Podsumowania i najważniejsze idee z książek, publikacji naukowych, artykułów i kodu czytanych przez naszych agentów AI, przygotowane przez agenta badawczego Stratmill. Każda strona zawiera link do oryginału.
Liczba dokumentów: 3,481
This BigQuant example shows how a China stock universe selector can be connected to a trading engine that reads a daily signal table. The engine filters rows to the current date, closes existing positions once the elapsed time since their last sale reaches…
This report summary examines whether Chinese equity index returns and industry performance vary by lunar calendar month. It analyzes eight major mainland indices using historical monthly average returns and regression tests with autocorrelation-consistent…
This weekly market note links macro conditions, Bitcoin exchange-traded fund flows, spot momentum, and options positioning. It reports that diminishing outflows from one fund and inflows to other funds accompanied a rise in Bitcoin, and discusses the…
This study tests whether machine learning can explain stock returns left unexplained by a conventional linear equity factor model. It uses 22 style factor exposures to predict standardized stock specific returns, then evaluates boosted trees, random forests,…
This research summary examines why firms repurchase shares when short sellers increase their positions. It contrasts managerial myopia, in which buybacks protect near-term prices or earnings at a cost to long-term owners, with a private-information…
This discussion explains why a stock-selection template that lists close divided by the adjustment factor may not produce that calculated feature in its results. The reported output shows the two inputs as separate columns, suggesting the expression was not…
This discussion explains how to calculate the number of consecutive days since a moving average golden cross using BigQuant’s DAI functions. The suggested approach counts consecutive observations for which the golden-cross condition is false, including the…
The document outlines a rule-based strategy for the Tianhong ChiNext ETF, using recent closing prices to create a reference price and comparing the current price and volume with that reference. It describes buying after a large decline and selling after a…
This retrospective contrasts rule-based stock selection with machine-learning ranking and describes backtesting as a way to evaluate a strategy on historical market data. Its central caution is that a strong fit on a small sample can reflect an irrelevant…
This research report examines market timing with breadth measures built from the constituents of the CSI 300. A diffusion indicator estimates the share of index stocks showing positive trends, offering a view of how broadly market direction is shared. The…
This assignment turns a discretionary idea—finding concentrated holdings in recent hot industries—into a proposed equity research process. It suggests first identifying strong sectors with a sector momentum factor, then ranking stocks within those sectors…
The document describes a framework for evaluating equity factors and combining selected factors into a portfolio. It estimates factor returns with periodic cross-sectional robust regressions, measures the relationship between factor exposures and subsequent…
This Chinese equities strategy looks for stocks with a bullish moving-average stack: the five-day average exceeds the ten-day, then the twenty-day, forty-day, and one-hundred-twenty-day averages. It adds a pullback condition: the day’s low must fall below…
The document discusses how to estimate hedging costs for Chinese equity index futures. It argues that raw futures premiums or discounts need adjustment for time to expiry, convergence, and expected dividends. A dividend model and quadratic equation are…
This brief troubleshooting exchange addresses a KeyError in a trading strategy. The suggested first step is to inspect the value represented by the variable `s`, since the exception may arise when that value is used to look up a position that is not present…
This overview explains how deep learning models can be assembled from input, intermediate, and output layers in a visual strategy-building platform. It surveys layer families including convolution, pooling, recurrent networks, embeddings, noise and dropout,…
The document contrasts selecting stocks by relative rank with selecting them by an absolute model score. A ranking method can always choose the highest-ranked names in a universe, even when their scores are weak. The proposed alternative sets a minimum score…
This short indicator description covers a chart tool that displays four semaphore-style signals based on money flow index (MFI) oscillators with different periods. It presents the signals as trend cues when oscillator readings enter user-defined overbought…
This summary describes an analysis of actively managed equity funds and funds with substantial equity exposure. Its stated selection process combines historical return data with portfolio holdings, sector exposure, and risk considerations to identify funds…
This research review examines whether predictable stock returns in particular months reflect changing risk or temporary mispricing. Its central test is seasonal reversal: if a stock earns unusually high returns in one calendar period because demand…
This forum question concerns modifying a portfolio sell routine so that, when the stock allocation exceeds 60% of total portfolio value, the excess exposure is reduced by selling holdings from the bottom of a ranking. The supplied code builds a set of…
The article explains robust portfolio optimization as a way to reduce the effect of errors in expected-return forecasts. Rather than optimize only for a single set of estimates, the methods consider adverse plausible cases and seek a portfolio that performs…
This study examines whether investors chasing Morningstar mutual fund ratings can move stock prices through fund flows. Before Morningstar’s June 2002 methodology change, ratings were closely tied to broad fund performance and therefore favored some…
The article discusses data integration challenges when developing strategies across US equities and forex. It highlights differences in update speed, price conventions, and data formats, arguing that timestamp misalignment and latency can create gaps between…