Langsung ke konten utama

Postingan

Menampilkan postingan dari Mei, 2008

Applying Corrective AI to Daily Seasonal Forex Trading

  By Sergei Belov, Ernest Chan, Nahid Jetha, and Akshay Nautiyal     ABSTRACT We applied Corrective AI (Chan, 2022) to a trading model that takes advantage of the intraday seasonality of forex returns. Breedon and Ranaldo (2012)   observed that foreign currencies depreciate vs. the US dollar during their local working hours and appreciate during the local working hours of the US dollar. We first backtested the results of Breedon and Ranaldo on recent EURUSD data from September 2021 to January 2023 and then applied Corrective AI to this trading strategy to achieve a significant increase in performance. Breedon and Ranaldo (2012) described a trading strategy that shorted EURUSD during European working hours (3 AM ET to 9 AM ET, where ET denotes the local time in New York, accounting for daylight savings) and bought EURUSD during US working hours (11 AM ET to 3 PM ET). The rationale is that large-scale institutional buying of the US dollar takes place during European working hours to pa
Posting Komentar
Baca selengkapnya

Parameterless trading models

A portfolio manager that I used to work for like to pronounce that his trading models have "no free parameters". As is customary in our secretive industry, he would not elaborate further on his technique. Lately, I begin to understand what a trading model with no free parameter means. It doesn't mean that it does not contain any lookback period for calculating trends, or thresholds for entry or exit. I think that would be impossible. It just means that all such parameters are dynamically optimized in a moving lookback window. This way, if you ask: "Does the model have a fixed profit cap?", the trader can honestly reply: "No, profit cap is not an input parameter. It is determined by the model itself." The advantage of a parameterless trading model is that it minimizes the danger of overfitting the model to multiple input parameters. (The so-called "data-snooping bias".) So the backtest performance should be much closer to the actual forward pe
Posting Komentar
Baca selengkapnya

Are high oil prices due to hedge fund speculation?

The economist Paul Krugman advances an interesting argument today in the New York Times against the idea that high oil prices are due to hedge fund speculation. He believes that speculative buying can lead to persistent high prices (which has been the case for the last few years) only if there is physical hoarding. Yet oil inventory level has been normal for this period. Indeed, I have been trying to find a mean-reverting strategy to trade oil and oil-related assets for some time now. So far, none have outperformed (even on a risk-adjusted basis) just buy-and-hold energy stocks for the long term!
Posting Komentar
Baca selengkapnya

5%: an important number for real estate investors

Equity investors like to check out a company's price/earnings ratio before they invest in its stock. Likewise, real estate investors should do the same before buying a house. The equivalent of price/earnings ratio for real estate is the price/rent ratio, or inversely, the rent/price yield. What is a reasonable rent/price yield for US residential real estate? According to Morris Davis of the University of Wisconsin-Madison, and Andreas Lehnert and Robert Martin of the Fed , the long-term average is 5% (i.e. the annual rent of a house should be about 5% of its market value). As the Economist magazine has reported, at the height of the US housing boom, this figure dropped to as low as 3.5%. Currently, this ratio is at about 4.3%, which implies that average US housing price has to drop another 14% in order to return to its historical fair value. Can quantitative traders profit from this prediction? Well, we can always short the S&P/Case-Shiller Home Price Indices futures at the C
Posting Komentar
Baca selengkapnya

A combination momentum and mean reversal model based on earnings annoucements

Mark Hulbert of the New York Times just discussed 2 momentum strategies investigated by professors David Aboody, Brett Trueman and Reuven Lehavy. Strategy A: pick stocks in the top percentile of 12-month returns. Buy them (individually) 5 days before their earnings announcements and sell them just before the announcement. Strategy B: pick stocks in the top percentile of 12-month returns. Buy them (individually) 5 days immediately after their earnings announcements and hold them for 5 days. Strategy A is very profitable: the annualized excess return is 47% before costs. (To be taken with a grain of salt due to the large transaction costs associated with trading momentum strategies, especially if small-cap stocks are involved.) Strategy B is very unprofitable: the annualized excess return is -43% before costs. So what are the ways we can make best use of this research? Naturally, instead of buying the top percentile after the earnings announcements, we should have shorted the stocks, t
Posting Komentar
Baca selengkapnya