Michael Arold Profile Picture Individual Investor

Michael Arold

Director, Channel Sales,Computer Software

  • Education University of Stuttgart, Germany
  • Qualifications Master in Aerospace Engineering
  • Investment Experience 16 years private investing, 4 years short term equity trading

Technical Swing

Using multiple technical indicators, Arold surveys  movements in the market and the sectors and stocks that are leading the way. Once interesting sectors or companies are identified, the manager takes a discretionary view, based on fundamentals, of likely moves in the opposite direction (i.e. have these been oversold or overbought). Short term model focusing on short term price swings.
Top down approach to market, considers what direction the market is moving and what sectors are leading that move, and within the sector what stocks. Identifies key metrics such as the price of the US dollar, the VIX, price of Gold or the Baltic Dry Index in order to develop a "market theme".  Takes a discretionary approach rather than using a black box programmatic system.  Occasionally remains at the sector level and captures trades across an industry through ETFs. Looking to capture a movement in price swing within 2 days to 2 months time frame.
Monitors all technical indicators and looks at multiple sources of data for sentiment direction including analyst recommendations, news, discussions, and multiple web sites. These websites include Investor's Business Daily, StockTwits, AbnormalReturns and BespokeInvestmentGroup.  Likes to use extreme public predications as contrary indicator.

For more on the methodology, please click here.
Final position decisions are made from a discretionary viewpoint blending in leading technical indicators with the macro perspective, company fundamentals if appropriate, and short term catalyst events. Maintains an active risk management model with no position putting more than 1% of the capital at risk, where the capital at risk is calculated from the volatility and price of the stock. Tries to hold 5-15 positions which is more than a classical swing trader, and to maintain some diversification of those positions across sectors.
Maintains soft stops on positions.  Will hold positions 2 days to 2 months with a goal of maintaining a 60 % success ratio and 50% higher profit on successful positions than loss on unprofitably trades.
Doesn't like stocks that can be subject to external events that may have a sudden and dramatic effect on the company, so tends to avoid biotech and micro-cap stocks.

Risk rating

5
19.4%

Best 30 days

-16.6%

Worst 30 days

Performance

  • 0.1%
    30 day
  • 19.7%
    365 days
  • 71.9%
    Since Inception
    September 06, 2007
Monthly vs S&P500
Sparkbar Graph, Technical Swing Investment Model Performance versus S&P500
17.0%

Last 12 months

  • $25,000 subscription min
  • margin account required
  • 1.5% fee

Replicability

100.0%
  • Replicable

Top 5 Holdings View all

13.0%
10.6%
10.0%
9.7%
-12.2%
  • AAPL
  • N
  • LULU
  • TOL
  • EZU

Model commentary

  1. Swing manager Arold calls Toll Brothers one of his best new ideas

    23 May 2012

    Arold says little international headline risk, room for analyst sentiment improvement, and breakout potential make Toll Brothers one of his very few long ideas.

  2. Deconstructing Wells Fargo with triple screen … 1 May 2012
  3. Keep an eye on China and copper prices 3 April 2012
  4. Why I sold my silver position 6 March 2012
  5. Getting more cautious, but still strongly long 6 March 2012

show more


Performance detail

  • Manager
  • S&P 500

Performance

Inception September 06, 2007
as of May 24, 2012 Manager S&P 500 Average Subscriber
Past 30 days 0.1% -3.7% -0.2%
Past 90 days 0.8% -3.3% -0.5%
Past 365 days 19.7% 0.0% 11.5%
Since Inception (Annualized) 12.2% -2.4% -
2012 (YTD) 7.7% 5.0% 6.2%
2011 14.6% 0.0% 7.7%
2010 20.6% 12.8% 11.2%
2009 -1.3% 23.5% -
2008 12.8% -38.5% -

Risk Metrics

Last 365 Days
as of May 24, 2012 Manager S&P 500
Best 30 days 10.7% 13.6%
Worst 30 days -5.2% -16.7%
Volatility 11.2% 23.2%
Sharpe Ratio 1.75 -0.01
Sortino Ratio 3.02 -0.01
Maximum Drawdown -6.7% -18.8%
Value-at-risk (95%, 1 week) -2.6% -5.4%
vs. S&P 500
Information Ratio 0.73
Alpha 18.8%
Beta -0.06
R-Squared 0.02

Latest transactions view all

Average trades per month 45.8
Executed Symbol Security Replicable Type Price
05/24/12 EZU ISHARES MSCI EMU Yes Sell short $26.41
05/24/12 AAPL Apple Inc Yes Buy $573.23
05/23/12 LULU LULULEMON ATHLETICA INC Yes Buy $72.07
05/23/12 N NETSUITE INC Yes Buy $46.11
05/23/12 DUG PROSHARES ULTRASHORT OIL & G Yes Buy $28.56
05/23/12 TDC Teradata Corp Yes Sell $68.93
05/23/12 DUG PROSHARES ULTRASHORT OIL & G Yes Buy $28.08
05/23/12 SLV iShares Silver Trust Yes Sell short $26.88
  • $25,000 subscription min
  • margin account required
  • 1.5% fee

Important Information

Important Information

1. Past performance is no guarantee of future results.

2. Performance of the model manager's account is calculated by Covestor on a daily time-weighted basis, including cash, dividends and earnings distributions, and broker commissions. Manager returns include trades that fail Covestor's trading rules, do not reflect any Covestor suitability or risk score restrictions and are exclusive of Covestor fees. More

3. Average subscription returns ("Avg Sub" or "Avg Client") are calculated by Covestor and are composed of the average, daily, time weighted returns of all active subscriptions to the underlying model. These daily average returns are then linked together for the timeframe requested. In addition, these returns include cash, dividends and earnings distributions, brokerage commissions, Covestor advisory fees, and reflect individual client suitability and risk score restrictions. More

4. All graph data is as of the end of day for the referenced period, unless otherwise specified. The subscription minimum is the minimum subscription required to follow a particular model. The minimum amount is determined by Covestor, based on the characteristics of the underlying model. It should not be considered as specific investment advice for your investment situation.

5. Benchmark returns have been calculated by Covestor using a time-weighted calculation of daily index valuations and do not include cash, dividends and earnings distributions, or transaction costs. More

6. Leverage indicates the level of margin utilized and is calculated by dividing gross exposure by portfolio net liquidation value.

7. All Model Manager information including personal data, profiles, strategies, monthly investment reports, and historical results outside of Covestor has been provided by the Model Manager. Covestor makes no representation or warranty of its accuracy, completeness or relevance and it does not represent the opinions of Covestor. Transaction history is available upon request. Model classifications (Approach, Asset Class) are provided by Covestor, and are intended to serve as a general guide.

8. Top Replicable Holdings: These securities are currently held in the model manager's brokerage account. Those marked as "Replicable Holdings" currently pass Covestor's trading rules, subject to individual client constraints. Eligibility for replication may change over time. Actual client subscription holdings may vary.

9. Latest Transactions: These transactions were executed in the model manager's brokerage account. Those marked as "Replicable" () passed Covestor's trading rules and were eligible for replication at the time of execution, subject to individual client constraints. Eligibility for replication may change over time. Actual client subscription trade activity may vary.

10. S&P 500 Index is an unmanaged index compiled by Standard & Poor´s Corp. Index returns do not reflect any management fees, transaction costs or expenses. Individuals cannot invest directly in an Index. S&P 500 index data: S&P 500 Copyright © 2012.

11. Dow Jones index data: CME Group Index Services, LLC 2012

12. This model was launched on Covestor on March 23, 2009. Trading history prior to launch was audited by Covestor and is consistent with current model strategy. Manager performance incorporates this historical data.