Recession Model Forecast: 05-01-2016

Posted on May 21, 2016 by

The following article updates the diffusion index, recession slack index, aggregate recession model, and aggregate peak-trough model through April 2016. Throughout 2015, I added a number of new economic and market-based variables with very strong explanatory power to the recession model. This allowed me to cull three of the original independent variables with the weakest historical performance and most questionable cause and effect recessionary influence. I added one new variable with surprisingly strong explanatory power at the end of February 2016. The current 21-variable model has a diverse set of explanatory variables and is quite robust.

Each of the explanatory variables has predictive power individually; when combined together, the group of indicators is able to identify early recession warnings from a wide range of diverse market-based, fundamental, technical, and economic sources. After the latest additions and deletions, the total number of explanatory recession model variables is now 21. The current and historical data in this report reflect the current model configuration with all 21 variables. Continue reading →

Share
Posted in Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing, Recession Forecasting Model, Risk Management | Tagged , , , , , , , , | Leave a comment

Non-Farm Payroll (NFP) Model Forecast – April 2016

Posted on May 5, 2016 by

This article presents the Trader Edge aggregate neural network model forecast for the April 2016 non-farm payroll data, which is scheduled to be released tomorrow morning at 8:30 AM EDT. Continue reading →

Share
Posted in Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing, NFP Forecasting Model | Tagged , , , , , , | Leave a comment

Bulls Beware

Posted on May 1, 2016 by

I have been working daily on designing and backtesting various option strategies, which will continue to be my focus for the foreseeable future. As a result, the time available for writing new posts has been and will continue to be quite limited.

That said, I feel obligated to comment on the status of the equity market, as I did at the end of 2015. Continue reading →

Share
Posted in Earnings, Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing, Recession Forecasting Model, Relative Strength, Risk Management | Tagged , , , | Leave a comment

04-29-2016 AAR Strategy Update Posted

Posted on April 29, 2016 by

The April 29, 2016 AAR Strategy update is now available on the AAR Subscribers page.  If you are not currently a subscriber and would like to learn more about the strategy, there is a detailed description on the AAR Strategy page.

The AAR strategy is a conservative, long-only, asset allocation strategy that rotates monthly among five large asset classes: large-cap U.S. stocks, developed country stocks in Europe and Asia, emerging market stocks, U.S. Treasury Notes, and commodities. The strategy was inspired by the Ivy League portfolio and uses trend and technical filters to reduce downside risk.

If none of the five candidates pass their respective trade filters, the AAR strategy remains in cash for the month. Stop-loss orders are used on every trade to control losses and to facilitate position sizing and risk management.

Brian Johnson

Copyright 2016 - Trading Insights, LLC - All Rights Reserved.

Share
Posted in Asset Allocation Rotational (AAR) Strategy, Market Timing, Relative Strength, Risk Management, Strategy Development | Tagged , , , , , , | Leave a comment

Recession Model Forecast: 04-01-2016

Posted on April 17, 2016 by

The following article updates the diffusion index, recession slack index, aggregate recession model, and aggregate peak-trough model through March 2016. Throughout 2015, I added a number of new economic and market-based variables with very strong explanatory power to the recession model. This allowed me to cull three of the original independent variables with the weakest historical performance and most questionable cause and effect recessionary influence. I added one new variable with surprisingly strong explanatory power at the end of February 2016. The current 21-variable model has a diverse set of explanatory variables and is quite robust.

Each of the explanatory variables has predictive power individually; when combined together, the group of indicators is able to identify early recession warnings from a wide range of diverse market-based, fundamental, technical, and economic sources. After the latest additions and deletions, the total number of explanatory recession model variables is now 21. The current and historical data in this report reflect the current model configuration with all 21 variables. Continue reading →

Share
Posted in Economic Indicators, Fundamental Analysis, Market Commentary, Market Timing, Recession Forecasting Model, Risk Management | Tagged , , , , , , , , | 1 Comment

Earnings Season is Here Again

Posted on April 11, 2016 by
Exploiting Earnings Volatility

Exploiting Earnings Volatility

It is earnings season again, which is one of the best times to exploit earnings-related option pricing anomalies. Option traders are savvy, but Earnings volatility is a difficult concept and it affects every option in the matrix differently.When markets move, it is very difficult for market-makers to accurately apply the unique earnings volatility adjustments across the entire matrix. This creates value-added opportunities for option traders with the right tools.

Fortunately, there is a precise framework that quantifies the exact impact of earnings volatility on the value of every option. I introduced this analytical framework in my recent book, Exploiting Earnings Volatility: An Innovative New Approach to Evaluating, Optimizing, and Trading Option Strategies to Profit from Earnings Announcements.

"Exploiting Earnings Volatility also includes two Excel spreadsheets. The Basic spreadsheet employs minimal input data to estimate current and historical earnings volatility and utilizes those estimates to forecast future levels of implied volatility around earnings announcements. The Integrated spreadsheet includes a comprehensive volatility model that simultaneously integrates and quantifies every component of real-world implied volatility, including earnings volatility. This powerful tool allows the reader to identify the precise level of over or undervaluation of every option in the matrix and to accurately forecast future option prices and option strategy profits and losses before and after earnings announcements. The Integrated spreadsheet even includes an optimization tool designed to identify the option strategy with the highest level of return per unit of risk, based on the user’s specific assumptions."

After releasing Exploiting Earnings Volatility last year, I made a breakthrough in applying these tools in my own proprietary trading. Continue reading →

Share
Posted in Earnings, Options, Recommended Reading | Tagged , , , , , , , | 3 Comments

03-31-2016 AAR Strategy Update Posted

Posted on March 31, 2016 by

The March 31, 2016 AAR Strategy update is now available on the AAR Subscribers page.  If you are not currently a subscriber and would like to learn more about the strategy, there is a detailed description on the AAR Strategy page.

The AAR strategy is a conservative, long-only, asset allocation strategy that rotates monthly among five large asset classes: large-cap U.S. stocks, developed country stocks in Europe and Asia, emerging market stocks, U.S. Treasury Notes, and commodities. The strategy was inspired by the Ivy League portfolio and uses trend and technical filters to reduce downside risk.

If none of the five candidates pass their respective trade filters, the AAR strategy remains in cash for the month. Stop-loss orders are used on every trade to control losses and to facilitate position sizing and risk management.

Brian Johnson

Copyright 2016 - Trading Insights, LLC - All Rights Reserved.

Share
Posted in Asset Allocation Rotational (AAR) Strategy, Market Timing, Relative Strength, Risk Management, Strategy Development | Tagged , , , , , , | Leave a comment

Non-Farm Payroll (NFP) Model Forecast – March 2016

Posted on March 31, 2016 by

This article presents the Trader Edge aggregate neural network model forecast for the March 2016 non-farm payroll data, which is scheduled to be released tomorrow morning at 8:30 AM EDT. Continue reading →

Share
Posted in Economic Indicators, Fundamental Analysis, Market Timing, NFP Forecasting Model, Risk Management | Tagged , , , , , , | Leave a comment