Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
1,116 documents
The document considers whether dedicated market makers are necessary for short-term directional trading. It frames market making as compensation for liquidity provision and asks whether informed directional traders gain when they trade against less informed…
The document explains time endogeneity in financial sampling as dependence between observation times and the value of the process being observed. It notes that correlation alone is too narrow a definition because it measures only linear dependence. In the…
The discussion surveys ways Fourier analysis can be applied in quantitative finance while cautioning against treating observed stock prices as periodic signals that can be extrapolated for forecasts. Its clearest established use is option valuation: when a…
The document raises a real-time data consistency problem in algorithmic trading. A model derives an ETF’s implied volatility from quotes for hundreds of components, but quote updates may arrive while a full recalculation is underway. The author asks how to…
The document raises a modeling question about tick-by-tick and high-frequency market data, especially in market making. It asks whether practitioners generally favor pure-jump processes, such as the variance gamma model, over diffusion models and sometimes…
The discussion compares predicting returns continuously with evaluating a model only after selected market events or conditions. It frames event-based prediction as a way to avoid unnecessary reevaluation and potentially reduce noise, while stressing that…
The discussion surveys whether Scala is used in trading and how it compares with other languages for financial software. Contributors report Scala use at a trading firm and describe JVM integration as a practical advantage for teams with Java systems.…
The document asks how to sell a large cryptocurrency position quickly while limiting market impact. It contrasts an immediate market order, which may consume multiple levels of the order book, with splitting the trade over time, which may reduce price…
The document asks whether separate foreign-exchange quote changes can share the same timestamp when data are recorded to millisecond precision. An answer based on an exchange-traded FX contract reports measuring intervals between top-of-book changes on a…
The document describes how to locate listed symbols and retrieve trade and bid/ask records from Netfonds. It identifies exchange codes for several markets and explains that the records are organized by date and symbol. Example rows show trade timestamps,…
The discussion presents realized kernels as a combination of intraday volatility estimation and kernel smoothing. It advises checking for sampling-frequency effects such as the signature-plot pattern and choosing a kernel time scale suited to real data,…
The document asks where to obtain real-time market data at millisecond or microsecond intervals for charting many symbols together. The team describes a visualization workload involving hundreds or thousands of feeds and says its desired feed would combine…
The document asks whether techniques with normality assumptions, such as vector autoregression, can be applied to high-frequency observations when prices move in discrete ticks and show autocorrelation. It uses a quote-revision model relating mid-price…
The document explains why limit orders in the book can matter even though they do not immediately set the last traded price. Depth shows the available liquidity at multiple price levels, helping estimate how an aggressive order may execute and how far it…
The document discusses building a micro-price from limit order book data to forecast short-term prices in futures and related instruments. It proposes progressively richer weighted-price estimates: start by incorporating best bid and offer quantities, then…
The document explains how to recover the inventory-dependent value function in an exponential-utility market-making model formulated through a Hamilton–Jacobi–Bellman equation. The central step is to set the terminal value for each inventory state, transform…
The document compares ways to reduce high-frequency order book data, emphasizing that the right sampling scheme depends on the modeling goal. Options include recording snapshots at trades, top-of-book changes, price ticks, volume thresholds, level formation…
The question asks whether directional order-flow signals can help predict prices over very short horizons, including periods as brief as 100 milliseconds. The answer points to research on incorporating signals into optimal trading, using signed order…
The document considers how to evaluate an automated strategy whose entry decisions depend on Level 2 order book data. The trader can obtain historical tick data through their broker but lacks historical market depth for the CME and Globex equity index…
The document responds to a newcomer’s request for resources on algorithmic execution, including market fundamentals, relevant mathematics, and newer research. It recommends books spanning market microstructure, financial mathematics of liquidity, algorithmic…
The document discusses repeated trade records that share a displayed timestamp and price but report different quantities. Its main explanation is that the source may round or aggregate event times to millisecond precision, making distinct executions appear…
The document explains why an order-management protocol distinguishes amending an existing order from canceling it and submitting a new one. A cancel-replace request can reduce the time spent waiting between cancellation and resubmission, while keeping an…
The document addresses an apparent disagreement between two weighted-midpoint formulas that combine top-of-book prices and displayed sizes. Its response argues that the appropriate interpretation depends on what the measure is meant to capture. A size…
The discussion surveys where GPUs and FPGAs may help in quantitative finance. GPUs suit highly parallel numerical workloads, such as solving partial differential equations with a small number of parameters. FPGAs can also parallelize computation and are…