Price and Price Range Prediction in Financial Markets

The call auction is a widely used trading mechanism, especially during the opening and closing periods of financial markets. In this paper, we study a standard call auction problem where orders are submitted according to Poisson processes, with random prices distributed according to a general distribution F, and may be cancelled at any time. We compute the analytical expressions of the distributions of the traded volume, of the lower and upper bounds of the clearing prices, and of the price range of these possible clearing prices of the call auction. Using results from the theory of order statistics and a theorem on the limit of sequences of random variables with independent random indices, we derive the weak limits of all these distributions. In this setting, traded volume and bounds of the clearing prices are found to be asymptotically normal, while the clearing price range is asymptotically exponential. All the parameters of these distributions are explicitly derived as functions of the parameters of the incoming orders' flows.

Download Full-text

Economic evaluation of asymmetric and price range information in gold and general financial markets

Journal of International Money and Finance ◽

10.1016/j.jimonfin.2017.03.001 ◽

2017 ◽

Vol 74 ◽

pp. 53-68 ◽

Cited By ~ 3

Author(s):

Chih-Chiang Wu ◽

Junmao Chiu

Keyword(s):

Economic Evaluation ◽

Financial Markets ◽

Price Range ◽

General Financial Markets

Download Full-text

Reference Prices and Turnover: Evidence from Small-Capitalization Stocks

Journal of Risk and Financial Management ◽

10.3390/jrfm14010029 ◽

2021 ◽

Vol 14 (1) ◽

pp. 29

Author(s):

Ashish Pandey

Keyword(s):

Financial Markets ◽

Reference Price ◽

Purchase Intention ◽

Firm Level ◽

Reference Prices ◽

Product Pricing ◽

Price Range ◽

Portfolio Managers ◽

Stock Market Investors

A large amount of literature in the field of social psychology and product pricing discusses the role of reference prices in affecting buyer’s price perception and purchase intention. Reference price denotes a standard against which the consumer compares the offer price of a product. In this paper, we investigate whether reference prices play any role in affecting the trading decision of stock market investors. We use firm-level, fixed-effect panel data methodology to empirically investigate whether investors respond to a violation of their internalized reference price range by executing a trading decision. Our results, based on a sample of Indian firms with small capitalization, show that investors respond to a violation of their internalized reference price range by executing a trading decision. However, consistent with the prior findings that investors suffer from myopic loss aversion, they continue to hold the positions when the reference price range is violated on the downside but sell stocks that have violated the high point of the reference price range. Our findings are robust for the reference price ranges that are constructed using the prior day’s trading prices, prior week’s trading prices, and prior year’s trading prices. The portfolio managers can develop a better understanding of expected trading intensity by incorporating reference price range in their models. The policymakers can use our results to find ways to improve the liquidity and efficiency of financial markets.

Download Full-text

The Total Return Swap Pricing Model under Fuzzy Random Environments

Discrete Dynamics in Nature and Society ◽

10.1155/2017/9762841 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Liang Wu ◽

Jun-tao Wang ◽

Jie-fang Liu ◽

Ya-ming Zhuang

Keyword(s):

Financial Markets ◽

Asset Price ◽

Jump Process ◽

Credit Spreads ◽

Random Environments ◽

Subjective Beliefs ◽

Price Range ◽

Double Exponential ◽

Asset Value ◽

Jump Diffusion Model

This paper models the jump amplitude and frequency of random parameters of asset value as a triangular fuzzy interval. In other words, we put forward a new double exponential jump diffusion model with fuzziness, express the parameters in terms of total return swap pricing, and derive a fuzzy form pricing formula for the total return swap. Following simulation, we find that the more the fuzziness in financial markets, the more the possibility of fuzzy credit spreads enlarging. On the other hand, when investors exhibit stronger subjective beliefs, fuzzy credit spreads diminish. Using fuzzy information and random analysis, one can consider more uncertain sources to explain how the asset price jump process works and the subjective judgment of investors in financial markets under a variety of fuzzy conditions. An appropriate price range will give investors more flexibility in making a choice.

Download Full-text