Price Bias Research Articles

Estimating Asymmetric Fuel Price Responses in Croatia

Abstract Background According to many studies, the transmission of oil prices to retail fuel prices is asymmetric. Fuel prices react faster if oil prices rise and more slowly if oil prices fall. Different standard econometric procedures lead to different results. The Linex approach, which is based on formulating the non-linear adjustment cost function, reflects the theory. It uses the generalised method of moments to estimate the reaction functions, which demands many observations. Objectives The paper investigates the price asymmetry in the Croatian retail fuel market using standard approaches and the Linex approach. Methods/Approach The simple and dynamic asymmetry models, error correction models, threshold autoregressive co-integration, and the Linex approach are used to verify the hypothesis of asymmetric reactions of gasoline and diesel prices in Croatia. Results The results using the standard methods are mixed, while the Linex approach indicates price asymmetry, the size of which is measured with the average price bias. The results correspond to other studies worldwide. Conclusions The authors' preferred Linex approach detects price asymmetries, even with large data samples with frequent changes in trends and volatilities. According to the approach, the question is not whether prices are formed asymmetrically but the size of the asymmetry.

Small price bias in the cryptocurrency market. A cognitive bias revealed by emotions on social networks

Cognitive biases influence cryptocurrency market outcomes. Of relevance for this work, investors react variably to low-priced cryptocurrencies, evident in market outcomes like volatility. We investigate whether low prices also drive emotional responses on Twitter. Results show emotions align with price levels, with stronger reactions to lower prices. We conclude that small prices affect investor emotions.

Persistent and transient variance components in option pricing models with variance-dependent Kernel

This paper examines theoretically and empirically a variance-dependent pricing kernel in the continuous-time two-factor stochastic volatility (SV) model. We investigate the relevance of such a kernel in the joint modeling of index returns and option prices. We contrast the pricing performance of this model in capturing the term structure effects and smile/smirk patterns to discrete-time GARCH models with similar variance-dependent kernels. We find negative and significant risk premium for both volatility factors, implying that investors are willing to pay for insurance against increases in volatility risk, even if it has little persistence. In-sample, the component GARCH model exhibits a slightly better fit overall and across all maturity buckets than the two-factor SV model. However, the two-factor SV model reduces strike price bias, giving rise to the model’s ability in reconciling the physical and risk-neutral distribution. Out-of-sample, the two-factor SV model has better fit to data.

Unveiling and mitigating bias in ride-hailing pricing for equitable policy making

AbstractRide-hailing services have skyrocketed in popularity due to their convenience. However, recent research has shown that their pricing strategies can have a disparate impact on some riders, such as those living in disadvantaged neighborhoods with a greater share of residents of color or residents below the poverty line. Analyzing real-world data, we additionally show that these communities tend to be more dependent on ride-hailing services (e.g., for work commutes) due to a lack of adequate public transportation infrastructure. To this end, we present the first thorough study on fair pricing for ride-hailing services by first devising applicable fairness measures to quantify this bias and then proposing novel fair pricing mechanisms to alleviate this bias. We present two pricing mechanisms to provide flexibility and account for different platform needs. By taking affordability into account and potentially providing discounts that may be government-subsidized, our approaches result in an increased number and more affordable rides for the disadvantaged community. Experiments on real-world Chicago ride-hailing data demonstrate worse scores for the proposed fairness metrics for rides corresponding to disadvantaged neighborhoods than those of a control group (random mix of neighborhoods). Subsequently, the results show that our fair pricing mechanisms eliminate this inequality gap. Our mechanisms provide a basis for the government and the ride-hailing platforms to implement fair ride-hailing policies.

Assessing proxies for market prices of thinly traded assets with scheduled cash flows

Pseudo-market prices of infrequently traded assets with scheduled cash flows – commercial real estate appraisals and matrix prices of commercial mortgage backed securities – are compared against a VAR model to assess the extent to which these widely-used proxies are grounded in economic fundamentals. Property appraisals fail to fully incorporate the economic fundamentals underlying commercial real estate transactions. During the financial crisis, CMBS matrix prices captured underlying economic fundamentals and exhibited little pricing bias. However, matrix prices no longer exhibited such economic discipline after the financial crisis. Incorporating VAR forecasts considerably improves the predictive ability of appraisals and matrix prices.

Efficiency of financial production process and its dependence on price anchors: Evidence from India

This paper measures the degree to which disclosed annual financial information assimilates into stock prices through the financial production process (FPP). Since it is established that price anchors impact investor trading decisions, the effect of proximity to chosen price anchors and the historical high and low prices on FPP efficiency is analysed for 611 Indian firms across 11 industries. Results show that a significant number of stocks are FPP inefficient, and the FPP efficiency is mean-reverting. Further, FPP efficiencies depend on proximity to price anchors, implying that FPP efficiency is a proxy measure of behavioural bias in stock prices.

Pricing levered warrants under the CEV diffusion model

Much of the work on the valuation of levered (and unlevered) warrants assumes that the volatility of the underlying state variable is constant. This paper extends the literature on warrant pricing to a more general assumption for the state variable process, the so-called constant elasticity of variance (CEV) process. The CEV model is well-known for its ability to capture some empirical observations found in the financial economics literature, namely the asymmetry between equity returns and volatility and the implied volatility skew. Using the CEV process, we are able to reduce pricing bias as the volatility becomes a function of the underlying state variable. We price European-style call warrants without restrictions on the debt maturity. When warrants have the same maturity as debt, it is possible to obtain closed-form solutions for warrants prices. When the maturity of warrants is different from the maturity of debt, prices can be computed numerically through very efficient and simple to implement valuation methodologies.

Does risk matter more in recessions than in expansions? Implications for monetary policy

We employ a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New Keynesian model with recursive preferences replicates these state-contingent responses when approximated to third order around its risky steady state due to a stronger upward nominal pricing bias in recessions than in expansions. Empirical evidence supports this state-contingent channel, and we show that it can greatly reduce the ability of systematic monetary policy to stabilize output during recessions.

Hidden Tax Analysis of Premium Level for Sanitary Napkins and Adult Diapers

As the social attention on womens dilemma, some unfair regulations have raised a heated discussion, and the pink tax which is a hidden tax levied on homogeneous products consumed by women, and most of those products have the same quality and raw material, but higher prices when it is marketed as female-targeted goods. In this paper, unlike the previous researches focusing on pink tax in united industry, it shows the price disparities also exist on conventional women commodity, and mainly investigate the similarity and difference of sanitary napkins and adult diapers. By analyzing the costs of raw material, comprehensive applications and market prices of both kinds of products, calculating and comparing the net profit margins of the two industries, the results confirm the existence of price disparity on these two goods under similar costs, but because of the lack of database and specific cases, further researches are necessary for verification. This work may widen peoples horizon on pink tax, which is not limited on the comparison of opposite genders products, but the price bias on feminine goods, and it can promote Economics gender equality.

43365 Minority Hair Tax: Pricing Bias in Haircare Products

43365 Minority Hair Tax: Pricing Bias in Haircare Products

Air pollution, bid price bias, and IPO underpricing

We examine the impact of air pollution on underpricing of initial public offerings (IPOs) and its underlying mechanisms. Our findings suggest that IPO underpricing increases when air pollution is more severe in cities where bidding investors are located. Mechanism tests show that air pollution influences investors' mood and cognition, leading them to make pessimistic bids and rely more on anchors. Additional tests document that the impact of air pollution on IPO underpricing is more salient when information asymmetry is more severe and when the IPO firm also faces severe air pollution. Our research contributes to the literature on the causal influence of air pollution on pricing efficiency in primary markets by linking air pollution to potential bias embedded in investors’ bid prices, which carries important implications for environmental regulations in emerging markets, given the economic cost of air pollution imposed on IPO firms.

The Multi-horizon Exchange Rate Exposure of Consumer Products and Services Sector in Malaysia

After the abolishment of fixed exchange regime under the Bretton Woods System in 1970s, the issue of foreign exchange risk expecially among multinational corporations operating under small and open economies of Malaysia remains relevant till today. According to Abdul Wahab et al. (2017) and Adler and Dumas (1984), exchange rate exposure refers to the extent of firm's sensitivity to exchange rate fluctuations. While there has been growing interest in examining foreign exchange risk incidence under Malaysia market, however limited studies have been focusing on single sector of consumer products and services in Malaysia. Under Bursa Malaysia, the sector consists of several sub-fields including agricultural products, automotive, food and beverages, household goods, personal goods, retailers and travel and leisure services. Given the wide range of products and services, the corporations under the sector have been involved in vigorous cross-border trading activities. The consumer products and services equities become the second largest sector in Bursa Malaysia which constitues 15.89% of total stocks in main market of Bursa Malaysia in July 2021 with a 265.02 billion of total market capitalization. In terms of methodological issue, the study addresses on the bias in exchange risk pricing in previous studies. Specifically, majority of past studies assume homogeneity of exchange risk across time domains which seems to be unrealistic. Capital market contains wide range of participants with heterogenous investment holdings and expectations. To address time domain bias, the study adopts Maximal Overlap Discrete Wavelet Transformation (MODWT) in foreign exchange risk pricing to decompose a single time domain series into multiple time domains. Given this, the primary objective of the study is to examine the extent of multi-horizon foreign exchange exposure of consumer products and services sector in Malaysia from January 2000 till December 2020. Keywords: Currency Exposure, Wavalet Technique, MODWT, Malaysian Consumer Sector

Asymmetric Reactions of Retail Gasoline Prices on the Changes in Crude Oil Prices in Chosen US Cities

Many empirical studies state that retail gasoline and diesel prices react more quickly when the crude oil price rises rather than decreases. In the paper, we confirm these asymmetric reactions of retail fuel prices in selected cities in the United States of America. We use the adjustment cost function in the linear-exponential form to derive nonlinear retail gasoline and diesel reaction functions. The correspondent model is estimated with the system's generalised method of moments. The model allows us to compute average one-gallon gasoline and diesel price biases from the increase in oil by one dollar per barrel caused by the given asymmetric reactions. The average biases differ from city to city; their values are between 0.02 cents in Los Angeles and 0.44 cents in Cleveland.

Anchoring on Historical Round Number Reference Points: Evidence from Durable Goods Resale Prices

This paper examines how people price the resale of durable goods in systematically biased ways. We show across four studies that the anchoring effect of durable goods’ prior sales prices on subsequent valuations is discontinuous at psychologically salient round number reference points (e.g., $10,000 increments) because these numbers create qualitative differences in how people perceive values below them versus values at/above them. Resellers set disproportionately larger subsequent prices when previous prices move from just below round number thresholds (e.g., $349,000) to those at or just above these thresholds (e.g., $351,000). The findings show that buyers who pay a price just below a round number, therefore, may sacrifice money because they receive disproportionately less when reselling the good. Market forces only partially attenuate this pricing bias, but valuator experience seems to play a moderating role. Archival data show that home buyers who previously paid just under a $10,000 reference point subsequently listed their homes for about 1.8% (over $3,700) less on average than did buyers selling comparable homes who previously paid at or above a round number threshold. This drop is observable controlling for home characteristics and the general relationship between previous and current prices. Three experimental studies looking at housing and used car markets replicate these findings, highlight the mechanism, and increase confidence in causality. Market mechanisms and the negotiation process attenuate discontinuities by about 30%, but lower initial listing prices persist to final sales prices. We find additional weak evidence suggesting that valuator experience may attenuate intergenerational pricing bias. Conflict of Interest: This manuscript was submitted, revised, and accepted prior to the nomination and appointment of Lamar Pierce as Editor-in-Chief. Funding: This project was supported by the University of Southern California Marshall School of Business Behavioral Laboratory. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1632 .

Anchoring on Historical Round Number Reference Points

Buyers typically strive to negotiate low prices for durable goods. Psychologically-salient round number reference points (e.g., $10,000) influence these purchasing decisions. However, existing research does not capture how these historical reference points influence the anchoring effect of previous sales prices on future valuations. We argue that the anchoring effect of prior sales prices on subsequent prices is discontinuous at round numbers, such that it matters disproportionately whether a previous sales price reached a round-number threshold. Buyers paying a price just below a round number may sacrifice money because they receive disproportionately less when reselling the good. We further argue that while market forces are unlikely to attenuate this effect, highly-experienced professional intermediaries may. Using data on over 13,000 repeat real estate transactions, we find that home buyers who previously paid just under a $10,000 reference point subsequently list and sell their homes for about 1.3 percent (over $2000) less on average than do buyers selling comparable homes who previously paid at or above a round number threshold. This drop is observable controlling for home characteristics and the general relationship between previous and current prices. Buyers who cross a $10,000 threshold by paying $1000 more therefore would earn a return of 215%. An experiment with 1010 participants replicates these findings and increases confidence in causality. Market mechanisms, the negotiation process, and organizational support provided to intermediaries does not correct substantively for these discontinuities: Lower initial listing prices persist to final sales prices. However, using a highly-experienced agent attenuates intergenerational pricing bias.

Are retail investors less aggressive on small price stocks?

We investigate whether number processing impacts the limit order aggressiveness of retail investors. When posting non-marketable orders, individual investors are less aggressive on small price stocks than on large price stocks. This difference is not explained by differences in liquidity and other usual drivers of order aggressiveness. No such difference exists for limit orders of high-frequency traders. The small price bias is detrimental to retail investors since it increases the costs borne when trading small price stocks.

Spot price biases in non-linear health insurance contracts

We study an apparent schism in the literature concerned with non-linear health insurance plans: consumers exposed to the same type of policy appear forward-looking and rational in their response to one policy feature – the end-of-year coverage reset – but not to another – that current prices depend on the year-to-date spending in a non-linear fashion. We exploit policy variation from within a unified institutional environment and uses of population-wide data. We replicate both phenomena empirically: consumers both shift the timing of their purchases in response to the end-of-year reset and react excessively to spot prices during the coverage year. Importantly, however, we show that also the end-of-year behavior is due to over-attention to short-run prices. Specifically, consumers respond entirely to the large and salient change in the spot price in connection with the reset of the coverage year, conditional on the true expected price change. We find that liquidity constraints, rather than plan literacy and cognitive decline are important for understanding the spot price bias.

Prévisions d’analystes financiers et ordre de grandeur des prix : une approche expérimentale

La littérature récente en comptabilité et en finance montre que le niveau des cours des actions influence les prévisions de prix des analystes (Roger, Roger et Schatt [2018]). Dans le présent article, nous montrons que ce résultat reste valide dans le cadre contrôlé du laboratoire quand des sujets doivent prévoir les prix futurs sur un marché expérimental auquel ils ne participent pas. Chaque sujet fait des prévisions lors de deux marchés successifs : l’un pour lequel la valeur fondamentale est faible et l’autre pour lequel la valeur fondamentale est élevée. Bien que les prix de marché soient plus élevés (par rapport à la valeur fondamentale) sur les marchés à petits prix du fait du biais de « petit prix » des sujets traders, nos résultats indiquent que les prévisions des analystes sont plus optimistes sur les marchés à petits prix que sur les marchés à prix élevés. Les sujets analystes ancrent leurs prévisions sur les prix de marché passés et n’atténuent pas le biais des sujets traders. Nos résultats montrent ainsi que l’existence de ce biais de « petit prix » reflète l’utilisation par les sujets de deux échelles mentales différentes pour traiter petits et grands nombres. Classification JEL : G14.

A unified entropic pricing framework of option: Using Cressie-Read family of divergences

The entropy valuation of option (Stutzer, 1996) provides a risk-neutral probability distribution (RND) as the pricing measure by minimizing the Kullback–Leibler (KL) divergence between the empirical probability distribution and its risk-neutral counterpart. This article establishes a unified entropic framework by developing a class of generalized entropy pricing models based upon Cressie-Read (CR) family of divergences. The main contributions of this study are: (1) this unified framework can readily incorporate a set of informative risk-neutral moments (RNMs) of underlying return extracted from the option market which accurately captures the characteristics of the underlying distribution; (2) the classical KL-based entropy pricing model is extended to a unified entropic pricing framework upon a family of CR divergences. For each of the proposed models under the unified framework, the optimal RND is derived by employing the dual method. Simulations show that, compared to the true price, each model of the proposed family can produce high accuracy for option pricing. Meanwhile, the pricing biases among the models are different, and we hence conduct theoretical analysis and experimental investigations to explore the driving causes.

European option pricing using Gumbel distribution

A risk-neutral-density (RND) function plays a key role in determining option prices accurately. The RND function is useful in understanding the negative skewness and the excess kurtosis of the stock returns. RND models bases on the log-normal distribution (for example, Black–Scholes (BS) model (Black, F and M Scholes (1973). The pricing of options and corporate liabilities, The Journal of Political Economy 3, 637–654)) are less accurate to capture the negative skewness and the excess kurtosis of stock returns (Markose, S and A Alentorn (2011). The generalized extreme value distribution, implied tail index, and option pricing, The Journal of Derivatives 18(3), 35–60). The Extreme Value Theory (EVT) is useful in addressing the tail behavior of stock returns. The tail shape parameter in a Generalized Extreme Value (GEV) distribution class helps control tails’ size and shape. This paper model, the RND function in pricing the European call option, is modeled using a GEV distribution class, namely, a Gumbel distribution. It then compares GEV distribution option values with the BS values. It observes that the BS model underprices the call option values near maturity compared to those obtained by the GEV model. The Gumbel distribution for stock returns is useful in reducing the pricing bias of the BS model.