In the first week of October the thirty-year Treasury yield closed at 5.60%, its highest since 2002. TLT, the long-bond fund in the three-asset, risk-balanced portfolio this publication uses as its baseline for a long-term macro strategy, trades at a price it last saw twenty-two years ago. Ray Dalio is short debt and expects a crisis within two years, and traders reloaded their shorts the day

At the end of Part 3 I said I wasnt exactly sure where this series would go next… But after some brainstorming, the answer was pretty clear. We already built a TSX momentum system, a US momentum system and an ASX momentum system. Three different markets and three different ways of trading momentum… but only on equities. All three of the systems thus far are long only equities systems, so

A common expectation: if the market has run hard in the hour before the cash open (start of the regular session), part of the move is done and less comes at the open. We ask about the size of the move at the open, not its direction. The push is the close of the last minute before the open minus the open of the first pre-open minute, divided by the ATR, the typical daily range (mean of the daily

Trading forums, indicator libraries and paid courses repeat a claim often enough that most traders take it as given: stop orders pile up just beyond obvious levels such as yesterday's high or low, larger players push price through to fill against them, after which price reverses. Traders act on it in two ways, placing their own stops some distance past the obvious level and buying the

Ex-prop trader on why solo trading is a different game, and how to win with real edges & portfolios of noisy strategies Rather than writing an article along with this pod, I think the relevant piece to refer you to is the series Im currently writing called The Part Time Trader because I think it tackles one of the main issues I discussed with Kris in this interview: specifically, how

We analyze a multi-asset calendar anomaly around U.S. federal elections that is consistent across assets and simple to trade. While our previous study documents a robust pre-election drift, the cross-asset pricing of its D+1 resolution remains unmapped beyond SPY. Using a diversified ETF basket spanning technology, emerging markets, real estate, high-yield credit, gold, oil, and foreign exchange,

For three months we thought we had found that good news pushes a stock up the following day. Here is what was really going on. When a company reports its quarterly earnings, it often does so just after the stock market closes at 4 pm. Traders read the announcement within minutes and buy or sell in after-hours trading, so the stock price moves right away. About an hour or so later, reporters

Momentum investors buy last year's winners. A well-known refinement, the frog in the pan of Da, Gurun and Warachka (2014), also looks at how a winner went up. A stock that climbed a little on most days is said to be a better buy than one that rose in a few big jumps, because news that arrives slowly is noticed late and keeps pushing the price. Alpha Architect's momentum method is built

Meme stocks are commonly studied through social-media activity, but this approach limits both the historical scope of research and the signals available to practitioners. In A Century of Meme Stocks and the Price of Coordination, Chad Schmerling develops an alternative: a machine-learning model trained to identify the holdings of the Roundhill MEME ETF using market and firm-level data rather than

McLean and Pontiff record stock-portfolio predictors whose performance is 26% lower out of sample than in sample, and 58% lower after publication. Suhonen, Lennkh, and Perez look at 215 smart-beta strategies banks offered and find a median deterioration of 73% in the Sharpe ratio from the backtest to the live period. Arakelian, Bolesta, Liu, Osterrieder, Poti, Schwendner, Sutiene, Vlah Jeri, and

In August we scored 22,000 analyst upgrades and downgrades against the market and found that the median one is a coin flip. That was the average call. This study asks what the average hides: does the same rating change mean something different depending on what the stock had already done? It does, in one place, and in the direction nobody acts on. A downgrade that lands on a stock that has already

Anyone who held stocks through 2008 or the Covid crash has asked the same question: is there a simple rule that gets you out before the worst of it? Two answers are famous. The 200-day line sells when the price ends the day below its average of the last 200 trading days. Volatility targeting holds less of the fund when its daily moves grow larger than usual, and more when they calm down. We tested

luster Risk Parity (CRP)was originally introduced in 2013 and conceived in 2012 by David Varadi and Michael Kapler (Systematic Investor). It was designed as an attempt to make ERC by Maillard, and Roncalli aware of the portfolios total asset allocation and allocate risk contributions equally both within and across the portfolio instead of across the individual assets which requires careful

"Be greedy when others are fearful" is Warren Buffett's best-known advice, and CNN's Fear & Greed Index is how many people check what the others feel. We rebuilt CNN's index from the seven market measures it combines, which takes it back to 2007, and followed the advice to the letter: buy the S&P 500 at Extreme Fear, sell it at Extreme Greed. From 2009 to 2026 the

Gil Cohen fits second-, third-, and fourth-degree polynomial moving regression bands to Nasdaq-100 names from 2017 through March 2024, charges 0.3% on each fill, and names the four-degree model best. Table 3 puts the average net profit at 162.75 dollars per name. The abstract, the conclusion, and Table 4 print 162.73. The risk case next to that crown is a profit factor of 0.55 and a minimum win

One of the most well-documented patterns in the cross-section of stock returns is that firms with high asset growth subsequently underperform firms with low asset growth. This asset growth anomaly is so well established that it now sits at the core of two of the most widely used benchmark factor models: the Fama-French five-factor model (via the conservative-minus-aggressive, or CMA, factor)

For most of the last century US stocks made their money on four days a month, the last trading day of the month and the first three of the next, which economists call the turn of the month. The usual explanation is a payday, because salaries and pensions arrive at the end of the month and part of that money goes into stocks. A payday everyone knows about invites buyers to get ahead of it, and US

This article demonstrates practical transaction-cost checks for systematic macro trading strategies, using a Python class from the Macrosynergy package. The method requires only basic estimates of transaction sizes and costs, which can often be obtained from trading desks or through LLM queries. These approximate cost checks help assess a strategys economic value, scalability, suitable

The question was simple: what do you find if you forget everything you think you know and search the data from scratch? No own setups, no favourite ideas, no weighting by gut feeling. Instead, every pattern family that books, forums and papers call profitable, on the same data and under the same rules. The rules were strict, because a pattern search always finds something otherwise. Test 900,000

US crude oil (WTI) rose 50% or more within a year 13 times from 1970 to August 2026, and US CPI inflation was higher at every one of the 13 oil peaks than a year earlier, by a median 2.0 percentage points. In the 8 oil spikes since 1970 that took WTI crude to a 5-year high, the S&P 500 fell in 5 over the 12 months to the oil peak (median 11.3%); in the 5 spikes that stayed under the

In the 7 episodes from 1963 to 2026 when the 10-year Treasury yield rose 1 point or more in a year and the S&P 500 fell, 10-year Treasuries lost money all 7 times (median 5.5%) and 1-month Treasury bills gained all 7 times (median +6.1%). In those 7 episodes a 60/40 portfolio of US stocks and 10-year Treasuries lost a median 6.6%, barely less than the 7.4% lost by US stocks alone; the same

Huang and Shum Nolan buy three names. Each month they take the tickers WallStreetBets mentioned most, keep a name only when the posts were majority bullish, and hold the equal-weight book for the next month. Regress that book's daily percent return on the market, size, value, and momentum portfolios (the Fama-French-Carhart regression) and the intercept is 0.433 percent a day. Multiply by

Hello everyone, The Quantpedia Awards are backand this time, were taking the winners announcement to the stage! For the 2027 edition, were bringing together an attractive prize pool, a panel of investment professionals and academics, and a new opportunity to put outstanding quantitative research in front of the industry. If you have been developing a systematic trading strategy,

The previous note inaugurated the replication arc with an anomaly that died by decay. The present replication examines a more recent published case of finer mechanics: the market intraday momentum documented by Gao, Han, Li and Zhou in 2018, according to which the sign of the first half hour of the session predicts the return of the last half hour. The outcome, stated upfront in one line, is less

On the non-microcap book, 0.50% times the Gu-Kelly-Xiu neural net's turnover of 0.869 costs 0.4345% a month. Its Fama-French six-factor alpha on that book is 0.312%. The ticket is larger than the alpha. Instrumented principal components, the linear model that lets betas move with firm characteristics, posts a six-factor alpha of 0.613% against a cost of 0.565% and clears by 0.048 percentage

What do systematic managers actually do with their money? This post distils 335 podcast episodes, about 3.7 million words of interviews with CTAs, quants and allocators, into practical lessons. Every claim links to the episode it came from. It is organised around the questions people ask most: which strategies they run, which signals and models they use, how they build portfolios and execute,

Correlation is an important component of portfolio and risk management. However, unlike volatility, which has received significant attention and for which numerous models have been developed, correlations have received considerably less attention from a modeling perspective. In this post, we give correlations the attention they deserve and examine their role in volatility dynamics, portfolio

From January 1963 to August 2026, the 10-year Treasury yield rose 1 percentage point or more within 12 months in 20 separate episodes; the S&P 500 fell over the same 12 months in 7 of them. All 7 of those S&P 500 losses came with US consumer-price inflation at 3% or more. In the 6 episodes where inflation was under 3%, including 1994, 2013 and 2021, the S&P 500 rose every time. Across

A feature that matches the sign of the next E-mini return on 4 days out of 5 leaves 0.722 bits of uncertainty about that sign. The part the feature removes is 0.278 bits of mutual information, out of the 1 bit in a fair coin. The binary channel that flips 1 transmitted bit in 5 has that 0.278 as its capacity, and no choice of how often the feature calls up versus down raises it. What this actually

Many trend rules can be drawn on the chart, and the 200-day line is the best known of them: hold the fund while the price is above its average of the last 200 days, step aside when it falls below. A Kalman filter comes at the same prices from statistics. It treats every close as a noisy reading of a trend nobody can see and updates its estimate of that trend each day, the way a guidance system

The Euro Stoxx 50 future's trade price led the DAX future's midpoint on 99% of trading days from January to June 2021, and the lag that maximized the correlation was 100 microseconds. Bender, Cestonaro, and Schmidt measure that lead on 19 Xetra and Eurex instruments, across nine microstructure series, with a lag-shifted Hayashi-Yoshida correlation: the sum of price changes whose time

In a previous article Building and Testing Trend-Following Strategies on One-Minute SPY Data, we investigated whether retail activity indicators derived from one-minute SPY data could be used to construct profitable trend-following strategies. The results suggested that we are able to construct strategies that are often able to achieve superior risk-adjusted performance. In this article, we

In a previous blog post, I described the NAAIM Exposure Index, which represents the average exposure to U.S. equity markets as reported by members of the National Association of Active Investment Managers (NAAIM) in a weekly survey. At the end of August 2026, the NAAIM Exposure Index hits a value of 102.66, meaning that U.S. active investment managers were in aggregate leveraged long in terms of

Mean reversion is the idea that a price pushed too far in a few days tends to come part of the way back. The research explains it as a trade: holders who must sell at once push the price below what the news justifies, and whoever buys from them is paid when it drifts back. We test its plainest trading form, the two-day RSI dip rule: buy a stock after a sharp two-day fall while its long trend is

On S&P 500 names from 2000 to 2022, the best book in Raymond Leung's grid is multi-view co-regularized spectral clustering with 25 clusters, a plain long-short spread, and an Ornstein-Uhlenbeck entry and exit. After a 5 basis point charge on each leg at entry and again at exit, that book has an annualized Sharpe ratio of 0.830, a mean excess return of 2.7% a year, and a maximum drawdown

A pairwise screen of the 64-futures book, at a 5% level and five lags, expects 1,008 false links when every cross-link is null. That book is the one in the old article "Network Momentum as a Cross-Asset Factor," and the screen is the bivariate test the old article "Stop Using Pairwise Granger: PCMCI for Financial Causality" took apart. The sequel is the object you trade. Both

Before the dot-com crash, the telecom companies building the internet's networks spent more on buildings and equipment than their businesses brought in, and borrowed or sold shares to pay the difference. Our thirty-year study of the tech industry found that their spending passed their own cash in 2000, and within two years they had cut it in half. Today's AI giants spend a similar share

Conformal prediction is not one technique – it is a family of methods, each with its own strengths and weaknesses. Split Conformal, Mondrian, ACI, CQR – they all produce valid prediction intervals, but they behave very differently depending on the signal you feed them. It is not an implementation detail. On the same alpha signal with the same data, switching from Split Conformal to ACI turns a

Divide a stock's 21-day moving average by its 200-day moving average. That is the whole signal, and it is about as retail as a signal gets. Avramov, Kaplanski and Subrahmanyam ran it across 13,828 US firms and 1,353,679 monthly returns from July 1977 through December 2018, and the value-weighted hedge portfolio produced an annual alpha of 9.05% against the five Fama-French factors plus

Part 1 was survival first: start slow, start boring, and treat the early years as skill acquisition rather than a race to 100% a year. This part is the bridge from that idea into the actual research. The subject is relative momentum: rank a universe of stocks by how strongly theyve risen, hold the strongest, and rotate as the ranking changes. It suits a part-time trader almost perfectly. It

Intraday trading strategies have gained increasing attention as advances in computing power and market data availability have made intraday strategy analysis more accessible. While many trading strategies are traditionally developed and evaluated using daily price data, shorter timeframes can provide additional opportunities to identify and exploit market trends within a single trading session. In

Since the dawn of the LLM age (only few years ago), there has been a flurry of alternative approaches and fundamental remixed on the classic ChatGPT style attention transformer. In 2023, Bloomberg released BloombertGPT which was the first financial LLM and claimed that it could outperform the current state-of-the-art in financial sentiment analysis. Just last year, a PhD student in

Barak, Razmi and Mousavi report an out-of-sample Sharpe ratio of 1.34 against 0.59 for the best static version of the identical trading logic, on 50 crypto futures from January 2022 to January 2024, with a Ledoit-Wolf bootstrap p-value of 0.008 on the difference. The machine doing the work is a LightGBM classifier that picks tomorrow's directional-change threshold out of {0.01, 0.02, 0.04}.

In 1968 Edward Altman took sixty-six manufacturers, half of which had gone bankrupt, and found five numbers from their accounts that together told the two halves apart. His Z-score is still taught, and it is now used for a different job: as a quality screen, a way of choosing which shares to own. The reasoning is easy to follow. A low score means trouble, so a high score should mean a sound

The panel in my September post was supposed to have zero alpha. It didnt quite. The market factor carried a drift of 0.0002 per day and the betas were drawn N(1, 0.3), so a book that tilted towards high-beta names had a true Sharpe of about +0.22 on a panel I described as containing nothing. The generator also clipped daily returns asymmetrically, at [0.5, +1.0], which leaves a name whose

Take a library of rules that loses money, put a model on top and let it decide which trades to take, then measure what that recovers across 420 rules, two markets and 43 months. A common pitch for machine learning in systematic trading leaves the strategies alone and puts a model on top of them. The rules keep generating signals, while a model trained on their past trades decides which signals to

Pham, Han, Nguyen, Pham and Do build one index and then trade it backwards. In Section 5.4 they write that an RCI near zero marks "widespread panic selling and a potentially buying opportunity," and that exuberance at the top "can indicate a market peak and a potential selling opportunity." Nine pages later, in Section 6, they lever the portfolio up to 125% when the same index

Crypto exchanges list new perpetual futures every week, and Binance alone has listed 832 USDT-margined perpetuals, so a research universe built on that exchange mixes contracts listed last week with contracts that have traded for years. Both kinds usually share one cost assumption and one strategy library, even though a new contract has no settled basis, no settled funding schedule and far more