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Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.

Filter trading is a technical trading rule that has been used extensively to test the efficient market hypothesis in the context of long-term trading. In this paper, the authors adopt the rule to analyze intraday trading, in which an open position is not left overnight. This paper aims to explore the relationship between intraday filter trading profitability and intraday realized volatilities. The bivariate thin plate spline (TPS) model is chosen to fit the predictor-response surface for high frequency data from the Hang Seng index futures (HSIF) market. The hypotheses follow the adaptive market hypothesis, arguing that intraday filter trading differs in profitability under different market conditions as measured by realized volatility, and furthermore, the optimal filter size for trading on each day is related to the realized volatility. The empirical results furnish new evidence that range-based realized volatilities (RaV) are more efficient in identifying trading profit than return-based volatilities (ReV). These results shed light on the efficiency of intraday high frequency trading in the HSIF market. Some trading suggestions are given based on the findings.

Among all the factors that affect the profit of filter trading, intraday realized volatility stands out as an important predictor. The authors explore several intraday volatilities measures using range-based or return-based methods of estimation. The authors then study how the filter trading profit will depend on realized volatility and how the optimal filter size is related to the realized volatility. The bivariate TPS model is used to model the predictor-response relationship.

The empirical results show that range-based realized volatility has a higher predictive power on filter rule trading profit than the return-based realized volatility.

First, the authors contribute to the literature by investigating the profitability of the filter trading rule on high frequency tick-by-tick data of HSIF market. Second, the authors test the assumption that the magnitude of the intraday momentum trading profit depends on the realized volatilities and aims to identify a relationship between them. Furthermore, the authors consider several intraday realized volatilities and find the RaV have the higher prediction power than ReV. Finally, the authors find some relationship between the optimal filter size and the realized volatilities. Based on the observations, the authors also give some trading suggestions to the intraday filter traders.

This study investigates the impact of simultaneously replacing both midday single-price call auction and lunch break with multi-price continuous trading on intraday volatility–volume patterns as well as the intraday volatility–volume nexus.

The analysis utilises 150 m tick-by-tick transaction data related to 333 stocks traded on Borsa Istanbul Equity Market covering a period of 2 months prior to and following the change. In addition to graphic comparisons, the study uses difference in mean tests, panel-fixed generalized least squares (GLS), panel-random GLS and random-effects linear models with AR(1) disturbance regression estimations.

The results show that intraday volatility and trading volume form an inverse J-shape and are positively correlated. It is observed that the implementation of the regulation change decreased intraday volatility and increased trading volume. Additionally, the results indicate a negative volatility–liquidity and a positive volume–liquidity relationship, supporting the mixture of distribution hypothesis.

Enhanced market efficiency provides greater opportunity for investment and risk management. Investors can benefit from the findings on the intraday volatility–volume nexus, which is an indicator of informed trading, and regulatory authorities can use volume to oversight volatility.

This very rare regulation change of the simultaneous replacement of the lunch break and midday call auction with continuous trading is investigated in the context of intraday volume and volatility. This study also expands upon some important findings on the volume–volatility nexus for the Turkish Stock Market.

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.

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.

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.

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.

The purpose of this study is to analyze the overnight and intraday returns of the most traded American Depositary Receipts (ADRs) of Asian companies, understand the different levels of volatilities realized in these asynchronous markets and develop trading strategies based on empirical findings.

This study presents an empirical analysis on the overnight and intraday returns of Asian ADRs. The authors propose a measure to quantify the relative contributions of the intraday and overnight returns to the ADR's total volatility. Furthermore, the return difference between S&P500 index and each ADR is fitted to an Ornstein–Uhlenbeck model via maximum-likelihood estimation.

This study finds that ADRs' overnight returns are more volatile, whereas the intraday returns are significantly more strongly correlated with the US market returns. The return spreads between the S&P500 and ADRs are found to be a mean-reverting time series and motivate a pairs trading strategy.

The methodology used in this study is not limited to Asian ADRs and can be adapted to analyze the overnight and intraday returns of other non-Asian ADRs and stocks.

Investors should be aware of the overnight price fluctuations while intraday traders may consider strategies that capture the mean-reverting return spread between an ADR (or an Exchange-Traded Funds [ETF] of Asian stocks) and the S&P500 index ETF (SPY).

ADRs are among the most popular securities for investing in foreign (non-US) companies. The total global investments in ADRs are estimated to be close to US$1tn. Understanding the risks of ADRs is important to not only individual/institutional investors but also regulators.

This study provides a new measure to quantify and compare the relative contributions of volatility by overnight and intraday returns. Optimized pairs trading strategies involving ADRs and ETFs are developed and backtested.

Since the liberalization of electricity markets in the European Union, prices are subject to market dynamics. Hence, understanding the short-term drivers of electricity prices is of major interest to electricity companies and policymakers. Accordingly, this paper aims to study movements of prices in the combined German and Austrian electricity market.

This paper estimates an autoregressive model with exogenous variables (ARX) in a two-step procedure. In the first step, both time series, which inherently feature seasonality, are de-seasonalized, and in the second step, the influence of all model variables on the two dependent variables, i.e. the day-ahead and intraday European Power Energy Exchange prices, is measured.

The results reveal that the short-term market is largely driven by seasonality, consumer demand and short-term feed-ins from renewable energy sources. As a contribution to the existing body of literature, this paper specifically compares the price movements in day-ahead and intraday markets. In intraday markets, the influences of renewable energies are much stronger than in day-ahead markets, i.e. by 24.12 per cent for wind and 116.82 per cent for solar infeeds.

Knowledge on the price setting mechanism in the intraday market is particularly scarce. This paper contributes to existing research on this topic by deriving drivers in the intraday market and then contrasting them to the day-ahead market. A more thorough understanding is especially crucial for all stakeholders, who can use this knowledge to optimize their bidding strategies. Furthermore, the findings suggest policy implications for a more stable and efficient electricity market.

The purpose of this paper is to study the relation between financial analysts’ ratings of firms’ disclosure policies and the intraday pattern in spreads between specialists’ bid and ask price quotes.

Measure of the disclosure policy is based on financial analysts’ ratings of the quality of firms’ annual reports, quarterly and other information, and investor relations activities. The bid‐ask spread is the ask price minus the bid price. Time‐weighted bid‐ask spreads were measured over half‐hour trading intervals. Generalized method of moments is used to estimate regressions of bid‐ask spreads on disclosure policy ratings and controls for trading volume, price volatility, and share price.

It was found that spreads are uniformly lower for firms with higher‐rated disclosure policies in all half‐hour trading intervals during the day. In addition, increases in spreads in the first two half‐hours of trading are smaller for firms with higher‐rated disclosures. Finally, our evidence suggests spreads increase more in the last half‐hour of trading for firms with better disclosure policies, and subsequent tests suggest this is due to greater end‐of‐day liquidity trading.

These results suggest that disclosure policy is a determinant of both the level and pattern of intraday bid‐ask spreads. Firms with higher‐rated disclosure policies have a more liquid market for their shares, which is theoretically linked to a lower cost of capital. In addition, better disclosure mitigates the decrease in market liquidity typically observed at the open of daily trading.

Better disclosures can help reduce market frictions.

This paper is the first to study the relation between disclosure policy and intraday spread patterns.

The purpose of this research is to consider whether market wide herding occurs intraday.

Using the 1995 Christie and Huang and the 2000 Chang et al. models, the paper tests whether market wide and industry sector herding occurs intraday in the Australian equities market.

Neither market wide nor industry sector herding occurs intraday.

Both herding measures focus on one specific type of herding, herding evidenced by changes in the cross‐sectional return distribution. Therefore the herding measures are ill suited to capture the effects of period specific abnormally high or low market returns and they can also capture herding of market participants or groups of market participants only in as far as it manifests itself in security specific returns.

No previous studies have considered the possibility of intraday herding in equities markets. Even if there is little evidence of herding over longer time periods, market frictions and inefficiencies continue to be exploited at least anecdotally by traders with very short time horizons to the detriment of longer term investors.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

We investigate intraday data for KOSPI 200 index and KOSPI 200 index futures. Hourly theoretical futures prices are calculated based on cost of carry model. we compare hourly index futures prices with their theoretical prices. Consistent with a large body of previous researches in this area, we find the persistent deviation of futures prices from their theoretical prices. Futures prices are undervalued relative to their theoretical prices. The data indicate that the difference between futures price and its theoretical price exhibits U-shaped pattern over the trading hours. The differences are higher at open and at 15:00 and are lower over intraday trading hours, implying that previous studies using daily closing prices overstate this mispricing.

We also examine the effect of intraday spot return on the behavior of the difference between the hourly futures price and its theoretical price. The finding indicates that the intraday momentum generates U-shaped pattern of this mispricing. This contrasts with Kim and Park (2011)'s finding that the difference also increases as the prior 60 day spot return increases. Our finding invalidates their explanation the activities of arbitrageurs bring monotonic increasing pattern of the magnitude of this mispricing in their daily data.

We propose a new explanation the U shaped patttern of the difference between the futures price and its theoretical price generated by the intraday spot return's moment. We introduce risk-seeking trader in our new explanation. The trader's risk-seeking behavior is based on prospect theory (Kahneman and Tversky (1979)). We argue that the risk-seeking traders cause intraday momentum effect to generate the U-shaped pattern of this mispricing. We add speculator's variables to Kim and Park (2011)'s regression equation and estimate it. The results from the regression analysis lend support to our new explanation as well as theirs, implying that speculators and arbitrageurs are present and active in the spot and futures markets and generate different pattern of the mispricing.