1-mathoc
<![CDATA[Using Column Generation to Solve Extensions to the Markowitz Model. (arXiv:1812.00093v1 [math.OC])]]>We introduce a solution scheme for portfolio optimization problems with
cardinality constraints. Typical portfolio optimization problems are extensions
of the classical Markowitz mean-variance portfolio optimization model. We solve
such type of problems using a scheme similar to column generation. In this
scheme, the original problem is restricted to a subset of the assets resulting
in a master convex quadratic problem. Then the dual information of the master
problem is used in a sub-problem to propose more assets to consider. We also
consider other extensions to the Markowitz model to diversify the portfolio
selection within the given intervals for the active weights.
]]>838703http://www.moneyscience.com/pg/blog/arXiv/read/838703/using-column-generation-to-solve-extensions-to-the-markowitz-model-arxiv181200093v1-mathochttp://www.moneyscience.com/pg/blog/arXiv/read/838702/ordeal-mechanisms-information-and-the-costeffectiveness-of-subsidies-evidence-from-subsidized-eyeglasses-in-rural-china-arxiv181200383v1-econgnMon, 03 Dec 2018 20:17:10 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/TyWF2kiW4Sw/ordeal-mechanisms-information-and-the-costeffectiveness-of-subsidies-evidence-from-subsidized-eyeglasses-in-rural-china-arxiv181200383v1-econgn
<![CDATA[Ordeal Mechanisms, Information, and the Cost-Effectiveness of Subsidies: Evidence from Subsidized Eyeglasses in Rural China. (arXiv:1812.00383v1 [econ.GN])]]>The cost-effectiveness of policies providing subsidized goods is often
compromised by limited use of the goods provided. Through a randomized trial,
we test two approaches to improve the cost-effectiveness of a program
distributing free eyeglasses to myopic children in rural China. Requiring
recipients to undergo an ordeal better targeted eyeglasses to those who used
them without reducing usage relative to free delivery. An information campaign
increased use when eyeglasses were freely delivered but not under an ordeal.
Free delivery plus information was determined to be the most socially
cost-effective approach and obtained the highest rate of eyeglass use.
]]>838702http://www.moneyscience.com/pg/blog/arXiv/read/838702/ordeal-mechanisms-information-and-the-costeffectiveness-of-subsidies-evidence-from-subsidized-eyeglasses-in-rural-china-arxiv181200383v1-econgnhttp://www.moneyscience.com/pg/blog/arXiv/read/838701/optimal-resource-allocation-over-networks-via-lotterybased-mechanisms-arxiv181200501v1-econthMon, 03 Dec 2018 20:17:09 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/EOHDnBdf4zs/optimal-resource-allocation-over-networks-via-lotterybased-mechanisms-arxiv181200501v1-econth
<![CDATA[Optimal Resource Allocation over Networks via Lottery-Based Mechanisms. (arXiv:1812.00501v1 [econ.TH])]]>We show that, in a resource allocation problem, the ex ante aggregate utility
of players with cumulative-prospect-theoretic preferences can be increased over
deterministic allocations by implementing lotteries. We formulate an
optimization problem, called the system problem, to find the optimal lottery
allocation. The system problem exhibits a two-layer structure comprised of a
permutation profile and optimal allocations given the permutation profile. For
any fixed permutation profile, we provide a market-based mechanism to find the
optimal allocations and prove the existence of equilibrium prices. We show that
the system problem has a duality gap, in general, and that the primal problem
is NP-hard. We then consider a relaxation of the system problem and derive some
qualitative features of the optimal lottery structure.
]]>838701http://www.moneyscience.com/pg/blog/arXiv/read/838701/optimal-resource-allocation-over-networks-via-lotterybased-mechanisms-arxiv181200501v1-econthhttp://www.moneyscience.com/pg/blog/arXiv/read/838700/limits-to-arbitrage-in-markets-with-stochastic-settlement-latency-arxiv181200595v1-qfintrMon, 03 Dec 2018 20:17:09 -0600
http://feedproxy.google.com/~r/FinancialResearchFocus/~3/EVYvDdM_Bj4/limits-to-arbitrage-in-markets-with-stochastic-settlement-latency-arxiv181200595v1-qfintr
<![CDATA[Limits to Arbitrage in Markets with Stochastic Settlement Latency. (arXiv:1812.00595v1 [q-fin.TR])]]>Distributed ledger technologies rely on consensus protocols confronting
traders with random waiting times until the transfer of ownership is
accomplished. This time-consuming settlement process exposes arbitrageurs to
price risk and imposes limits to arbitrage. We derive theoretical arbitrage
boundaries under general assumptions and show that they increase with expected
latency, latency uncertainty, spot volatility, and risk aversion. Using
high-frequency data from the Bitcoin network, we estimate arbitrage boundaries
due to settlement latency of on average 124 basis points, covering 88 percent
of the observed cross-exchange price differences. Settlement through
decentralized systems thus induces non-trivial frictions affecting market
efficiency and price formation.
]]>838700http://www.moneyscience.com/pg/blog/arXiv/read/838700/limits-to-arbitrage-in-markets-with-stochastic-settlement-latency-arxiv181200595v1-qfintr