scholarly journals WHAT MAKES INVESTORS SHORT SELL ETFs?

2016 ◽  
Vol 16 (2) ◽  
pp. 16-27
Author(s):  
Dagmar Linnertová ◽  
Oleg Deev
Keyword(s):  
Short Sell

Short‐sell moratorium effects on regional bank performance

2013 ◽  
Vol 5 (2) ◽  
pp. 92-110
Author(s):  
Michael Devaney ◽  
William L. Weber
Keyword(s):  
Trading Volume ◽  
Short Selling ◽  
Bank Risk ◽  
Too Big To Fail ◽  
Content Type ◽  
Naked Short Selling ◽  
Regional Bank ◽  
Capm Model ◽  
Short Sell ◽  
Regional Banks

PurposeThe purpose of this paper is to investigate the effects of the 2008 SEC short‐sell moratorium on regional bank risk and return. The paper also examines the decline in “failures to deliver” securities in the wake of SEC short‐sell moratorium.Design/methodology/approachIn total, six regional bank portfolios are derived and the beta coefficients from a CAPM model are estimated using the integrated generalized autoregressive conditional heteroskedasticity (IGARCH) method accounting for the short‐sell moratorium. Data on 110 regional banks in six US regions from January 2002 to December 30, 2011 are used to estimate the model.FindingsThe ban on naked short selling and the SEC short‐sell moratorium significantly increased individual bank risk for a majority of banks in six geographic regions, but also increased return in three of three regions. There was also reduced naked short selling as failures to deliver securities declined sharply after the September 2008 moratorium took effect.Originality/valueRegional banks have generally not achieved the size needed to be deemed “too big to fail” by policy‐makers. Thus, policy changes such as the SEC short‐sell moratorium might be expected to have larger effects on regional banks than on larger banks, which might be shielded from the policy change by having achieved “too big to fail” status. The authors' results are consistent with research that has shown that short‐sell restrictions increase risk by reducing liquidity and trading volume.

International Real Estate Review

2001 ◽  
Vol 4 (1) ◽  
pp. 43-56
Author(s):  
Tsong-Yue Lai ◽  
◽  
Hin Man Mak ◽  
Ko Wang ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Short Selling ◽  
Local Market ◽  
Short Sales ◽  
Rates Of Return ◽  
Short Sale ◽  
Asset Pricing Models ◽  
Short Sell ◽  
Property Markets

Asset pricing models have been used extensively in the recent real estate literature to evaluate real estate performance and estimate required rates of return of properties. In this paper, we show that the CAPM and its variants will derive a biased result when short sales are not allowed in the market. This problem is particularly serious for Asian property markets where investors are not able to short sell real estate indexes as a substitute for short selling real properties. We also demonstrate that the bias resulting from the short-sale constraint is related to the supply-and-demand conditions in the local market.

scholarly journals Statistical Arbitrage in Cryptocurrency Markets

2019 ◽  
Vol 12 (1) ◽  
pp. 31 ◽  
Author(s):  
Thomas Fischer ◽  
Christopher Krauss ◽  
Alexander Deinert
Keyword(s):  
Machine Learning ◽  
Cross Sectional ◽  
Academic Literature ◽  
Limits To Arbitrage ◽  
Statistical Arbitrage ◽  
Out Of Sample ◽  
Learning Research ◽  
Short Sell ◽  
Half Turn ◽  
Binned Data

Machine learning research has gained momentum—also in finance. Consequently, initial machine-learning-based statistical arbitrage strategies have emerged in the U.S. equities markets in the academic literature, see e.g., Takeuchi and Lee (2013); Moritz and Zimmermann (2014); Krauss et al. (2017). With our paper, we pose the question how such a statistical arbitrage approach would fare in the cryptocurrency space on minute-binned data. Specifically, we train a random forest on lagged returns of 40 cryptocurrency coins, with the objective to predict whether a coin outperforms the cross-sectional median of all 40 coins over the subsequent 120 min. We buy the coins with the top-3 predictions and short-sell the coins with the flop-3 predictions, only to reverse the positions after 120 min. During the out-of-sample period of our backtest, ranging from 18 June 2018 to 17 September 2018, and after more than 100,000 trades, we find statistically and economically significant returns of 7.1 bps per day, after transaction costs of 15 bps per half-turn. While this finding poses a challenge to the semi-strong from of market efficiency, we critically discuss it in light of limits to arbitrage, focusing on total volume constraints of the presented intraday-strategy.

Structural and Market Efficacy Implications of the Short-Sell Ban in Europe

2010 ◽  
Vol 5 (3) ◽  
pp. 10-16
Author(s):  
Jose Marques ◽  
Mainak Sarkar
Keyword(s):  
Short Sell

scholarly journals AN EVALUATION OF HEDGE FUNDS: RISK, RETURN AND PITFALLS

2002 ◽  
Vol 47 (01) ◽  
pp. 153-171 ◽  
Author(s):  
FRANCIS KOH ◽  
DAVID K. C. LEE ◽  
KOK FAI PHOON
Keyword(s):  
Hedge Funds ◽  
Legal Status ◽  
Hedge Fund ◽  
Empirical Work ◽  
Risk And Return ◽  
Net Worth ◽  
Empirical Risk ◽  
And Performance ◽  
Short Sell ◽  
Risk Dimensions

Hedge funds are collective investment vehicles fast becoming popular with high net worth individuals as well as institutional investors. These are funds that are often established with a special legal status that allows their investment managers a free hand to use derivatives, short sell and exploit leverage to raise returns and cushion risk. Given that they have substantial latitude to invest, it is instructive to examine the performance of hedge funds as compared to other forms of managed funds. This paper provides an overview of hedge funds and discusses their empirical risk and return profiles. It also poses some concerns regarding the empirical measurements. Given the complexity of hedge fund investments, meaningful analytical methods are required to provide greater risk transparency and performance reporting. Hedge fund performance is also beset by a number of practical issues generating "practical risks". These risks are not fully addressed by the usual risk-adjusted performance measures in the literature. A penalty function to discount these extraneous risk dimensions is proposed. The paper concludes that further empirical work is required to provide informative statistics about the risk and return of hedge funds.

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