A short one today. Suppose I offer you N trading strategies to choose between. We can run some kind of bootstrap of their historical returns to get a final distribution of CAGR, with all the caveats implied by that. Or suppose I ask you to pick the correct level of leverage on a trading strategy.(...)

I was given access to Trading Breakthroughs with AI by Algo Advantage on using Claude Code as a research assistant for systematic trading. The idea is simple. You come up with the idea to test. Claude writes the code, runs the backtests and writes up the results. What caught my attention is that(...)

After a summer break, this is post (checks notes) #11 in my 2026 series on portfolio optimisation. Up until now I've been focusing on the optimisation of forecast weights -the weights of signals to predict a given instrument - on a pre cost basis. So now it seems that we should introduce the(...)

We spent the past four articles developing four robust momentum systems, and now it’s time to combine them into the momentum mini portfolio. The four systems we developed to be a part of this mini portfolio are: The TSX Dual Factor Momentum System The US Pullback Momentum System The ASX(...)

The Triple Screen is the trading system at the centre of Alexander Elder's "Trading for a Living". It reads a stock three ways: the long trend, a dip against that trend, and the turn that ends the dip. Elder measures the dip with his own Force Index, the day's price change times(...)

Almost every experiment in this series died of the same cause: the signal did not exist, or it existed only inside a measurement bias. The one that closes the tour of forex is different, and that is why it deserves its own note: here the signal exists, it survives nineteen placebos in each of(...)

An average correlation puts a quiet day and a selloff on the same edge, and so does the symmetric graph in the old article "Network Momentum as a Cross-Asset Factor." Pham, Han, Nguyen, Pham and Do estimate common volatility, the shared multiplier on residual variance they call COVOL,(...)

With the calendar about to change from October to November, the market will enter its “Best 6 Months”. The “Best 6 Months” tendency was first published by Yale Hirsch, founder of the Stock Trader’s Almanac, in 1986. The concept behind the “Best 6 Months” is simple. Hirsch’s research suggests that(...)

According to a well-known paper, most of the US stock market's return arrives while the market is closed. That sounds like easy money, which is exactly why I wanted to check whether anyone can actually collect it. 1. The theory In "A Tug of War: Overnight Versus Intraday Expected(...)

Buy S&P 500 futures at the 16:00 New York close on the trading day before each scheduled Fed decision, and sell at 14:00 on decision day, just before the statement comes out. That is the whole rule: one trade per scheduled meeting, eight a year, and nothing in between. The idea is not mine.(...)

Inside the cheap end of the market Greenblatt's weighting did what he said it would. More money in the cheaper companies earned more than the same money spread evenly, with financial companies in or out, with a limit or without, and the even split earned more than the split by size. Against(...)

Market dynamics are changing rapidly, and managing a hedge fund is becoming increasingly competitive and challenging. The same is true for investors seeking to allocate capital to hedge funds. In this post, we explore whether investing in hedge funds is worthwhile and how to evaluate their(...)

Ning's equal-weight book of six sector pairs earns a daily Sharpe of 0.09 in 2022. Daily Sharpe here is the mean daily percent return divided by the daily percent standard deviation, with no square root of 252 attached. You enter long when a pair's spread falls half a standard deviation(...)

We present a cost-efficient method for outperforming the broad U.S. equity market. It uses deep learning and macroeconomic factors to optimize individual stock weights, thus creating a “macro-aware” portfolio. Rather than building a separate macro factor model for each company, we select a small(...)

On the morning of October 30, 2025, International Paper (IP $36.37 +0.94%) held its third-quarter call. The first analyst to speak opened with "Congratulations on your progress in a challenging environment." Two of the next five said much the same. By the following day's close the(...)

McMillan finds that from 2009 a US stock-bond book needs an 80% stock weight to stay on the return path a 50/50 book had traced before 2000. The correlation between stock and bond returns flipped from positive to negative around 2000 in six of the G7 markets, and it moves back toward positive in(...)

Batten, Loncarski, Szilagyi, and Zhou put a long gold book next to the 10-year real yield and the dollar. On monthly data from February 2003 to February 2026, the log change in the London gold fix falls by 0.0639 for each percentage point the 10-year TIPS yield rises, holding the ICE dollar index(...)

If you have read anything about tactical asset allocation, you have met this rule. Each month, compare the S&P 500's price to its 10-month moving average. Above it, hold stocks. Below it, hold bonds or cash. Mebane Faber's 2007 paper made it the default starting point for a generation(...)

At 4:07 p.m. on Friday, September 25, DraftKings (DKNG $20.78 -2.07%) filed an 8-K saying its audit committee had dismissed BDO as its auditor and appointed Deloitte. Nothing in it was alarming. The filing reports no disagreements with BDO, the switch takes effect after the 2026 audit, and the(...)

Half a million tests can map an opportunity or manufacture a winner; the difference is how the outputs are used. Then the coin toss every ranking has to beat. Welcome back to the series on building rotational momentum strategies. Earlier I called broad reconnaissance the opposite of overfitting.(...)

Trending Value is a stock-picking formula from James O'Shaughnessy's book "What Works on Wall Street", and stock screeners have copied it for years. It has two components. The value component finds the cheapest stocks in the market, judged on six price measures at once. The(...)

Whenever current portfolio weights differ from their target weights, either due to market movements, signal changes or other reasons, a portfolio manager in a frictionless world would immediately trade to the target portfolio. In reality, however, every adjustment incurs trading costs. Therefore a(...)

If you trade macro themes, you have seen the pitch: let a language model read the news and position you across futures. If you backtest rules, you know the question to ask first: what is the edge, and does it hold on years the model never saw? I built that AI macro fund and backtested it on 12(...)

Every Wednesday at 10:30 New York time (Thursday at 11:00 in holiday weeks) the US Energy Information Administration reports how crude and gasoline inventories changed. The oil price reacts within seconds. The question behind this: after the first five minutes does the price keep running in the(...)

Every trader knows the idea: a market rises for weeks, quietly, with small pullbacks and low volatility. At some point the rise gets steeper and momentum picks up. The mechanism usually named is dealer hedging: whoever sold call options has to buy more as the price rises, and when the VIX rises at(...)

Leveraged ETFs provide amplified exposure to an underlying index, but their daily reset mechanism creates volatility drag, which can substantially reduce their long-term value. This raises the possibility of exploiting the effect by simultaneously shorting leveraged ETFs with opposite exposures. We(...)

In finance, various studies have explored the use of regression models in forecasting stock prices […] based on historical data and other relevant variables1. Among these models, the log-linear regression model is of particular importance due to its relationship with the geometric Brownian motion(...)

A common piece of advice for any leveraged portfolio is to hold some long volatility on the side, a small position in VIX futures that pays when the stock market crashes. This article tests that advice on a risk-parity portfolio of stocks, bonds and gold and finds it wrong: VIX insures stocks, and(...)

Do round prices such as US$2,000 act as barriers for gold? Using 5,138 daily XAUUSD bars from 2005 to 2024, we test whether gold closes back on its side after touching a US$100 level and compare the round grid with 80 placebo grids of the same spacing, using rank-based tests, a Holm correction and(...)

Most back-tests are wrong before the first trade is placed; here’s everything I settled before I let a single result count. Apologies for some of this content being dry, I just want to make sure that if you take this series in its entirety, you basically have a mini-course in building momentum(...)

The Ornstein-Uhlenbeck process is the textbook model of mean reversion: a price that wanders away from its usual level is pulled back toward it, like a ball on a spring. Traders use it to buy a stock when its price is unusually far below its estimated level, and to sell when the price has come(...)

Momentum is one of the oldest ideas in trading: buy what has been rising, and hold it while it keeps rising. Its known weakness is the fall. When a trend breaks, yesterday's strongest stocks can fall the hardest. A common fix is a second check before holding a stock: its rate of change, how(...)

A popular TradingView script trades EURUSD at the New York stock market open: a buy stop at the last swing high, a sell stop at the last swing low, a 2:1 target. We measured it on 2019 to 2021 one-minute data, 664 trades. It made +0.524 pip per trade before costs. Spread and commission cost 1.21(...)

The VWAP (volume-weighted average price since the session start) is seen as the fair price of the day, the EMA(9) as a fast trend line. When the fast line crosses the VWAP upwards, you buy, downwards you sell. The rule appears in many day-trading courses and was missing from our earlier indicator(...)

Stock market bubbles are easy to identify in hindsight. The dot-com boom, the run-up to the global financial crisis, and the surge in technology stocks during the pandemic are all familiar examples. But identifying a bubble while it is forming is much more difficult. The challenge is that rising(...)

A one-standard-deviation rise in a country's commodity export prices predicts a 0.39% appreciation of its currency against the dollar over the next month. Jeanneret and Sokolovski find that slope in eight commodity-exposed currencies from January 1985 to April 2020, and the Australian dollar(...)

Buying after a short, sharp sell-off provides liquidity to those who have to sell, and it pays when the price comes back. On the S&P 500, Nasdaq 100 and Dow exactly this rule passed our holdout: RSI(2) below 10 above the 200-day average, +48 bps per trade after costs. The obvious question: is(...)

For anyone trading or investing in Bitcoin, a familiar indicator can become a dangerous comfort blanket. Josh Molnar’s Bitcoin Runs on a Clock argues that classic cycle signals—such as MVRV, the Mayer Multiple and Pi Cycle Top—have weakened as Bitcoin’s price swings become less extreme. Thresholds(...)

A gold breakout system on r/algotrading showed +188% in 18 months, with a profit factor of 1.74. Its author asked if it holds up outside that window. We ran it on 2019 to 2021 real-tick data with full costs. At its own speed of about three trades a day, every matching setting lost 76% to 97% of the(...)

“The biggest risk is that you have a losing strategy when you think you have a winning one.” Jeff Yass Last month, while listening to Annie Duke’s TED Talk about risk, I learned the quote above from Jeff Yass, founder of Susquehanna International Group. Annie is a former professional poker player(...)

Hedgefundie's Excellent Adventure is a well-known strategy built from leveraged funds. A leveraged fund borrows so that it moves more than the market each day. The strategy borrows its name from the film Bill & Ted's Excellent Adventure. Like the film, it travels through time very(...)

The figures below are the interactive versions of the figures in the article, in the article’s order and under the article’s numbers. Hover a series for its values, drag across a chart to zoom and double-click to reset, and click a legend entry to hide or isolate a series. The security master(...)

Many investors change their mix of stocks with the market's mood. When the market is calm, they lean on the stocks that have been rising. When it turns choppy or stressed, they move toward profitable, cheaper companies, which they expect to hold up better. Investors call these moods regimes.(...)

Twelve commodity futures, three momentum windows and an intercept, ten years of daily closes: 444 coefficients on 2,520 rows. Jacquier, Muhle-Karbe, and Mulligan compute the fraction of the in-sample Sharpe ratio this linear book is expected to keep on new data. Their commodity case study puts that(...)

Liquidity is an important factor in financial markets, but it is not always the first consideration in asset pricing, trading, or risk management. In this post, we examine the importance of liquidity from two different perspectives: its predictive relationship with stock returns and its role in(...)

Fieberg, Liedtke, Poddig, Walker, and Zaremba build a weekly score from 28 technical indicators, buy the value-weighted top fifth of coins, and short the bottom fifth. From April 2015 to May 2022 that hedge earns 3.87% a week, t-statistic 5.19, annualized Sharpe ratio 1.94. They then rebuild the(...)

This is a test of OptimumV from Todd Tresidder of Financial Mentor. Backtested results from 1987 follow. Results are net of transaction costs – see backtest assumptions. Learn about what we do and follow 100+ asset allocation strategies like this one in real-time. Logarithmically-scaled. Click for(...)

Stocks on the Move is a 2015 book by Andreas Clenow. It gives simple rules for picking stocks from the S&P 500. In short: buy the stocks that rose fastest and most smoothly over the last three months, and stop buying new stocks while the whole market is falling. The book's promise is to(...)

The first note of this series told how a post-earnings drift sleeve with a 0.63 Sharpe died upon applying point-in-time membership: that number was an inclusion look-ahead, not an edge. A question was left pending, promised as an epilogue: with the bias corrected, what remains of the underlying(...)

This paper investigates whether longer historical training periods improve the out-of-sample performance of a Hidden Markov Model (HMM) used for identifying financial market regimes. Four four-state Gaussian HMMs are compared, differing only in the starting point of their training data (1970, 1980,(...)