Research articles for the 2020-03-01

A Study on Performance Evaluation of Equity Linked Saving Schemes (ELSS) of Mutual Funds
Panigrahi, CMA(Dr.) Ashok,Mistry, Mohit,Shukla, Raghav,Gupta, Abhishek
SSRN
A mutual fund is a company that pools money from a group of investors and invests the money in different types of securities such as stocks, bonds, debt, etc. A mutual fund is one of the fastest-growing sectors in India and it plays a significant role in the Indian capital market. The equity-linked saving scheme is an open-ended equity diversified fund, which provides a tax benefit to investors under section 80 C of the Income Tax Act, 1961. Rs.1.5 lakh “income” gets tax benefit of up to Rs.45,000 at 30% tax without considering surcharge. However, with a large number of ELSS funds available, investors face the challenge of selecting suitable ELSS funds to suit their needs. This research paper is an attempt to evaluate the performance of the top five ELSS schemes of different mutual funds in India using various tools like Beta, Sharpe ratio, Jensen ratio, etc. It also suggests suitable ELSS schemes for investors so that they can achieve their investment objectives. The analysis reveals that the majority of funds have outperformed under Treynor's Ratio and Sharpe Ratio, giving constant and appreciable results during the course.

A martingale concept for non-monotone information in a jump process framework
Marcus C. Christiansen
arXiv

The classical concept of martingales and compensators bases on the monotony of filtrations. This paper looks at the situation where innovations can have an expiry date such that the information dynamics becomes non-monotone. The central idea is to focus only on those properties that martingales and compensators show on infinitesimally short intervals. Infinitesimal martingale representations are derived that extend classical martingale representations to non-monotone information. While the classical representations describe innovations only, the extended representations have an additional symmetric counterpart that quantifies the effect of information loss.



After Further Review: How the N.C.A.A.’s Division I Should Implement Name, Image, and Likeness Rights to Save Themselves and Best Preserve the Integrity of College Athletics
Bayard, David
SSRN
California SB 206 bans California public schools from NCAA membership unless the NCAA alters its name-image-likeness (NIL) policy by 2021. The NCAA Board of Governors ordered each division to modernize and adapt its rules to honor the California law, while still respecting certain principles of amateurism. These two mandates are untenable, as the NCAA is hesitant to create an open market for athletes to shop their NIL rights to the school with the highest bidding boosters.The author started with SB 206 and identified areas where the NCAA was in violation. The author then examined the NCAA Board of Governor’s charge to the newly created Federal and State Legislation Working Group and its subsequent report. The author then sought out relevant quotations from leaders of the NCAA, university athletics, and legislators. The author then read hundreds of newspaper and magazine articles regarding SB 206 and NIL policy. Keeping the Working Group’s restrictions in mind, the author crafted a recommendation.This Article attempts to guide NCAA Division I in crafting its NIL policy. It examines the NCAA’s history of pay-to-play and the limitations placed on reform by the working group and gives the NCAA justifications and recommendations for NIL reform. Lastly, the author forecasts only three possible outcomes: preemption of federal NIL legislation, withdrawal of the California law, or NCAA litigation with California.

Algorithmic market making for options
Bastien Baldacci,Philippe Bergault,Olivier Guéant
arXiv

In this article, we tackle the problem of a market maker in charge of a book of options on a single liquid underlying asset. By using an approximation of the portfolio in terms of its vega, we show that the seemingly high-dimensional stochastic optimal control problem of an option market maker is in fact tractable. More precisely, when volatility is modeled using a classical stochastic volatility model -- e.g. the Heston model -- the problem faced by an option market maker is characterized by a low-dimensional functional equation that can be solved numerically using a Euler scheme along with interpolation techniques, even for large portfolios. In order to illustrate our findings, numerical examples are provided.



An empirical study of neural networks for trend detection in time series
Alexandre Miot,Gilles Drigout
arXiv

Detecting structure in noisy time series is a difficult task. One intuitive feature is the notion of trend. From theoretical hints and using simulated time series, we empirically investigate the efficiency of standard recurrent neural networks (RNNs) to detect trends. We show the overall superiority and versatility of certain standard RNNs structures over various other estimators. These RNNs could be used as basic blocks to build more complex time series trend estimators.



Cleaning up Bubbles: The Collateral Effects of Information in Auctions
Ramcharan, Rodney
SSRN
This paper shows that the information environment at auctions affects auction outcomes and has aggregate implications. Using data from the residential real estate market for about 800,000 listed properties across 70,000 auctions, I find that prices and liquidity are both significantly reduced in auctions with more opaque information environments â€" when assets for sale are heterogenous and located far away from the point of sale. Assets bought in more opaque information environments also earn lower realized returns. Increased opacity in these auction markets also induces greater home bias, shrinking the distance between the point of sale and the equilibrium buyer. The effects of information are also felt beyond the auction setting, as increased auction opacity depresses local housing markets and pushes up the cost of consumer credit.

Equilibrium Model of Limit Order Books: A Mean-field Game View
Jin Ma,Eunjung Noh
arXiv

In this paper we study a continuous time equilibrium model of limit order book (LOB) in which the liquidity dynamics follows a non-local, reflected mean-field stochastic differential equation (SDE) with evolving intensity. Generalizing the basic idea of Ma et.al. (2015), we argue that the frontier of the LOB (e.g., the best asking price) is the value function of a mean-field stochastic control problem, as the limiting version of a Bertrand-type competition among the liquidity providers. With a detailed analysis on the $N$-seller static Bertrand game, we formulate a continuous time limiting mean-field control problem of the representative seller. We then validate the dynamic programming principle (DPP), and show that the value function is a viscosity solution of the corresponding Hamilton-Jacobi-Bellman (HJB) equation. We argue that the value function can be used to obtain the equilibrium density function of the LOB, following the idea of Ma et.al. (2015).



High Dimensional Estimation, Basis Assets, and Adaptive Multi-Factor Models
Liao Zhu,Sumanta Basu,Robert A. Jarrow,Martin T. Wells
arXiv

The paper proposes a new algorithm for the high-dimensional financial data -- the Groupwise Interpretable Basis Selection (GIBS) algorithm, to estimate a new Adaptive Multi-Factor (AMF) asset pricing model, implied by the recently developed Generalized Arbitrage Pricing Theory, which relaxes the convention that the number of risk-factors is small. We first obtain an adaptive collection of basis assets and then simultaneously test which basis assets correspond to which securities, using high-dimensional methods. The AMF model, along with the GIBS algorithm, is shown to have a significantly better fitting and prediction power than the Fama-French 5-factor model.



Hot-Stove Effects: The Impact of CEO Past Professional Experiences on Dividend Policy
Faulkner, Matthew,García-Feijóo, Luis
SSRN
The personal traits of chief executive officers (CEOs) have been found to influence corporate policy decisions. We examine the impact of past professional distress experiences on payout policy. We hypothesize that CEOs experiencing a distress event in their past career, before becoming CEO, alter their implementation of corporate payout policy. We find that CEOs having experienced prior professional career distress are less likely to pay dividends and repurchase shares. These CEOs pay out lower levels of dividends, and when they pay, they smooth dividends more. Additionally, when CEOs with past professional career distress do have a payout policy greater than zero dollars, they exhibit a preference toward the use of repurchases, adding to the literature of substitution and differences between the two forms of payout. Overall, we report that experience-driven conservatism alters payout policy, a novel finding in the literature.

Rational hyperbolic discounting
José Cláudio do Nascimento
arXiv

How much should you receive in a week to be indifferent to \$ 100 in six months? Note that the indifference requires a rule to ensure the similarity between early and late payments. Assuming that rational individuals have low accuracy, then the following rule is valid: if the amounts to be paid are much less than the personal wealth, then the $q$-exponential discounting guarantees indifference in several periods. Thus, the discounting can be interpolated between hyperbolic and exponential functions due to the low accuracy to distinguish time averages when the payments have low impact on personal wealth. Therefore, there are physical conditions that allow the hyperbolic discounting regardless psycho-behavioral assumption.



Robo-Advisors: Exploring and Leveraging the Competition
Sarpong, Prince
SSRN
There are lot of talks about robo-advisors taking the jobs of human financial advisors. Amid the excitement or anxiety about robots doing better than humans in many aspects, there is little discussion on the potential limitations of machines in taking over certain aspects of the financial planning process. What are the technologies behind robo-advisory systems, what are the pitfalls, and will they really replace human advisors? In this paper, I review recent literature on robo-advice and conclude that human advisors adopting robo-advisors into their practices will enhance their practices even further and deliver better outcomes than either standalone robo-advisors or human advisors.

Smart or Dumb? Asset Allocation Ability of Mutual Fund Investors and the Role of Broker Advice
Fang-Klingler, Jieyan
SSRN
In this paper, I investigate the asset allocation ability of mutual fund investors. Specifically, I examine differences among non-proprietary brokers, proprietary brokers and direct channels regarding their asset allocation ability. In aggregate, mutual fund investors do not seem to have superior asset allocation ability. However, I do find that money flows through non-proprietary brokers show significantly higher asset allocation performance than money flows through proprietary brokers. This is consistent with the view that non-proprietary agents are more likely to act on behalf of their customers as opposed to proprietary agents who represent their affiliated companies.

The Effect of the PSI in the Relationship between Sovereign and Bank Credit Risk Evidence from the Euro Area
Papafilis, Michalis-Panayiotis,Psillaki, Maria,Margaritis, Dimitris
SSRN
This study examines the nexus between sovereigns and banks during a crisis with a focus on the effects of PSI, the voluntary exchange program of Greek sovereign bonds with private sector involvement. The effectiveness of the program is evaluated through its impact on credit default swaps of 8 Eurozone countries and 21 banks, using daily data from 2009 to 2014. Using linear and nonlinear causality analyses, it is found that the link between sovereign and bank risk weakened after PSI, while the persistence and magnitude of lead-lag interactions also declined in the same period. A difference-in-difference model confirms this result. The findings are also robust to second moment filtering, with GARCH-BEKK residuals indicating the presence of significant albeit declining nonlinear causal effects. The empirical evidence suggests that sovereign debt restructuring initiatives, such as PSI, could be an effective policy measure to ease off pressure on the nexus between banks and their sovereigns.

Weak Limits of Random Coefficient Autoregressive Processes and their Application in Ruin Theory
Yuchao Dong,Jérôme Spielmann
arXiv

We prove that a large class of discrete-time insurance surplus processes converge weakly to a generalized Ornstein-Uhlenbeck process, under a suitable re-normalization and when the time-step goes to 0. Motivated by ruin theory, we use this result to obtain approximations for the moments, the ultimate ruin probability and the discounted penalty function of the discrete-time process.