Narrow Results

In this paper an extension of the Lintner model [1] is considered: the problem of portfolio optimization is studied when short-selling is allowed through the mechanism of margin requirements. This induces a non-linear constraint on the wealth. When interest on deposited margin is present, Lintner ingeniously solved the problem by recovering the unique optimal solution of the linear model (no margin requirements). In this paper an alternative and more realistic approach is explored: the nonlinear constraint is maintained but no interest is perceived on the money deposited against short-selling. This leads to a fully non-linear problem which admits multiple and unstable solutions very different among themselves but corresponding to similar risk levels. Our analysis is built on a seminal idea by Galluccio, Bouchaud and Potters [3], who have re-stated the problem of finding solutions of the portfolio optimization problem in futures markets in terms of a spin glass problem. In order to get the best portfolio (i.e. the one lying on the efficiency frontier), we have to implement a two-step procedure. A worked example with real data is presented.

It is suggested to consider long term trends of financial markets as a growth phenomenon. The question is what conditions are needed for a long term sustainable growth or contraction in a financial market? The paper discusses the role of traditional market players of long only mutual funds versus hedge funds which take both short and long positions. It will be argued that financial markets since their very origins and only till very recently, have been in a state of "broken symmetry" which favored long term growth instead of contraction. The reason for this "broken symmetry" in a long term "bull phase" is the historical almost complete dominance by long only players in financial markets. Only with the recent arrival of investors that take up short positions is the symmetry slowly being restored, with the implications, as will be argued, of an increased probability for lasting decline of the markets, i.e., appearance of a long term "bear phase". Recent short trade data of the Nasdaq Composite index show an increase in the short activity prior to or at the same time as dips in the market, and reveal an steady increase in short trading activity, reaching levels never seen before.

To investigate the effect of short-selling constraints on investor behavior, we formulate an optimal stopping model in which the decision to cover a short position is affected by two short sale-specific frictions — margin risk and recall risk. Margin risk is introduced by assuming that a short seller is forced to close out their position involuntarily if they cannot fund margin calls (since short sales are collateralized transactions). Recall risk is introduced by permitting the lender to recall borrowed stock at any time, once again triggering an involuntary close-out. Examining the effect of these frictions on the optimal close-out strategy and associated value function, we finding that the optimal behavior can be qualitatively different in their presence. Moreover, these frictions lead to a substantial loss in value, relative to the first-best situation without them (a reduction of approximately 17% for our conservative base-case parameters). This significant effect has important implications for many familiar no-arbitrage identities, which are predicated on the assumption of unfettered short selling.

Returns of the same companies' common stocks, both non-market-adjusted and market-adjusted, exhibit greater volatility, on the Stock Exchange of Hong Kong where short selling is allowed than on the Shanghai Stock Exchange and Shenzhen Stock Exchange where short selling is restrained. This unique evidence indicates that short selling increases stock price volatility for the Chinese stocks in the Chinese stock markets.

In this paper, we study mean–variance–Conditional Value-at-Risk (CVaR) portfolio optimization problem with short selling, cardinality constraint and transaction costs. To tackle its mixed-integer quadratic optimization model for large number of scenarios, we take advantage of the penalty decomposition method (PDM). It needs solving a quadratic optimization problem and a mixed-integer linear program at each iteration, where the later one has explicit optimal solution. The convergence of PDM to a partial minimum of original problem is proved. Finally, numerical experiments using the S&P index for 2020 are conducted to evaluate efficiency of the proposed algorithm in terms of return, variance and CVaR gaps and CPU times.

The use and effect of derivatives and short selling by US equity and bond open-end mutual funds are studied using a large and unique database. We find that the likelihood of their use is positively related to fund size, family size, and fund turnover for both fund types except for short selling by equity funds from larger families. Our findings suggest that funds that use derivatives exhibit significantly higher benchmark-adjusted performances based on both gross- and net-of-fees returns. This is done without adversely affecting market betas, net expense ratios (NERs), or brokerage fees as a proportion of total net assets (TNA). We find that for bond funds derivative use is negatively associated with non-systematic risk and short selling use is positively associated with total and systematic risk.

We investigate the accrual anomaly by examining the stock market reaction around the release of short interest information for firms with high accruals. We show that arbitrage activity, proxied by short interest, focuses on mispricing of firms with high accruals. In particular, we provide evidence that high accrual firms experience significant negative returns when high short interest levels are announced. In contrast, the announcement effect does not vary by short selling activity for low accrual firms. Our findings are consistent with the view that the accrual anomaly is due to overpricing.

We study the pricing of exchange traded funds (ETFs) and the associated arbitrage trading of them in the primary and secondary markets. We find a direct relation between primary and secondary market trading that is consistent with market-makers using the primary market to hedge their inventory risk in the secondary market, as well as to facilitate arbitrage. Such trading in both markets keeps ETF prices in line with their net asset value. We conclude that the existence of the primary market enhances secondary market efficiency.

In this chapter, we first discuss utility theory and utility function in detail, then we show how asset allocation can be done in terms of the quadratic utility function. Based upon these concepts, we show Markowitz’s portfolio selection model can be executed by constrained maximization approach. Real world examples in terms of three securities are also demonstrated. In the Markowitz selection model, we consider that short sale is both allowed and not allowed.

This chapter presents advancement of several widely applied portfolio models to ensure flexibility in their applications: Mean–variance (MV), Mean–absolute deviation (MAD), linearized value-at-risk (LVaR), conditional value-at-risk (CVaR), and Omega models. We include short-sales and transaction costs in modeling portfolios and further investigate their effectiveness. Using the daily data of international ETFs over 15 years, we generate the results of the rebalancing portfolios. The empirical findings show that the MV, MAD, and Omega models yield higher realized return with lower portfolio diversity than the LVaR and CVaR models. The outperformance of these risk-return-based models over the downside-risk-focused models comes from efficient asset allocation but not only the saving of transaction costs.

China Huishan Dairy Holdings Co Ltd. was accused in December, 2017 of accounting fraud and embezzlement by a US-based short selling investment firm named Muddy Waters. The accusations were based on on-the-ground investigations into the integrity of Huishan’s financials. Not a few months after Muddy Waters published their findings, Huishan’s stock price dropped 85% in 90 minutes. This case analyzes Muddy Waters’ research findings, Huishan’s operational inconsistencies and suspicious executive behavior, Huishan’s response to Muddy Waters’ research, and the morality of fraud and embezzlement.

Short selling, in short, is legal betting against the continued growth of a publicly traded firm. It predicts that, for one reason or another, the stock price of a given firm will decrease, thus benefitting the investor holding the short position. The company Muddy Waters was founded by a short selling expert named Carson Block, who made a name for himself and his firm by allegedly discovering fraud at a number of publicly listed Chinese companies through investigative research. Once discovered, Muddy Waters would publish a research report summarizing their findings. The case describes two cases in which the company applied this business model to Chinese companies and asks whether it is ethical to profit from another’s losses and whether investors should be allowed to invest in the failure of a firm.

In this chapter, we first discuss utility theory and utility function in detail, then we show how asset allocation can be done in terms of quadratic utility function. Based upon these concepts, we show that Markowitz’s portfolio selection model can be executed by the constrained maximization approach. Real-world examples in terms of three securities are also demonstrated. In the Markowitz selection model, we consider that short sale is both allowed and not allowed.

This paper presents the advancement of several widely applied portfolio models to ensure flexibility in their applications: Mean-variance (MV), Mean-absolute deviation (MAD), Linearized value-at-risk (LVaR), Conditional value-at-risk (CVaR), and Omega models. We include short sales and transaction costs in modeling portfolios and further investigate their effectiveness. Using the daily data of international ETFs over 15 years, we generate the results of the rebalancing portfolios. The empirical findings show that the MV, MAD, and Omega models yield a higher realized return with lower portfolio diversity than the LVaR and CVaR models. The outperformance of these risk–return-based models over the downside-risk-focused models comes from efficient asset allocation and not only the saving of transaction costs.

We show that in a financial market given by semimartingales, an arbitrage opportunity, provided it exists, can only be exploited through short selling. This finding provides a theoretical basis for differences in regulation for financial services providers that are allowed to go short and those without short sales. The privilege to be allowed to short sell gives access to potential arbitrage opportunities, which creates by design a bankruptcy risk.

Restrictions imposed on short selling provides incentive for these traders to be better informed, leading to the use of short interest data as an information measure. We add to the literature on whether short sellers are, indeed, better informed traders by investigating whether there are changes in short interest near-term to extreme earnings surprises. If short sellers are better informed (or better able to anticipate corporate events), short interest data should reflect noticeable changes in advance of these significant announcements. After controlling for company-specific factors, we find only limited evidence that the average short seller trades with superior information.