What Can We Learn from Insider Trading in the 18th Century?

21.March 2022

Directors, board members, and large shareholders are just some of those who might have non-public material information about their firm. Even though this information could be easily used to profit by trading their own stocks, this insider trading behavior is strictly prohibited. But how profitable can it be? We can study insider trading in the time when it wasn’t regulated at all – in the early 1700s. The 300 hundred-year-old dataset consists of data recovered from original handwritten ledger books and transfer files of the three largest companies in the London stock market at the time. It gives us a glimpse into the evidence of how big the insider’s advantage is, and the result is quite surprising – the authors calculated their outperformance to just 7% per year.

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Trend-following and Mean-reversion in Bitcoin

15.March 2022

Indisputably, trend-following and mean-reversion are two key concepts in quantitative investing or technical analysis. What about the Bitcoin? Are there trend-following or mean-reversion patterns? Or are both effects present and co-exist? In this short research, we examine how Bitcoin’s price is affected by its maximal or minimal price over the previous 10 to 50 days. Our finding shows that when the BTC is at the local maxima, it tends to continue trending upwards. Furthermore, the local minima are also connected with abnormal price action.

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Full vs. Synthetic Replication and Tracking Errors in ETFs

11.March 2022

The growth of passive investing and ETFs is indisputable. Consequently, this boom also affects financial markets (e.g., market elasticity or by creating predictable buys and sells) and assets that ETFs track. Even though all passive ETFs aim to replicate some benchmark index, there are two distinct approaches to doing so. The first approach is directly replicating the benchmark (by buying underlying assets) either by full direct replication or sampling. The second approach consists of synthetic replication using derivatives – most commonly by total return swaps (or futures). How do replication methods influence tracking error?

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Factor Performance in Cold War Crises – A Lesson for Russia-Ukraine Conflict

8.March 2022

The Russia-Ukraine war is a conflict that has not been in Europe since WW2. And it has great implications not only on human lives but also on security prices. It bears numerous characteristics of the cold war crises, where two nuclear powers (Soviet Union and USA/NATO) were often very close to hot war or were waging a proxy war in 3rd countries. We thought it might be wise to look at similar periods from the past to understand what happens in such situations. We selected five events and analyzed the performance of main equity factors (market, HML, SMB, momentum & 2x reversal) and energy and fixed income proxy portfolios.

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Quantpedia in February 2022

4.March 2022

Hello all,

What have we accomplished in the last month?

– A new Quantpedia Pro report – Kelly & Optimal F
– 11 new Quantpedia Premium strategies have been added to our database
– 15 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 10 new backtests written in QuantConnect code
– And finally, 3+3 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

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Beware of Excessive Leverage – Introduction to Kelly and Optimal F

26.February 2022

Most investors focus solely on the profitability of their investment strategy. And, even though having a profitable strategy is important, it is not everything. There are still numerous other things to consider. One of them is the size of the investment. The investment size can increase or decrease the profitability of a strategy, so it is essential to choose it right. The following article is our introduction to Kelly and Optimal F methodologies, that underlies our upcoming Quantpedia Pro report.

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