In the past, I shared thoughts about the need to combine creative and organized thinking in order to generate investment alpha. “A robust investment process” and “a strict disciplined application” are concepts that one often hears in typical quant and fundamental investment teams. These are

Real estate stocks featured moderate correlations to stock markets over the last 30 years However, diversification benefits for equity portfolios were only marginal Other strategies provide similar yield and downside protection characteristics INTRODUCTION Surveys often reveal investor behaviour

A subscriber requested review of an analysis concluding that combining economic trend and market trend signals enhances market timing performance. Specifically, per the example in the referenced analysis, we look at combining: The 10-month simple moving average (SMA10) for the broad U.S. stock

The possibilities for quantifying risk in portfolio analytics seems to be limited only by the imagination of researchers. Indeed, you can find dictionaries that wade through an ever-lengthening list of indicators. But any short list of robust metrics surely deserves to include drawdown, which offers

This analysis was inspired by EconomPic and Meb Faber. Here we test a simple strategy that goes long Global Stocks (ACWI) when they make a new all-time month-end high, otherwise US bonds. The takeaway: Don’t fear buying stock (indices) when they close at all-time highs. A new high shouldn’t be

In this tutorial I explain how to adapt the traditional k-fold CV to financial applications with purging, embargoing, and combinatorial backtest paths.

At QuantStart we often receive email queries about the possibility of making a career transition to quantitative finance, particularly for individuals who currently consider themselves mid-career. In a more general sense we have previously discussed whether it is possible to become a quant during

No, it’s not a good idea, which should surprise no one. The fact that it is a GREAT idea, well, that should surprise everyone. Most investors fret when markets hit new highs, but should they? The below is inspired by our friend Jake @ Econompic, who examined the following query: “What if you

Support Vector Machines were widely used a decade back, but now they have fallen out of favour. The below data from google trends can establish this more clearly. (Source: Google Trends) Why did this happen? As more and more advanced models were developed, support vector machines fell out of favour.

Monday not only saw SPY make a 50-day high, but it was also the 2nd day in a row with an unfilled gap up. The study below is from last night’s letter and was previously discussed several other times in the subscriber letter (click here for free trial). It examined other times SPY left at least 2

As the book about the most successful quant, Jim Simons, comes out tomorrow (“The Man Who Solved the Market”), I felt inspired to review the ‘recent press’ on quant investing, but with a focus on the quantamental theme - where quantitative and qualitative ideas can ‘collaborate’ well to

This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies

While trend following may help investors avoid prolonged drawdowns, it is susceptible to whipsaw where false signals cause investors to either buy high and sell low (realizing losses) or sell low and buy high (a missed opportunity). Empirical evidence suggests that using economic data in the United

The trends in factor performance are similar in emerging and developed markets Factor returns were higher in emerging than in developed markets However, higher transaction costs need to be considered carefully INTRODUCTION Capital markets of developed countries like the US are highly efficient and

Financial market prices and return indices are non-stationary time series, even in logarithmic form. This means not only that they are drifting, but also that their distribution changes overtime. The main purpose of de-trending is to mitigate the effects of non-stationarity on estimated price or

Following on from my last post, below is a selection of the typical resultant output from the Bayesopt Library minimisation 3 3 2 2 2 8 99 22 30 1 3 3 2 3 2 39 9 25 25 1 2 2 3 2 2 60 43 83 54 3 2 1 2 2 2 2 0 90 96 43 3 2 3 2 2 2 2 43 33 1 2 3 2 3 2 2 0 62 98 21 2 2 2 2 2 18 43 49 2 2 2 3 2 4 1 2 0

A reader asked about the usefulness of the S&P Short-range Oscillator as sometimes used by Jim Cramer to forecast U.S. stock market returns. The self-reported “Performance” of the oscillator, relying on in-sample visual inspection with snooped thresholds, is of small use. Since continuous

As a site that tracks all things asset allocation, it seems like a miss not to include the most well known of asset allocation strategies: “Sell in May and go away” (aka the Halloween Indicator). This is a fitting time to add it to the lineup: The strategy is killing it this year and a change in

I have recently come across the idea of weight agnostic neural net training and have implemented a crude version of this combined with the recent work I have been doing on Taken's Theorem ( see my posts here, here and here ) and using the statistical mechanics approach to creating synthetic

Anomalies such as Value and Momentum have been exploited for years, yet the source of these premiums emerged as a major unresolved puzzle. Potential explanations can be grouped into two broad categories: “compensation for risk” or “mispricing”. This paper studies this puzzle by investigating

As Nassim Taleb states, ideas come and go, stories stay. So today Maximiliano and myself are going to build for you a story which hopefully will carve in your mind the importance of doing things right; or put differently, of using logarithmic returns instead of arithmetic returns when you should. To

Earlier this month I briefly reviewed a recent BlackRock report that highlighted that macroeconomic factors are typically driving investment strategy results. As a follow-up, let’s take a quick look at a basic real-world example of analyzing portfolios through a macroeconomic lens. First, let’s

Interest rates and yield curves are not observable, but need to be estimated from prices of fixed-income securities. Common patterns in prices of fixed-income securities can be expressed in three ways: yield curves, forward rate curves or discount functions. When working with interest rates, we need

Investing is simple, but not easy, as Warren Buffett says. And yes — technically the investment process should be as simple as possible. But does it mean that an average investor should not even think about active investment strategies and entirely rely on a passive portfolio? Which strategy is

We are continuing in our short series of articles about calendar / seasonal trading. In our previous work, we have examined various calendar / seasonal equity trading strategies. In this study, we aim to take this composite calendar strategy as a building block and add another block to enhance the

The size premium is one of the factors that we have researched and dug into several times on the blog. You can find just a few here, here, and here. This paper though took a fresh look at the size premium and adds a new perspective that we haven’t previously covered. What are the research

Concept: Large price moves tend to be followed by large price moves, and small price moves tend to be followed by small price moves (Volatility Clustering). Research Question: Can we improve performance of the original volatility clustering model via standard deviation filtering of large price

When developing a new trading strategy you are usually confronted with multiple tasks: Design the entry, design the exit and design position sizing and overall risk control. This article is about how you can test the edge of your entry signal before thinking about your exit strategy. The results of

To generate returns that are different than the market, we must adopt a positioning that is different than the market. With the increasing adoption of systematic factor portfolios, we explore whether an anti-factor stance can generate contrarian-based profits. Specifically, we explore the idea of

Tradable economics is a technology for building systematic trading strategies based on economic data. Economic data are statistics that – unlike market prices – directly inform on economic activity. Tradable economics is not a zero-sum game. Trading profits are ultimately paid out of the

Factor exposure analysis is essential for performance and risk contribution However, the results vary depending on methodologies, factor definitions, and other assumptions A holdings-based approach is preferable over regression analysis INTRODUCTION A large part of a capital allocator’s job is to

The inspiration for this post comes from a new paper titled Predictable End-of-Month Treasury Returns (h/t Capital Spectator). A description from the authors: We document a distinct pattern in the timing of excess returns on coupon Treasury securities. Average returns are positive and highly

Researchers love novel datasets–it gives them a new set of information to conduct studies and test theories. That brings us to this paper, titled “Core Earnings: New Data and Evidence” by Ethan Rouen, Eric So, and Charles C.Y. Wang. The paper uses a novel database created by our friends at

For this post, I want to take a look at the concept of intra-day momentum and investigate whether we are able to identify any positive signs of such a phenomenon occurring across (quite a large) universe of NYSE stocks. It has been suggested that, for the wider market in general at least, there is a

Let’s start with an experiment. We divide people into two groups, A and B. Then, we ask group A to guess how old Mahatma Gandhi was when he died, taking into account it was after age 9. And we ask group B the same question but taking into account that it was before age 140. Of course, the extra

Pairs trading is supposedly one of the most popular types of trading strategy. In this strategy, usually a pair of stocks are traded in a market-neutral strategy, i.e. it doesn’t matter whether the market is trending upwards or downwards, the two open positions for each stock hedge against each

Many famous investors are outspoken about their investment philosophies, and carefully apply them to a select number of securities. Who among us hasn’t thought if they could at least capture some of the talents of our favorite investors in a bottle, we too could be super investors? Turns out you

While the quality factor has been identified in the literature (including papers such as “Buffett’s Alpha,” “Global Return Premiums on Earnings Quality, Value, and Size,” and “The Excess Returns of ‘Quality’ Stocks: A Behavioral Anomaly”), and there are now a number of investment

Some bloke* once said "The most overlooked characteristic of a strategy is the expected skew of it's returns, i.e. how symmetrical they are" * It was me. "Systematic Trading" page 40 Skew then is an important concept, and one which I find myself thinking about a lot. So

Equity income mutual funds have underperformed the S&P 500 since 1988 Especially on a post-tax basis Investors can create tax-efficient equity portfolios, but it does not represent a free lunch INTRODUCTION Warren Buffett is probably the most well-known and well-liked investor, which is easily

After the Great Financial Crisis, the Momentum factor has exhibited positive returns, but those returns have been largely driven by the short side of the portfolio. One research note suggests that this is driven by increased risk aversion among investors, using the correlation of high volatility and

Most asset allocation approaches are more or less static. From 60/40 to Risk Parity, such allocations can be easily replicated with a couple ETF’s, and so the outcomes of static asset allocation portfolios, especially the risks such as drawdowns, are 90%+ pre-determined. There is a strand of

I have recently been reading about more modern ways to decompose a matrix. Singular value decomposition is a popular way, but there are more. I went down the rabbit whole. After a couple of “see references therein” I found something which looks to justify spending time on this. An excellent

Explaining the Demise of Value Investing Baruch Lev (NY University) and Anup Srivastava (U. of Calgary) August 25, 2019 The business press claims that the long-standing and highly popular value investing strategy—investing in low-valued stocks and selling short high-valued equities—lost its edge

Scikit-learn is one of the most versatile and efficient Machine Learning libraries available across the board. Built on top of other popular libraries such as NumPy, SciPy and Matplotlib, scikit learn contains a lot of powerful tools for machine learning and statistical modelling. No wonder scikit

The crowning achievement for investors is the ability to identify which of the few active mutual funds will outperform in the future. Despite an overwhelming body of academic research which has demonstrated that past performance doesn’t guarantee future performance and (as the annual SPIVA

Most of us focus our research time looking to find better entries. We don’t spend enough time thinking about our exits. I am definitely guilty of this. A popular way to enter a mean reversion trade is by using a limit order. I use that on the strategy on RSI2 Strategy: Double returns with a simple

In the first three posts of this mini-series on pairs trading with Zorro and R, we: Implemented a Kalman filter in R Implemented a simple pairs trading algorithm in Zorro Connected Zorro and R and exchanged data between the two platforms In this fourth and final post, we’re going to put it all

What good is synthetic data for in a financial setting? This is a very valid question, given that data augmentation techniques can be hard to evaluate and the time series they produce are very complex. As we will see in this post however, it turns out that synthetic series can be very useful!

What is a crowded trade? What is asset centrality? Does asset centrality predict bubbles? Can it be exploited? What are the Academic Insights? In the normal course of events, investors perceive and act upon changes in fundamentals that will persist indefinitely (or until the next change in