Price Discovery Process Research Articles

The Pricing Model of Rice: Evidence from Thailand

Although the rice market in Thailand is linked tightly with the world market, it is fraught with government intervention policies from time to time. In 2011 the Yingluck Shinawatra government embarked the rice pledging scheme that aimed to bid up domestic paddy prices above the global market. Such scheme set the premium of 40-50 percent higher than the world price. Nevertheless, the program was discontinued in 2014. This paper attempts to shed light on how the price structure in Thailand was affected by government intervention policies. In particular, we conducted a field survey to unearth the transmission mechanism that channel information about market factors on prices in various levels, ranging from world rice price to the wholesale paddy prices. The findings show that the paddy price was mainly determined by the rice mill, the central paddy market, the middleman, and the exporters. The government intervention policies could influence the paddy price temporarily, i.e., when the scheme was in place. In the long-run equilibrium, the paddy price is determined by a combination of the price at which the mills are willing to buy and the world price. Our empirical investigation, based on the Engel-Granger Cointegration test and the Error-correction model, confirms this conjecture. Moreover, the price expectation embedded in the millers’ offer price played a significant role in the price discovery process. The causality test revealed that the expected future price causes the spot wholesale price in the Granger sense. It is also found that the causation is bi-directional implying that the flows of information between markets are essential in determining the equilibrium price in the rice market.

Algorithmic trading and market quality: Evidence from the Taiwan index futures market

AbstractThis study examines the effects of different algorithmic traders on market quality and the price discovery process, considering the impact of different trading strategies and market conditions. Algorithmic foreign institutions and proprietary firms act strategically, by monitoring market conditions. During stable market conditions, they supply liquidity, and this strategic activity both improves price efficiency and increases fundamental volatility. In more turbulent market conditions, algorithmic foreign institutions and proprietary firms instead demand liquidity, and their trading activity leads to an increase in price efficiency and a decrease in excessive volatility. Overall, algorithmic trades do not harm market quality.

Dynamic Information Flow between Spot and Future Markets in Agro-Commodities Markets in India

With globalisation in place after 1991 and other regulatory changes, commodity markets in India too have been developing at a fast pace. This article identifies the price discovery mechanism in some of the actively traded agricultural commodities on NCDEX, covering all the four active categories of commodities, namely, cereals, oilseeds, spices and guar complex, using the data in the time period after SEBI has taken over as regulator of commodity markets in India. An extensive literature review is conducted to identify the various processes and factors leading to an efficient price discovery process in spot and future commodity markets. VAR model is used to model the daily price data of over six years for ten commodities and arriving at conclusions regarding causality and the direction of causality between spot and future prices of chosen agri-commodities. The findings would greatly help the Government, regulators and the investors to understand the price discovery behaviour in commodity markets and plan their interventions in a timely manner.

Listed real estate futures trading, market efficiency, and direct real estate linkages: International evidence

Futures contracts focused on listed real estate firms have increased in popularity in recent years, with strong developed markets now established in Australia, Europe, Japan, and the United States. This study builds upon what is still relatively small literature to consider two key elements. Firstly, using the approach of Bessembinder & Seguin (1992), we examine whether futures trading leads to a stabilization of listed real estate. The results show that the inception of listed real estate futures contracts does have a stabilization effect by improving the market efficiency and reducing market noise in international real estate stocks. Secondly, we assess the impact of futures trading on price discovery using a Spline-GARCH model, panel analysis, and a Granger causality test. In particular, we examine the linkages with underlying private real estate. The empirical results reveal that reduced market noise of real estate stocks via the futures trading improves the price discovery process, leading to enhanced linkages between public and private real estate, as well as market fundamentals.

Informativeness of CME Micro Bitcoin Futures in Pricing of Bitcoin: Intraday Evidence

This study is the first to measure the informativeness of Chicago Mercantile Exchange(CME)-traded Micro Bitcoin futures (MBT) by exploring its contribution made to the price discovery process and realized volatility spillover of CME Bitcoin futures (BTC) and underlying Bitcoin spot markets. Hasbrouck's information share, and Lien and Shrestha's modified information share suggest that MBT contributes approximately equal or slightly greater proportion to price discovery with BTC. The dominance of MBT is marginally higher in Bitstamp and itBit compared to Coinbase and Kraken. The Diebold and Yilmaz index suggests bi-directional realized volatility spillover between CME futures and between Bitcoin and MBT.

Factors Affecting Spatial Autocorrelation in Residential Property Prices

Within housing literature, the presence of spatial autocorrelation (S.A.) in housing prices is typically examined horizontally in a two-dimensional setting. However, in the context of apartment buildings, there is also a vertical component of S.A. for housing units located on different floor levels. This paper therefore explores the determinants of both horizontal and vertical S.A. within residential property prices. First, we posit that S.A. in housing prices is a consequence of the price discovery process of real estate, in which property traders acquire price information from recent market transactions (i.e., comparables) to value a subject property. Furthermore, we contend that the extent to which property traders rely on comparables to determine housing prices is governed by the liquidity and volatility conditions of the market, which in turn affects the magnitude of the S.A. By developing and testing several spatial autoregressive hedonic models using open market transaction data for the Hong Kong residential property market, we find that market liquidity tends to increase both vertical and horizontal S.A., whilst market volatility is more prone to increase vertical S.A. but depress horizontal S.A.

The impact of global economies on US inflation: A test of the Phillips curve

Understanding the relationship between employment and inflation is of great interest to policymakers and market participants. This paper introduces a new global inflation measure based on the principal component analysis (PCA) of the inflation rates of major US trade partners. We find that US domestic inflation correlates strongly with global inflation in the short- and long term. Moreover, global inflation leads the US inflation and accounts for 80% of the price discovery process. Additionally, we show that the Phillips curve equation improves in-sample and out-of-sample forecasting of US inflation rates by incorporating our spill-over-based global inflation (SGI) measure. Also, the utilization of the SGI in the Phillips equation increases the responsivity of the inflation rate data to the unemployment gap by 37%. In summary, the present results support the hypothesis that global inflation is a crucial determinant of domestic (US) inflation. The paper's main findings draw vital policy implications that emphasize the need for stronger cooperation among central banks to cope with the spill-over effect of global inflations on domestic economies.

Investigating the Efficiency of Bitcoin Futures in Price Discovery

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.

A Multi-market Comparison of the Intraday Lead-Lag Relations Among Stock Index-Based Spot, Futures and Options.

Using 1-min data, we explore the dynamic variation of the intraday lead–lag relations between stock indices and their derivatives through a comprehensive study with broader coverage of research objectives and methodologies. This paper provides explicit evidence that the futures and options exhibit price leadership over the spot market, and the options is ahead of the futures on most trading days in all three markets. This paper also reports a new finding that the relation between the derivative and its underlying index reverses when the index return has a significantly larger mean value, and the reversal phenomenon is also observed in the relations between the futures and the options, which enriches the empirical results of intraday lead–lag relations. Moreover, these conclusions still hold under the impact of extreme events, e.g., the outbreak of the Covid-19. Finally, we construct a pair trading strategy based on the intraday lead–lag relationships, which can get better performance than the corresponding spot index. Our findings can potentially help regulators understand the price discovery process between the index and its derivatives, and also be of great value for timely adjustment of investors intraday trading strategies.

Short sales, short risk, and return predictability in Asia-Pacific real estate markets

This paper investigates the information content of short sales across Asia-Pacific real estate markets. While the transparent nature of securitized real estate markets within the United States may render short selling activities relatively uninformative with respect to future firm values, such relations have not been broadly explored with respect to the rapidly developing Asia-Pacific region. Within this more informationally opaque market setting, we find evidence that short selling is significantly riskier than shorting in the U.S. Moreover, such risks may well influence investor behavior, as lower levels of shorting are observed across listed Asia-Pacific real estate firms than their U.S. based counterparts. Finally, we also document short sale considerations within this market sector are more informative with respect to future return predictability than similar signals observed for U.S. listed real estate firms. Specifically, increased levels of short interest outstanding, as well as elevated levels of exposure to short sale risk, both exhibit significant (negative) predictive ability over future equity returns. As such, we conclude the relative opacity of international equity markets creates limits to arbitrage, and thereby hinders the efficiency of the price discovery process for listed property companies across the Asia-Pacific region.

The information content of ETF options

We examine the information content of China's Shanghai Stock Exchange (SSE) 50 ETF options introduced in 2015. Trading volume and implied volatilities of calls versus puts differ markedly: trading volume is consistently higher for calls, and implied volatility is higher for puts. Put-call volume and implied volatility ratios are not good predictors of future SSE 50 returns. Implied volatility follows a right-skewed smirk across strike prices, indicating a tendency among option traders to turn bullish and expect the stock market to recover from the June 2015 market crash. The options market dominates the price discovery process, with an average information leadership share of 67%. Our price discovery results persist during the COVID outbreak.

Price Discovery and Volatility Spillover in Commodity Futures and Spot Market in India: An Empirical Analysis

Purpose: This paper aims to investigate the price discovery process, persistence of volatility and spillover of volatility in commodity futures and spot market in India. Methodology: In this paper, commodities namely, mentha oil, cotton, gold and aluminium have been selected to explore the process of price discovery, volatility persistence and spillover of volatility using cointegration test, vector error correction (VECM), granger causality and GARCH model. Findings: The results of VECM suggest that price discovery takes place in futures market in case of all commodities except for mentha oil where price discovery occurs in spot market. The Block Exogeneity Wald test (granger causality) results also show that futures market has stronger ability to predict the spot prices. The results of GARCH model indicate that volatility is persistent for all commodities except mentha oil futures return. In the support of VECM and granger causality test results, GARCH model results also indicate that volatility spillovers from futures return to spot return for all selected commodities except cotton where volatility spillovers from spot return to futures return. Practical Implications: The findings of this study significantly contribute to the Indian commodity derivatives market literature and useful for future researchers, investors, hedgers, economists and policy makers. Originality: There are very few studies that have examined the price discovery process and spillover of volatility using combination of both agricultural and nonagricultural commodities in India.

Informed trading in the CDS and OTM put option markets

This paper investigates the role of liquidity in the price discovery process. Specifically, we focus on how informed traders straddle the credit default swap (CDS) and option markets, with OTM put options particularly, and how their choice where to trade depends on the relative liquidity in these markets. We employ daily data of the two most actively traded North American CDX Investment Grade and High Yield indexes from 2010 to 2018. Our empirical results show that relative liquidity is a key factor in where informed trading occurs in CDS and put option markets. Our results suggest that liquidity is the main factor that determines the leadership of the price discovery process between the two markets. When the CDS market is relatively illiquid, informed investors trade in the options market such as OTM put options.

Reconnoitering Price Discovery and Market Efficiency Process Among Indian HRITHIK Stocks Using VAR Causality and VECM Tests

The purpose of this paper was to ascertain the impact of futures prices on market efficiency and price discovery in India in HRITHIK stocks from 2017 – 2020. The paper investigated the impact of futures prices on market efficiency and price discovery in India in HRITHIK stocks from 2017 – 2020. The current study comprised the daily near-month futures and daily spot closing prices of the HRITHIK stocks from January 1, 2017 – December 31, 2020, including the COVID-19 pandemic period. The paper used the vector autoregression (VAR) Engel Granger causality test to test the short-run equilibrium between spot and futures prices and the vector error correction model (VECM) to test for long-run equilibrium. A bi-directional relationship was found among six stocks out of the seven HRITHIK stocks. This confirmed the causal relationship that futures prices have on the spot prices. The VAR Engel Granger causality test indicated that the spot market narrowly led the futures despite a bi-directional flow of information. The results from the VECM model proved that the futures market acted as the dominant market in the long - run. Usually, researchers have leveraged sector-wise stocks to provide insights into the futures market’s function in price discovery. For the first time, HRITHIK stocks were analyzed to examine the cause-and-effect relationship for individual stocks in India’s futures and spot markets. The study considered the pre-COVID 19 and the post-COVID 19 periods and investigated the impact of the pandemic on these stocks. The research used daily closing prices of HRITHIK stocks; however, intraday data could be more conclusive and accurate in revealing the dominant market.

Filing speed, information leakage, and price formation

This study investigates the price discovery process in equity markets with informed institutional investors. Consistent with extant theories, we show empirically that institutional investors, in contrast to retail investors, trade based on the leaked sign of unanticipated news and then (partially) reverse their trades when the news become public. We also find that the longer the leakage period for institutional investors to exploit, the less informative the news is when it becomes public. These results are robust to controls for firm press releases and news articles and endogeneity concerns.

Real-time price discovery via verbal communication: Method and application to Fedspeak

We study the price discovery process on FOMC days. For several asset classes, we find that price movements around the post-meeting statement release are strong predictors of price movements around the subsequent press conference. The correlation is 58% for medium-term Eurodollar futures and 44% for the S&P500 index. We then time-stamp the words pronounced in press conference videos and align these words with high-frequency financial data. Minutes in which the chairman discusses changes in the newly issued policy statement underlie the positive correlation. We discuss potential explanations and consider the implications of our findings for asset pricing and monetary economics.

Price Discovery of Currency Futures at NSE

The current study aimed to examine the causal relationship between the NSE currency future rates and currency spot rates in order to identify the price discovery mechanism at NSE market and its integration with foreign exchange market (spot market). To study the causal relationship between the said markets, we have considered daily closing rates for NSE currency futures and currency spot rates for selected pairs of currencies, i.e. USD/INR, GBP/INR, JPY/INR and EURO/INR. The data was obtained from www.nseindia.com and www.investing.com for the period from Jan-2010 to Sep-2017, which makes approximately 1750 observations for each currency pair in each market. It is found that the spot rate for JPY/INR leads the future rate. It is also identified that the spot rate for USD/INR does not cause the changes in futures. It indicates that the market integration between spot and futures at NSE for currency pair USD/INR is strong compared to other selected currency pairs. From the variance decomposition test we found that there is almost no impact of variance in USD/INR spot rate on future rate variance forecast errors. It implies that the causal relationship between for USD/INR spot and future rates is strong and mature compared to the measured causal relationships for the remaining currency pairs. This study concludes that the price discovery process for currency pair USD/INR is better at NSE currency futures among the selected currency pairs.

Do as Essay, Not as I Do? How Inflated List Prices of Unsold Essayer Homes Affect the Price Discovery Process

Do as Essay, Not as I Do? How Inflated List Prices of Unsold Essayer Homes Affect the Price Discovery Process

Do As Essay, Not As I Do? How Inflated List Prices of Unsold Essayer Homes Affect the Price Discovery Process

Do As Essay, Not As I Do? How Inflated List Prices of Unsold Essayer Homes Affect the Price Discovery Process

The Role of CDS Market in the Price Discovery Process of the “PIIGS” Countries Sovereign Credit Risk During the Recent Decade of Monetary Easing

Abstract The aim of this paper is to analyze the long-lasting dynamic relationship between the credit default swap (CDS) premia and the government bond spreads (GBS), with regard to the sovereign credit risk. The practical focus is to evaluate whether the CDS market effectively is the leading or the lagging market in the credit risk price discovery process during the last decade of monetary easing. The analysis extends to all “sensitive” countries in the Eurozone, the so-called “PIIGS” countries (excluded Greece) for the interval 2007-2017. JEL classification numbers: G01, G12, G14, G20. Keywords: CDS spread, Government bond spread, Sovereign credit risk, Cointegration, Vector error correction model, Granger-causality.