A new information share measure

Lien, Donald; Shrestha, Keshab

doi:10.1002/fut.20356

Cited by 137 publications

(177 citation statements)

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“…CFW stands for the common factor weights proposed by Schwarz and Szakmary (1994) and Gonzalo and Granger (1995). IS is the information share (mean of upper and lower bound) by Hasbrouck (1995), and MIS denotes the modified information share developed by Lien and Shrestha (2009).…”

Section: Discussionmentioning

confidence: 99%

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Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?

Adämmer

Bohl

Gross

2015

Journal of Futures Markets

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractIt is still an unanswered question how much trading activity is needed for efficient price discovery in commodity futures markets. For this purpose, we investigate the price discovery process of two thinly traded agricultural futures contracts traded at the European Exchange in Frankfurt. Our empirical results show that the trading volume threshold which is necessary to facilitate efficient price discovery is very low.As our findings are based on constant and time-varying vector error correction models, we also show that neglecting time-variation in the parameters can lead to misleading results.JEL Classification: G12, G13, Q14

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Section: Discussionmentioning

confidence: 99%

“…Our third measure of price discovery is the modified information share as proposed by Lien and Shrestha (2009). The advantage to the traditional information share is its independence from the particular ordering of the time series in the VECM.…”

Section: Vector Error Correction Model and Price Discovery Measuresmentioning

confidence: 99%

Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?

Adämmer

Bohl

Gross

2015

Journal of Futures Markets

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“…But for stock index futures, we cannot get its rich basic information. In the past times, some scholars used M-GARCH model to analyze the information concluding in the futures market [1] (Lien D, Shrestha K., 2009). And some scholars studied the relationship between the growth of economic and stock price [2] (Fama, 1992).…”

Section: Introductionmentioning

confidence: 99%

Analysis of CSI 300 Stock Index Futures Price Trend Based on ARIMA Model

Zhang¹,

Sun²

2018

dtssehs

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Abstract. Stock index futures has become the major tools for investors to avoid risk or make speculative arbitrage. However, the leverage of stock index futures is large. If they cannot make a correct judgment on the trend of stock index futures, the loss will be great. This paper is based on this background and engages in intensive study. Using traditional and modern econometric methods respectively, the CSI 300 index futures were fitted. In addition, RMSE (root mean square error) was used to find the optimal model. After finding the model, we can put the trading strategy forward.

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“…Lien and Shrestha (2009) come with a great contribution to this literature. They suggest an alternative IS measure which rests on the spectral decomposition of the correlation matrix, delivering the so desired unique ISs.…”

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confidence: 98%

“…This solution has two drawbacks. First, the average IS measures do not sum up to one and they do not satisfy a factor structure as pointed out by Lien and Shrestha (2009). Second, averaging across permutations can also be inconvenient in the context of high-dimensional price systems.…”

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confidence: 99%

Price discovery in dual‐class shares across multiple markets

Fernandes¹,

Scherrer

2017

Journal of Futures Markets

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This paper proposes a new measure of price discovery that uses the spectral decomposition. The methodology is especially important in the context of large price systems, such as interest rate parities with spot and futures contracts or dual-class shares in multiple markets. We employ high frequency data to study price discovery in dual-class Brazilian stocks and their ADRs. We find that the foreign market is at least as informative as the home market and that shocks in the dual-class premium entail a permanent effect in normal times, but transitory in periods of financial distressFinancial markets have the important function of discovering the price of a given asset. The increasing availability of highfrequency data allows us to study how efficiently and timely each market reacts to news in a much more precise manner. There is a large number of companies being listed in more than one exchange mainly because cross-listing allows raising equity capital, at a lower cost and increasing liquidity. Besides, it may also improve minority shareholder protection (Stulz, 1999), increase firm value (Doidge, Karolyi, & Stulz, 2004), and lower private benefits of control (Doidge, 2004). There are 498 foreign companies from 46 different countries listed on NYSE as of June 30, 2016. As a result, geographical price discovery is of major interest for domestic stock exchanges and companies (see, for instance, Eun & Sabherwal, 2003). This paper extends the standard price discovery methodology to deal with high-dimension portfolios. Applications include interest rate parities using both spot and future contracts in interest rate and exchange rate markets as well as dual-class assets traded on multiple markets. We focus on the latter. The idea is to exploit every piece of information about the fundamental value of a firm by looking at the prices of both common and preferred shares across different trading platforms. As a by-product, by looking at the difference between prices of common and preferred shares, we may also shed some light on the behavior of the dual-class premium.The main technical difficulty is to contrive a unique price discovery measure that does not assume a priori which share class and/or market lead the impounding of new information. For the standard information share (IS) measure of price discovery (Hasbrouck, 1995), which gauges the fraction of the variance of the fundamental price innovation due to the variance of a given asset/market price innovation, one normally imposes a triangular structure from the most informative to the least informative market price in order to handle contemporaneous correlations. ISs will thus depend on the specific ordering in the price system.One solution is to consider the average IS across different orderings of market prices. This is a simple and effective solution if there are only a few market prices. However, as the number of assets/markets increase, one would have to average over thousands J Futures Markets. 2018;38:129-155.wileyonlinelibrary.com/journal/fut

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A new information share measure

Cited by 137 publications

References 29 publications

Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?

Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?

Analysis of CSI 300 Stock Index Futures Price Trend Based on ARIMA Model

Price discovery in dual‐class shares across multiple markets

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