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Journal articles on the topic 'Price discovery'

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Author: Grafiati

Published: 4 June 2021

Last updated: 9 March 2023

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1

Makarov, Igor, and Antoinette Schoar. "Price Discovery in Cryptocurrency Markets." AEA Papers and Proceedings 109 (May 1, 2019): 97–99. http://dx.doi.org/10.1257/pandp.20191020.

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We ask which markets drive bitcoin prices and how price discovery happens across different exchanges. Does the greater exuberance for cryptocurrencies outside the United States affect prices only on local markets or does it impact price formation on global cryptocurrency markets? We document significant heterogeneity in which price formation happens across exchanges and time. When markets are more integrated, shocks to prices on all exchanges contribute to price discovery. However, when markets become segmented, those exchanges that have large arbitrage spreads relative to the US price, i.e. where investors are more exuberant become much less important for price discovery.

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2

Myeonghoon Yeom, 류두진, and Jae-Seung Baek. "Price Discovery Index and Price Discovery Factors." Korean Journal of Financial Engineering 12, no. 4 (December 2013): 1–25. http://dx.doi.org/10.35527/kfedoi.2013.12.4.001.

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3

Yang, Jian, and David J. Leatham. "Price Discovery in Wheat Futures Markets." Journal of Agricultural and Applied Economics 31, no. 2 (August 1999): 359–70. http://dx.doi.org/10.1017/s1074070800008634.

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AbstractThis paper examines the price discovery function for three U.S. wheat futures markets: the Chicago Board of Trade, Kansas City Board of Trade, and Minneapolis Grain Exchange. The maintained hypothesis is that futures markets search more for information than cash markets to find an equilibrium price, thus greatly improving the price discovery function. The tests reveal the existence of one equilibrium price across the three futures markets in the long run, but no cointegration among prices in the three representative cash markets.

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4

Maynard, Leigh J. "Price Discovery in the Egg Industry." Agricultural and Resource Economics Review 26, no. 1 (April 1997): 23–30. http://dx.doi.org/10.1017/s1068280500000800.

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Formula pricing of eggs is typically based on quotations issued by Urner Barry Publications, and egg producers worry that the quotes are systematically lower than equilibrium levels. Egg Clearinghouse, Inc. (ECI) provides a public forum for cash trading, intended to facilitate price discovery. Evidence from 1994–95 does not suggest that Urner Barry understates producer level prices on average. Granger causality tests indicate a feedback relationship between the Urner Barry quotes and ECI prices, with ECI leading during price upswings. Lead times appear to have fallen since the late 1970s and early 1980s, confirming earlier predictions regarding market efficiency.

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5

STEIN, JEROME L. "Price Discovery Processes." Economic Record 68 (December 1992): 34–45. http://dx.doi.org/10.1111/j.1475-4932.1992.tb02294.x.

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6

Clapham, Benjamin, and Kai Zimmermann. "Price discovery and convergence in fragmented securities markets." International Journal of Managerial Finance 12, no. 4 (August 1, 2016): 381–407. http://dx.doi.org/10.1108/ijmf-02-2015-0037.

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Purpose – The purpose of this paper is to study price discovery and price convergence in securities trading within a fragmented market environment where stocks are traded on multiple venues. The results provide novel empirical insights questioning the generalizability of the current literature and aim to expand the understanding of price determination in a fragmented market microstructure. Design/methodology/approach – This paper provides an empirical data analysis based on an event study methodology. The authors applied Thomson Reuters Tick History data covering German blue chip stocks listed on multiple venues in 2009 and 2013. Different time aggregations up to one second are applied to provide an in-depth analysis. Findings – The paper empirically discovers a persistent price leader-follower relationship not only during intraday auctions but also in subsequent continuous trading. The authors found that trading on alternative venues instantly dries out in case the dominant market switches to a call auction. In these situations, alternative markets await and adopt the official price signal of the dominant market although prices on alternative venues still indicate a certain extent of price discovery. This phenomenon remains persistent at different levels of market fragmentation, indicating that alternative trading venues fully accept the price leadership role of the dominant market, no matter their own market share. Originality/value – This paper provides an innovative empirical setup to analyze price co-movement and convergence based on high-frequent data. Further, the results provide novel and robust insights into the price determination process in fragmented markets that clarify the role of price follower and price leader.

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Seon, Junghoon, and Ji Soo Lee. "A Comparison of Price Efficiency between Korean New Market and Main Board." Journal of Derivatives and Quantitative Studies 23, no. 3 (August 31, 2015): 421–37. http://dx.doi.org/10.1108/jdqs-03-2015-b0005.

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In this paper, we make a comparison of price efficiency between the new market (KOSDAQ) and the main board (KOSPI) in the Korean stock market. More specifically, we evaluate the relative price efficiency of both markets by comparing the speed, degree and accuracy in process of intraday price discovery. Each market’s speed and degree of price discovery are measured by WPC (weighted price contribution) devised by Barclay and Warner (1993) and WPCT (weighted price contribution per trade) proposed by Barclay and Hendershott (2003), respectively. Each market’s accuracy of price discovery is measured by unbiased regression coefficient used by Biais et al. (1999). We analyze 535 KOSPI stocks and 803 KOSDAQ stocks using 1-minute-interval transaction data collected from Bloomberg. The major findings of this paper are summarized as follows: Fist, the price discovery in KOSDAQ, the new market is slower than in KOSPI, the main board. Second, the morning session’s degree of price discovery per trade in KOSDAQ is smaller than KOSPI. Finally, the price discovery in KOSDAQ is more accurate than in KOSPI. Overall, our results indicate that the prices of KOSDAQ stocks are as efficient as the prices of KOSPI stocks, thought they have smaller firm size, younger ages, and greater uncertainty in cash flow and asset value than the main board stocks do.

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8

ARNADE, CARLOS, and LINWOOD HOFFMAN. "THE IMPACT OF PRICE VARIABILITY ON CASH/FUTURES MARKET RELATIONSHIPS: IMPLICATIONS FOR MARKET EFFICIENCY AND PRICE DISCOVERY." Journal of Agricultural and Applied Economics 47, no. 4 (November 2015): 539–59. http://dx.doi.org/10.1017/aae.2015.24.

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AbstractThis study investigates the relationship between cash and futures prices of soybeans and soybean meal from 1992 to 2013. Error correction models are estimated for the prices of both commodities. An exogenous measure of price variability is included in both models to determine if variability increases the speed with which cash and futures prices return to their long-run equilibrium relationship. This is used to measure the impact of price variability on short-run market efficiency and the price discovery process. The findings indicate that the level of price variability influences market adjustment rates and the price discovery process.

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9

Singh, Sanjay Kumar, Mukesh Kumar Jain, and Shoeba. "Information Spillover in Indian Agricultural Commodities Market." Asia-Pacific Journal of Management Research and Innovation 16, no. 3 (September 2020): 179–87. http://dx.doi.org/10.1177/2319510x21994048.

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Role of agricultural sector in Indian economy is prominent, as being an agrarian economy and having the second highest population in the world. Thus, the efficiency of this sector is the foremost factor for development and growth of the economy. This article attempts to examine the price discovery relationship of future and spot prices of five agricultural commodities, namely cardamom, crude palm oil, cotton, mentha oil and kapas, during the period 2011–2019. Johansen’s co-integration test, vector error correction model (VECM) and Granger causality block exogeneity test were employed for the study. We found that price discovery process is established for agricultural commodities under consideration. Future prices act as a leader in achieving long-run equilibrium for all commodities except cardamom. Causality was significantly reported for all commodities, as bidirectional causality runs between the prices. The study suggests that Forward Market Commission should be empowered more to control and regulate the market, which will ensure the efficient market situations in these commodities’ market. Attempt was made to evaluate price discovery process in agricultural commodities market during post sub-prime crisis period, which was ignored by majority of researchers.

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10

Pani, Upananda, Ştefan Cristian Gherghina, Mário Nuno Mata, Joaquim António Ferrão, and Pedro Neves Mata. "Does Indian Commodity Futures Markets Exhibit Price Discovery? An Empirical Analysis." Discrete Dynamics in Nature and Society 2022 (March 8, 2022): 1–14. http://dx.doi.org/10.1155/2022/6431403.

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Price discovery function analyses the dynamics of futures and spot price behavior in an asset’s intertemporal dimensions. The present study examines the price discovery function of the bullion, metal, and energy commodity futures and spot prices through the Granger causality and Johansen–Juselius cointegration tests. The Granger causality test results show bidirectional causality between the spot and futures returns for gold, silver, aluminum, lead, nickel, and zinc. The Johansen cointegration test shows that spot and futures prices are in the long-run equilibrium path for silver, aluminum, lead, nickel, zinc, crude oil, and natural gas. The vector error correction model results suggest that both the spot and futures markets are equally efficient in price discovery for the nickel. The spot market leads the futures market in price discovery for copper and zinc. However, the futures market leads the spot market in price discovery for silver, aluminum, and lead. The findings of the study suggest the market participants for implementing hedging and arbitrage strategies. It also helps the market regulators to examine the stability of these rapidly growing commodity futures markets in India.

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11

Chen, Tao. "Does retail trading matter to price discovery?" German Economic Review 21, no. 4 (December 16, 2020): 475–92. http://dx.doi.org/10.1515/ger-2019-0041.

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AbstractThe diminishing importance of retail investors and the institutionalization of markets are arguably a result of the general perception that individuals are not well informed and, hence, are better off using professional services (Davis, 2009). However, this paper provides evidence supporting the opposite. Using a global sample, we examine whether retail trading is informative around the world. Overall, retail investors are documented to enhance price efficiency by trading in the same direction as permanent price changes, contributing 24.8 % to price discovery, and accelerating the information from both scheduled and unscheduled news to be impounded into prices.

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12

Zeng, Yong, and Lei Chen. "Price Discovery Analysis of Oil Futures Market: A View of Interaction Effect." Advanced Materials Research 433-440 (January 2012): 4366–76. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4366.

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Whether oil futures market can perform price discovery function well is very important in global economics and energy markets. The interaction between oil spot and futures prices exists due to intraday information transfer and arbitrage trading. However, the traditional methods used in price discovery analysis ignore the interaction, and thus introduce the biased conclusions. This paper uses simultaneous equation analyze the interaction effect between oil spot and futures returns, estimates the model by the method of modified identification through heteroskedasticity (modified ITH) and examines price discovery function of oil futures markets. Using weekly spot and futures prices of Brent crude oil, gas oil and heating oil between Feb 12, 1999 and Jan 30, 2009, the results suggest oil futures return will affect the corresponding oil spot return. The unidirectional interaction exists. This indicates the information will transfer from futures markets to spot markets and oil futures markets have the major price discovery function. This paper also offers a new view of examining price discovery, i.e. interaction effect.

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13

Stockton, Mathew C., David A. Bessler, and Roger K. Wilson. "Price Discovery in Nebraska Cattle Markets." Journal of Agricultural and Applied Economics 42, no. 1 (February 2010): 1–14. http://dx.doi.org/10.1017/s1074070800003254.

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Monthly observations on prices from 10 weight/gender classifications of Nebraska beef cattle are studied in an error correction model (ECM) framework. This study attempts a replication of the 2003 paper on Texas prices by Bessler and Davis, where they find medium heifers (600-700 1b) at the center of price discovery. Using the ECM results Nebraska light steers are found to be weakly exogenous, with the innovation accounting results showing marked differences. Industry structure, production choices, and animal type and breeding herd differences between Texas and Nebraska are proposed as plausible reasons for partial (or incomplete) success at replication.

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14

Naipunya, J., I. Bhavani Devi, and D. Vishnusankar Rao. "Efficiency of chilli futures trading in terms of price discovery and price transmission." INTERNATIONAL RESEARCH JOURNAL OF AGRICULTURAL ECONOMICS AND STATISTICS 11, no. 2 (September 15, 2020): 137–43. http://dx.doi.org/10.15740/has/irjaes/11.2/137-143.

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This paper has examined the efficiency of futures trading of chilli in terms of price discovery and transmission. Seemingly unrelated regression” (SUR) model, Johansen’s multiple cointegrationtest, granger causality test and vector error correction model was applied to draw the results. Chilli spot market (Guntur) was efficient in price discovery. The Silbers and Garbage value of futures market was 0.0403 being significant at 1 per cent level (0.0037) indicating that futures market of chilli was inefficient in price discovery. The findings of the ADF test suggested that futures and spot prices of chilli attained stationarity at first difference. The co-integration test revealed the presence of one co-integrating equation and confirmed the long-run equilibrium relationship among futures and spot prices of chilli and spot markets came to short-run equilibrium as indicated by level of significance at 5 per cent i.e. (0.022), any disturbances in price would get corrected within 3 hours in spot markets as indicated by co-efficient values.

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15

Schroeder, Ted C., and J. Mintert. "Market hog price discovery." Kansas Agricultural Experiment Station Research Reports, no. 10 (January 1, 1999): 5–8. http://dx.doi.org/10.4148/2378-5977.6579.

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16

Jacoby, Gady, and Rose C. Liao. "Price discovery and sentiment." International Review of Financial Analysis 21 (January 2012): 108–18. http://dx.doi.org/10.1016/j.irfa.2011.09.005.

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17

Avino, Davide, Emese Lazar, and Simone Varotto. "Time varying price discovery." Economics Letters 126 (January 2015): 18–21. http://dx.doi.org/10.1016/j.econlet.2014.09.030.

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18

Mallika, Mathew, and M. M. Sulphey. "Gold Exchange Traded Fund - Price Discovery and Performance Analysis." Scientific Annals of Economics and Business 65, no. 4 (December 1, 2018): 477–95. http://dx.doi.org/10.2478/saeb-2018-0024.

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Abstract The paper aims to examine the price discovery process and the performance of Gold Exchange Traded Funds especially with respect to two Gold ETFs, namely, Goldman Sachs Gold Exchange Traded Scheme (GoldBeEs) and SBI Gold Exchange Traded Scheme (SBIGETS), for the period 2009 – 2016. The study has employed Johansen cointegration and Johansen’s Vector Error Correction Model (VECM) for the price discovery analysis. The results of VECM reveal that the spot prices lead the Gold ETFs price during the study period. Tracking Error analysis shows that Gold ETFs have neither outperformed nor underperformed the spot price. Price Deviation analysis indicates that Gold ETFs are trading on an average lower than the spot price of gold. The entire analysis reveals that although the price discovery takes place in the spot market, Gold ETFs have performed as well as physical gold and the slight difference in price with that of Gold is only because of certain fees, which are applicable in the management of Gold ETFs.

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19

Lin, Chiou-Fa, Cheng-Huei Chiao, and Bin Wang. "The impact of post-trade transparency on price efficiency and price discovery." Managerial Finance 45, no. 8 (August 12, 2019): 1062–75. http://dx.doi.org/10.1108/mf-05-2018-0217.

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Purpose The purpose of this paper is to examine the impact of post-trade transparency on price efficiency and price discovery. Design/methodology/approach The authors use an exogeneous change in market transparency in the Taiwan Stock Exchange that mandates the disclosure of unexecuted orders of the five best bid and ask prices after each trade, and conduct an event study analysis. Findings After the change, price efficiency enhances for both large and small firms, although the impact on stock prices is greater when the firm is larger. The authors also find that post-change trading reveals more private information for large firms but more public information for small firms. The findings support the view that transparency has a positive impact on market quality. Originality/value The paper adds to a large body of literature investigating the relationship between transparency and market behavior, especially the ongoing debate about whether trading transparency positively affects price dynamics. The findings also have important policy implications for the regulators.

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20

Garg, Mohit, Shelly Singhal, Kiran Sood, Ramona Rupeika-Apoga, and Simon Grima. "Price Discovery Mechanism and Volatility Spillover between National Agriculture Market and National Commodity and Derivatives Exchange: The Study of the Indian Agricultural Commodity Market." Journal of Risk and Financial Management 16, no. 2 (January 19, 2023): 62. http://dx.doi.org/10.3390/jrfm16020062.

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Agricultural commodity markets are critical to the global economy. This study investigates the price discovery mechanism, lead-lag relationship, and volatility spillover between spot prices on the National Agriculture Market (E-NAM) and futures and spot prices on the National Commodity and Derivative Exchange (NCDEX) in the Indian agricultural commodity market. The Johansen Cointegration, Vector Error Correction (VEC), Granger causality tests, and bivariate GARCH models were applied to daily data from April 2016 to December 2020 for twelve agricultural commodities traded on the E-NAM and NCDEX. We discovered the long-run relationship using the Johansen Cointegration test and concluded that the NCDEX spot and futures market is dominant in the price discovery mechanism, and the NCDEX futures and spot markets lead the E-NAM spot prices having a unidirectional or bidirectional relationship. Furthermore, the bivariate GARCH model suggested a volatility spillover from E-NAM spot prices to NCDEX futures and spot markets for most commodities, except for bajra, barley, and jeera, which have no volatility spillover. The study’s findings have important implications for various stakeholders, including policymakers, farmers, investors, traders, and others who want to reduce price risks by using information from the E-NAM market’s spot prices.

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Kropienė, Rūta, and Daina Karpavičiūtė. "EU Carbon Futures Market: The Aspects of Price Discovery." Lietuvos statistikos darbai 50, no. 1 (December 20, 2011): 5–13. http://dx.doi.org/10.15388/ljs.2011.13913.

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The main purpose of this article is to study the relationship between the spot and future price of European emissionallowances in order to test market efficiency hypothesis and determine which price leads the price discovery process.The work consists of several parts: presentation of theoretical background of model cost of carry; validation of cost of carrymodel assumptions; analysis of price development and conclusion.The cost of carry and cointegration theory is provided as well as overview of the related literature and existing research.The empirical examination reveals structural breaks in data and evidence that spot and futures prices are linked by the cost-ofcarryapproach in the second half of the analysed period. The examination of price development in the market indicated futures price leadership.Conclusion summarized the main results of the performed research.

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22

COFFEY, BRIAN K., DUSTIN L. PENDELL, and GLYNN T. TONSOR. "CONTEMPORANEOUS AND LAGGED CAUSAL RELATIONSHIPS AMONG NEGOTIATED LIVE CATTLE CASH MARKETS." Journal of Agricultural and Applied Economics 51, no. 1 (January 15, 2019): 182–98. http://dx.doi.org/10.1017/aae.2018.31.

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AbstractU.S. live cattle markets have experienced dramatic shifts in marketing methods over the past two decades, changing the way live cattle prices are discovered. We identify relationships between prices of the five major live cattle marketing regions using Granger causality and directed graph analysis. The two approaches complement each other and reveal that interweek and intraweek price discovery roles for given markets differ. Evidence indicates that Colorado, though a minor market in terms of relative volume, has become an important source of interweek price information to other markets.

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23

Vollmer, Teresa, Helmut Herwartz, and Stephan von Cramon-Taubadel. "Measuring price discovery in the European wheat market using the partial cointegration approach." European Review of Agricultural Economics 47, no. 3 (December 5, 2019): 1173–200. http://dx.doi.org/10.1093/erae/jbz040.

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Abstract Understanding price discovery in agricultural spot and futures markets is important for market participants and policy makers, because it can contribute to better management decisions and more informed policy debates on market regulation. Combining partial cointegration with state space modelling, we generate time-varying price discovery metrics for the European wheat market that allow for shifts in the long-run relationship. We find that the futures market dominates price discovery in terms of efficiency, but that this dominance is reduced in phases of higher price volatility. We find evidence of persistent shocks in the long-run relationship between spot and futures prices that appear to be related to variations in the quality of the wheat harvest, and to the concatenation of the futures prices.

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Jiang, Christine X., Tanakorn Likitapiwat, and Thomas H. McInish. "Information Content of Earnings Announcements: Evidence from After-Hours Trading." Journal of Financial and Quantitative Analysis 47, no. 6 (October 4, 2012): 1303–30. http://dx.doi.org/10.1017/s002210901200049x.

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AbstractWe study after-hours trading (AHT), price contributions, and price discovery following quarterly earnings announcements released outside of the normal trading hours. For Standard & Poor’s (S&P) 500 index stocks from 2004–2008, AHT is heightened on announcement days. A significant portion of the price change and price discovery occurs immediately after the earnings releases. Prices in AHT show a large degree of informational efficiency, further demonstrating the importance of price discovery in AHT. We also provide evidence suggesting that firms prefer after-hours earnings announcements, as trades are mainly from informed traders, and those trades are relied upon to convey information to the general public.

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R L, Manogna, and Aswini Kumar Mishra. "Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India." Journal of Agribusiness in Developing and Emerging Economies 10, no. 4 (May 23, 2020): 447–73. http://dx.doi.org/10.1108/jadee-10-2019-0175.

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PurposePrice discovery and spillover effect are prominent indicators in the commodity futures market to protect the interest of consumers, farmers and to hedge sharp price fluctuations. The purpose of this paper is to investigate empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets.Design/methodology/approachThis study uses Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) to examines the price discovery and spillover effects for nine most liquid agricultural commodities in spot and futures markets traded on National Commodity and Derivatives Exchange (NCDEX).FindingsThe VECM results show that price discovery exists in all the nine commodities with futures market leading the spot in case of six commodities, namely soybean seed, coriander, turmeric, castor seed, guar seed and chana. Whereas in case of three commodities (cotton seed, rape mustard seed and jeera), price discovery takes place in the spot market. The Granger causality tests indicate that futures markets have stronger ability to predict spot prices. Supporting these, the results from EGARCH volatility test reveal that there exist mutual spillover effects on futures and spot markets. Thus, it could be inferred that futures market is more efficient in price discovery of agricultural commodities in India.Research limitations/implicationsThese results can help the market participants to benefit by hedging out the uncertainty and the policymakers to design futures contracts to improve the efficiency of the agricultural commodity derivatives market.Practical implicationsThe findings provide fresh view on lead–lag relationship between future and spot prices using the latest data confirming that futures market indeed is dominant in price discovery.Originality/valueThere are very few studies that have explored the efficiency of the agricultural commodity spot and futures markets in India using both price discovery and volatility spillover in a detailed manner, especially at the individual agriculture commodity level.

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Farzanegan, Elham. "Time-varying price discovery in Bahar-e-Azadi Gold Coin spot and futures contracts." Investment Management and Financial Innovations 19, no. 3 (August 18, 2022): 153–66. http://dx.doi.org/10.21511/imfi.19(3).2022.13.

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This paper aims to analyze the daily price discovery of Bahar-e-Azadi Gold Coin (GC) spot and futures contracts in Iran, using the fractionally cointegrated error-correction model (FCECM). The residuals of the FCECM are modeled by the BEKK-GARCH specification to calculate the time-varying conditional information share between GC spot and futures prices. Using data covering December 21, 2008 to April 14, 2018, the paper establishes the novel finding that the GC spot and futures price series are fractionally integrated of orders 0.98347 and 0.95169, respectively. This implies the long memory behavior in the price series. Further, the results show that the series are fractionally cointegrated of order 0.542. The empirical findings from the methodology indicate that in the price discovery process, the GC spot market dominates the GC futures market. This analysis is robust to alternative construction of futures price series and sub-samples decomposed based on structural breaks. One possible explanation could be the higher trading volume associated with the GC spot market compared to the GC futures market. Incompleteness and market frictions also can cause a delay in the process of information incorporation into the futures market and may discourage market players from trading in these markets.

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Xu, Pei, Todd Lone, and Naydith Torres. "Market Integration and Price Discovery in California’s Almond Marketing: A Vector Auto-Regressive (VAR) Approach." International Journal of Business and Management 17, no. 9 (August 3, 2022): 43. http://dx.doi.org/10.5539/ijbm.v17n9p43.

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California almonds production and marketing have been the focus of the state’s economy. Since almonds are a high-cost food product facing high market price volatility, reducing price forecasting error increases the likelihood of success (profitability) at the farm level. By focusing on the linkage between the local wholesale inshell price from 2015 to 2021 and international export prices to major trading partners in Europe and Eastern Asian countries, this study contributes to understanding how export prices affect the farm level wholesale price and what causes price shocks in the system. A clear result of this study is farmers can rely on current market price when forecasting local almond price in the short run of upcoming two months.  This study also finds the California local almond wholesale market is integrated into the world almond market, as well as the markets of its trading partners in Europe and East Asia. Specifically, when U.S. export price to the world increase in the current month, its export price to East Asian countries will automatically adjust and decrease in the following months. Lastly, analysis of the sample of prices considered in this study does not establish a long-run equilibrium nor market price integration.

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28

Mintert, J., and Ted C. Schroeder. "Alternatives to cash prices in fed-cattle price discovery." Kansas Agricultural Experiment Station Research Reports, no. 1 (January 1, 2000): 92–94. http://dx.doi.org/10.4148/2378-5977.1811.

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29

Lu, Chiuling, and Raymond W. So. "Price Discovery in the Taipei Residential Real Estate Market." Review of Pacific Basin Financial Markets and Policies 02, no. 04 (December 1999): 459–70. http://dx.doi.org/10.1142/s0219091599000254.

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The price discovery process of the Taipei residential real estate market is examined. Using data from the Ta-An District of Taipei City, empirical evidence indicates that there exists a causal relationship between rental rates and property prices. Results here suggest that the two real estate markets are linked together; hence investors and end users can use price information in one market to predict future movements of the other market.

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Thazhugal Govindan Nair, Saji. "Price discovery and pairs trading potentials: the case of metals markets." Journal of Financial Economic Policy 13, no. 5 (March 8, 2021): 565–86. http://dx.doi.org/10.1108/jfep-06-2020-0139.

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Purpose This study aims to validate the “expectancy theory” of asset pricing and explores the price discovery process in metals futures markets. Design/methodology/approach This paper adopts the Johansen cointegration and vector error correction model approach to investigate the potentials of Pairs trading in the metals market during the period 2008–2019. Findings The results find the price movements in metal markets are not random walk and the current “futures” prices are the reasonable estimate of the “spot” metal prices in future. This study does not notice any significant differences in the price efficiency across metals markets, which signal the effects of limited idiosyncratic forces in price transmission. Practical implications The research suggests the covert use of metal futures to make gains from arbitrage trading. Originality/value The study emphasizes the potential of “pair trading” in commodity market context that is seldom discussed in academic papers.

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Sharma, Prashant, Prashant Gupta, Dinesh Kumar Sharma, and Gaurav Agarwal. "Investigating the Efficiency of Bitcoin Futures in Price Discovery." International Journal of Economics and Financial Issues 12, no. 3 (May 17, 2022): 104–9. http://dx.doi.org/10.32479/ijefi.12783.

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The present study investigates the efficiency of the Bitcoin futures in the price discovery process by assessing the lead-lag relationship between the futures and spot prices of Bitcoin. The study tests whether the Bitcoin futures market is leading the price discovery mechanism for the Bitcoin spot market. The study considers daily closing prices of both Bitcoin spot and future indices from December 12, 2017 to December 31, 2020. The stationarity of the two time-series variables is tested using Augmented Dickey-Fuller test while the long-run co-integrating relationship is tested using Johansen Co-integration test. To test the long-run causality, the Error Correction Mechanism framework (ECM) is used while the Wald test is applied to assess the short-run causality between the Bitcoin future and spot prices. The results of trace and max-eigen statistics indicate that there is long term co-integrating relationship between Bitcoin futures and Bitcoin spot markets. The negative significant coefficient of error correction term indicates that there is long-run causality from the Bitcoin futures towards the Bitcoin spot market. The significant Chi-square test statistics of the Wald test suggest that there is short-run causality from the Bitcoin futures towards the Bitcoin spot market. This shows that the Bitcoin futures market is acting as a leading indicator and the Bitcoin spot market as a lagging indicator. Thus, it is concluded that the price discovery is taking place between Bitcoin futures and the Bitcoin spot market. With the entrance of the new information in the cryptocurrency market, it is first observed in the Bitcoin futures followed by the Bitcoin spot prices.

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Lee, Woo–baik. "An Empirical Analysis on Change in Price Discovery of KOSPI200 Futures Through Market Maturity Process." Journal of Derivatives and Quantitative Studies 14, no. 2 (November 30, 2006): 51–77. http://dx.doi.org/10.1108/jdqs-02-2006-b0003.

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This paper estimates the contribution of KOSPI200 futures to spot price discovery based on methodology of ‘information share’, which is suggested by Hasbrouck (1995). Using the intraday data covering sample period from year 1997 to 2003, I estimate information share with specification of Vector Error Correction Model. Main empirical findings are summarized as followings; First. estimate of information share is above 60 percent on average through-out the entire sample period. Second. the contribution of KOSPI200 futures to error correction increased during the recent year of sample period. showing that futures price have strong tendency to lead the spot price. Third. price discovery of KOSPI200 futures have significantly positive relationship with program trading volume and seems to increase under contango. These empirical findings explain the ‘market maturity effect’ that role of futures in spot price discovery enhances as cointegration between futures and spot prices strengthens and futures market countervails the arbitrage opportunity. In general. this paper presents that mature futures market Significantly contributes to spot market efficiency and price discovery process.

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Shrestha, Keshab, Ravichandran Subramaniam, and Thangarajah Thiyagarajan. "Price Discovery in Agricultural Markets." American Business Review 23, no. 1 (May 2020): 53–69. http://dx.doi.org/10.37625/abr.23.1.53-69.

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In this study, we empirically analyze the contribution of futures markets to the price discovery process for seven agricultural commodities using the generalized information share proposed by Lien and Shrestha (2014) and component share based on the permanent-temporary decomposition proposed by Gonzalo and Granger (1995). We find that most of the price discovery takes place in the futures markets with the exception of cocoa. Our results show that futures markets play an important role in price discovery process. These results are important to academicians, practitioners, policymakers as well as business leaders.

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Medrano, Luis Angel, and Xavier Vives. "Strategic Behavior and Price Discovery." RAND Journal of Economics 32, no. 2 (2001): 221. http://dx.doi.org/10.2307/2696407.

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Ellis, M. E. "Derivatives, Volatility and Price Discovery." CFA Digest 30, no. 2 (May 2000): 93–95. http://dx.doi.org/10.2469/dig.v30.n2.686.

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Kettler, Paul Carlisle, Aleh L. Yablonski, and Frank Proske. "Market Microstructure and Price Discovery." Journal of Mathematical Finance 03, no. 01 (2013): 1–9. http://dx.doi.org/10.4236/jmf.2013.31001.

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Kim, Jaeho, and Scott C. Linn. "Price discovery under model uncertainty." Energy Economics 107 (March 2022): 105833. http://dx.doi.org/10.1016/j.eneco.2022.105833.

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38

Schreiber, Paul S., and Robert A. Schwartz. "Price discovery in securities markets." Journal of Portfolio Management 12, no. 4 (July 31, 1986): 43–48. http://dx.doi.org/10.3905/jpm.1986.409071.

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Aitken, Michael, Niall Almeida, Frederick H. deB Harris, and Thomas H. McInish. "Financial analysts and price discovery." Accounting & Finance 48, no. 1 (March 2008): 1–24. http://dx.doi.org/10.1111/j.1467-629x.2007.00235.x.

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Biais, Bruno, and Isabelle Martinez. "Price Discovery across the Rhine *." Review of Finance 8, no. 1 (March 1, 2004): 49–74. http://dx.doi.org/10.1023/b:eufi.0000022157.66264.c1.

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De Jong, F., and P. C. Schotman. "Price Discovery in Fragmented Markets." Journal of Financial Econometrics 8, no. 1 (September 10, 2009): 1–28. http://dx.doi.org/10.1093/jjfinec/nbp015.

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Peri, Massimo, Lucia Baldi, and Daniela Vandone. "Price discovery in commodity markets." Applied Economics Letters 20, no. 4 (March 2013): 397–403. http://dx.doi.org/10.1080/13504851.2012.709590.

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Narayan, Paresh Kumar, Dinh Hoang Bach Phan, Kannan Thuraisamy, and Joakim Westerlund. "Price discovery and asset pricing." Pacific-Basin Finance Journal 40 (December 2016): 224–35. http://dx.doi.org/10.1016/j.pacfin.2016.08.009.

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Fassas, Athanasios P., Stephanos Papadamou, and Alexandros Koulis. "Price discovery in bitcoin futures." Research in International Business and Finance 52 (April 2020): 101116. http://dx.doi.org/10.1016/j.ribaf.2019.101116.

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Osler, Carol L., Alexander Mende, and Lukas Menkhoff. "Price discovery in currency markets." Journal of International Money and Finance 30, no. 8 (December 2011): 1696–718. http://dx.doi.org/10.1016/j.jimonfin.2011.08.004.

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Madura, Jeff, Nivine Richie, and Alan L. Tucker. "Trading Halts and Price Discovery." Journal of Financial Services Research 30, no. 3 (December 2006): 311–28. http://dx.doi.org/10.1007/s10693-006-0421-x.

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Brandvold, Morten, Peter Molnár, Kristian Vagstad, and Ole Christian Andreas Valstad. "Price discovery on Bitcoin exchanges." Journal of International Financial Markets, Institutions and Money 36 (May 2015): 18–35. http://dx.doi.org/10.1016/j.intfin.2015.02.010.

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Pagnottoni, Paolo, and Thomas Dimpfl. "Price discovery on Bitcoin markets." Digital Finance 1, no. 1-4 (March 27, 2019): 139–61. http://dx.doi.org/10.1007/s42521-019-00006-x.

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Frijns, Bart, and Peter Schotman. "Price discovery in tick time." Journal of Empirical Finance 16, no. 5 (December 2009): 759–76. http://dx.doi.org/10.1016/j.jempfin.2009.07.002.

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Riordan, Ryan, and Andreas Storkenmaier. "Latency, liquidity and price discovery." Journal of Financial Markets 15, no. 4 (November 2012): 416–37. http://dx.doi.org/10.1016/j.finmar.2012.05.003.

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