Microscopic understanding of heavy-tailed return distributions in an agent-based model

The distribution of returns in financial time series exhibits heavy tails. In empirical studies, it has been found that gaps between the orders in the order book lead to large price shifts and thereby to these heavy tails. We set up an agent based model to study this issue and, in particular, how the gaps in the order book emerge. The trading mechanism in our model is based on a double-auction order book, which is used on nearly all stock exchanges. In situations where the order book is densely occupied with limit orders we do not observe fat-tailed distributions. As soon as less liquidity is available, a gap structure forms which leads to return distributions with heavy tails. We show that return distributions with heavy tails are an order-book effect if the available liquidity is constrained. This is largely independent of the specific trading strategies

Strategies used as spectroscopy of financial markets reveal new stylized facts

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions and (iii) real investors to random strategies with respect to timing that share otherwise all other characteristics. We find that more trading results in smaller net return due to trading frictions. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by investors. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.Comment: 13 pages including 5 figures and 1 tabl

PERSONALIZED IMMUNE DIAGNOSTICS: EPITOPE MAPPING OF THE IMMUNOME

Statistical phage display is a highly complex, but rapid and efficient way to identify “binding peptides” from a unique and specially designed library. It avoids repeated selection rounds and can therefore provide much more complex data than just a few sequences usually obtained with repeated peptide library selection. The complexity of the data analyzed is sufficient to cover hundreds of potential binder/target combinations in parallel.Applying this novel way to generate and analyze data from peptide phage display with antibodies allows to predict potential epitopes at amino acid resolution. Fingerprinting of monoclonal antibodies reveals the large variety of peptides binding to any given antibody. Independent of such laborious and failure prone methods like peptide arrays or phage display with antigen gene fragments. Surprisingly easy this can explain the specificity of antibodies and it is a valuable tool for antibody quality control.Beyond the application to individual antibodies we are able to analyze the immunome of patient sera. Theoretically, there are hundreds of antibody molecules for each recently encountered antigen epitope in a few µl. This is enough to define individual antibody epitopes. Since a single patient sample allows to record the entire immunome data, there is a tremendous amount of information hidden in the data sets we obtain. Nevertheless, all patients show different epitope patterns and for the generation of diagnostic tools we must compare many different sera. Results from examples will be given for allergic disease, viral infection diagnostics and the vaccine imprint on the immunome of one individual patient history.In infectious disease diagnostics (e.g. EBV, COVID-19, influenza) epitope-based kits can provide a robust analysis of existing and past disease as well as effective monitoring of vaccine efficacy. The aspect that the immune system carries the memories of antigens at least for many months allows a complex analysis even identifying different viral strains in a single experiment.In allergic disease we carried out epitope mapping with hundreds of sera from patients with sensibilization to allergenic food ingredients. Predicted epitopes were validated by binding IgE and IgG from many more patient sera for the main food allergy agents. Since peptide epitope diagnostics do not suffer from the undefined cross reactivities of present methods, we are gathering now a rather different understanding of what food allergies really are. In particular, we can also use IgG measurement based on immunoassays with epitopes, which has been regarded as impossible.Presently we are extending our work also in auto-immune diseases connected to long-COVID and psychiatric diseases