Reversal signals in a bull market should be analyzed very carefully because they have a high failure rate. Since the beginning of this year this bull market has generated plenty of false reversals. The losses of the shorts caught in bear traps provide even more fuel to the bull market. Therefore, false hopes for a reversal to satisfy the contrarian instincts at least temporarily is a normal market mode. But once in a while, when bears start to turn bulls, the reversal signals are true.
Rolling 60-day correlations of SPY with TLT, FXE, GLD, SLV, USO and DBC, and trends developing since the last report on April 26, 2013. Most correlations have remained stable as traders are trying to figure out their next move.
The SPY2p5 system was machined designed on April 4, 2012 by Price Action Lab using an in-sample from SPY inception (01/29/1993) to December 31, 2008. Then the system was validated on unseen data, called the the out-of-sample, from January 2, 2009 to April 5, 2012 and the results were published in this blog two days later. By the end of last year the SPY2p5 system had outperformed the ETF in forward trading. This post poresents a study of the significance of this trading system.
Random trading can produce high positive returns as well as very low negative returns. In a post a week ago with the title Random Trading Versus Trading Randomly I included distributions from random SPY trading and I showed how they impose limits on the significance of strategies for trading that market. In this post I show that results from Monte Carlo simulations may overestimate or underestimate the significance and potential of trading strategies when convergence is not obtained.
The high probability day trade two days ago was for IAU and made $0.07 per share but one could trade instead GLD for +0.68 per share since their moves match. This alert is about 7 new raw signals in 6 popular ETFs for entry at the open and exit at the close. Portfolio backtests must be used to indicate which patterns have a persistent edge that implies a low, but still finite, probability that they are random.
This alert is about one long signal in a popular ETF for entry at the open and exit at the close. Portfolio backtests indicated that the pattern that generated the signal has a persistent edge and that implies a low, but still finite, probability that it is random.
On May 3 of last year I wrote that “the market will punish those who sell in May and go away“. And they were punished hard twice. First they chased the market and then they were squeezed out, only to see the market rallying again by year’s end. But this year it appears that the large sect of May sellers is bluffing to give the impression that they will stay invested with the intention to sell maybe in June and recover last year’s losses.
This trend-following trading system is based on an algorithm that adapts to market conditions and it is significant at the 99.86% level in the case of SPY based on the performance results obtained from 20,000 simulations of a random system. There are only two parameters in the system and it is profitable in several tickers without any adjustments. Since inception of SPY the win rate is 100% and the CAR is 10.66%.
Suppose a trader has purposely used a random system to trade SPY since its inception. What was the probability to make annually more than the buy and hold return? Or suppose a trader has worked hard to develop a trading system that generated a positive return over the same period. Was her system intelligent or it was tossing a coin? This post offers two examples that try to answer these questions.
The 10-year Note yield rose 7.4% yesterday as managers were rebalancing their portfolios to reflect new information about the state of the economy and the objectives of the FED. This is a high level of daily volatility in bond yields and a phenomenon that appeared after the financial crisis began as it is shown on the chart below.
