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Wall Street Veteran Charles Gradante: Hedge Funds Would Be Smart to Be Smaller

By John Jannarone Hedge funds aren’t the enemy some make them out to be, but they would be better off managing smaller sums of money and focusing on securities where it’s possible to have a true edge. That’s according to Wall Street legend Charles Gradante, who spoke publicly for the first time in several years to a group […] Read More...

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="By&nbsp;John Jannarone” data-reactid=”18″>By John Jannarone

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="Hedge funds aren’t the enemy some make them out to be, but they would be better off managing smaller sums of money and focusing on securities where it’s possible to have a true edge. That’s according to Wall Street legend Charles Gradante, who spoke&nbsp;publicly for the first time in several years&nbsp;to a group of investors at the&nbsp;Palm Beach Global Finance&nbsp;Forum, a recent event hosted by&nbsp;the&nbsp;Palm Beach Hedge Fund Association&nbsp;with support from&nbsp;Markets Group.” data-reactid=”19″>Hedge funds aren’t the enemy some make them out to be, but they would be better off managing smaller sums of money and focusing on securities where it’s possible to have a true edge. That’s according to Wall Street legend Charles Gradante, who spoke publicly for the first time in several years to a group of investors at the Palm Beach Global Finance Forum, a recent event hosted by the Palm Beach Hedge Fund Association with support from Markets Group.

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="In a wide-ranging interview moderated by&nbsp;CorpGov, Mr. Gradante discussed his decision to support hedge funds publicly after the collapse of Long-Term Capital Management&nbsp;and made clear that lenders bore as much responsibility as the highly-levered fund. He&nbsp;also explained&nbsp;the little-known history of hedging and&nbsp;how investment banks like Drexel Burnham Lambert innovated the long/short format in the 1980s that&nbsp;many&nbsp;hedge funds&nbsp;embrace today.&nbsp;The full interview is below.” data-reactid=”20″>In a wide-ranging interview moderated by CorpGov, Mr. Gradante discussed his decision to support hedge funds publicly after the collapse of Long-Term Capital Management and made clear that lenders bore as much responsibility as the highly-levered fund. He also explained the little-known history of hedging and how investment banks like Drexel Burnham Lambert innovated the long/short format in the 1980s that many hedge funds embrace today. The full interview is below.

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="After a successful career at Citigroup,&nbsp;Mr. Gradante&nbsp;joined Drexel Burnham Lambert in 1986 and spearheaded the firm’s efforts in Europe which led to his position as CEO of&nbsp;the failing Chelsea National Bank&nbsp;for&nbsp;which he engineered&nbsp;a&nbsp;turnaround and sale.&nbsp;He subsequently became a partner of the&nbsp;Hennessee Hedge Fund Advisory Group, then a part of E.F. Hutton&nbsp;and later spun off as a wholly-owned&nbsp;private company (Hennessee Group LLC), where he co-founded the Hennessee Hedge Fund Index (the first of its kind) providing hedge fund research to clients. The Hennessee Group LLC managed $1.6 billion. Not long afterwards, in the wake of the collapse of&nbsp;Long-Term Capital Management,&nbsp;Mr. Gradante&nbsp;repudiated public perception of the&nbsp;hedge fund industry&nbsp;as “ruthless risk takers threatening the stability of capital markets”&nbsp;when he testified before the House and the Senate in 1998 and again in 2004. In 2007, Charles predicted the subprime mortgage meltdown, which triggered a global financial crisis. He continues to manage money today in a private fund.” data-reactid=”21″>After a successful career at Citigroup, Mr. Gradante joined Drexel Burnham Lambert in 1986 and spearheaded the firm’s efforts in Europe which led to his position as CEO of the failing Chelsea National Bank for which he engineered a turnaround and sale. He subsequently became a partner of the Hennessee Hedge Fund Advisory Group, then a part of E.F. Hutton and later spun off as a wholly-owned private company (Hennessee Group LLC), where he co-founded the Hennessee Hedge Fund Index (the first of its kind) providing hedge fund research to clients. The Hennessee Group LLC managed $1.6 billion. Not long afterwards, in the wake of the collapse of Long-Term Capital Management, Mr. Gradante repudiated public perception of the hedge fund industry as “ruthless risk takers threatening the stability of capital markets” when he testified before the House and the Senate in 1998 and again in 2004. In 2007, Charles predicted the subprime mortgage meltdown, which triggered a global financial crisis. He continues to manage money today in a private fund.

 

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="CorpGov: Hedge funds have been around for longer than many people think. Can you tell us about what you observed when you were involved in their early days?” data-reactid=”23″>CorpGov: Hedge funds have been around for longer than many people think. Can you tell us about what you observed when you were involved in their early days?

Mr. Gradante: It’s a little-known fact where the whole concept of hedging began. A lot of people think that hedge funds were the originators of the long/short format, but in fact investment banks were and still are the biggest hedge funds on the Street.

But more importantly, the concept goes back to farmers. For example, a farmer may have had 100 acres of crops. He would sell 50 acres in the futures market and keep 50 acres for the cash market – so he was long and short, say, corn.

That is really where hedging began, and investment banks in the early 1900s took that concept from farmers and did it with long/short equities and bonds. Hedge funds didn’t really exist until the 1960s when we had about five major hedge funds. They were below the radar: They weren’t allowed to advertise or attend conferences and their phone numbers weren’t even listed in the phone books back then.

It wasn’t until the 1980s we realized we had about 100 hedge funds, particularly because of the 1987 crash. All known hedge funds at the time made money in the crash and the high net worth individuals who were investing in them spread the word around. It quickly got out that hedge funds were a panacea to market crashes and that drew a lot of attention to the hedge fund community.

I was at Drexel Burnham in the 80s and we ran our prop trading desk like a hedge fund. I oversaw the equity and bond trading desks in Europe. We would trade equities and bonds in a long/short format. I noticed stock pickers who used fundamentals on the trading desk had a different strategy from my day traders who used more technicals and then the options guys had their own approach. I found that when one strategy was making money the other might be losing money so I combined them into a team to get the best of all worlds.

It worked something like this: The fundamentals guy came up with stocks to go long and short on a fundamental basis; the guy in technicals would find the best entry and exit points; and the options guy would sell puts and covered calls to accentuate the performance.

 

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="CorpGov: Can you tell us how hedge funds were portrayed as villainous in the 1990s and how you stood up for them?” data-reactid=”35″>CorpGov: Can you tell us how hedge funds were portrayed as villainous in the 1990s and how you stood up for them?

Mr. Gradante: In 1998, I testified before the House, the Senate, the SEC, the CFTC – you name it. Mainly because no one else was willing to stand up to the arrows that were being launched at Long-Term Capital Management.

It’s true LTCM had a failed business model. But in the beginning, they were great bond arbitrageurs led by John Meriwether, who was a famous bond trader from Salomon Brothers. On his team were no less than five people with a Ph.D. degree from MIT and two Nobel laureates, Myron Scholes and Robert C. Merton. They were making money hand over fist and they were benefitting from a star system. Banks provided them with a tremendous amount of leverage because they were making money for themselves and their banks.

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="Little did LTCM know that the banks that were lending them money were replicating their trades. When Russia defaulted on their sovereign debt, which sent a shockwave through the bond market, LTCM’s computers told them to hold onto their positions&nbsp;– they’re going to come back&nbsp;in a reversion to the mean. But they&nbsp;couldn’t hold on long enough as the&nbsp;New York&nbsp;Fed and big banks had to step in and save LTCM, basically to conduct an orderly liquidation to avoid a global meltdown in capital markets.&nbsp;It wasn’t just because they had lent them money but because they had the same positions on in size in the bellies of their&nbsp;own&nbsp;banks.&nbsp;And it wasn’t just U.S. banks. European banks and global insurance companies were replicating LTCM trades.” data-reactid=”38″>Little did LTCM know that the banks that were lending them money were replicating their trades. When Russia defaulted on their sovereign debt, which sent a shockwave through the bond market, LTCM’s computers told them to hold onto their positions – they’re going to come back in a reversion to the mean. But they couldn’t hold on long enough as the New York Fed and big banks had to step in and save LTCM, basically to conduct an orderly liquidation to avoid a global meltdown in capital markets. It wasn’t just because they had lent them money but because they had the same positions on in size in the bellies of their own banks. And it wasn’t just U.S. banks. European banks and global insurance companies were replicating LTCM trades.

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="The option of letting LTCM liquidate&nbsp;their own portfolio&nbsp;was not an option because no one knew what the true exposure was&nbsp;globally. I told congress the banks had violated the “know your customer” rule because they didn’t&nbsp;understand&nbsp;LTCM’s portfolio risk nor the true leverage on their balance sheet.&nbsp;” data-reactid=”39″>The option of letting LTCM liquidate their own portfolio was not an option because no one knew what the true exposure was globally. I told congress the banks had violated the “know your customer” rule because they didn’t understand LTCM’s portfolio risk nor the true leverage on their balance sheet. 

I also mentioned Donald Trump in the same testimony, drawing a parallel to the real estate crisis in banking during the 80s. To the banking community, Donald Trump was a real estate star and as such the banks lent him money without digging into his global balance sheet. As with LTCM, when the real estate market collapsed, the banks were sitting there wondering what the exposure truly was.

One major lesson from LTCM was that statistics alone aren’t enough to ensure success. In my opinion, statistical analysis to predict market moves is useful but highly overrated. Bollinger bands, stochastics and in general statistics weren’t designed for money management. Statistics came into play for quality control of production lines in manufacturing. They came into prominence during World War I when large quantities of bullets were jamming in guns on the front line. Lives were being lost because bullet casings were too wide or not wide enough to fire. How could we be 99% sure that the guns won’t jam? They developed “statistical acceptance sampling theory” which concluded that if they sampled 15% of the bullets manufactured each hour and they were all within three standard deviations of the mean dimensions required they would be 99% confident that the batch of bullets were acceptable and the production machines did not need recalibration. But it’s not perfect even in a fairly controlled environment like a production line.

Then after World War II and the rise of the middle class, along came “modern portfolio theory” and a major segment of it translated quality control statistical analysis to money management. But whereas statistical sampling analysis and linear regression did wonders for consistent production of quality products by accurately predicting mean time to failure of a machine, its application to money management fell short of predicting a forthcoming malfunction and failure in a stock or the market as with LTCM. Value at risk modeling used by LTCM failed.

The second major lesson from LTCM was that position size should not outweigh your information flow. LTCM did not have good quality information flow coming out of Russia or Amsterdam (or other foreign markets) where they also had big positions. Bottom line – computers are useful tools but information flow is paramount.

 

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="CorpGov: What could&nbsp;funds&nbsp;these days be doing better?” data-reactid=”45″>CorpGov: What could funds these days be doing better?

Mr. Gradante: I’ve met over 1,000 hedge funds and discussed how they manage money and what I’ve found is that most hedge fund managers come out of the research side of wall Street. They know the fundamentals – balance sheet, cash flow, Ebitda, multiples – all that stuff. The issue is that they tend to fall in love with their research and don’t pay attention to their “batting average.”

At Drexel I implemented the batting average for each prop trader and portfolio manager. That is how many stocks made a profit and how many didn’t within a given year. Obviously if you hold a good stock long enough you will probably make money. But the prop desk and hedge funds are measured on an annual basis.

If you look at your annual results you’ll probably find – if your “batting average” is really good – that you’re right 60% of the time and you’re wrong 40% of the time. What I observed among my prop-traders and money managers is you must have a set of disciplined loss cutting rules which are a function of a specific stock’s expected volatility. The higher the vol the wider the band. Often I would see hedge fund managers up 7% in a given year that the market was up 20%. Why such a wide gap? Even in cases where their “batting average” was excellent! What I found is that while they had a 60/40 “batting average”, which is exceptional, the “winners” were up 25% beating the market but their losers were down 20% netting 7% performance for the year (+15% – 8%)! Key is understanding that you may have the right fundamentals (long or short) but the wrong entry point. Value managers are notorious for buying more when a stock is down 10%, 20%, 30% from their entry point. “If I liked it at $100, I like it more at $70!! But now you’ve averaged down to a cost basis of say $85 but you need the stock to go up over 17% just to break even. So when wrong on the entry point, cut your losses quickly. You can always get back in at a lower price!

You need to have good downside risk management. On the prop desk when I managed it, if a position was down 10%, we trimmed 50%. It didn’t matter what the fundamentals said. If it was down 20% you either got out or the trader doubled down and risked his bonus – maybe even his job. In short, the market is the sum total of information, momentum and emotion, so when a stock (whose normal volatility is +/- 2% in a given month) is trending down 10%, 20% and beyond…step aside and regroup the trade even if fundamentals haven’t changed.

 

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="CorpGov: Should funds employ more options strategy?” data-reactid=”51″>CorpGov: Should funds employ more options strategy?

Yes. Here’s an example: If the entry point is there, you should leg into it. If you want to own 3,000 shares, I like to buy 1,000 shares initially. But why not also sell some out of the money puts below my initial entry point?

If the stock goes down, you get the stock at a lower price. If not, you receive cash flow from the short puts that lower your cost basis on the second and third leg of buys. Likewise, when you’re planning to exit a position, you can sell calls on stocks that remain in your portfolio after you begin “legging out”. There are other strategies to accentuate performance but these are the fundamental ones.

It’s a very simple strategy that can add 3-5% to your returns annually on your portfolio.

 

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="CorpGov: What do you think about hedge funds that get very large? Is it problematic?” data-reactid=”56″>CorpGov: What do you think about hedge funds that get very large? Is it problematic?

Mr. Gradante: The industry had its best performance years in the 90s. It wasn’t because funds were smarter then than they are now. Back then, they were targeting small and mid-cap stocks. The average hedge fund was $100 million to $500 million in size. The industry was $500 billion. Today the top 18 hedge funds have over $1.2 trillion AUM ranging from $25 to $207 billion with an average of $66 billion.

Now, with hedge funds managing $10 billion or more, it’s far more difficult to generate “alpha” in the traditional hedge fund format. Managing $10 billion in a long/short format forces you into big cap stocks or even activism and private equity in order to generate alpha.

Here’s why: Managers usually want each position at cost to be no more than 2% to 5% of their portfolio and they usually don’t want to own more than 5% of the outstanding shares. So you have between 20 and 50 position in the portfolio. If you do the math on $10 billion, that forces you into big cap stocks. The issue then becomes how do you generate “alpha” in big cap stocks. Where is your research edge in FAANG stocks which accounted for much of the major market moves since 2013?

In the 1990s, we had an information edge because we were dealing with unloved, under-researched small and mid-cap stocks. Wall Street put their junior analysts in these market cap sectors, largely because the investment banking division wanted the top analysts researching current big-cap banking clients and targeted banking prospects. We were competing with junior analysts! Occasionally, we would help them out and bounced our research ideas off them (after we established our own position).  Now, hedge funds are competing with some pretty astute guys in big cap stocks who in addition have investment banking connections. Where are large hedge funds going to find the edge in FAANG stocks? That’s one of the key reasons hedge funds have underperformed since 2013.

Also remember that the real disruptors tend to be small and mid-cap companies. Take the semiconductor sector for example. Nvidia was a small cap company not too long ago. Now it’s blazing a trail in gaming, AI, network security, cloud processing, computer graphics and blockchain.

When Nvidia was smaller (less than $5 billion market cap in 2010), trading at say $10 compared to $150 today, that’s when managers should have gotten into the stock. That was the time when research was really important. A 2% position in Nvidia’s market cap back then ($100 million) would have been too small for hedge funds over $10 billion. The opportunity for “organic alpha” declines as you go up the market cap scale.

Today most of the money is with the large hedge funds and it’s not best for the industry. I’d like to see more small cap hedge funds managing $500 million and mid cap managers managing $3 billion.

 

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="CorpGov: What keeps&nbsp;you up at&nbsp;night&nbsp;when&nbsp;it comes&nbsp;to market risks?” data-reactid=”65″>CorpGov: What keeps you up at night when it comes to market risks?

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="Mr. Gradante: The biggest concern for decades has been the&nbsp;dark markets”&nbsp;like structured derivatives. No one knows for certain the size of the market for structured derivatives, but the latest estimate I’ve seen was $80 trillion. The global GDP is $100 trillion so that gives you an idea of how much is out there. It’s a&nbsp;zero sum&nbsp;game but there’s counterparty risk that can&nbsp;trigger&nbsp;a domino effect&nbsp;and cause&nbsp;a&nbsp;tremendous market&nbsp;meltdown.” data-reactid=”66″>Mr. Gradante: The biggest concern for decades has been the dark markets” like structured derivatives. No one knows for certain the size of the market for structured derivatives, but the latest estimate I’ve seen was $80 trillion. The global GDP is $100 trillion so that gives you an idea of how much is out there. It’s a zero sum game but there’s counterparty risk that can trigger a domino effect and cause a tremendous market meltdown.

Then there’s real estate market. I’m not bullish on residential real estate. The baby boomers have unrealized capital gains in real estate and they cannot realize them. Their children’s generation cannot afford to acquire their parents’ houses for the first time in history. We’re going to see a giant sucking sound in real estate valuations, especially residential, in the next 10 years.

The other issue is the “uptick rule”. I don’t know why they abolished it but it should be reinstated. It allows computers to short stocks non-stop.

Finally, the dollar as a global reserve currency. There’s a huge push to reduce reliance on it as a reserve currency. If this happens, it will put our printing press in reverse, resulting in global deleveraging and a sharp decline in the dollar, which will be horrendous.

 

Contact:

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="John Jannarone, Editor-in-Chief” data-reactid=”72″>John Jannarone, Editor-in-Chief

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="www.CorpGov.com” data-reactid=”73″>www.CorpGov.com

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="[email protected]” data-reactid=”74″>[email protected]

<p class="canvas-atom canvas-text Mb(1.0em) Mb(0)–sm Mt(0.8em)–sm" type="text" content="Twitter:&nbsp;@CorpGovernor” data-reactid=”75″>Twitter: @CorpGovernor

 

 

 

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