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It’s been over a month since our last post and for that we must apologize. We endeavor to be more prolific, but sometimes work and life get in the way. On the work front, let’s just say we won’t have to spend as much time selling encyclopedias door-to-door, which should free up more time to

Pairs trading is popular due to its simple approach and effectiveness. At the heart of the strategy is how the prices of two assets diverge and converge over time. Pairs trading algorithms profit from betting on the fact that spread deviations return to their mean. One of the more notable hedge

So the crypto markets on May 19th were fun!? If you have been a part of these markets for any time, this volatility is not that surprising. That said it is still pretty amazing that the price can drop 30% in a single day. This is maybe more surprising since it is to the backdrop of an increase in

The value spread is the difference between the value signal in the long versus the short portfolio. This isn’t the first time we have hit on this topic. Wes and I have done several posts on the subject: Timing Value and Momentum with Valuation-Spreads The Returns to Value Strategies When Valuation

I examine the performance records of performance of Ben Graham's well-known disciples: Walter Schloss, Tom Knapp, Warren Buffett, Bill Ruane, Charlie Munger, Rick Guerin, and Stan Perlmeter. The research question I seek to address is the following: Do the academic "value" and

The previous article dealt with John Ehlers’ AM and FM demodulating technology for separating signal and noise in price curves. In the S&C June issue he described a practical example. Applying his FM demodulator makes a strategy noticeably more robust – at least with parameter optimization.

The relationship among ESG ratings from third-party providers has historically produced conflicting results. Differences in sourced information and weighting schemes have produced low correlations between ratings and as a result, have handicapped the efforts to understand the relationship between

The CSI 300 is a capitalization-weighted stock market index that tracks the top 300 stocks listed on the two main stock exchanges in mainland China. In April 2020, South China Morning Post reported that “the 120-day correlation between the CSI 300 Index and the S&P 500 index recently rose to

We track more than 60 Tactical Asset Allocation strategies, which members can combine together into custom portfolios. To make creating those portfolios easier, we provide an optimizer showing the best performing combinations of strategies based on the member’s investment objective, such as

In the 4/12/19 blog I showed a study about US tax day (normally April 15th). The reason tax day may be important is that it is the last day that people can make IRA contributions to count for the previous tax year. This can create a last-minute rush and you will often have an inflow of funds heading

Managed futures strategies aim to exploit short- or long-term trends Short-term trend followers are often seen as offering better stock market crash protection characteristics Our analysis highlights that the differences are marginal INTRODUCTION Aesop’s famous story of the race between the

Long-Horizon Stock Returns Are Positively Skewed Adam Farago and Erik Hjalmarsson (University of Gothenburg) April 28, 2021 At long horizons, multiplicative compounding induces strong-to-extreme positive skewness into stock returns; the magnitude of the effect is primarily determined by

Since the late 1990s, the negative price correlation of equity and high-grade bonds has reduced the volatility of balanced portfolios and boosted Sharpe ratios of leveraged “long-long” equity-bond strategies. However, this correlation is not structurally stable. Over the past 150 years,

In the previous posts I described an Reinforcement Learning approach to “Learning the Exit” part 1, part 2. My initial conclusions there have been: reward smoothing (with the labeler) leads to more robust results than a reward on position exit without smoothing the learning process struggled and

I love programming! There is something really satisfying about solving a complicated problem concisely. That said I see programming languages as a tool to solve a problem rather than purely coding for coding sake. I have used a lot of programming languages over the last 20 years namely Java, R,

In Part 1, we defined fixed income factors. But factors alone will not solve each investor’s problem. Below, we extend the discussion by walking through a case study that shows how an asset allocator might use factors to solve a common problem: how to invest in a low yield environment given the

Getting historical intraday financial data can be a pain, especially for non-US markets. If you have deep pockets you can simply buy the data you need, but for retail investors the cost is prohibitive. If you want historical transaction-level data for the Brazilian stock market, for instance,

This is a snippet from a strategy backtesting system that I am currently building in Mathematica. One of the challenges when building systems in WL is to avoid looping wherever possible. This can usually be accomplished with some thought, and the efficiency gains can be significant. But it can be

Recently for my own trading, I have been researching rotational strategies on both the weekly and monthly timeframes. The most common indicator that I use for ranking stocks is Rate of Change (ROC) of the closing price. I read about using Rate of Change on the EMA to rank stocks. I liked a small

It has been almost 11 years since the first official Bitcoin trades in July of 2010. It's price has experienced quite a run. Although controversial, cryptocurrencies have firmly taken hold of the current investing landscape, won hearts and minds of groups of investors, suggesting they are here

A few weeks ago I saw comments on Twitter regarding the Russell 3,000 Value and Growth indices having approximately the same returns since inception. For example, here is Ben Johnson from Morningstar 1 As viewed from this tweet, and is born out in the data for the Russell indices, it appears that

The world is awash in efforts to model a theoretical value for the stock market – the CAPE ratio, for example. But while the equities hog much of the attention on this front, similar analytics for the world’s most important interest rate are no less valuable. How to begin? Not surprisingly,

This is the sixth article of the copula-based statistical arbitrage series. You can read all the articles in chronological order below. In this series, we dedicate articles 1-3 to pairs-trading using bivariate copulas and 4-6 to multi-assets statistical arbitrage using vine copulas. Copula for Pairs

Contrary to a more developed market, arbitrage opportunities are not readily realised which suggests there might be opportunities for those looking and able to take advantage of them. This project focuses on China's futures market using Statistical Arbitrage and Pair trading techniques. This

The stock market volatility, skewness, and yield curve influence the performance of the value factor Investors require a certain market environment to buy troubled companies The key performance driver of the value factor is risk sentiment INTRODUCTION Ted Theodore first wrote about value versus

For the last seven years since I started trading my own account I've pretty much kept the same set of futures markets: around 40 or so, with very occasional changes. The number is limited, as to trade more markets I'd need more capital. The set of markets I have is a compromise between

This is a follow up to a strategy we’ve covered previously: Accelerating Dual Momentum (ADM) from EngineeredPortfolio.com. See our first test of ADM, which includes a description of the strategy rules and our own analysis of the strategy. Here we’ve extended our test by 20 years to include a

This article is a primer into the methodology we use for the Portfolio Risk Parity report, which is a part of our Quantpedia Pro offering. We explain three risk parity methodologies – Naive Risk Parity (inverse volatility weighted), Equal Risk Contribution and Maximum Diversification. Quantpedia

One year ago, I wrote about the U.S. Value factor and what I found by extending its history back in time before 1926. In summary, I wrote that Value’s drawdown in March 2020 was normal and likely close to its bottom. Without the insights from the extended history, Value had appeared ‘dead’

This is the first part of a series of guest posts by Kai Wu, the CIO & Founder of Sparkline Capital. The Factor Zoo As readers of Alpha Architect’s blog, you’re certainly familiar with factor investing. Factors are quantifiable firm characteristics that explain cross-sectional stock returns.

The dramatic underperformance of value stocks as defined by the HmL (the return on high book-to-market stocks minus the return on low book-to-market stocks) since 2017 has led many to question the existence of the value premium. The recent drawdown has been by far the largest ever experienced. From

Mid-year learning and knowledge sharing for the quant finance community A week of 5 precision-engineered digital summits, laser-focused on the most innovative research. Choose the days that matter to you. Meet the quants finding solutions to the same problems you face.

Bonds have become less useful in asset allocation given low to negative expected returns Liquid alternative strategies can be used to replace bonds From a historic perspective, long volatility strategies would have been especially attractive INTRODUCTION John Maynard Keynes famously asked, “when

Financial markets are not macro information efficient. This means that investment decisions miss out on ample relevant macroeconomic data and facts. Information goes to waste due to research costs, trading restrictions, and external effects. Evidence of macro information inefficiency includes

When it comes to predicting long-term equity returns, several well-known indicators come to mind—for example, the CAPE ratio, Tobin’s Q, and Market Cap to GDP, to name a few. Yet there is another indicator without nearly as high of a profile that has outperformed the aforementioned indicators

Forecasting Bond Risk Premia using Stationary Yield Factors Tobias Hoogteijling (Robeco Asset Management), et al. April 12, 2021 The standard way to summarize the yield curve is to use the first three principal components of the yield curve, resulting in level, slope and curvature factors. Yields,

This is the fifth article of the copula-based statistical arbitrage series. You can read the previous four articles with the first three focusing on pairs-trading: Copula for Pairs Trading: A Detailed, But Practical Introduction. Copula for Pairs Trading: Sampling and Fitting to Data. Copula for

One common problem when looking at financial data is the enormous number of dimensions we have to deal with. For instance, if we are looking at data from the S&P 500® index, we will have around 500 dimensions to work with! If we have enough computing power, we will be able to process so much

I have been thinking a lot about risk lately. The liquidity injections from the FED are pushing risk assets higher and higher. There seem to be bubbles in nearly every speculative assets. The main concern long term would be rising rates at the same time as a falling dollar suggesting there is no

As described in my prior post Learning the Exit (part 1), I have a model that indicates mean reversion entries with ~81% accuracy, however I did not have a good approach in handling the exit. While 81% of MR signals had a minimum profit of 25% (of prior amplitude), the mean profit available was

The data from Professor French has laid the foundation for factor investing However, over time factor portfolio construction grew complex and with many nuances Returns may look more or less attractive, which makes a weak foundation INTRODUCTION When I was growing up one of my favourite TV shows was

Zipline is a fantastic tool for backtesting and data is the main raw material for doing this kind of analysis. In this post, we are going to focus on how to load our own data files. Through an example, we will create a bundle to load data from csv files downloaded from Yahoo finance.

Since the development of the first asset pricing model, the Capital Asset Pricing Model (CAPM), academic research has attempted to develop models that increase the explanatory power of the cross-section of stock returns. We moved from the single-factor CAPM (market beta), to the three-factor

Various research papers show that market sentiment, also called investor sentiment, plays a role in market returns. Market sentiment refers to the general mood on the financial markets and investors’ overall tendency to trade. The mood on the market is divided into two main types, bullish and

This article focuses on “climate-aware” asset allocation and the associated impacts of higher temperatures on equity excess returns and risk. The objective of this research is to demonstrate how portfolios can incorporate climate change risk and rewards into the decision-making process. The

In this series of posts I’m trying some of the ideas in the book Advances in Financial Machine Learning, by Marcos López de Prado. Here I tackle an idea from chapter 5: fractional differencing. the problem Stock prices are nonstationary - their means and variances change systematically over time.

The link between central bank policy, money supply, and inflation seems to have changed QE money printing had no substantial impact on inflation, aside from asset price inflation More direct stimuli might change that INTRODUCTION London ranks ninth on the UBS Global Real Estate Bubble index for

Any asset can use a portfolio of similar assets to hedge against its factor exposure. The factor residual risk of the hedged position is called statistical arbitrage risk. Consequently, the statistical arbitrage risk premium is the expected return of such a hedged position. A recent paper shows that

Every form of strength is also a form of weakness*. I love statistics, but I focus to much on methodology, which is not for everyone. Some people (right or wrong) question: “wonderful sir, but what can I do with it?”. A new paper titled “Beta in the tails” is a showcase application for why