Empirically observed intertemporal choices about money have long been thought to exhibit present bias, i.e. higher short-term compared to long-term discount rates. Recently, this view has been called into question on both empirical and theoretical grounds, and a spate of recent findings suggest that present bias for money is minimal or non-existent when one allows for curvature in the utility function and transaction costs are tightly controlled. However, an alternative interpretation of many of these findings is that, in the interest of equalizing transaction costs across earlier and later payments, small delays were introduced between the time of the experiment and the soonest payment. We conduct a laboratory experiment in Kenya in which we elicit time and risk preference parameters from 494 participants, using convex time budgets and tightly controlling for transaction costs. We vary whether same-day payments are made immediately after the experimental session or at the close of the business day. Using the Kenyan mobile money system M-Pesa to make real-time transfers to subjects' phones allows us to make the soonest payments truly immediate. We find strong evidence of present bias, with estimates of the present bias parameter ranging from 0.902 to 0.924 -- but only when same-day payments are made immediately after the experiment. This result suggests that present bias for money does in fact exist, but only for truly immediate payments.
How Soon Is Now? Evidence of Present Bias from Convex Time Budget Experiments -- by Uttara Balakrishnan, Johannes Haushofer, Pamela Jakiela
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Investing in the Presence of Massive Flows: The Case of MSCI Country Reclassifications -- by Terence C. Burnham, Harry Gakidis, Jeffrey Wurgler
Almost $10 trillion is benchmarked to Morgan Stanley Capital International's Developed, Emerging, Frontier, and standalone market indexes. Reclassifications from one index to another require thousands of investors to decide how to react. We study a comprehensive sample of past reclassifications to inform this decision. On average, reclassified markets' prices substantially overshoot between the announcement and effective dates--prices fall when a market moves from an index with more benchmarked ownership to one with less, such from Emerging to Frontier, and vice-versa--but largely revert within a year. We identify alpha-maximizing responses to reclassifications for both benchmarked and more flexible investors.
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Segmented money markets and covered interest parity arbitrage
This paper studies the violation of the most basic no-arbitrage condition in international finance - Covered Interest Parity (CIP). To understand the CIP conundrum, it is key to (i) account for funding frictions in U.S. dollar money markets, and (ii) to study the challenges of swap intermediaries when funding liquidity evolves differently across major currency areas. We find that CIP holds ...
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July 10, 2017 - TMI Trust Company Chooses SS&C Precision LM™ to Support Growth and Innovation in Corporate Loan Agency
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Weekly Top 5 Papers – July 10th 2017
1. Why Not Taxation and Representation? A Note on the American Revolution by Sebastian Galiani (University of Maryland – Department of Economics) and Gustavo Torrens (Indiana University)
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Preparing for FRTB – what you need to know
As the deadline to Fundamental Review of the Trading Book (FRTB) approaches, banks must be ready to prove regulatory compliance. Numerix, an industry leader in derivatives technology, has developed an FRTB solution using Microsoft Cloud technology. We sat down with Numerixâs Chief Strategy Officer, Satyam Kancharla, to get a sense of what banks are doing to prepare for the 2020 FRTB deadline, and what still needs to be done.
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The Wealth of Nations: Complexity Science for an Interdisciplinary Approach in Economics. (arXiv:1707.02853v1 [q-fin.GN])
Classic economic science is reaching the limits of its explanatory powers. Complexity science uses an increasingly larger set of different methods to analyze physical, biological, cultural, social, and economic factors, providing a broader understanding of the socio-economic dynamics involved in the development of nations worldwide. The use of tools developed in the natural sciences, such as thermodynamics, evolutionary biology, and analysis of complex systems, help us to integrate aspects, formerly reserved to the social sciences, with the natural sciences. This integration reveals details of the synergistic mechanisms that drive the evolution of societies. By doing so, we increase the available alternatives for economic analysis and provide ways to increase the efficiency of decision-making mechanisms in complex social contexts. This interdisciplinary analysis seeks to deepen our understanding of why chronic poverty is still common, and how the emergence of prosperous technological societies can be made possible. This understanding should increase the chances of achieving a sustainable, harmonious and prosperous future for humanity. The analysis evidences that complex fundamental economic problems require multidisciplinary approaches and rigorous application of the scientific method if we want to advance significantly our understanding of them. The analysis reveals viable routes for the generation of wealth and the reduction of poverty, but also reveals huge gaps in our knowledge about the dynamics of our societies and about the means to guide social development towards a better future for all.
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Residual Value Forecasting Using Asymmetric Cost Functions. (arXiv:1707.02736v1 [stat.ML])
Leasing is a popular channel to market new cars. Pricing a leasing contract is complicated because the leasing rate embodies an expectation of the residual value of the car after contract expiration. To aid lessors in their pricing decisions, the paper develops resale price forecasting models. A peculiarity of the leasing business is that forecast errors entail different costs. Identifying effective ways to address this characteristic is the main objective of the paper. More specifically, the paper contributes to the literature through i) consolidating and integrating previous work in forecasting with asymmetric cost of error functions, ii) systematically evaluating previous approaches and comparing them to a new approach, and iii) demonstrating that forecasting with asymmetric cost of error functions enhances the quality of decision support in car leasing. For example, under the assumption that the costs of overestimating resale prices is twice that of the opposite error, incorporating corresponding cost asymmetry into forecast model development reduces decision costs by about eight percent, compared to a standard forecasting model. Higher asymmetry produces even larger improvements.
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Dynamic Quantile Function Models. (arXiv:1707.02587v1 [stat.ME])
We offer a novel way of thinking about the modelling of the time-varying distributions of financial asset returns. Borrowing ideas from symbolic data analysis, we consider data representations beyond scalars and vectors. Specifically, we consider a quantile function as an observation, and develop a new class of dynamic models for quantile-function-valued (QF-valued) time series. In order to make statistical inferences and account for parameter uncertainty, we propose a method whereby a likelihood function can be constructed for QF-valued data, and develop an adaptive MCMC sampling algorithm for simulating from the posterior distribution. Compared to modelling realised measures, modelling the entire quantile functions of intra-daily returns allows one to gain more insight into the dynamic structure of price movements. Via simulations, we show that the proposed MCMC algorithm is effective in recovering the posterior distribution, and that the posterior means are reasonable point estimates of the model parameters. For empirical studies, the new model is applied to analysing one-minute returns of major international stock indices. Through quantile scaling, we further demonstrate the usefulness of our method by forecasting one-step-ahead the Value-at-Risk of daily returns.
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Consistency of extended Nelson-Siegel curve families with the Ho-Lee and Hull and White short rate models. (arXiv:1707.02496v1 [q-fin.MF])
Nelson and Siegel curves are widely used to fit the observed term structure of interest rates in a particular date. By the other hand, several interest rate models have been developed such their initial forward rate curve can be adjusted to any observed data, as the Ho-Lee and the Hull and White one factor models. In this work we study the evolution of the forward curve process for each of this models assuming that the initial curve is of Nelson-Siegel type. We conclude that the forward curve process produces curves belonging to a parametric family of curves that can be seen as extended Nelson and Siegel curves.
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The LIVING Supply Chain: The Evolving Imperative of Operating in Real Time
Creates a managerial compass for entering into the LIVING (Live, Intelligent, Velocity, Interactive, Networked, and Good) era of supply chain management and defines the imperative for creating Velocity and Visibility as the focal point for exploiting new digital, mobile, and cloud-based technologies
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Viability and Arbitrage under Knightian Uncertainty. (arXiv:1707.03335v1 [q-fin.EC])
We reconsider the microeconomic foundations of financial economics under Knightian Uncertainty. In a general framework, we discuss the absence of arbitrage, its relation to economic viability, and the existence of suitable nonlinear pricing expectations. Classical financial markets under risk and no ambiguity are contained as special cases, including various forms of the Efficient Market Hypothesis. For Knightian uncertainty, our approach unifies recent versions of the Fundamental Theorem of Asset Pricing under a common framework.
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The discontinuation of the EUR/CHF minimum exchange rate in January 2015: was it expected?
We derive risk-neutral probability densities for future euro/Swiss franc exchange rates as implied by option prices. We find that the credibility of the Swiss franc floor somewhat decreased as the spot exchange rate approached the lower bound of 1.20 CHF per euro. We also compare the forecasting performance of a random walk benchmark model with ...
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Perceived Versus Real Risk Tolerance
Picture Credit: Denise Krebs || What RFK said is not applicable to investing. Â Safety First! Â Don’t lose money!
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It’s not you – solving a Rubik’s cube quickly is officially hard
The question of whether a scrambled Rubikâs cube of any size can be solved in a given number of moves is NP-complete https://t.co/G2MMphhhZ4 â moneyscienceâ¦
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Biased Algorithms Are Everywhere, and No One Seems to Care
"Biased Algorithms Are Everywhere, and No One Seems to Care" https://t.co/AccY2Mb9xx â JC Kommer (@Alea_) July 12, 2017
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Grooming Future Leaders
Retired Brigadier General Bernard Banks, now teaching at Kellogg, offers some interesting insights on developing future leaders. Banks explains that companies need to begin grooming future leaders when individuals are not yet managing others. He advocates providing individuals temporary opportunities to lead others as an initial developmental opportunity, before people are promoted to managerial positions. Banks explains:
According to Banks, a better path is to begin grooming future managers when they are still in nonmanagement roles, so that they can develop prior to moving up the ladder. For example, a company might place people on teams where they have no formal authority, but are nonetheless expected to work collaboratively with others. Or a company might temporarily provide leadership assignments. When a manager leaves for vacation or is occupied with another assignment for a finite period of time, a nonmanagerârather than a colleague already in a managerial roleâmight be asked to fill in. This early investment can feel like a risk at the time, admits Banks, but he has seen it pay off in future leaders. âWhen they make that transition, they have a reasonable expectation of succeeding in that new role.â
Banks also argues that individuals need to take ownership of their development plan. Companies should not simply be telling workers what they need to do next to develop as leaders. The process should involve a healthy dose of self-direction. Individuals need to identify opportunities for development, rather than always waiting to be told what to do.
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Modeling the price of Bitcoin with fractional Brownian motion: a Monte Carlo approach. (arXiv:1707.03746v1 [q-fin.CP])
The long-term dependence of Bitcoin (BTC), manifesting itself through a Hurst exponent $H>0.5$, is exploited in order to predict future BTC/USD price. A Monte Carlo simulation with $10^5$ fractional Brownian motion realisations is performed as extensions on historical data. The accuracy of statistical inferences is 20\%. The most probable Bitcoin price in 180 days is 4537 USD.
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Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution. (arXiv:1707.03715v1 [q-fin.RM])
The realized GARCH framework is extended to incorporate the two-sided Weibull distribution, for the purpose of volatility and tail risk forecasting in a financial time series. Further, the realized range, as a competitor for realized variance or daily returns, is employed in the realized GARCH framework. Further, sub-sampling and scaling methods are applied to both the realized range and realized variance, to help deal with inherent micro-structure noise and inefficiency. An adaptive Bayesian Markov Chain Monte Carlo method is developed and employed for estimation and forecasting, whose properties are assessed and compared with maximum likelihood, via a simulation study. Compared to a range of well-known parametric GARCH, GARCH with two-sided Weibull distribution and realized GARCH models, tail risk forecasting results across 7 market index return series and 2 individual assets clearly favor the realized GARCH models incorporating two-sided Weibull distribution, especially models employing the sub-sampled realized variance and sub-sampled realized range, over a six year period that includes the global financial crisis.
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A Model of Interbank Flows, Borrowing, and Investing. (arXiv:1707.03542v1 [q-fin.RM])
We consider a model when private banks with interbank cash flows as in (Carmona, Fouque, Sun, 2013) borrow from the outside economy at a certain interest rate, controlled by the central bank, and invest in risky assets. The cash flow between private banks is also facilitated by the central bank. Each private bank aims to maximize its expected terminal logarithmic utility. The central bank, in turn, aims to control the overall size of financial system, and the rate of circulation between banks. A default occurs when the net worth of a bank goes below a certain threshold. We consider systemic risk by studying probability of a certain number of defaults over fixed finite time horizon.
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