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on Market Microstructure |
| By: | Derick Diana; Tim Gebbie |
| Abstract: | We extend a Discrete Time Random Walk (DTRW) numerical scheme to simulate the anomalous diffusion of financial market orders in a simulated order book. Here using random walks with Sibuya waiting times to include a time-dependent stochastic forcing function with non-uniformly sampled times between order book events in the setting of fractional diffusion. This models the fluid limit of an order book by modelling the continuous arrival, cancellation and diffusion of orders in the presence of information shocks. We study the impulse response and stylised facts of orders undergoing anomalous diffusion for different forcing functions and model parameters. Concretely, we demonstrate the price impact for flash limit-orders and market orders and show how the numerical method generate kinks in the price impact. We use cubic spline interpolation to generate smoothed price impact curves. The work promotes the use of non-uniform sampling in the presence of diffusive dynamics as the preferred simulation method. |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.06079&r=mst |
| By: | Leilei Shi; Bing Han; Yingzi Zhu; Liyan Han; Yiwen Wang; Yan Piao |
| Abstract: | It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor's attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd's trading action in terms of behavior analysis, and test two adaptive hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade a stock in efficient adaptation except for simple heuristics, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction and competition among themselves no matter whether it is highly overestimated or underestimated. This suggests that asset prices include not only a fundamental value but also private information, speculative, sentiment, attention, gamble, and entertainment values etc. Moreover, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.05322&r=mst |
| By: | Peter Andre; Philipp Schirmer; Johannes Wohlfart |
| Abstract: | Investors’ return expectations are pivotal in stock markets, but the reasoning behind these expectations remains a black box for economists. This paper sheds light on economic agents’ mental models – their subjective understanding – of the stock market, drawing on surveys with the US general population, US retail investors, US financial professionals, and academic experts. Respondents make return forecasts in scenarios describing stale news about the future earnings streams of companies, and we collect rich data on respondents’ reasoning. We document three main results. First, inference from stale news is rare among academic experts but common among households and financial professionals, who believe that stale good news lead to persistently higher expected returns in the future. Second, while experts refer to the notion of market efficiency to explain their forecasts, households and financial professionals reveal a neglect of equilibrium forces. They naively equate higher future earnings with higher future returns, neglecting the offsetting effect of endogenous price adjustments. Third, a series of experimental interventions demonstrate that these naive forecasts do not result from inattention to trading or price responses but reflect a gap in respondents’ mental models – a fundamental unfamiliarity with the concept of equilibrium. |
| Keywords: | mental models, return expectations |
| JEL: | D83 D84 G11 G12 G41 G51 G53 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10691&r=mst |
| By: | Antigoni Polychroniadou; Gilad Asharov; Benjamin Diamond; Tucker Balch; Hans Buehler; Richard Hua; Suwen Gu; Greg Gimler; Manuela Veloso |
| Abstract: | Inventory matching is a standard mechanism/auction for trading financial stocks by which buyers and sellers can be paired. In the financial world, banks often undertake the task of finding such matches between their clients. The related stocks can be traded without adversely impacting the market price for either client. If matches between clients are found, the bank can offer the trade at advantageous rates. If no match is found, the parties have to buy or sell the stock in the public market, which introduces additional costs. A problem with the process as it is presently conducted is that the involved parties must share their order to buy or sell a particular stock, along with the intended quantity (number of shares), to the bank. Clients worry that if this information were to leak somehow, then other market participants would become aware of their intentions and thus cause the price to move adversely against them before their transaction finalizes. We provide a solution, Prime Match, that enables clients to match their orders efficiently with reduced market impact while maintaining privacy. In the case where there are no matches, no information is revealed. Our main cryptographic innovation is a two-round secure linear comparison protocol for computing the minimum between two quantities without preprocessing and with malicious security, which can be of independent interest. We report benchmarks of our Prime Match system, which runs in production and is adopted by J.P. Morgan. The system is designed utilizing a star topology network, which provides clients with a centralized node (the bank) as an alternative to the idealized assumption of point-to-point connections, which would be impractical and undesired for the clients to implement in reality. Prime Match is the first secure multiparty computation solution running live in the traditional financial world. |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.09621&r=mst |
| By: | Elif Feyza Özcan Kodaz; Serdar Yürek |
| Abstract: | In this paper, we examine firms’ price-setting decisions to identify underlying pricing behaviour and discuss their implications for aggregate inflation dynamics. By employing retail-product level micro price data from Türkiye, we first construct aggregate indicators of the average frequency and size of individual price changes. Second, we i) compare the behaviours of these indicators across low and high inflation environments, ii) utilize two large exchange rate shocks, three value-added tax (VAT) adjustments, and thirteen hikes in a sectoral cost indicator to show how firms react to large and sudden shocks. Our results indicate that firms adjust their prices more frequently during periods of high inflation and change their prices immediately after large-scale shocks. Despite the substantial variation in the frequency of price changes, there is either moderate or no movement in the size of price changes, suggesting that firms’ pricing behaviour fits perfectly into state-dependent pricing. These findings also show that pass-through of shocks to prices accelerates after large shocks and in high-inflation environments. Thus, standard models, which assume constant speed of pass-through from macroeconomic conditions to prices, may produce misleading forecasts. |
| Keywords: | Firm behavior, Inflation, Inflation forecasting |
| JEL: | L20 E31 E37 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:tcb:wpaper:2304&r=mst |