Ladislav Durian - QuantPedia

Avoid Equity Bear Markets with a Market Timing Strategy – Revisiting Our Research

18.August 2023

In March, we posted a series of three articles where our goal was to construct a market timing strategy that would reliably sidestep the equity market during bear markets. In this article, we revisit our research to address the forward-looking bias in our final market timing strategy. Upon careful examination, we identified a bias in our macroeconomic trading signal based on the U.S. S&P Composite dividends. To eliminate the issue, we have replaced the signal from U.S. S&P Composite dividends with Housing Starts Growth sourced from FRED, ensuring the strategy is no longer biased.

The unbiased version of our TrendYCMacro strategy, which uses the HOUSE signal, yields an annual excess return of 6.59%, slightly below the 7.10% of the biased version with the DIVIDEND signal. Interestingly, the unbiased version experiences slightly lower annualized volatility at 11.87% compared to the 11.89% of the biased version. Both versions have suffered the same maximal drawdown of -25.13% and exhibit comparable risk-adjusted returns, with the unbiased version having a Sharpe ratio of 0.56 and the biased version having a Sharpe ratio of 0.60.

ETFs: What’s Better? Full Replication vs. Representative Sampling?

10.August 2022

ETFs employ two fundamentally distinct methods to replicate their underlying benchmark index. The more conventional method, physical replication, involves holding all constituent securities (full replication) or a representative sample (representative sampling) of the benchmark index. In contrast, the synthetic replication achieves the benchmark return by entering into a total return swap or another derivative contract with a counterparty, typically a large investment bank. As we have previously discussed, there is no significant difference in the tracking ability between the physical and synthetic ETFs in the long term. And while our article compares physical and synthetic ETFs, it does not address the differences between the full replication ETFs and sampling ETFs. Therefore, one may ask a question: “When selecting a physically replicated ETF, which replication method is better, full replication or representative sampling?”

The Buffett Indicator

29.July 2022

Despite Warren Buffett’s claim that the MVE/GDP ratio is “probably the best single measure of where valuations stand at any given moment,” its predictive ability has been the subject of relatively little academic scrutiny. A novel paper by Swinkels and Umlauft (2022) fills this gap and examines whether the MVE/GDP ratio can forecast international equity returns, which complements the existing research limited to the United States. A simple trading strategy that invests in countries with the highest model-predicted returns yields statistically significant and economically meaningful alpha over a corresponding buy-and-hold benchmark while experiencing lower volatility and maximum drawdown.

Cryptocurrency Stablecoins – A Review of Recent Research

15.February 2022

Since January 2020, the annualized volatility of Bitcoin stands around 70%, 6-times the volatility of commodities like Gold or Oil, more than twice the volatility of the S&P 500, and 10 times the volatility of the EURUSD exchange rate. Stablecoins represent a specific category of cryptocurrencies aiming to keep their value stable against a benchmark asset, usually a fiat currency like the US dollar. So how do stablecoins work, and do they really offer needed stability?

Should Factor Investors Neutralize the Sector Exposure?

8.February 2022

Factor investors face numerous choices that do not end even after picking the set of factors. For instance, should they neutralize the factor exposure? If the investor pursues sector neutralization, does the decision depend on a particular factor? Or are the choices different for the long-only investor compared to the long-short investor? The research paper by Ehsani, Harvey, and Li (2021) answers these questions and provides investors with an interesting insight on this topic.

Periodicity in Cryptocurrencies – Recurrent Patterns in Volatility and Volume

11.January 2022

The high-frequency data in cryptocurrency markets is available at any time of the day, which facilitates the studies of periodicity measures beyond what’s possible in other markets. The research paper by Hansen, Kim, and Kimbrough (2021) investigates the periodicity in volatility and liquidity in two major cryptocurrencies, Bitcoin and Ether, using data from three exchanges, Binance, Coinbase Pro, and Uniswap V2. In particular, the authors measure relative volatility and relative volume across days, hours, and minutes. Their results have confirmed the presence of recurrent patterns in volatility and volume in studied cryptocurrencies for the periods day-of-the-week, hour-of-the-day, and within the hour.