Financial advisors primarily use Monte Carlo simulations to forecast returns However, this methodology is flawed as it ignores the valuations of asset classes Using capital market assumptions is likely a better approach INTRODUCTION The Shanghai Composite Index (SSE) was booming in early 2015, and

Hello everyone, Two weeks ago, we promised you a surprise, and now it’s finally time to unveil what we have prepared for you :). Our Quantpedia Awards 2024 aims to be the premier competition for all quantitative trading researchers. If you have an idea in your head about systematic/quantitative

This article continues our recent articles on stat arb: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas In this article, I’ll brainstorm some ideas for predictive features that you could potentially use in a crypto stat arb model. The ideas draw

The dividend discount model suggests that stock prices are negatively related to expected real interest rates and positively to earnings growth. The economic position of households or consumers influences both. Consumer strength spurs demand and exerts price pressure, thus pushing up real policy

Because of the strong evidence, momentum continues to receive much attention from researchers. Out of the hundreds of exhibits in the factor zoo, one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in

Value at risk (VaR) is a tool professional traders use to manage risk. It estimates how much a portfolio might lose, given normal market conditions, over a set time period. There are three ways to compute VaR: the parametric method, the historical method, and the Monte Carlo method. In contrast to

Something I am always thinking about is how the markets are behaving now vs the past few years vs several years ago. My edge on the strategies I trade depends on two main ideas. One, current market behavior is similar to what I tested on which is normally the last 5-10 years. Two, not too many

Last week, I wrote a short article about statistical arbitrage trading in the real world. Statistical arbitrage is a well-understood concept: find pairs or baskets of assets you expect to move together, wait for them to diverge, and bet on them converging again. Simple enough. But making it work,

Portfolio optimization is a balance between maximizing returns and minimizing risk. While it might sound easy, it’s actually very difficult compare investment strategies. First, we have to accurately forecast future returns and risk. Then, we have to use tricky optimization models to build the

Popular benchmarks in academic research studies to evaluate the performance of investment strategies are cap-weighted (market-, or value-weighted), and equal-weighted portfolios. Capitalization-weighted portfolios are used because they are the simplest and cheapest to implement, representing the

Short-only trend following in stocks generated consistent losses across markets However, combining the strategy with an equities portfolio generated diversification benefits Like other hedging strategies it would be difficult to execute this strategy over the long-term INTRODUCTION Trend following

This is a test of the “simple” variation of Dr. Keller and Keuning’s strategy from their paper Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA). We’ve covered the “balanced” version of HAA previously. It has become one of the more popular strategies on

Commodity Trading Advisor (CTA) funds are commonly associated with managed futures investing in futures and options, and are a subset of the broader hedge fund universe[1]. Beyond commodities, they have the flexibility to venture into other assets, including interest rates, currencies, fixed income

Trend following is a relatively simple strategy, at least at the concept level: buy when prices go up, and sell when they go down. The main way that trend followers differentiate themselves is the timeframe over which they measure whether the price has gone up or down. For example, one manager might

This post extends the replication from the Adaptive Asset Allocation Replication post by running the analysis on OOS (out-of-sample) data from 2015 through 2023. Thanks to Dale Rosenthal for helpful comments. The paper uses the 5 portfolios below. Each section of this post will give a short

The same multi-vol quant strategy we all love, but now with 2000+ vol signals to choose from. quant_rv is a daily SPY strategy that uses realized volatility measures of SPY to predict days of lower volatility ahead, that in turn predict positive returns. In the net, quant_rv wins by very modest

FX forward-implied carry is a popular ingredient in currency trading strategies because it is related to risk premia and implicit policy subsidies. Its signal value can often be increased by considering inflation differentials, hedging costs, data outliers, and market restrictions. However, even

One of the most common questions I get: What books should I read for quant finance, algorithmic trading, and market data analysis? And one of my favorite hobbies is collecting books on the subject. 46 awesome books for quant finance, algo trading, and market data analysis 46 books for quant finance,

The factor betas of value-focused ETFs range dramatically Non-value-focused funds can have high betas to the value factor However, these often come with large unintended bets INTRODUCTION While some investors are die-hard believers in value investing, others regard this more opportunistically and

The primary motivation behind our study stems from an observation of the Global Tactical Asset Allocation (GTAA) strategies throughout the existing papers – the majority of them require relatively frequent rebalancing from the point of view of the ordinary investor. Portfolio rebalancing is

In textbooks, one often sees pairs trading algorithms start by regressing prices of Asset A on Asset B to calculate a hedge ratio. I’ve rarely seen anyone actually do this in the real world. That’s because it is a very unstable thing – especially for a pair of volatile assets, and especially

As professor John Cochrane observed, the literature on investment factors now fills a veritable “factor zoo,” with hundreds of options. How do investors select from among this huge array of possibilities? In order to minimize the risk that outcomes result from data mining, in our book “Your

Optimal Portfolio Choice with Fat Tails and Parameter Uncertainty Raymond Kan (U. of Toronto) and Nathan Lassance (LFIN/LIDAM) December 2023 Existing portfolio combination rules that optimize the out-of-sample performance under estimation risk are calibrated assuming multivariate normally

An old friend asking for help... how can I resist? Here is the perplexing paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4042239 And here is the (not that senstional) abstract: Bitcoin (BTC) returns exhibit pronounced positive skewness with a third central moment of approximately 150%

Most portfolios are centered around stocks. Stocks are thought of as the primary return driver, while other additions to the portfolio are thought of less as return drivers, and more as diversifiers. The popular 60 / 40 portfolio is a prime example of this. The vast majority of the returns to this

This is a test of Paul Choi’s paper Balance Between Growth and Dividend: Dividend & Growth Allocation (DGA). This strategy would have delivered exceptional performance over the last 50 years, but we would temper future expectations for several reasons we discuss below. Backtested results from

In the previous post, I introduced the index tracking problem1, which consists in finding a portfolio that tracks as closely as possible2 a given financial market index. Because such a portfolio might contain any number of assets, with for example an S&P 500 tracking portfolio possibly

Is there a defensive equity factor? Can one be built? Although it seems like an easy question, the answer is not straightforward. The authors of this piece argue for a careful assessment of factor strategies to deliver a defensive profile convincing enough to attract investors. A defensive

Sectors and factors were not very sensitive to changes in interest rates on average However, the averages are misleading as the sensitivity varies significantly over time The duration of factors was more dispersed than that of sectors INTRODUCTION If equity investors are from Mars, then fixed-income

Investing in emerging markets (EM) or developed markets (DM) outside of the United States tends to follow cyclical trends. At times, it becomes popular and crowded to focus solely on U.S. stocks, while in other periods, the trend shifts to favor everything except U.S. equities. This inclination

Arbitrageurs keep markets efficient by moving prices to reflect their fundamental values. However, anomalies can persist because of limits to arbitrage—the costs and risks of shorting. The costs and risks of shorting, however, are not the only risks that arbitrageurs face. The publication of

In the last post, we wrote code to test for the pnl of a system that continuously rebalances and shorts the atm straddle on index options. Sketching the Option Backtester (with Code downloadable for ALL readers) HangukQuant · December 21, 2023 Sketching the Option Backtester (with Code downloadable

In the world of trend following, the biggest, most longstanding debate is about whether or not to target a certain level of volatility on an ongoing basis. Listeners of the podcast Top Traders Unplugged will be very familiar with this debate. Unfortunately, some of the language surrounding this

This blog is just a personal hobby. When I’m extra busy as I was this year the blog is a front-line casualty. This is why 2023 saw a weaker posting stream. Nonetheless I am pleased with just over 30K visits this year, with an average of roughly one minute per visit (engagement time, whatever

The performance of factors was unexciting and poor in 2023 Quality performed the best, low volatility the worst Low-risk and cheap stocks are currently highly correlated INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10 years. Specifically, we only

The weekend (or Monday) effect in the stock market refers to the phenomenon where stock returns exhibit different patterns on Mondays compared to the rest of the week. Historically, there has been a tendency for stock prices to be lower on Mondays. Various theories attempt to explain the weekend

Over 1,200,000 options contracts trade daily. Storing options data for analysis has become something only professionals can do using sophisticated tools. One of the professionals recently open sourced their tools for lightening fast data storage and retrieval. ArcticDB is a DataFrame database that

Systematic default risk is the probability of a critical share of the corporate sector defaulting simultaneously. It can be analyzed through a corporate default model that accounts for both firm-level and communal macro shocks. Point-in-time estimation of such a risk metric requires accounting data

That riskier assets should command higher expected returns is the most basic of asset pricing theories. Clearly, financial distress is a risk characteristic, but it presents a puzzle, as there has not been a linear relationship between it and stock returns. For example, John Birge and Yi Zhang,

Trend following boils down to one basic idea: buy when the price goes up, and sell when it goes down. Its implementation, though, could be much more complicated. There are a myriad methods and timeframes to choose from, and these methods and timeframes are by and large the dials that CTAs can turn

Trading strategies often rely on parameters. To enhance and effectively cross-validate these parameters can provide a competitive advantage in the market. However, reliable cross-validation strategies can lead to look-ahead bias and other pitfalls that can lead to overestimating a strategy’s

The question of whether stock returns are predictable is of long-standing interest to both academics and investment practitioners. Commonly accepted investment strategies, for example, will behave quite differently in the presence of stock return predictability. The research literature is unclear on

Because of the strong evidence, momentum continues to receive much attention from researchers. Out of the hundreds of exhibits in the factor zoo, one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in

This end of year rally which started on October 2023 has been strong. My trading buddy and I started wondering how this compares to the past. Is this a “normal” strong rally or an “abnormally” strong one? Determining this is always tough because it depends on the indicators you use. Because

In my previous post I said I was trying to develop new indicators from the results of my new PositionBook optimisation routine. In doing so, I need to have a methodology for judging the quality of the indicator(s). In the past I created a Data-Snooping-Tests-GitHub which contains some tests for

Factor Zoo (.zip) Alexander Swade (Lancaster University) et al. October 2023 The number of factors allegedly driving the cross-section of stock returns has grown steadily over time. We explore how much this ‘factor zoo’ can be compressed, focusing on explaining the available alpha rather than

An equity investor can purchase two kinds of financial insurance. The first, more straightforward kind, is a put option. This contract simply pays off when the S&P 500 (which we’ll use as our stand-in for “equity”) goes down. In other words, it’s like any other insurance contract. It

In a previous post, I described a parametric approach to computing Value-at-Risk (VaR) - called modified VaR12 - that adjusts Gaussian VaR for asymmetry and fat tails present in financial asset returns3 thanks to the usage of a Cornish–Fisher expansion. Modified VaR, when properly used4, provides

The study emphasizes the importance of integrating machine learning with other tools for investment managers, pension-plan administrators, financial advisors, and independent analysts to help investors select active mutual funds with positive alpha. It also highlights the significance of fund

RSI, MACD, Stochastic, ROC, CCI, %b - technical indicators come in many shapes and sizes.[1] Their names suggest something very technical at play. Maybe even scientific. Yet, they are a polarizing tool. They generate strong, opposing opinions. Some traders value them with near religious zeal, while